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Case study research: the view from complexity science.

Anderson RA, Crabtree B, Steele DJ, et al. Case study research: the view from complexity science. Qual Health Res. 2005;15(5):669-85.

The authors advocate using the complexity science perspective in case study research. They propose that complexity theory, which looks at relationship patterns within a complex adaptive system, is better suited for studying and understanding health care systems than traditional theoretical models.

How improving practice relationships among clinicians and nonclinicians can improve quality in primary care. September 9, 2009

Understanding differences in electronic health record (EHR) use: linking individual physicians' perceptions of uncertainty and EHR use patterns in ambulatory care. June 19, 2013

Relationships within inpatient physician housestaff teams and their association with hospitalized patient outcomes. January 7, 2015

Health care huddles: managing complexity to achieve high reliability. March 26, 2014

A typology of electronic health record workarounds in small-to-medium size primary care practices. August 21, 2013

Physician and nurse well-being and preferred interventions to address burnout in hospital practice: factors associated with turnover, outcomes, and patient safety. July 19, 2023

Results of the Medications At Transitions and Clinical Handoffs (MATCH) study: an analysis of medication reconciliation errors and risk factors at hospital admission. March 17, 2010

A randomized trial of a multifactorial strategy to prevent serious fall injuries. July 29, 2020

Cognitive error in an academic emergency department. October 10, 2018

Teaching medication reconciliation through simulation: a patient safety initiative for second year medical students. July 23, 2008

The 2017 ACGME common work hour standards: promoting physician learning and professional development in a safe, humane environment. January 31, 2018

Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock: 2016 March 3, 2017

Effect of promoting high-quality staff interactions on fall prevention in nursing homes: a cluster-randomized trial. October 25, 2017

The quality of pharmacologic care for vulnerable older patients. March 6, 2005

Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010–2011. May 25, 2016

Association between surgeon technical skills and patient outcomes. September 9, 2020

Optimizing Pediatric Patient Safety in the Emergency Care Setting. October 19, 2022

Hospitalwide adverse drug events before and after limiting weekly work hours of medical residents to 80. August 3, 2005

Cascade iatrogenesis: factors leading to the development of adverse events in hospitalized older adults. September 23, 2009

Detecting medication order discrepancies in nursing homes: how RNs and LPNs differ. October 10, 2015

Patterns of medical and nursing staff communication in nursing homes: implications and insights from complexity science. February 8, 2006

Extraneous tissue a potential source for diagnostic error in surgical pathology. January 4, 2012

Disorganized care: the findings of an iterative, in-depth analysis of surgical morbidity and mortality. November 21, 2012

Recommended guidelines for monitoring, reporting, and conducting research on medical emergency team, outreach, and rapid response systems: an Utstein-style scientific statement. February 13, 2008

Effects of teamwork training on adverse outcomes and process of care in labor and delivery: a randomized controlled trial. January 17, 2007

Wide variation and overprescription of opioids after elective surgery. October 11, 2017

Technology-enhanced simulation for health professions education: a systematic review and meta-analysis. September 14, 2011

Organizational, cultural, and psychological determinants of smart infusion pump work arounds: a study of 3 U.S. health systems. September 17, 2014

The I-READI quality and safety framework: a health system’s response to airway complications in mechanically ventilated patients with Covid-19. February 17, 2021

Changes in prevalence of health care-associated infections in U.S. hospitals. November 14, 2018

Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions. August 4, 2021

Do medical inpatients who report poor service quality experience more adverse events and medical errors? February 13, 2008

Effect of genetic diagnosis on patients with previously undiagnosed disease. November 7, 2018

Patient safety event reporting expectation: does it influence residents' attitudes and reporting behaviors? June 5, 2013

Do telephone call interruptions have an impact on radiology resident diagnostic accuracy? October 22, 2014

Unsafe by design: infusion task reallocation and safety perceptions in U.S. hospitals. January 11, 2023

Using social and behavioural science to support COVID-19 pandemic response. June 3, 2020

Prevalence and causes of diagnostic errors in hospitalized patients under investigation for COVID-19. April 12, 2023

Promoting a culture of patient safety: a review of the Florida moratoria data: what we have learned in 6 years and the need for continued patient education. April 4, 2007

The effect of automated alerts on provider ordering behavior in an outpatient setting. September 21, 2005

Evaluation of clinical practice guidelines on fall prevention and management for older adults: a systematic review. January 12, 2022

Expert consensus on currently accepted measures of harm. September 9, 2020

Patient safety, systems design and ergonomics. June 21, 2006

Effect of a postdischarge virtual ward on readmission or death for high-risk patients: a randomized clinical trial. June 17, 2015

National incidence of medication error in surgical patients before and after Accreditation Council for Graduate Medical Education duty-hour reform. July 8, 2015

Implementation of the I-PASS handoff program in diverse clinical environments: a multicenter prospective effectiveness implementation study. November 16, 2022

Differential safety between top-ranked cancer hospitals and their affiliates for complex cancer surgery. April 24, 2019

Variations in surgical safety according to affiliation status with a top-ranked cancer hospital. July 24, 2019

Patient outcomes in dose reduction or discontinuation of long-term opioid therapy: a systematic review. July 26, 2017

Natural history of retained surgical items supports the need for team training, early recognition, and prompt retrieval. September 24, 2014

Prevalence, underlying causes, and preventability of sepsis-associated mortality in US acute care hospitals. February 27, 2019

Relationship between preventability of death after coronary artery bypass graft surgery and all-cause risk-adjusted mortality rates. July 9, 2008

Beyond 'find and fix': improving quality and safety through resilient healthcare systems. April 15, 2020

Seroprevalence of SARS-CoV-2 among frontline health care personnel in a multistate hospital network--13 academic medical centers, April-June 2020. September 23, 2020

Surgical site infection prevention: a review. February 1, 2023

The influence of 'Tall Man' lettering on errors of visual perception in the recognition of written drug names. March 16, 2011

Primary care pediatricians' interest in diagnostic error reduction. July 20, 2016

Diagnostic errors in primary care pediatrics: Project RedDE. November 29, 2017

A new professionalism? Surgical residents, duty hours restrictions, and shift transitions. November 17, 2010

Interventions to improve oral chemotherapy safety and quality: a systematic review. June 21, 2017

Health care-associated invasive MRSA infections, 2005-2008. August 18, 2010

Public reporting of health care–associated surveillance data: recommendations from the Healthcare Infection Control Practices Advisory Committee. January 22, 2014

Eradicating central line–associated bloodstream infections statewide: the Hawaii experience. November 16, 2011

Surgical safety does not happen by accident: learning from perioperative near miss case studies. January 24, 2024

Value assessment of deprescribing interventions: suggestions for improvement. August 16, 2023

Liability claims and costs before and after implementation of a medical error disclosure program. August 25, 2010

Changing and sustaining medical students' knowledge, skills, and attitudes about patient safety and medical fallibility. January 11, 2006

Associations of physician burnout with career engagement and quality of patient care: systematic review and meta-analysis. September 28, 2022

Association between state medical malpractice environment and postoperative outcomes in the United States. June 21, 2017

Implications of the failure to identify high-risk electrocardiogram findings for the quality of care of patients with acute myocardial infarction: results of the Emergency Department Quality in Myocardial Infarction (EDQMI) study. November 8, 2006

Liquid medication errors and dosing tools: a randomized controlled experiment. October 5, 2016

Pictograms, units and dosing tools, and parent medication errors: a randomized study. July 19, 2017

Liquid medication dosing errors by Hispanic parents: role of health literacy and English proficiency. May 31, 2017

Perspectives about racism and patient-clinician communication among black adults with serious illness. July 26, 2023

Reducing prescribing errors in hospitalized children on the ketogenic diet. February 24, 2021

Safety climate and medical errors in 62 US emergency departments. January 9, 2013

The safety of emergency care systems: results of a survey of clinicians in 65 US emergency departments. March 4, 2009

The National Emergency Department Safety Study: study rationale and design. January 9, 2008

Medication use and cognitive impairment among residents of aged care facilities. June 23, 2021

Developing an intervention to reduce harm in hospitalized patients: patients and families in research. December 5, 2018

Detection of postoperative respiratory failure: how predictive is the Agency for Healthcare Research and Quality's Patient Safety Indicator? September 29, 2010

Multistate point-prevalence survey of health care-associated infections. April 9, 2014

Perspectives on patient and family engagement with reduction in harm: the forgotten voice. August 15, 2018

Operational failures detected by frontline acute care nurses. March 29, 2017

Controversy and quality improvement: lingering questions about ethics, oversight, and patient safety research. May 28, 2008

Use of unsolicited patient observations to identify surgeons with increased risk for postoperative complications. March 1, 2017

Prospective validation of classification of intraoperative adverse events (ClassIntra): international, multicentre cohort study. October 7, 2020

ASHP Guidelines on the Safe Use of Automated Compounding Devices for the Preparation of Parenteral Nutrition Admixtures. June 15, 2022

Impact of COVID-19 on inpatient clinical emergencies: a single-center experience. June 9, 2021

Do patients who read visit notes on the patient portal have a higher rate of "loop closure" on diagnostic tests and referrals in primary care? A retrospective cohort study. January 17, 2024

A Department of Medicine infrastructure for patient safety and clinical quality improvement. December 20, 2017

Achieving rapid door-to-balloon times: how top hospitals improve complex clinical systems. March 8, 2006

Positive predictive value of the AHRQ accidental puncture or laceration patient safety indicator. January 20, 2010

Helping patients simplify and safely use complex prescription regimens. March 16, 2011

Experience of wrong site surgery and surgical marking practices among clinicians in the UK. November 15, 2006

Designing an abstraction instrument: lessons from efforts to validate the AHRQ Patient Safety Indicators. January 12, 2011

Implementation of a mandatory checklist of protocols and objectives improves compliance with a wide range of evidence-based intensive care unit practices. July 29, 2009

Factors associated with the use of cognitive aids in operating room crises: a cross-sectional study of US hospitals and ambulatory surgical centers. May 9, 2018

Pain management best practices from multispecialty organizations during the COVID-19 pandemic and public health crises. April 29, 2020

Association of coworker reports about unprofessional behavior by surgeons with surgical complications in their patients. July 10, 2019

CHPSO Annual Reports. July 10, 2024

Patient Safety Innovations

Ambulatory Safety Nets to Reduce Missed and Delayed Diagnoses of Cancer

Annual Perspective

The I-READI Quality and Safety Framework: Strong Communications Channels and Effective Practices to Rapidly Update and Implement Clinical Protocols During a Time of Crisis

Developing and aligning a safety event taxonomy for inpatient psychiatry. July 13, 2022

The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: a summary of data reported to the National Healthcare Safety Network. September 22, 2021

Common general surgical never events: analysis of NHS England never event data. April 7, 2021

From fable to reality at Parkland Hospital: the impact of evidence-based design strategies on patient safety, healing, and satisfaction in an adult inpatient environment. February 10, 2021

A comprehensive estimation of the costs of 30-day postoperative complications using actual costs from multiple, diverse hospitals. October 14, 2020

Covid-19: Assessing the Risk to Public Protection Posed by a Doctor as a Result of Concerns about their Practice during the Pandemic. September 30, 2020

Preserving organizational resilience, patient safety, and staff retention during COVID-19 requires a holistic consideration of the psychological safety of healthcare workers July 8, 2020

Outbreak investigation of COVID-19 among residents and staff of an independent and assisted living community for older adults in Seattle, Washington. June 10, 2020

Closing the loop with ambulatory staff on safety reports. December 4, 2019

A mixed-methods study of challenges experienced by clinical teams in measuring improvement. September 11, 2019

Patient Safety Primers

Managing risk in hazardous conditions: improvisation is not enough. July 24, 2019

How organisations contribute to improving the quality of healthcare. June 12, 2019

Can we import improvements from industry to healthcare? May 1, 2019

Structural racism--a 60-year-old black woman with breast cancer. April 10, 2019

Is excessive resource utilization an adverse event? March 8, 2017

America's Hospitals: Improving Quality and Safety—The Joint Commission's Annual Report 2016. November 23, 2016

Using Kotter's change model for implementing bedside handoff: a quality improvement project. August 24, 2016

Improving safety for hospitalized patients: much progress but many challenges remain. August 17, 2016

Peer support for clinicians: a programmatic approach. July 20, 2016

When doctors share visit notes with patients: a study of patient and doctor perceptions of documentation errors, safety opportunities and the patient–doctor relationship. June 15, 2016

Learning from incidents in healthcare: the journey, not the arrival, matters. April 27, 2016

Understanding why quality initiatives succeed or fail: a sociotechnical systems perspective. March 23, 2016

Rating the raters: the inconsistent quality of health care performance measurement. March 2, 2016

Aviation and healthcare: a comparative review with implications for patient safety. February 3, 2016

Introduction to the STS National Database Series: outcomes analysis, quality improvement, and patient safety. November 18, 2015

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DOI: 10.1177/1049732305275208
Corpus ID: 16245099

Case Study Research: The View From Complexity Science

Ruth A. Anderson , B. Crabtree , +1 author R. McDaniel
Published in Qualitative Health Research 1 May 2005
Medicine, Sociology

318 Citations

Combining case study research and systems theory as a heuristic model.

Highly Influenced

A Complexity Science View of Conflict

Embedding research in health systems: lessons from complexity theory, developing the descarte model, redefining case study, implementing managerial innovations in primary care: can we rank change drivers in complex adaptive organizations, applying complexity theory: a review to inform evaluation design., primary care practice transformation is hard work: insights from a 15-year developmental program of research, a complexity perspective on organisational change : making sense of emerging patterns in self-organising systems, the challenge and promise of complexity theory for teacher education research, 99 references, harnessing complexity: organizational implications of a scientific frontier, complexity and management: fad or radical challenge to systems thinking, theory testing using case studies, case study research: design and methods, the architecture of simplicity, understanding change in primary care practice using complexity theory., theory testing using case studies in business-to-business research, complexity, leadership, and management in healthcare organisations, organizations as adaptive systems in complex environments: the case of china, primary care practice organization and preventive services delivery: a qualitative analysis., related papers.

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Case Study Research: The View From Complexity Science

2005, Qualitative Health Research

Related Papers

Journal of Evaluation in Clinical …

Carmel Martin

Perturbing ongoing conversations about systems and complexity in health services and systems 1. Carmel M. Martin MBBS MSc PhD FRACGP1,*, 2. Joachim P. Sturmberg MBBS DORACOG MFM PhD FRACGP2 Article first published online: 26 MAY 2009 DOI: 10.1111/j.1365-2753.2009.01164.x The term ‘unintended consequences’[1] has become ubiquitous [2] in health policy and delivery circles. We argue that this is a sign of the growing unease arising from the realization of the limitations of the still dominant reductionist research approaches, ‘evidence’ and linear thinking in relation to health system1 and health services2 policy redesigning. Complexity theorists argue that many of the problems of health services and systems will not be solved through the application of more reductionism [3]. The most revered tool in reductionist research is the randomized controlled trial (RCT). However, as Cartwright has pointed out RCTs have very significant limitations for real world problems. ‘The claims of . . . RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. . . . the benefit that the RCT conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. . . . (in order) to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain’[4]. Health services researchers, decision makers and practitioners are now faced with at least two challenges: how to respond to the limitations of current research and decision-making models that have taken us ‘just so far’; and how to integrate other sources of evidence into policy and practice in the real world [5]. What matters is making sense of what is relevant, i.e. how a particular intervention works in the dynamics of particular settings and contexts. It is not very useful to change a system based on deductive, in Cartwright's words – average explanations. As Stengers [3] pointed out – the most useful questions addressing complex problems must imply an open situation: ‘What will the intervention be able to produce?’ and ‘What kind of behaviour will emerge? What are our frames of reference? What are our ideas and values in relation to success?’ In relation to policy development Glouberman, an applied philosopher adds: ‘Frameworks for understanding policy development do not merely describe the process. They invariably indicate what a “well-functioning” process is like. And so they place a value on certain structures and behaviour. As our theories change, so do our views of what is good’[6]. Responses to the challenges to our contemporary frameworks are many and varied. They include the rise of translational research [7], narrative evidence-based medicine [8], the quest for utility in patient-reported outcome measures, together with new statements about trials and multifaceted interventions [9–12]. Acknowledging these challenges is not only a sign of understanding the crisis of scientific knowledge [13], but also evidence that new conversations have started [7,14,15]. Common to complex systems are two fundamental themes – the universal interconnectedness and interdependence of all phenomena, and the intrinsically dynamic nature of reality [16]. ‘At each level of complexity we encounter systems that are integrated, self-organizing wholes consisting of smaller parts and, at the same time, acting as parts of larger wholes’[17]. Notable international examples of an emerging and evolving discourse about complex systems in health services research and quality improvement include the Institute of Medicine's report ‘Crossing the Quality Chasm’[18] with a resultant series of US quality initiatives, and Glouberman and Zimmerman's report to the Romanow Commission in Canada [19]. Approaches to understanding complex systems developed by Kurtz and Snowden [20] for IBM international e-business management have been successfully applied, with frontline health care providers taking a lead to improve outcomes in the successful redesign of New York State Veteran's Affairs [21]. Other examples include the successes of taking a systems approach to tobacco control on overall smoking rates within the Veterans Affairs health services clients [22] and in the broader health systems against major resistance by the licit and illicit tobacco industry [23,24]. Ongoing challenges to smoking cessation and tobacco control strategies remain. Deprived communities are not only at greater risk from the adverse effects of smoking related morbidity, they are also at greater risk from social factors that predispose to smoking. In addition, social and environmental factors such as unemployment interact with endogenous or biological risk factors such as a predisposition to anxiety or other mental illness. As Galea et al.[25] argued in a overview of the social epidemiology of smoking, there are complex multiple interacting factors at individual and societal levels (biopsychosocial levels). In the future, it is important to make sense of the complexity ‘of not only how social factors may influence substance use in isolation but also how social factors may modify relations between biological characteristics and substance use behaviour’[25]. Atun [26], Evans [27] and Shiell [28] have recognized that economic evaluations of a complex adaptive health system need to encompass multiple perspectives and dynamic influences in an environment. For example, opportunity costs result from a decision to take a certain approach that entails not pursuing or even considering some options [29]. These opportunity costs are important in health service decision making, as a basis for efficient use of resources. Reductionist analysis of opportunity costs is content with restricted possibilities, i.e. it accepts the categorical exclusion of certain individuals or community considerations in its economic evaluations, that later show up as unintended consequences on the wider health system. For example, studies exploring the economic impact of doctor behaviours suggest that ‘assigning a monetary value (aiming to reduce opportunity costs) to every aspect of a doctor's time and effort may actually reduce productivity, impair the overall quality of performance, and thereby even increase costs' [30]. The focus on the monetary value of narrowly defined tasks incurs an opportunity cost as it undermines doctors' social contract for altruism with patients, society and other professionals [30], outweighing the ‘calculated benefits accrued’[31]. This example and others demonstrate that narrowly focused and static evaluations cannot assess the true efficiencies in complex health systems [29]. Slowness in the uptake of complexity 1. Top of page 2. Slowness in the uptake of complexity 3. The way forward 4. References Somewhat surprisingly, despite the flurry of interest in recent decades, diffusion of knowledge and innovation about complexity and adaptation in systems for health care has been slow [15,28]. Reductionism remains the dominant paradigm and is increasingly influencing policy like the introduction of simple disease management protocols or pay-for-performance targets [30]. Clinician work is increasingly being reduced to a series of discrete activities based on a business model driven by the agenda of cost containment [30] rather than improved patient health. Moreover, there has been almost no discourse to distinguish what is amenable to reductionist approaches and what is not, and how to apply holism and holistic frameworks and approaches. Why might this be the case? Singer, the Director of the Max Planck Institute for Brain Research in Frankfurt, Germany provides important insights towards answering this question [32]. The rise of human culture and civilization, great works of philosophy, literature and art or the modern communication systems via the Internet and the blackberry are not explained by our decentrally organized brains, and the dynamic states and plasticity of the many billions of linked and interacting neurons in the brain. Both our brains and our social organizations have evolved to be complex, dynamic and adaptable with emergent properties not explained by the structures that they contain. Singer reflects, apparently, ‘our cognitive abilities have evolved in a world in which there was no advantage to be gained by understanding nonlinear complex multidimensional processes’[32]. Whether or not the current dominance of reductionism [13] is a social or an evolutionary brain phenomenon, in history, there has always been the counter position of holism. As stated by the eminent Greek philosopher Aristotle [33], ‘the whole is greater than the sum of the parts’. Thus, despite a tendency to reductionism, ‘this does not mean that we cannot or will not develop analytical methods to identify these (complex) system states and to track them chronologically; however, the descriptions will be abstract and vague, and will bear no similarity to our familiar perceptions and concepts’[32]. So we must conterintuitively work to develop appropriate abstract frameworks and categories, and reflect on our ways of knowing, if we are to gain a deeper understanding of the processes that operate in complex systems, and how to intervene more successfully [29,32]. Our main imperative to go beyond the more intuitive and reductive is the lack of success of many well-intended health services interventions [34,35] and the unintended consequences of interventions in the real world of health systems [36–38]. However, many may still see the current limitations in knowledge and practice, as a stimulus to more rules, and greater compartmentalization, categorization, description and reductive measurement of the complex processes of the health systems in which we operate rather than take up the challenges of Singer, Sengers and many others [9]. Yet the imperative to act is now, to communicate through complexity science and knowledge to make visible and comprehensible, the dynamics of health and health care, else approaches based on easily measured phenomenon will prevail in health systems. As Delamothe in the British Medical Journal says, ‘In the current financial and political climate is it wise to defend (primary) care solely by invoking its warm fuzzy heart, beating away in its black box, far from the close scrutiny of all but its adepts’[39]? Making a plea for innovation and real world dynamic understandings in a different context, Lawrence Green, an international public health expert says: ‘Public health asks of systems science, as it did of sociology 40 years ago, that it help us unravel the complexity of causal forces in our varied populations and the ecologically layered community and societal circumstances of public health practice. We seek a more evidence-based public health practice, but too much of our evidence comes from artificially controlled research that does not fit the realities of practice. What can we learn from our experience with sociology in the past that might guide us in drawing effectively on systems science’[40]? Thus dissatisfaction with the status quo may well be the tipping point away from reductionist approaches [31]. Yet, will the ground work for innovation and change be sufficiently advanced when the time comes, that the reductionist approach can no longer cope with both the enormous amount of information that comes from sciences, technologies and social sciences – and the astonishing complexity that they reveal? Do we have the ways forward towards knowledge frameworks and the methodological developments to support approaches working in complex health services and wider health systems? This new Forum takes up this challenge of accelerating the exposition, understanding and promotion of complexity and health services, research and evaluation of health systems, and bringing together those who are currently working busily away on this complexity enterprise in isolation. The way forward 1. Top of page 2. Slowness in the uptake of complexity 3. The way forward 4. References We concur with Pizzocaro who stated that ‘the awareness of complexity does not imply answering questions or solving problems: rather, it means opening problems up to dynamic reality, as well as increasing the relative level of awareness. Thus, the notion of complexity – whatever the discipline, strongly supports the possibility that – given a form of scientific investigation – questions and answers may change, as well as the nature of questions and answers upon which scientific investigation is built’[41]. In this sense, complexity may be seen as an opportunity rather than a constraint, and consequently assumed as a challenge [42]. Some ‘wicked questions’ might include: what might complexity formulations look like? How can we make sense of the impact of the capacity of an individual, an organization or a system to adapt to local needs and constraints to improve quality of life? How can we increase patient, practitioner, and health system intelligence and adaptability to changing needs? We need to continue to perturb, reflect and act on the vast knowledge that exists within and outside of our individual disciplines, including linking with other systems approaches such as systems biology and systems in biomedicine. Vast amounts of knowledge about our systems will likely emerge by looking at what we know through new eyes. Thus, in particular, we need to think deeply about changes to our conceptual frameworks and principles, and the methods we use. On the whole, complexity theory and science provide approaches to an uncertain and dynamic reality to make sense of dynamic emergent reality, which changes as we observe it. Embracing or reframing theories and designing research as we proceed will inform the dynamic health systems in which we operate. Broad areas of theoretical and scientific development that signify important emerging influences in shaping health and health care systems are: * 1 philosophy, conceptual, and theoretical debates and developments; * 2 non-linear dynamics and mathematical analyses of complex adaptive care; and * 3 narratives and participatory action research to make sense of and to shape local system design. Different research strategies and multiple methods are needed to make sense of complex health care systems that encompass systems and subsystems of * • systems biology and translational medicine; * • clinical care and patient-centred medicine; * • health service organization and evaluation; * • health policy and determinants of health; and * • education for medicine, nursing, pharmacy, dentistry, therapists and all health workers. It is helpful to see evidence in terms of simple and complicated systems, and complex and chaotic systems, and the transitions between these states. We hope that the new Forum and debates will address questions about and provide examples of how complexity in health systems research can be approached – theoretically and methodologically? What are the tools of the trade – do they differ from or are they located within current mainstream research? Or is it that philosophy and theoretical frameworks are different? We will be publishing peer reviewed research papers using mathematical dynamics and clustering, philosophical analysis, narrative research and economic evaluation. The next issue will explore a variety of approaches contributing to a broader understanding of the complex nature of health and health care. The third forum will examine health system reform issues from a complexity perspective. Health policy is the theme of the fourth forum. The final forum focuses on education and economics. We hope to provide a stimulus for health services research and policy to open up to look outside the box – the nature of human health, environment, socioeconomics, organization, informatics, education, work practices etc – all of which are the scope of the Forum and journal. The editors of the new Forum hope that it will evolve into a full Supplement from 2010 onwards, and we are keenly looking forward to your comments and inputs. The trick in any great social project is to stop looking at the discrete elements and start trying to understand the complex relationships between them. By studying fascinating real-life examples of social change through this systems-and-relationships lens, for example one can begin to tease out the rules of engagement between patients, health care providers, organizations and circumstance [43]. References 1. Top of page 2. Slowness in the uptake of complexity 3. The way forward 4. References * 1 Merton, R. K. (1936) The unanticipated consequences of purposive social action. American Sociological Review, 1 (6), 894–904. o CrossRef, o Web of Science® Times Cited: 289 * 2 Institute of Medicine (2001) Unintended Consequences of Health Policy Programs and Policies: Workshop Summary. Washington, D.C.: Institute of Medicine. * 3 Stengers, I. (2004) The challenge of complexity: unfolding the ethics of science. In memoriam Ilya Prigogine. Emergency: Complexity & Organization, 6 (1–2), 92–99. * 4 Cartwright, N. (2007) Are RCTs the gold standard? BioSocieties, 2, 11–20. o CrossRef * 5 Young, C. & Godlee, F. (2008) The BMJ evidence centre. British Medical Journal, 337, a2438. o CrossRef, o PubMed, o Web of Science® Times Cited: 1 * 6 Glouberman, S. (2003) Towards a New Perspective on Health Policy. Final Report CPRN Study No. H|03. Available at http://www.healthandeverything.org (last accessed 1 April 2009). * 7 Ash, J. S., Anderson, N. R. & Tarczy-Hornoch, P. (2008) People and organizational issues in research systems implementation. Journal of the American Medical Informatics Association: JAMIA, 15 (3), 283–289. o CrossRef, o PubMed, o Web of Science® Times Cited: 6 * 8 Charon, R., Wyer, P., for the NEBM Working Group. (2008) Perspectives, narrative evidence based medicine. The Lancet, 371 (9609), 296–297. o CrossRef, o PubMed, o Web of Science® Times Cited: 9 * 9 Craig, P., Dieppe, P., Macintyre, S., Michie, S., Nazareth, I. & Petticrew, M. (2008) Developing and evaluating complex interventions: the new Medical Research Council guidance. British Medical Journal, 337, a1655. o CrossRef, o PubMed, o Web of Science® Times Cited: 28 * 10 Featherstone, K. & Donovan, J. L. (1998) Random allocation or allocation at random? Patients' perspectives of participation in a randomised controlled trial. 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Copenhagen: WHO Regional Office for Europe's Health Evidence Network (HEN). http://www.who.dk/document/Hen/primaryspecialist.pdf (last accessed 7 April 2009). * 27 Evans, T., Nishtar, S. & Atun, R. et al. (2008) Scaling up research and learning for health systems: time to act. The Lancet, 372, 1529–1531. o CrossRef, o PubMed, o Web of Science® Times Cited: 2 * 28 Shiell, A., Hawe, P. & Gold, L. (2008) Complex interventions or complex systems? Implications for health economic evaluation. British Medical Journal, 336 (7656), 1281–1283. o CrossRef, o PubMed, o Web of Science® Times Cited: 12 * 29 Auyang, S. Y. (1998) Foundations of Complex-system Theories in Economics, Evolutionary Biology, and Statistical Physics. Cambridge: Cambridge University Press. o CrossRef * 30 Hartzband, P. & Groopman, J. (2009) Money and the changing culture of medicine. 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(2008) The net fiscal impact of a chronic disease management program: Indiana Medicaid. Health Affairs, 27 (3), 855–864. o CrossRef, o PubMed, o Web of Science® Times Cited: 6 * 36 Meadowcroft, J. (2008) Patients, politics, and power: government failure and the politicization of U.K. Health Care. The Journal of Medicine and Philosophy, 33 (5), 427–444. o CrossRef, o PubMed, o Web of Science® Times Cited: 2 * 37 Solberg, L. I., Kottke, T. E., Brekke, M. L., Magnan, S., Davidson, G., Calomeni, C. A. & Conn, S. A. (2000) Failure of a continuous quality improvement intervention to increase the delivery of preventive services. A randomized trial. Effective Clinical Practice: ECP, 3 (3), 105–115. o PubMed, o ChemPort * 38 Anderson, I. (2004) A health development agenda for Indigenous Australians. In UniNews. Melbourne: University of Melbourne. http://www.uninews.unimelb.edu.au/news/1606 * 39 Delamothe, T. (2008) A good QOFfing whine. 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(2007) Knowledge, capacity, and readiness: translating successful experiences in community-based participatory research for health promotion. Pimatisiwin: A Journal of Aboriginal and Indigenous Community Health, 5 (2), 125–151. Footnotes * 1 A health system incorporates health services and broad social systems that influence human wellbeing and survival. * 2 Health services are specific entities responsible for conducting activities to directly improve health. Examples include a doctor's office, cancer care centres, emergency departments. Health services are subsystems of a broader health system.

Journal of Multidisciplinary Healthcare

Social Science & Medicine

Tim Tenbensel

BMC Health Services Research

Carl Savage

Background Successful application of Quality Improvement (QI) methods is challenging, and awareness of the role context plays has increased. Complexity science has been advocated as a way to inform change efforts. However, empirical support is scarce, and it is still difficult to grasp the practical implications for QI interventions. The aim of this study was to use a complexity-based leadership framework to explain how managers in a clinical department addressed external requirements to cut costs without compromising patient outcomes and experience. Methods Explanatory case study design of a Danish OB/GYN department tasked to improve efficiency. Data came from documents, 30 interviews, and 250 h of observations over 3 years. A Complexity Analysis Framework that combined two complexity-based leadership frameworks was developed to analyze all changes implemented to reduce cost, while maintaining clinical quality. Results Managers reframed the efficiency requirement as an opportunity ...

Journal of advanced nursing

Jo Rycroft-Malone

To examine the application of core concepts from Complexity Theory to explain the findings from a process evaluation undertaken in a trial evaluating implementation strategies for recommendations about reducing surgical fasting times. The proliferation of evidence-based guidance requires a greater focus on its implementation. Theory is required to explain the complex processes across the multiple healthcare organizational levels. This social healthcare context involves the interaction between professionals, patients and the organizational systems in care delivery. Complexity Theory may provide an explanatory framework to explain the complexities inherent in implementation in social healthcare contexts. A secondary thematic analysis of qualitative process evaluation data informed by Complexity Theory. Seminal texts applying Complexity Theory to the social context were annotated, key concepts extracted and core Complexity Theory concepts identified. These core concepts were applied as...

Erika Kustra

Health Care …

Michelle Jordan

Handbook of Systems and Complexity in Health

Joachim Sturmberg

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Case study research: the view from complexity science.

Many wonder why there has been so little change in care quality despite substantial quality improvement efforts. Questioning why current approaches are not making true changes draws attention to the organization as a source of answers. The authors bring together the case study method and complexity science to suggest new ways to study health care organizations. The case study provides a method for studying systems. Complexity theory suggests that keys to understanding the system are contained in patterns of relationships and interactions among the system's agents. They propose some of the "objects" of study that are implicated by complexity theory and discuss how studying these using case methods might provide useful maps of the system. They offer complexity theory, partnered with case study method, as a place to begin the daunting task of studying a system as an integrated whole.

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A scoping review of complexity science in nursing

Affiliations.

1 Faculty of Health and Occupational Studies, Department of Caring Science, University of Gävle, Gävle, Sweden.
2 Department of Neurobiology, Care Sciences and Society, Division of Clinical geriatrics, Karolinska Institutet, Stockholm, Sweden.
3 School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden.
4 Health Services Research, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.
5 Centre for Clinical Research, Västmanland County Hospital, Västerås, Sweden.
6 Unit of Anaesthesiology and Intensive Care, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
PMID: 32281684
DOI: 10.1111/jan.14382

Abstract in English, Chinese

Aim: To describe how complexity science has been integrated into nursing.

Design: A scoping review.

Data source/review method: Academic Search Elite, Scopus, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, PubMed and Web of Science were searched November 2016, updated in October 2017 and January 2020. The working process included: problem identification, literature search, data evaluation, synthesizing and presentation.

Results: Four categories were found in the included 89 articles: (a) how complexity science is integrated into the nursing literature in relation to nursing education and teaching; (b) patients' symptoms, illness outcome and safety as characteristics of complexity science in nursing; (c) that leaders and managers should see organizations as complex and adaptive systems, rather than as linear machines; and (d) the need for a novel approach to studying complex phenomena such as healthcare organizations. Lastly, the literature explains how complexity science has been incorporated into the discourse in nursing and its development.

Conclusion: The review provided strong support for use in complexity science in the contemporary nursing literature. Complexity science is also highly applicable and relevant to clinical nursing practice and nursing management from an organizational perspective. The application of complexity science as a tool in the analysis of complex nursing systems could improve our understanding of effective interactions among patients, families, physicians and hospital and skilled nursing facility staff as well as of education.

Impact: Understanding complexity science in relation to the key role of nurses in the healthcare environment can improve nursing work and nursing theory development. The use of complexity science provides nurses with a language that liberates them from the reductionist view on nursing education, practice and management.

目的: 描述复杂性科学如何融入护理学。设计: 范围评估。数据来源/评估方法: 于2016年11月检索学术期刊全文数据库、Scopus、PsycINFO、护理和联合卫生文献累积索引、PubMed和科学引文索引数据库,并分别于2017年10月和2020年1月更新检索。工作流程包括:问题识别、文献检索、数据评估、综合汇总与呈现展示。结果: 纳入的89篇文章可分为四类:(1)复杂性科学在护理教育教学中如何融入护理学文献;(2)护理学中以病人症状、疾病结局和安全性为特征的复杂性科学;(c)领导者和管理者应将组织视为复杂适应性系统,而非线性机器;以及(d)需要一种新型方法来研究诸如医疗保健组织等的复杂现象。最后,文献还对复杂性科学是如何被纳入护理学话语及其发展进行了解释说明。结论: 本项评估工作为当代护理学文献中复杂性科学的应用提供了有力的支持。从组织的角度来看,复杂性科学对临床护理实践和护理管理也具有高度的适用性和相关性。将复杂性科学作为分析复杂护理系统的工具,有助于增进我们对患者、家庭、医生、医院和专业护理机构工作人员之间有效互动以及教育的理解。影响: 了解与护士在医疗保健环境中的关键作用相关的复杂性科学可促进护理工作和护理理论的发展。复杂性科学的应用为护士提供了一门语言,使他们从护理教育、实践和管理的还原主义观点中解放出来。.

Keywords: complex adaptive systems; complexity science; nursing; scoping review.

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The application of complexity science to business

Management Decision

ISSN : 0025-1747

Article publication date: 1 August 2006

Wilding, R. (2006), "The application of complexity science to business", Management Decision , Vol. 44 No. 7. https://doi.org/10.1108/md.2006.00144gaa.001

Emerald Group Publishing Limited

My interest in complexity science, in particular Chaos Theory started in the early 1990s. After working in industry for a number of years and then “accidentally” falling into academia I decided it would be interesting to undertake doctorial research in my spare time. As with most doctorial students I only really understood what I had let myself in for once commencing my studies. My area of study was the relatively new area of supply chain management and in particular the generation of uncertainty by the methods used to manage inventory. At the time I was working at the University of Warwick and a chance conversation got me thinking about the possibility that the systems and equations I was looking at were generating deterministic chaos. Within Warwick there were a number of thought leaders in this area Professor Ian Stewart the Mathematician and author of Does God Play Dice? ( Stewart, 1989 ), Professor George Rowlands the physicist and developer of chaos analysis tools ( Sprott and Rowlands, 1995 ) and Professor Jackie McGlade, the biologist who had applied chaos theory to eco-system development. Through meetings and discussions in this multidisciplinary environment methodologies were developed and I was able to demonstrate that supply chains do actually behave chaotically under certain conditions. With this type of research the critical issue to demonstrate relevance to practicing managers and those in business and this was done creating new guidelines for supply chain design. My work in this area was completed in 1998 ( Wilding, 1998a, b ) but I still follow with interest how complexity science is applied into business and the new insights it provides.

With this background the opportunity to act as editor for a special issue in this area captured my interest. The application of complexity science to business has always been a difficult area because the concepts are complex and sometimes demonstrating relevance to a practicing manager is hard. The call for papers for this special issue required the following criteria to be met. Papers should:

focus on the application of complexity science and its sub-areas to business;

demonstrate the significant impact that complexity science can have on everyday managerial practice;

demonstrate practical application to business; and

provide a showcase for excellent examples of applied research and practical cases.

The papers selected for this issue cover a variety of perspectives. Our first paper by Pina e Cunha and Vieira da Cunha presents a model of strategy from a complexity perspective. The model integrates research from a variety of areas of complexity science and uses them as a “lens” to understand the strategic process of organisations in highly dynamic environments.

This is followed by Smith and Graetz presenting a discussion of how complexity theory can be used as a guide to creating organisations. Traditional views on organising are focused on the reduction of uncertainty and the potential for chaos, but this approach can curtail innovation. By creating organisations operating on the “edge of chaos” (but not full chaos) innovation can be enhanced.

Cruz, Pedrozo and Estivalete’s paper also uses complexity science as a “lens”. In their paper they look at the evolution of strategy of organisations in pursuit of sustainable development using the contributions of Edgar Morin as a foundation. This provides an interesting insight for managers who choose to apply such approaches.

Paraskevas presents an interesting approach of using complexity science as a lens to view the development of crisis and crisis management within organisations. This work, through the use of a case study shows that complexity science can provide an alternative more informed view of a “crisis” environment.

Blecker and Abdelkafi use Suh’s complexity theory to address a problem experienced by many organisations, the management of complexity and variety within a business. This work provides insights into strategies for the management of complexity and variety within highly responsive environments.

A novel approach to using complexity science is then presented by Sharif and Irani. Specifically “a fussy-morphological approach” to modelling managerial decision making. This technical paper demonstrates the “rich” understanding that can be gained of an environment by applying complex systems thinking to such problems.

Finally, Gregory elegantly establishes how complexity theory can be used to view the development of our economy and society. Arguing that events such as the industrial revolution can be seen as a bifurcation points and our age where “mass media holds us in a state of collective paralysis” is providing a foundation for a second bifurcation launching “The Values Revolution”.

The above papers provide an interesting cross section of the types of research being undertaken in the area of complexity science.

Finally I would like to thank the 40 reviewers from industry and academia who supported this special issue and all the authors of submitted papers both those who were successful in being included in this special edition but also those who are re-working their papers for possible inclusion in future publications.

The application of complexity science to business is an area great potential for research. The key is to take these ideas and make them relevant to practitioners; I hope the articles in this special edition will provoke discussion and further work in this area.

Richard Wilding Guest Editor

Sprott, J.C. and Rowlands, G. (1995), Chaos Data Analyser, 2nd ed., Physics Academic Software, New York, NY

Stewart, I. (1989), Does God Play Dice?, Penguin, London

Wilding, R.D. (1998a), “Chaos theory: implications for supply chain management”, International Journal of Logistics Management, Vol. 9 No. 1, pp. 43–56

Wilding, R.D. (1998b), “The supply chain complexity triangle: uncertainty generation in the supply chain”, International Journal of Physical Distribution & Logistics Management, Vol. 28 No. 8, pp. 599–616

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Open access
Published: 10 November 2020

Case study research for better evaluations of complex interventions: rationale and challenges

Sara Paparini ORCID: orcid.org/0000-0002-1909-2481 1 ,
Judith Green 2 ,
Chrysanthi Papoutsi 1 ,
Jamie Murdoch 3 ,
Mark Petticrew 4 ,
Trish Greenhalgh 1 ,
Benjamin Hanckel 5 &
Sara Shaw 1

BMC Medicine volume 18 , Article number: 301 ( 2020 ) Cite this article

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The need for better methods for evaluation in health research has been widely recognised. The ‘complexity turn’ has drawn attention to the limitations of relying on causal inference from randomised controlled trials alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes. We argue that case study research—currently denigrated as poor evidence—is an under-utilised resource for not only providing evidence about context and transferability, but also for helping strengthen causal inferences when pathways between intervention and effects are likely to be non-linear.

Case study research, as an overall approach, is based on in-depth explorations of complex phenomena in their natural, or real-life, settings. Empirical case studies typically enable dynamic understanding of complex challenges and provide evidence about causal mechanisms and the necessary and sufficient conditions (contexts) for intervention implementation and effects. This is essential evidence not just for researchers concerned about internal and external validity, but also research users in policy and practice who need to know what the likely effects of complex programmes or interventions will be in their settings. The health sciences have much to learn from scholarship on case study methodology in the social sciences. However, there are multiple challenges in fully exploiting the potential learning from case study research. First are misconceptions that case study research can only provide exploratory or descriptive evidence. Second, there is little consensus about what a case study is, and considerable diversity in how empirical case studies are conducted and reported. Finally, as case study researchers typically (and appropriately) focus on thick description (that captures contextual detail), it can be challenging to identify the key messages related to intervention evaluation from case study reports.

Whilst the diversity of published case studies in health services and public health research is rich and productive, we recommend further clarity and specific methodological guidance for those reporting case study research for evaluation audiences.

Peer Review reports

The need for methodological development to address the most urgent challenges in health research has been well-documented. Many of the most pressing questions for public health research, where the focus is on system-level determinants [ 1 , 2 ], and for health services research, where provisions typically vary across sites and are provided through interlocking networks of services [ 3 ], require methodological approaches that can attend to complexity. The need for methodological advance has arisen, in part, as a result of the diminishing returns from randomised controlled trials (RCTs) where they have been used to answer questions about the effects of interventions in complex systems [ 4 , 5 , 6 ]. In conditions of complexity, there is limited value in maintaining the current orientation to experimental trial designs in the health sciences as providing ‘gold standard’ evidence of effect.

There are increasing calls for methodological pluralism [ 7 , 8 ], with the recognition that complex intervention and context are not easily or usefully separated (as is often the situation when using trial design), and that system interruptions may have effects that are not reducible to linear causal pathways between intervention and outcome. These calls are reflected in a shifting and contested discourse of trial design, seen with the emergence of realist [ 9 ], adaptive and hybrid (types 1, 2 and 3) [ 10 , 11 ] trials that blend studies of effectiveness with a close consideration of the contexts of implementation. Similarly, process evaluation has now become a core component of complex healthcare intervention trials, reflected in MRC guidance on how to explore implementation, causal mechanisms and context [ 12 ].

Evidence about the context of an intervention is crucial for questions of external validity. As Woolcock [ 4 ] notes, even if RCT designs are accepted as robust for maximising internal validity, questions of transferability (how well the intervention works in different contexts) and generalisability (how well the intervention can be scaled up) remain unanswered [ 5 , 13 ]. For research evidence to have impact on policy and systems organisation, and thus to improve population and patient health, there is an urgent need for better methods for strengthening external validity, including a better understanding of the relationship between intervention and context [ 14 ].

Policymakers, healthcare commissioners and other research users require credible evidence of relevance to their settings and populations [ 15 ], to perform what Rosengarten and Savransky [ 16 ] call ‘careful abstraction’ to the locales that matter for them. They also require robust evidence for understanding complex causal pathways. Case study research, currently under-utilised in public health and health services evaluation, can offer considerable potential for strengthening faith in both external and internal validity. For example, in an empirical case study of how the policy of free bus travel had specific health effects in London, UK, a quasi-experimental evaluation (led by JG) identified how important aspects of context (a good public transport system) and intervention (that it was universal) were necessary conditions for the observed effects, thus providing useful, actionable evidence for decision-makers in other contexts [ 17 ].

The overall approach of case study research is based on the in-depth exploration of complex phenomena in their natural, or ‘real-life’, settings. Empirical case studies typically enable dynamic understanding of complex challenges rather than restricting the focus on narrow problem delineations and simple fixes. Case study research is a diverse and somewhat contested field, with multiple definitions and perspectives grounded in different ways of viewing the world, and involving different combinations of methods. In this paper, we raise awareness of such plurality and highlight the contribution that case study research can make to the evaluation of complex system-level interventions. We review some of the challenges in exploiting the current evidence base from empirical case studies and conclude by recommending that further guidance and minimum reporting criteria for evaluation using case studies, appropriate for audiences in the health sciences, can enhance the take-up of evidence from case study research.

Case study research offers evidence about context, causal inference in complex systems and implementation

Well-conducted and described empirical case studies provide evidence on context, complexity and mechanisms for understanding how, where and why interventions have their observed effects. Recognition of the importance of context for understanding the relationships between interventions and outcomes is hardly new. In 1943, Canguilhem berated an over-reliance on experimental designs for determining universal physiological laws: ‘As if one could determine a phenomenon’s essence apart from its conditions! As if conditions were a mask or frame which changed neither the face nor the picture!’ ([ 18 ] p126). More recently, a concern with context has been expressed in health systems and public health research as part of what has been called the ‘complexity turn’ [ 1 ]: a recognition that many of the most enduring challenges for developing an evidence base require a consideration of system-level effects [ 1 ] and the conceptualisation of interventions as interruptions in systems [ 19 ].

The case study approach is widely recognised as offering an invaluable resource for understanding the dynamic and evolving influence of context on complex, system-level interventions [ 20 , 21 , 22 , 23 ]. Empirically, case studies can directly inform assessments of where, when, how and for whom interventions might be successfully implemented, by helping to specify the necessary and sufficient conditions under which interventions might have effects and to consolidate learning on how interdependencies, emergence and unpredictability can be managed to achieve and sustain desired effects. Case study research has the potential to address four objectives for improving research and reporting of context recently set out by guidance on taking account of context in population health research [ 24 ], that is to (1) improve the appropriateness of intervention development for specific contexts, (2) improve understanding of ‘how’ interventions work, (3) better understand how and why impacts vary across contexts and (4) ensure reports of intervention studies are most useful for decision-makers and researchers.

However, evaluations of complex healthcare interventions have arguably not exploited the full potential of case study research and can learn much from other disciplines. For evaluative research, exploratory case studies have had a traditional role of providing data on ‘process’, or initial ‘hypothesis-generating’ scoping, but might also have an increasing salience for explanatory aims. Across the social and political sciences, different kinds of case studies are undertaken to meet diverse aims (description, exploration or explanation) and across different scales (from small N qualitative studies that aim to elucidate processes, or provide thick description, to more systematic techniques designed for medium-to-large N cases).

Case studies with explanatory aims vary in terms of their positioning within mixed-methods projects, with designs including (but not restricted to) (1) single N of 1 studies of interventions in specific contexts, where the overall design is a case study that may incorporate one or more (randomised or not) comparisons over time and between variables within the case; (2) a series of cases conducted or synthesised to provide explanation from variations between cases; and (3) case studies of particular settings within RCT or quasi-experimental designs to explore variation in effects or implementation.

Detailed qualitative research (typically done as ‘case studies’ within process evaluations) provides evidence for the plausibility of mechanisms [ 25 ], offering theoretical generalisations for how interventions may function under different conditions. Although RCT designs reduce many threats to internal validity, the mechanisms of effect remain opaque, particularly when the causal pathways between ‘intervention’ and ‘effect’ are long and potentially non-linear: case study research has a more fundamental role here, in providing detailed observational evidence for causal claims [ 26 ] as well as producing a rich, nuanced picture of tensions and multiple perspectives [ 8 ].

Longitudinal or cross-case analysis may be best suited for evidence generation in system-level evaluative research. Turner [ 27 ], for instance, reflecting on the complex processes in major system change, has argued for the need for methods that integrate learning across cases, to develop theoretical knowledge that would enable inferences beyond the single case, and to develop generalisable theory about organisational and structural change in health systems. Qualitative Comparative Analysis (QCA) [ 28 ] is one such formal method for deriving causal claims, using set theory mathematics to integrate data from empirical case studies to answer questions about the configurations of causal pathways linking conditions to outcomes [ 29 , 30 ].

Nonetheless, the single N case study, too, provides opportunities for theoretical development [ 31 ], and theoretical generalisation or analytical refinement [ 32 ]. How ‘the case’ and ‘context’ are conceptualised is crucial here. Findings from the single case may seem to be confined to its intrinsic particularities in a specific and distinct context [ 33 ]. However, if such context is viewed as exemplifying wider social and political forces, the single case can be ‘telling’, rather than ‘typical’, and offer insight into a wider issue [ 34 ]. Internal comparisons within the case can offer rich possibilities for logical inferences about causation [ 17 ]. Further, case studies of any size can be used for theory testing through refutation [ 22 ]. The potential lies, then, in utilising the strengths and plurality of case study to support theory-driven research within different methodological paradigms.

Evaluation research in health has much to learn from a range of social sciences where case study methodology has been used to develop various kinds of causal inference. For instance, Gerring [ 35 ] expands on the within-case variations utilised to make causal claims. For Gerring [ 35 ], case studies come into their own with regard to invariant or strong causal claims (such as X is a necessary and/or sufficient condition for Y) rather than for probabilistic causal claims. For the latter (where experimental methods might have an advantage in estimating effect sizes), case studies offer evidence on mechanisms: from observations of X affecting Y, from process tracing or from pattern matching. Case studies also support the study of emergent causation, that is, the multiple interacting properties that account for particular and unexpected outcomes in complex systems, such as in healthcare [ 8 ].

Finally, efficacy (or beliefs about efficacy) is not the only contributor to intervention uptake, with a range of organisational and policy contingencies affecting whether an intervention is likely to be rolled out in practice. Case study research is, therefore, invaluable for learning about contextual contingencies and identifying the conditions necessary for interventions to become normalised (i.e. implemented routinely) in practice [ 36 ].

The challenges in exploiting evidence from case study research

At present, there are significant challenges in exploiting the benefits of case study research in evaluative health research, which relate to status, definition and reporting. Case study research has been marginalised at the bottom of an evidence hierarchy, seen to offer little by way of explanatory power, if nonetheless useful for adding descriptive data on process or providing useful illustrations for policymakers [ 37 ]. This is an opportune moment to revisit this low status. As health researchers are increasingly charged with evaluating ‘natural experiments’—the use of face masks in the response to the COVID-19 pandemic being a recent example [ 38 ]—rather than interventions that take place in settings that can be controlled, research approaches using methods to strengthen causal inference that does not require randomisation become more relevant.

A second challenge for improving the use of case study evidence in evaluative health research is that, as we have seen, what is meant by ‘case study’ varies widely, not only across but also within disciplines. There is indeed little consensus amongst methodologists as to how to define ‘a case study’. Definitions focus, variously, on small sample size or lack of control over the intervention (e.g. [ 39 ] p194), on in-depth study and context [ 40 , 41 ], on the logic of inference used [ 35 ] or on distinct research strategies which incorporate a number of methods to address questions of ‘how’ and ‘why’ [ 42 ]. Moreover, definitions developed for specific disciplines do not capture the range of ways in which case study research is carried out across disciplines. Multiple definitions of case study reflect the richness and diversity of the approach. However, evidence suggests that a lack of consensus across methodologists results in some of the limitations of published reports of empirical case studies [ 43 , 44 ]. Hyett and colleagues [ 43 ], for instance, reviewing reports in qualitative journals, found little match between methodological definitions of case study research and how authors used the term.

This raises the third challenge we identify that case study reports are typically not written in ways that are accessible or useful for the evaluation research community and policymakers. Case studies may not appear in journals widely read by those in the health sciences, either because space constraints preclude the reporting of rich, thick descriptions, or because of the reported lack of willingness of some biomedical journals to publish research that uses qualitative methods [ 45 ], signalling the persistence of the aforementioned evidence hierarchy. Where they do, however, the term ‘case study’ is used to indicate, interchangeably, a qualitative study, an N of 1 sample, or a multi-method, in-depth analysis of one example from a population of phenomena. Definitions of what constitutes the ‘case’ are frequently lacking and appear to be used as a synonym for the settings in which the research is conducted. Despite offering insights for evaluation, the primary aims may not have been evaluative, so the implications may not be explicitly drawn out. Indeed, some case study reports might properly be aiming for thick description without necessarily seeking to inform about context or causality.

Acknowledging plurality and developing guidance

We recognise that definitional and methodological plurality is not only inevitable, but also a necessary and creative reflection of the very different epistemological and disciplinary origins of health researchers, and the aims they have in doing and reporting case study research. Indeed, to provide some clarity, Thomas [ 46 ] has suggested a typology of subject/purpose/approach/process for classifying aims (e.g. evaluative or exploratory), sample rationale and selection and methods for data generation of case studies. We also recognise that the diversity of methods used in case study research, and the necessary focus on narrative reporting, does not lend itself to straightforward development of formal quality or reporting criteria.

Existing checklists for reporting case study research from the social sciences—for example Lincoln and Guba’s [ 47 ] and Stake’s [ 33 ]—are primarily orientated to the quality of narrative produced, and the extent to which they encapsulate thick description, rather than the more pragmatic issues of implications for intervention effects. Those designed for clinical settings, such as the CARE (CAse REports) guidelines, provide specific reporting guidelines for medical case reports about single, or small groups of patients [ 48 ], not for case study research.

The Design of Case Study Research in Health Care (DESCARTE) model [ 44 ] suggests a series of questions to be asked of a case study researcher (including clarity about the philosophy underpinning their research), study design (with a focus on case definition) and analysis (to improve process). The model resembles toolkits for enhancing the quality and robustness of qualitative and mixed-methods research reporting, and it is usefully open-ended and non-prescriptive. However, even if it does include some reflections on context, the model does not fully address aspects of context, logic and causal inference that are perhaps most relevant for evaluative research in health.

Hence, for evaluative research where the aim is to report empirical findings in ways that are intended to be pragmatically useful for health policy and practice, this may be an opportune time to consider how to best navigate plurality around what is (minimally) important to report when publishing empirical case studies, especially with regards to the complex relationships between context and interventions, information that case study research is well placed to provide.

The conventional scientific quest for certainty, predictability and linear causality (maximised in RCT designs) has to be augmented by the study of uncertainty, unpredictability and emergent causality [ 8 ] in complex systems. This will require methodological pluralism, and openness to broadening the evidence base to better understand both causality in and the transferability of system change intervention [ 14 , 20 , 23 , 25 ]. Case study research evidence is essential, yet is currently under exploited in the health sciences. If evaluative health research is to move beyond the current impasse on methods for understanding interventions as interruptions in complex systems, we need to consider in more detail how researchers can conduct and report empirical case studies which do aim to elucidate the contextual factors which interact with interventions to produce particular effects. To this end, supported by the UK’s Medical Research Council, we are embracing the challenge to develop guidance for case study researchers studying complex interventions. Following a meta-narrative review of the literature, we are planning a Delphi study to inform guidance that will, at minimum, cover the value of case study research for evaluating the interrelationship between context and complex system-level interventions; for situating and defining ‘the case’, and generalising from case studies; as well as provide specific guidance on conducting, analysing and reporting case study research. Our hope is that such guidance can support researchers evaluating interventions in complex systems to better exploit the diversity and richness of case study research.

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Abbreviations

Qualitative comparative analysis

Quasi-experimental design

Randomised controlled trial

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This work was funded by the Medical Research Council - MRC Award MR/S014632/1 HCS: Case study, Context and Complex interventions (TRIPLE C). SP was additionally funded by the University of Oxford's Higher Education Innovation Fund (HEIF).

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Paparini, S., Green, J., Papoutsi, C. et al. Case study research for better evaluations of complex interventions: rationale and challenges. BMC Med 18 , 301 (2020). https://doi.org/10.1186/s12916-020-01777-6

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Integrating the complexity of healthcare improvement with implementation science: a longitudinal qualitative case study

Angela melder.

1 Monash Centre for Health Research and Implementation, Monash University, 43-51 Kanooka Gve, Clayton, Victoria 3168 Australia

Tracy Robinson

2 School of Nursing, Paramedicine and Healthcare Science, Charles Sturt University, Bathurst, Australia

Ian Mcloughlin

3 Monash Business School, Monash University, Melbourne, Australia

Rick Iedema

4 Centre for Team Based Practice & Learning in Health Care, King’s College, London, UK

Helena Teede

Associated data.

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Implementation science seeks to enable change, underpinned by theories and frameworks such as the Consolidated Framework for Implementation Research (CFIR). Yet academia and frontline healthcare improvement remain largely siloed, with limited integration of implementation science methods into frontline improvement where the drivers include pragmatic, rapid change. Using the CIFR lens, we aimed to explore how pragmatic and complex healthcare improvement and implementation science can be integrated.

Our research involved the investigation of a case study that was undertaking the implementation of an improvement intervention at a large public health service. Our research involved qualitative data collection methods of semi-structured interviews and non-participant observations of the implementation team delivering the intervention. Thematic analysis identified key themes from the qualitative data. We examined our themes through the lens of CFIR to gain in-depth understanding of how the CFIR components operated in a ‘real-world’ context.

The key themes emerging from our research outlined that leadership, context and process are the key components that dominate and affect the implementation process. Leadership which cultivates connections with front line clinicians, fosters engagement and trust. Navigating context was facilitated by ‘bottom-up’ governance. Multi-disciplinary and cross-sector capability were key processes that supported pragmatic and agile responses in a changing complex environment. Process reflected the theoretically-informed, and iterative implementation approach. Mapping CFIR domains and constructs, with these themes demonstrated close alignment with the CFIR. The findings bring further depth to CFIR. Our research demonstrates that leadership which has a focus on patient need as a key motivator to engage clinicians, which applies and ensures iterative processes which leverage contextual factors can achieve successful, sustained implementation and healthcare improvement outcomes.

Conclusions

Our longitudinal study highlights insights that strengthen alignment between implementation science and pragmatic frontline healthcare improvement. We identify opportunities to enhance the relevance of CFIR in the ‘real-world’ setting through the interconnected nature of our themes. Our study demonstrates actionable knowledge to enhance the integration of implementation science in healthcare improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07505-5.

Given the pace of technological advancement and growth in healthcare demand, governments are mandating healthcare transformation. Health systems are highly complex in their design, networks and interacting components and change is challenging to enact, sustain and scale. Recent evidence shows that healthcare improvement (HCI) is often delivered using simple methods that may lack rigour and efficacy [ 1 – 3 ]. Policy makers, academics, clinicians and those who deliver HCI at the coalface of healthcare, require greater insight into how transformative change can be enacted in complex systems, while at the same time, delivering HCI that is pragmatic and patient centric [ 1 – 3 ].

Implementation science (IS) brings rigour and evidence-based approaches to healthcare improvement, however it is a complex field involving many disciplines that bring different perspectives and often focus on generating theoretical concepts to advance academic understanding. This can contrast with the pragmatic need for “how to” approaches required to inform frontline healthcare improvement in practice [ 1 – 3 ]. Current IS frameworks can provide guidance for planning and undertaking improvement but more knowledge is needed about how to apply these frameworks to better understand how multi-disciplinary teams, embedded in complex improvement interventions, function over time, and how local adaptations and contexts can inform the spread and scale of HCI interventions [ 3 ].

Calls are increasing for integration between the IS and HCI to apply rigorous methods, and pragmatic approaches to improvement work [ 1 ]. The CFIR is used to design, implement and evaluate evidence-based interventions, and comprises five domains and 39 associated constructs [ 4 ]. The comprehensive nature of the CIFR makes it ideal for capturing the complexities of improvement work [ 5 – 8 ]. It encompasses: intervention characteristics : including perceived source and evidence strength and quality; outer setting: including community needs, resources and external policies or incentives; inner setting : such as perceived need for change and internal resources; characteristics of individuals : including knowledge and beliefs about the intervention, and implementation process: such as quality of planning and engaging staff.

Although widely used to plan and evaluate implementation studies, information on the use of the CFIR to evaluate complex, multi-faceted, person centred interventions is scant [ 9 ]. The CFIR can be seen as a determinants framework in that it can be applied with deductive reasoning to identify enablers and barriers to implementation outcomes. It is important to acknowledge how factors that influence implementation outcomes can manifest differently due to variations in health system structures, population cohort morbidities and resource availability [ 10 ]. This means that frameworks such as the CFIR may require adaptation and, while there has been significant growth in the use of the CFIR to support implementation research, missing elements, or limitations, of the framework have been identified, including sustainability and a focus on teams [ 10 ]. In addition, little is known about its application in pragmatic and sustained HCI. Some studies report difficulties translating the complex and sometimes repetitive construct definitions in the CFIR to fit their initiatives [ 8 , 9 ]. Hence, using the CFIR lens, we aimed to explore how pragmatic and complex healthcare improvement and implementation science, can be integrated. We do so by examining the implementation process involved in delivering a complex healthcare improvement intervention . The implementation of the intervention, as a case study, involved integrating and evaluating routine mental health screening in a service providing antenatal care for refugee women. Details outlined in Additional file 2 . This improvement intervention is driven by clear evidence that women of refugee background have an increased risk of mental illness during pregnancy that is compounded by pre and post settlement stressors [ 11 ]. Importantly, we aimed to gain greater insight into the process of the implementation of this intervention, not the specific details of the intervention, so as to provide insight from emergent themes for actionable knowledge to enhance effective and sustainable healthcare improvement and implementation.

Study design and data collection

This case study research was undertaken by the authors (AM, TR, RI, IM and HT) and was embedded within a larger ‘parent study’ investigating healthcare improvement at a system level with four public health services and a government department in Australia [ 12 ]. Here, we report findings from an in-depth longitudinal case study of an improvement intervention being implemented at one health service (Service P). The case study implemented an improvement intervention at Service P, the largest health service in its jurisdiction including six hospitals and highly diverse out-patient and community services, offering generalizability to a broad spectrum of larger health services, Additional file 2 The improvement intervention was delivered by a Service P Implementation Team. To understand how to undertake pragmatic implementation and improvement in complex healthcare settings, we utilised exploratory and qualitative methods with ‘open-ended inquiry’ [ 13 ] using ethnographic observations of implementation team meetings, document reviews, and interviews with thematic analysis. The use of multiple methods allowed for an approach sensitive to context, participants, processes and behaviours and to explore the constructs and factors that have most influence on effective implementation and improvement [ 14 – 16 ].

The researcher (AM) was in situ throughout, allowing ‘real-time’ data collection in a ‘real-world’ context to limit retrospective bias [ 17 ]. Field-level participants included the implementation team, Additional file 2 . Frontline clinicians (hereafter, referred to as target clinicians) who were expected to implement routine mental health screening, were excluded as our focus was on the “how to” of improvement work. We focused on the intervention implementation team actions, how they utilised resources, their interaction with diverse stakeholders and how they progressed the process of improvement.

Qualitative data was collected over 24 months (January 2017–December 2018). Semi-structured interviews (30–60 min) were completed with case study implementation team members involved in planning, implementing and evaluating the intervention. Document review was undertaken across internal project documents, meeting agendas and minutes, presentations and published literature (stemming from the case study) plus researcher field notes and unstructured observations of implementation team meetings. The data collection process is illustrated in Fig. 1 .

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Data collection for this research (Includes Case Study implementation process)

Interview questions were informed by theoretical approaches of IS (particularly CFIR), complexity and improvement science [ 3 ]. General concepts explored in the interviews included constructs of leadership, context, process and content with the interview guide presented in Additional file 1 . Interviews were audio recorded and transcribed. The data from interviews was transcribed, and along with field observations, was analysed using QSR NVivo 12 [ 18 ].

Themes were analysed progressively, until saturation was reached. Analysis was grounded and inductive, influenced by aspects of implementation, complexity and improvement science. Broad themes were elicited through an open-coding process [ 19 ], allowing first order constructs to be identified. This thematic analysis was undertaken by AM, TR and HT to minimise bias and substantiate themes and constructs that emerged. Themes emerged from the data as first order constructs, which were progressively collapsed into higher order second- and third-level constructs. A thematic structure emerged made up of main themes and related sub-themes reflecting the critical features of improvement work as it progressed, to achieve its aim of successful implementation. The conduct and reporting of this research was guided by the Consolidated Criteria for Reporting Qualitative Research [ 20 ].

The second phase of the analysis explored critical success features (themes) emerging from pragmatic ‘real-world’ improvement through the lens of the CFIR [ 4 ]. An analytic matrix was developed, juxtaposing our themes with CFIR components (domains and constructs) for a more in-depth understanding of how the CFIR components operated in a ‘real-world’ context. We also examined whether CFIR captured the observed pragmatic elements of this work. The mapping process identified commonalities, discord and revealed nuances across the CFIR. We aimed, here, to identify specific constructs that might enable better integration of HCI with implementation science to provide actionable knowledge to enhance effective and sustainable improvements in healthcare.

Characteristics of the case study

The case study is presented according to the CFIR constructs described in Additional file 2 , also showing data collection timelines aligned with project progress. This provides an in-depth case description including the roles of implementation team involved, the process of improvement and the contextual issues that affected the work [ 4 ].

Case study outcomes

The intended improvement outcomes of the case study are presented in Table 1 . This provides evidence that the case study intervention outcomes were achieved. That is, the case study intervention (the mental health screening tool and new model of care with referral pathways) was used in practice and feasibility and acceptability (of the case study intervention) was demonstrated. These outcomes are the results of the case study intervention, not the results of our research which was to examine the process of how the case study implemented their intervention.

Improvement outcomes of the case study intervention

Case Study Improvement Outcomes
• The implementation of a screening tool and associated processes was found to be acceptable and feasible for health professionals • From the perspective of patients involved, screening for mental health in pregnancy using a digital platform was found to be acceptable and feasible

Case Study Improvement Outcomes

• The implementation of a screening tool and associated processes was found to be acceptable and feasible for health professionals

• From the perspective of patients involved, screening for mental health in pregnancy using a digital platform was found to be acceptable and feasible

a published work, authorship withheld to protect the identity of participants and the heath service

Our ethnographic case study collected data from 18 interviews, 16 non-participant meeting observations and 16 examined documents.

Thematic analysis

Main themes emerged on “how to” undertake pragmatic implementation in a complex healthcare setting across:

Leadership: characteristics of the team leading the improvement work
Application of an evidence-based research process, with pragmatic iterative action to ensure improvement work progress (this included designing and planning for sustainability and scale) and
Navigating context (local and broader issues, organisational and local settings, aspects of the clinical condition) that affected the improvement work

Table 2 outlines the main themes and sub-themes and the inter-related dynamism across these. The team displayed leadership qualities of agency and collaboration engaging clinicians as they navigated a shifting and complex context, while applying scientific thinking with pragmatic, responsive and iterative action. Table 3 provides example quotes for each theme, and indicated as Quote (Q) 1 to 11.

Thematic Analysis and main themes

Main Themes	Leadership	Processes applied	Navigating Context
	• Agency • Capability for engagement • Teamwork and collaborative approaches	• Focus on patient need • Planning, execution, evaluation - Designed for sustainability and scale-up - Theory driven improvement and implementation - Iterative • Project management	‘Bottom-up’ approach - Embedded at the point of change - Co-designed

Main Themes

Leadership

Processes applied

Navigating Context

• Agency

• Capability for engagement

• Teamwork and collaborative approaches

• Focus on patient need

• Planning, execution, evaluation

- Designed for sustainability and scale-up

- Theory driven improvement and implementation

- Iterative

• Project management

‘Bottom-up’ approach

- Embedded at the point of change

- Co-designed

Exemplar responses illustrating the major themes: Leadership; Process; Context

(Quote (Q) 1) I think having champions is really useful, so having people who are - and they have to be the right people, because it’s not necessarily going to be the senior leader, it’s someone who is respected within the space, who people listen to, who isn’t necessarily the named leader - and engaging them in a meaningful way and then getting them to lead the change. So I don’t think we necessarily need the senior leaders or the whole units at the table, but we need selected important people to be engaged and be able to be seen to be engaged so that they can take it forward.

But I think we do need everyone, and I think there are so many units that if we don’t give the opportunity, at least, for each of them to be engaged then they can be lost. If it’s just engaged at a program level there are an awful lot of people who sit under the same banner and have really, really diverse practices and workforce and everything else, so being able to have representation from areas is, I think, going to be important at the outset, rather than just bringing them in once it’s been decided.

(Q2) I think it’s a very collaborative process, because...Mostly people aren’t, people are pretty happy to work you know and I think there may be times in the future where for example, [X] and [Y] are interested in following up some of the children and I would be happy to hand that over, that’s their areas of expertise and I don’t think, I think we all recognise each other’s area and we are all building to each other’s strengths. And so far there hasn’t really been any competiveness.

(Q3) We spoke to settlement services, community members, the managers and staff I worked with at the community health centre, because you want to look at where you’re going to get your referrals from. People need to know about the service, they need to know what’s happening and how it’s going to be implemented. Feel that they’re actually a part of the process, not just left out - through meetings, chatting. I think essentially I feel I’m a good networker, and I think that’s something that - when I think back to that work we did in the refugee work and this as well, I’ve also been really fortunate, I’ve worked in [X health service] for 30 years so I know a lot of people, the midwifery staff know me, I know them. I’ve worked with a lot of them. So all those things have helped a lot too. And because, in the sense I’m one of them, that’s probably helped.

(Q4) Before we even did the formative research, the important thing was we knew we needed to speak to community members

(Q5) The main driver was that it was a very high risk population and we were concerned about that gap and care for them. So as we went through we started talking to more and more people, we met more people. And then we met the CEO from a not for profit non-government organisation that has funding to provide to try and introduce screening in pregnancy for anxiety and depression and they already had – so they had tools and resources and experience that we could leverage off.

(Q6) I contacted the maternity services, found out why they weren’t doing it. Looked at what could we do that would enable us to try it and then the important thing for us was you know, before we even did the formative research, the important thing was we knew we needed to speak to community members. Because a lot of people anecdotally have always said that you can’t scene with cultural and linguistically diverse women or women from those backgrounds. Because the screening tool doesn’t work with them, because they have different concepts of mental health and therefore they won’t want to engage with it. But that wasn’t the message and that’s why we really made an effort too.

(Q7) The national guidelines are for every woman. We decided to start with refugee women, acknowledging that it was a high risk population and yep, probably where the greatest unmet need was. Of course it was also the most complex population which is one of the reasons why it hasn’t been done. And there was a little bit of an attitude of well if we can make it work in this population we can probably make it work in the general population. So the chances of being able to roll it out across all of the Maternity Service would be great if we could get it to work in this most challenging circumstance. If we can demonstrate that it works in this situation then there can be very little criticism or very little but what if? There are very few excuses that can come up that we have not already seen and addressed.

(Q8) We need to prove the effectiveness of the assessment tool, before we set about sustaining it in practice. If it wasn’t effective at achieving the set objective then we would not want to sustain it.

(Q9) We’ve received funding from [X health service] and [X university] and from [X research translation centre] as well. And the leverage that then gives us is that if we experience really serious barriers we can go to very high levels at those organisations who hold quite a lot of power and say, “Look, you and these other organisations have invested considerably in this project, recognising that it is a key priority for you, and we are experiencing these problems that we haven’t been able to address ourselves and we need some high level support on it.” And we’ve not had to use that because it’s quite a blunt instrument. Yeah we haven’t had to really call that into use yet but it’s nice to have that strategic high level support.

(Q10) I can’t speak highly enough of the people above me. I think that they really are cognisant of the impact of perinatal mental health on women and newborn well-being, and they’ve been very keen to explore opportunities to do things differently or to do some short sharp, change management as an intervention that might make a difference to the outcomes that we’re getting. Yeah, so certainly at the levels that I’ve been, they’ve been very engaged and very curious about what we can do and have been more than supportive.

(Q11) But it’s got to the point where a lot of the hard work has been done. But I think some of that has been because I’ve been quite strategic. I’ve been around long enough to know that research is something that buys you credibility in academic environments. And to be strategically aligned with projects like this, or other projects, buys me credibility, in terms of, you know having bargaining power and having some influence, I suppose.

Main theme – leadership: characteristics of the implementation team leading and engaging with target clinicians with improvement work

This main theme and sub-themes captured the implementation team’s demonstration of diplomacy and communication required for interaction and engagement with those involved in healthcare improvement. The sub-themes included agency, capability and teamwork. (Q1 to Q3).

Agency is the capacity to act with purpose, power and courage to initiate improvement in response to gaps or suboptimal quality of care [ 21 ]. Agency was exhibited in response to patient need, reinforced by national guidelines. The implementation team recognised the relevance and importance of aligning internal organisational strategic directions and external levers, such as national guidelines. The team utilised this structural lever to initiate dialogue with stakeholders, who brought expertise to the improvement work from within the health service and externally. It galvanised the belief in the work and the desire to improve with clear the rationale for immediate action from stakeholders, such as fellow clinicians, health service personnel and organisational leaders, as champions. The team identified and engaged with others with additional expertise and a shared vision. The implementation team’s actions revealed passion, competence and expertise, with confidence to act and lead. As leaders of change with agency to drive the work, the team recognised and leveraged their expertise, position and role. This was a significant characteristic, consistently displayed throughout the work and with all stakeholders.

Capability for engagement

Diplomacy, or high-level communication skills were applied to achieve engagement and negotiation with target clinicians. The team worked hard to connect, understand and engage with clinicians around the new practice considering context and barriers and enablers of the intervention and its implementation. They adopted collaborative, shared leadership, to adapt, modify and shape the process, according to contextual issues, such as time limits, patient needs, or information technology capacities. The team consistently inspired others using strong communication skills, achieved through regular meetings between the implementation members and target clinicians within the setting where the intervention was delivered.Emotional intelligence and diplomacy skills, tacitly demonstrated and explicitly described by the team were recorded. Tacit characteristics included engagement with target clinicians within a clinical setting to gauge their reactions and to respond to unspoken messaging And also evidenced in observations of team meeting discussions. This quality reflected personal motivations of the implementers and the leveraging of a shared motivation with target clinicians to achieve “best practice” for patient care.

Teamwork and collaboration

Teamwork was a dominant characteristic and was connected to aspects of networking, negotiating, relationship-building and connection development. In terms of explicit characteristics, strong teamwork principles of collaboration and co-design were applied including frontline managers and clinical teams (target clinicians). Implementers worked hard to build connections and relationships between target clinicians and improvement work, including intervention co-development and refinement. Communication and connection-building served to foster trust and enhance relevance of the improvement work with target clinicians. The team communicated consistently and frequently with all target clinicians, as observed in team meetings and through interview discussions with case study implementation team members.

Collaborative approaches included problem-solving, where no problem was too insignificant or to intractable. Frontline teamwork was demonstrated through consistent target clinician engagement and on-ground coaching, demonstrating high levels of communication with frontline staff and recognition of on-ground problems and progress.

Main theme - process of improvement and implementation

This theme highlights key motivations for the improvement work and the structural and practical elements of implementation team action. It includes team processes utilised, and actions taken to progress the work. Sub-themes included the focus on patient need as a key motivator for clinicians and the planning, execution and evaluation of the implementation process. Other sub-themes involved intervention development, theory-driven implementation processes, consideration of sustainability and scale up issues, analysis of implementation barriers, enablers, and measurement and use of process and outcome evaluation. (Q4-Q8).

Method of improvement and change process (planning, execution and evaluation)

Observation of the method of improvement and change process applied by the implementation team was a key aspect of our research. The Case study methods involved a structured approach containing key activities included planning, execution and evaluation, are outlined as “Process” in Additional file 2 , Fig. Fig.1 1 illustrates the these process. Driven by a national guideline [ 22 ] the case study implementation team sort to implement ‘best practice’ using a complex intervention (Additional file 2 ) The case study strongly focused on sustainability and scalability, once proven effectiveness was proven. This team applied an established implementation theoretical framework (the Normalization Process Theory) [ 23 ] that underpinned evaluation and measurement of practice change and health outcomes.

In studying the process of implementation, we observed case study implementation team undertake in-depth assessment of patient needs and clinician perspectives to inform the co-designed improvement process. The team reported (and published) extensive communication with multiple stakeholders internally and externally to the health service, before and during the implementation. Iterative co-design with target clinicians, clinical leaders, technology experts and academics occurred throughout. Modifications and solution development occurred more intensely at the beginning and less so over the implementation. Coaching with target clinicians was also intense at the beginning to ensure feasibility and practical use of the newly implemented assessment tool. While the screening tool was designed for sustainability and spread, it was an additional task to usual practice. To this end, sustainability was considered and planned from the outset, but strategies were only instigated after evaluation indicated efficacy. Several implementation team members indicated, “If we can get it right in this setting [refugee, maternal health services], it should be easier to establish it in a less challenging general maternity setting”.

A prevailing observation was the unremitting effort and the availability of the project officer and clinical leaders (both part of the team) for clinicians adopting new practices and tools. All team members, particularly the project officer, were readily available to observe, coach and engage frontline target clinicians as well as acting as liaison between these clinicians and the implementation team.

The recognition of patient need was demonstrated through the clear commitment to ensuring this worked for the target clinicians and of prime importance, for the refugee women. Considerable effort was committed to developing and refining the screening tool to ensure it was understood by the women, across terminology, cultural appropriateness and translation into different languages.

Project management

Project management was an important role for the improvement/change facilitator, who was also a coach and PhD Scholar, with a background as a midwife and maternal child health clinician. Tasks involved organising meetings, progressing the project and reporting updates on all aspects of project progress. This was a regular and ongoing task to articulate and investigate problems and trouble-shoot and resolve situations that reconciled both research purposes with pragmatic actions.

Main theme - navigating context

This theme captured diverse aspects of the case study context and how the implementation team navigated this. Sub-themes included project governance at a local and organisational level, and the team positioning, allowing multi-disciplinary capability, to respond to a changing complex environment, adjusting iteratively. (Q9-Q11).

Although governance represented a ‘bottom-up’ approach informed by implementation research, co-design and a collaborative approach to improvement, leadership and support ‘on the ground’ came from local leaders directly involved in service delivery with the identified vulnerable population and improvement setting. The senior clinical lead in the implementation team engaged with progress and problems with the Department head and manager, to secure ongoing support including for sustainable implementation.

Team members had roles that straddled an integrated Research Translation Centre (RTC) or “implementation laboratory”, firmly established as a partnership across the university and health service [ 24 ]. The team were also largely clinicians and central stakeholders in the health service and improvement process. This leveraged the onsite partnership between the RTC and the health service. Team members often wore two hats, as implementers and clinician leaders. This research lens and expertise facilitated insightful perspectives about the improvement process, balanced with practical implementation ‘at the coalface’. Additional academic funding was attracted to support the project, while senior researchers undertook the work as part of their academic roles. The clinician leaders in the implementation team also undertook the work as part of their role in delivering high quality care.

Mapping our themes with CFIR

To enhance understanding of the “how to” issues of pragmatic implementation and improvement in complex healthcare settings, we mapped themes that emerged from our longitudinal ethnographic research of an improvement case study to the CFIR constructs to better understand how a real-world improvement could integrate with IS. We aimed to bring further depth to understanding the process of IS and HCI. The mapping process revealed strong alignment, limitations and enhancements to CFIR in the following ways.

Leadership and process themes from our case study cut across the CFIR constructs and domains, this is unsurprising given our research focus was on the process the implementation teams used, and these CFIR components reflect much of the contextual and process aspects that impact implementation work. Patient need while included as domain in the CFIR, our case study illustrated the significant influence it played in our case study. An identified limitation between our process theme and CFIR was that of sustainability and scale-up. While evaluation and reflection of progress (in CFIR) was an ongoing activity, our case provided further granulation about the process of design and execution to ensuring sustainability. The complexity of contextual issues aligned strongly with several CFIR context constructs and domains, focussed mainly on the outer and inner settings.

The CFIR identifies five constructs essential to implementation success (inner setting, outer setting, etc.). Our themes aligned with all five constructs, presented in Table 4 , however, our themes of leadership (particularly distributed models of leadership was persistent, iterative and attentive to collaborative engagement with stakeholders) and process cut across all CFIR constructs. The implementation team navigated and embraced the complex and dynamic contextual circumstances, as well as the intervention development and implementation process itself. Our research reflected an inter-related nature of the themes and constructs, reflecting the dynamic aspects of the improvement work. Our leadership theme, in particular, aligned to all aspects of the CFIR, through agency, engagement and skills. Furthermore, it aligned to other CFIR constructs; Outer setting (B. Cosmopolitanism), Inner setting (Networks and Communications) and Process (B. Engaging) (Table (Table4). 4 ). In this distributed leadership model of our case study, no one person held all responsibility and the team collaborated, reflecting individual capabilities and responsibilities, and led the work by engaging others and navigating context. This provides insights into a leadership model that appears to enhance implementation success. Rather than articulating anything missing in the CFIR, the mapping activity provided depth and demonstration of the inter-connection of CFIR constructs.

Mapping of themes with CFIR constructs and domains

Our themes	CFIR Constructs & Domains
Our themes	Outer setting	Inner setting	Characteristics of individuals	Intervention characteristics	Process
	B. Cosmopolitanism	B. Networks and Communications E. Readiness for Implementation- E1. Leadership Engagement			B. Engaging B1. Opinion Leaders B2. Formally Appointed Internal Implementation leaders B3. Champions B4. External Change Agents
	A. Patient needs & resources B. Cosmopolitanism D. External Policies & Incentives	B. Networks and Communications D. Implementation Climate • D3. Relative priority E. Readiness for Implementation • E1. Leadership Engagement • E2. Available Resources	A. Knowledge and Beliefs B. Self-efficacy
	A. Patient needs & resources	D. Implementation Climate • D4. Organisational Incentive and rewards: • D5. Goals and Feedback • D6. Learning Climate. E. Readiness for implementation: • E3. Access to information and knowledge		C. Relative advantage D. Adaptability F. Complexity	A. Planning C. Executing D. Reflecting and Evaluating

a Characteristics of individuals not directly observed by the researchers, but discussed by the implementation team and observed in their actions toward/with the target clinicians

In terms of applying CFIR to pragmatic and sustained HCI, the reality is that all of the elements of complexity or implementation science are at play in a real-world implementation setting and CFIR enables the synthesis of many complex factors that focus on, and impact, the processes of implementation.

The mapping provided an in-depth examination of the CFIR domains and constructs in light of a real-world circumstances. This revealed the complex interplay of factors operating in healthcare improvement work, highlighting the critical nature of relationships between the constructs, and presenting a complex nuanced assessment of how implementation teams interact with stakeholders and contexts and iterative processes that underpin and confront change at the clinical frontline.

There is a clear need to optimise approaches to deliver effective and sustainable improvement in health care, integrating methodological rigor and theory driven implementation science with pragmatic healthcare improvement methods [ 1 , 6 , 8 , 9 ]. In this context, our research reports three main themes from the improvement work; leadership, context and process. Our study highlights the fluidity of CFIR constructs and how they overlap and are interconnected. At the same time, this study provides a more nuanced understanding of the CFIR constructs and the integral role of leadership and team work that cut across all domains.

Leadership and engagement

While leadership engagement is included in CFIR we bring a more nuanced and pragmatic understanding of leadership to the framework. Our research provides an in-depth demonstration of what leadership of improvement looks like and how these leaders enacted the process of improvement with stakeholders. Key leadership capabilities included agency to lead the work and capability to engage and communicate about the improvement process with target clinicians and to facilitate the process continuously with them, learning iteratively together.

The importance of leadership was highlighted by Damschroder 2009 [ 4 ] and the need to build a cohesive team consisting of effective champions and stakeholders, who are most likely to make the implementation a success. Here, the multidisciplinary implementation team demonstrated leadership through the agency, skills and capability to engage with target clinicians.

A recent integrative evidence review [ 25 ] described attributes of effective facilitators involved in healthcare improvement, with key qualities aligning to the leadership displayed by the implementation team. Ellegdge 2019 reported that self-awareness, self-management, social awareness, relationship management, skills, and knowledge translation and understanding represented key competencies for facilitators to effectively influence success of knowledge translation to improve practice [ 25 ].

Illot 2012 [ 5 ] noted that the issue of leadership in the CFIR is under-developed and could potentially go further to describe the connection of leadership with other constructs of implementation and describe how this component continually interacts with the stakeholders involved in the improvement process and context in a pervasive and active manner. Leadership is a complex and critical factor of implementation and improvement work, is relevant to context and process and requires more in-depth framing and investigation that captures the breadth of its influence in future research and healthcare improvement efforts.

Our context theme encompassed both aspects of the CFIR inner and outer setting. These CFIR constructs reflect some granulation that was illustrated in our case study research. However, CFIR could go further to emphasise the aspect of ‘patient need’ influencing the implementation process, and the significance of it as a critical motivator for target clinicians to participate in taking up new practices to benefit patients.

In terms of outer setting constructs, patient needs, especially in vulnerable groups, provided a critical trigger for the improvement work and galvanised all involved. In addition, an external best-practice guideline provided an incentive to implement evidence-informed practice.

Our context theme incorporates patient needs which is contained within an outer setting domain of CFIR. Our research emphasised the significance of this important driving factor in the consistent inclusion and reflection throughout the improvement process. It was a key trigger for the improvement work, and was of paramount importance to the implementation team to meet women’s mental health needs. It was highly relevant for the women involved in the process and the feedback they provided with respect to their support needs, and it dominated the purpose for delivering high quality care from the perspective of the target clinicians. Focus on patient need was woven throughout, actively and passively with the women and target clinicians. Illot 2012 [ 5 ] and Safaeinili 2019 [ 9 ] undertook a validation process which examined the comprehensiveness of CFIR with healthcare improvement projects and highlighted this as an underrepresented aspect and a gap in the framework. Safaeinili 2019 [ 9 ] goes so far as to suggest that patient involvement should be an additional domain to the CFIR. Our work would suggest that patient need and engagement enhanced clinician engagement and was vital in this improvement work.

Furthermore, our context theme captures the governance of bottom-up approaches to improvement work. Cosmopolitanism and networks were reflected in this bottom-up approach, and the partnership between the implementation team members, made up of research and clinician experts embedded within a RTC that was externally positioned to maintain knowledge exchange, and focus to progress the work, combined with internal members (local leaders and champions) who were established and connected within the local healthcare setting as clinician managers and service directors [ 26 ]. This contextual fit supported and enabled the team to progress the improvement work, while still providing required care and aligning other local priorities. Having a team that was present at the point of change is also emphasised in research by Bonawitz 2020, who highlights this embedded aspect of having change champions who understand the practicalities at the frontline and who can leverage organisational influences, or resources, to facilitate the process to achieve the envisaged change [ 27 ].

There is increasing recognition of the complexity of healthcare delivery and the need for improvement work to acknowledge that to achieve success in a complex setting where a responsive, bottom-up approach is better suited [ 2 , 28 – 30 ]. Our case study demonstrated local involvement in refining the approach and when this was fostered (through the implementation team), the impact was positive (in terms of practice change). The attentive response of the implementation team to local issues, enabled a stronger feedback mechanism with “grass-root” creativity to resolve improvement process problems. An agile, attentive and engaged leadership demonstrated by the implementation team, leveraged networks within and external to the setting, communicated with each other and with clinicians about the improvement work, and connected extensively with patients around the new practices. McCullough 2015 reinforces this finding and identified key contextual elements, such as leadership, teamwork, and communication, interacting with each other and contributing to site-level uptake of the evidence-based practices [ 31 ]. Here we observe the presence of these important factors affecting the uptake of introduced practices. Further research is needed to provide insight into how specific characteristics of context, particularly the application of a bottom-up approach, can influence improvement outcomes.

Damschroder 2009 [ 4 ] reports that process is the “single most difficult domain to define, measure, or evaluate in implementation research”. Our theme of process amalgamated CFIR intervention characteristics and process. We did this because intervention characteristics, patient need and clinician requirements influenced our process theme. The iterative, interactive and collaborative process used by the implementation team, aligned with the components in these CFIR domains and constructs. These processes conferred through the leadership of the implementation team and engaged stakeholders in the vision, ensured adaptability and addressed complexity to safeguard success across the planning, execution and evaluation phases. Furthermore, the process consistently considered and addressed patient and clinician needs and resources, provided and discussed shared goals, and updated progress in an iteratively collaborative learning scenario to identify and improve where needed. The team were not deterred by uncertainty; rather they demonstrated confidence in each other’s expertise, as well as the expertise and feedback of the target clinicians they were working with to implement a new practice and tool, and in doing so, further enhanced and fostered engagement of all stakeholders in the improvement work.

An identified limitation between our process theme and CFIR was that of sustainability and scale-up. While evaluation and reflection of progress was an ongoing activity, our case set out to design an intervention and implementation strategy for sustainability and scale-up. The case study process involved activities to ensure sustainability and scale-up, which is not incorporated explicitly in the CFIR. Ilott 2012 also identifies this gap and points out the limitations of the ‘reflect and evaluation’ domain, highlighting the need for further definition and investigation on how to capitalise on organisational change efforts [ 5 ].

Limitations and strengths

The limitation of including a single health service in a public universal healthcare setting may limit generalisability. However this health service was part of a national public health system and this was one of the largest services with broad reach. The case study itself was designed for and is now being scaled broadly and has been independently evaluated by the study team and shown to be acceptable and scalable. With scale-up, evaluation will provide insight into broader implementation.

Here we retrospectively applied the CFIR, acknowledging that this is designed for prospective use to guide implementation research. However, it is based on learnings of what works in implementation and by its nature was in part constructed from retrospective evaluations such as this. Here our aim was to provide insight into the CFIR components, and how they may interact with each other. Prospective application would not have aligned with the ethnographic approach of observing real-life work, rather than primary case study implementation research unfolding.

We acknowledge that our approach of the in situ researcher has limitations including potential bias that might have influenced the process of the improvement work. However, it is precisely the strength of the longitudinal immersion and insider status that enabled this research and provided the insights into the normally overlooked deeper aspects of the context in which HCI takes place. As the case study scales further evaluation will enable further evaluation above and beyond that from in situ researcher, although it will lack the depth of such an approach.

This research on a ‘real-world’ healthcare improvement case study using the CFIR lens, provides an in-depth and rich understanding of integrated IS and pragmatic HCI. It provides an illustration of the cross-interaction of the components, and presents a nuanced picture of CFIR and the implementation processes that it aims to guide. Key themes included leadership, context and process, which mapped closely to the CFIR. Specific findings include the vital role of leadership agency to cultivate relationships with target frontline clinicians, engaging them in the process of improvement, enhancing participation through planning, execution, evaluation and sustainability at the frontline. The importance of leaders with clinical and rigorous implementation expertise emerged, as did engagement of multi-disciplinary cross-sector support to manage complexity, contextual issues and delivery on the shared vision of improved outcomes. The vital role of stakeholder engagement and co-design emerged, with patient and clinician need key throughout the improvement work. We highlight the opportunity to integrate sustainability and scalability, not currently explicit in the CFIR, yet fundamental to pragmatic healthcare improvement. Overall, applying the CFIR lens, we produce actionable knowledge to enhance integration of implementation science and pragmatic health care improvement, to improve practice and patient outcomes.

Acknowledgements

The authors acknowledge the generous contribution of our study participants.

Abbreviations

CFIR	Consolidated Framework for Implementation Research
HCI	Healthcare improvement
IS	Implementation science
AM	Angela Melder
TR	Tracy Robinson
IM	Ian Mcloughlin
RI	Rick Iedema
HT	Helena Teede
RTC	Research Translation Centre

Authors’ contributions

AM: Contributed to the conceptualization, methodology, formal analysis, investigation and co-writing (original draft, review and editing). HT: Conceptualization and methodology, investigation and co-writing (original draft, review and editing). TR: Participated in investigation and analysis, and co-writing (review and editing). IM: Conceptualization and methodology, investigation and co-writing (review and editing). RI: Contributed to investigation and analysis, and co-writing (review and editing). IM, HT, TR, RI: provided oversight and leadership responsibility for the research activity planning and execution, including mentorship to AM. Authors have read and approved the manuscript.

The research was supported through the parent study, funded by the Australian Research Council (LP140100243) and in kind support from the partnering Health Service participating in the research. The role of the funder was to evaluate the research progress and outputs.

Availability of data and materials

Declarations.

The study was reviewed and approved by Service P Human Research Ethics Committee (Ref # LNR/16/MonH/259). Informed consent was obtained from all subjects. All methods were carried out in accordance with relevant guidelines and regulations [ 20 ].

All authors can confirm that that they have approved the manuscript for submission. All participants confirmed consent to publish this material as part of their consent to participate in the case study research.

All authors have no issues relating to journal policies; we have no potential competing interests to declare.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The complexity of chemistry mindset beliefs: a multiple case study approach †

First published on 9th July 2024

Mindset is a construct of interest for challenging learning environments, as science courses often are, in that, it has implications for behavioral responses to academic challenges. Previous work examining mindset in science learning contexts has been primarily quantitative in nature, limiting the theoretical basis for mindset perspectives specific to science domains. A few studies in physics education research have revealed domain-specific complexities applying to the mindset construct that suggest a need to explore undergraduate perspectives on mindset within each science domain. Here we present a multiple case study examining chemistry-specific mindset beliefs of students enrolled in general and organic chemistry lecture courses. A between-case analysis is used to describe six unique perspectives on chemistry mindset beliefs. This analysis revealed that students’ beliefs about their own ability to improve in chemistry intelligence or regarding chemistry-specific cognitive abilities did not consistently match their views on the potential for change for other students in chemistry. The nature of the abilities themselves (whether they were naturally occurring or developed with effort), and the presence of a natural inclination toward chemistry learning were observed to play a role in students’ perspectives. The findings from this analysis are used to propose a more complex model for chemistry-specific mindset beliefs to inform future work.

Introduction

Mindset has been identified as a relevant psychological construct to include in the investigation of persistence behaviors as it involves beliefs about the malleability of intelligence and is linked to persistence and challenge-seeking behaviors ( Molden and Dweck, 2006 ; Doron et al. , 2009 ; Burnette et al. , 2013 ; Lou and Noels, 2016 ; Karlen et al. 2019 ). The term “mindset” originates from research on Implicit Theories of Intelligence, which states that individuals hold either incremental theories (beliefs that intelligence can increase) or entity theories of intelligence (beliefs that intelligence is a fixed trait). Incremental theories are linked to persistence because improvement is believed to be achievable with effort. Entity theories are linked to giving up because challenges are believed to be associated with evidence that one's intelligence is insufficient for the task ( Dweck and Leggett, 1988 ). The terms “growth mindset” and “fixed mindset” are more commonly used in more recent studies but are still based on the original definitions of “incremental” and “entity” theories of intelligence, respectively ( Lüftenegger and Chen, 2017 ).

In recent years, there has been an increasing interest in understanding mindset in STEM contexts ( Gorson and O'Rourke, 2019 ; Little et al. , 2019 ; Limeri et al. , 2020a ; Limeri et al. , 2020b ; Lytle and Shin, 2020 ; Morris et al. , 2019 ; Kalender et al. , 2022 ). This increased research interest has been provoked by findings suggesting that student beliefs about specific domains vary and are more predictive of their outcomes in that domain relative to their general mindset beliefs ( Shively and Ryan, 2013 ; Scott and Ghinea, 2014 ; van Aalderen-Smeets et al. , 2019 ). Gender and racial stereotypes likely influence students’ beliefs about who can succeed in certain STEM fields, and thus their field-specific mindset beliefs ( Aronson et al. , 2002 ; Good et al. , 2003 ; Burkley et al. , 2010 ; Good et al. , 2012 ; Leslie et al. , 2015 ; Lytle and Shin, 2020 ; Ibourk et al. , 2022 ). Several studies have found that domain-specific mindset beliefs: (1) decline over time in STEM courses, and (2) are more predictive of student outcomes relative to general mindset beliefs ( Shively and Ryan, 2013 ; Dai and Cromley, 2014 ; Scott and Ghinea, 2014 ). These findings highlight the profound effects of experiences in STEM courses and the importance of understanding students’ beliefs in association with these domains.

Most mindset theory development occurred through an examination of phenomena in young children to explain behavioral differences ( Dweck and Leggett, 1988 ; Macakova and Wood, 2020 ). There is evidence to suggest that not only are mindset beliefs at the undergraduate level more complex relative to younger students, but also that the domain-specificity becomes more relevant as students age ( Gunderson et al. , 2017 ). Gunderson and coworkers found that students' beliefs about their peers’ ability in math become less growth relative to their beliefs about their peers’ ability in language with increasing age (2017). These belief gaps only increase when it comes to student beliefs about adults working in math-related fields compared to writing-related fields. Recent meta-analyses conducted over large samples of mindset studies have found inconsistent results for mindset interventions and the predictive relation of mindset with achievement for adult students ( Costa and Faria, 2018 ; Sisk et al. , 2018 ). The average effect sizes for the impact of mindset (with or without intervention) on achievement observed across studies decreased with students’ increasing age. An improved understanding of the underlying differences in the impact of adult student mindset and associated behaviors on achievement can help to differentiate these effects from those observed in younger students.

Reports that students can endorse both growth and fixed mindset beliefs simultaneously have existed since early in the mindset research ( Dweck et al. , 1995a, 1995b ). However, the notion that mindset beliefs are context-dependent has gained traction in research lately. The learning environment can activate one view over another ( Little et al. , 2016 ), which may yield various effects on student behaviors. The shift in beliefs as a function of a performance feedback loop for STEM subjects also suggests that context matters ( Dai and Cromley, 2014 ; Scott and Ghinea, 2014 ; Limeri et al. 2020a ). Likewise, findings that instructors’ mindsets about students and the messaging expressed in instruction and teacher-student communication impact student outcomes also point to the environmental influences on student beliefs ( Barger, 2019 ; Canning et al. , 2019 ; Muenks et al. , 2020 ; LaCosse et al. , 2021 ). Little and coworkers called for a shift in methodology away from survey measures that capture a small snapshot of students’ views toward rich qualitative analysis to begin understanding the nature of context influences on student mindsets in physics (2016), which could be equally important in other STEM domains like chemistry.

A deeper understanding of the various aspects of undergraduate chemistry mindset perspectives is needed, along with an examination of contextual influences on the expression of these beliefs in chemistry courses. This multiple-case study examines eight students’ chemistry-intelligence beliefs and experiences in general and organic chemistry to characterize chemistry-specific mindset perspectives as indicated by their expressed beliefs, behaviors, and interpretations of challenges.

Theoretical framework

Domain-general mindset theory.

The key difference between these two operating theories lies in the meaning attributed to failures or challenges ( Molden and Dweck, 2006 ). A student who endorses incremental theory beliefs will interpret failures as challenges that have yet to be overcome because they believe their intelligence can attain the necessary level for success at a task. On the other hand, entity theorists view failures as an indicator of their insufficient ability and do not believe it is possible to affect their intelligence level. The lack of control over intelligence associated with entity beliefs yields helpless responses and negative affect when exposed to failure experiences in attempts to deflect attention from their insufficient ability. Some behaviors associated with entity theories are procrastination ( Howell and Buro, 2009 ), reduction of effort ( Burnette et al. , 2013 ), avoiding help-seeking, evaluation, and difficult tasks ( Hong et al. , 1999 ), and minimizing the importance of the failure by changing pursuits ( Molden and Dweck, 2006 ). In sharp contrast, the presence of a feeling of control over intelligence associated with incremental beliefs encourages efforts to improve, persistence, maintained confidence, enjoyment of challenge, and positive affect associated with minor improvements ( Dweck and Leggett, 1988 ; Molden and Dweck, 2006 ).

Behavior-aligned mindset model

A general mindset model synthesizing the literature on the interconnections between three major mindset themes (mindset beliefs, challenge experiences, and behaviors) was developed by the authors as a framework for analysis, inspired by the SOMA model. Fig. 1 presents this general mindset model as a Venn diagram. At the center of the three interacting factors in student experiences lies ego threat. Ego threat here is conceptualized as the meaning associated with challenge as a function of the beliefs that determine behavioral responses. It should be noted that the work associated with the SOMA model was conducted across domains (domain-general) and through quantitative techniques, thus lacking the specificity to academic and STEM contexts as well as the depth of qualitative investigation.


	A three-pronged mindset meaning model for case analysis indicating the interactions between mindset, challenges, and behaviors, where green represents growth mindset interpretations (productive strategies or beliefs) and actions and red represents fixed mindset interpretations and actions (unproductive strategies or beliefs).

Theoretical model interpretation

It is important to explain the hypotheses associated with each overlap between factors represented in the general mindset model from Fig. 1 . We can begin by considering the overlap of mindset and challenge. When a challenge is present, differences in interpretations of that challenge arise as a function of mindset. A growth mindset interprets challenge as a need to increase or modify effort strategies, and a fixed mindset interprets challenge as indicative of lacking ability. Similarly, when challenge is absent, differences in interpretation are possible as functions of mindset: a growth mindset interprets the lack of challenge as a demonstration that previous effort has allowed relevant skills to be developed, while a fixed mindset interprets the lack of challenge as indicative of high or natural ability in the relevant area.

The next relationship to consider is the interaction between challenge and behavior. The interpretation of challenge as ability-related leads to helpless responses such as avoiding demonstrating ability or evaluation, sabotaging performance by other means such as procrastination, and giving up or disengaging emotionally to deflect blame on the level of caring. This ability emphasis also leads to focusing attention on negative feedback and performance outcomes. Meanwhile, the interpretation of challenge as effort-related or “needs-development” leads to mastery responses such as seeking help from other sources, altering strategies, exerting more effort, and increasing self-regulation. The effort emphasis also leads to focusing attention on improvement and the learning process.

The final relationship depicted in the model is between mindset and behavior, such that, the behavioral responses indicate the students’ mindset through practical demonstration of their beliefs. When considering students’ effort beliefs, the belief that necessary effort implies low ability reveals a fixed mindset, while the belief that effort is the means to improve at any ability reveals a growth mindset. When considering students’ willingness to change and improve, ignoring feedback as useful for improvement and decreasing effort reveals a fixed mindset, while attention to improving through feedback and increasing effort reveals a growth mindset.

Using this model, we can contrast theoretical criteria for identifying growth and fixed mindset individuals as opposite ends of a continuum. A student with a strong growth mindset believes that any ability can be developed or improved given the appropriate resources and will to do it, does not give up easily in the face of challenge, and focuses on understanding and mastery as a litmus test for success. Alternatively, a student with a strongly fixed mindset believes that abilities tend to be naturally derived and explain the differences between people in achievement and intelligence. This student will also more readily give up in the face of challenge, especially if it is the first serious challenge encountered in life and focuses on achievement and competitive measures of success. This theoretical model will be used in the data analysis of this study as a lens to recognize behavioral indicators of growth or fixed mindset beliefs.

Science domain-specific mindset theory

Study goals and design.

1. How can differences in chemistry mindset be characterized considering students’ beliefs on the nature of chemistry-related abilities, interpretations of challenge, and behavioral responses?

2. What degree of alignment is observed between interview themes and extant general intelligence mindset theory to provide insight into chemistry mindset as a distinct construct?

To address these research questions, interview content will be analyzed inductively for chemistry-specific mindset content using broader themes from the general mindset model ( Fig. 1 ).

Multiple case study design

Participant recruitment and case selection.

During Fall 2021, only selected case study participants were invited to participate in a follow-up interview to gain additional insight into their views. For this second interview, a $20 incentive was offered to ensure high participation and reduce attrition. To select individuals for a multiple case study from the larger interview participant pool, students who had completed both pre- and post-semester surveys in Fall 2020 and Spring 2021 (a total of 4 survey time points) were identified. This criterion was used because it indicates full data existed for each of the participants selected for the case study, leading to an inclusion of eight individuals. Seven were initially interviewed in Fall 2020 and one, Camille, was interviewed in Spring 2021. The case study participant characteristics are described in Fig. 2 . Two students were first-year (freshmen) undergraduates during the first interview semester, three were second-year students (sophomores), two were third-year (juniors), and one was a post-baccalaureate student completing course prerequisites for medical school admission. Three students initially participated during general chemistry I, two during general chemistry II, and three during organic chemistry I. Students who initially participated in organic chemistry II courses were not included since they were no longer enrolled in introductory courses by Spring 2021. This reason also applied to fourth-year seniors; they could not participate once they had graduated. Students in this study had a range of demographic backgrounds and previous educational experiences.


	Multiple case study participant selection with student characteristics at the time of first interview and the data sources utilized within each case.

Data sources and collection

In addition to survey response data, case study participants provided in-depth interview content for analysis. The first interviews were conducted during Fall 2020 and were semi-structured. Interviews took less than one hour and incorporated questions as well as several tasks to prompt deeper discussion of mindset topics. Interviews were conducted online using a virtual meeting platform and students were sent a PowerPoint © file containing the tasks before beginning. The full interview protocol and the tasks students completed during these interviews are available in the Appendices A and B. Interviews were screen-captured and audio-recorded for later analysis. After initial questions, students were prompted to share their screens and present the slides associated with a particular task. Students were instructed on how to complete the task and told to use a think-aloud method as they completed each task. Probing questions about the reasons behind task decisions and beliefs indicated in the task were then used to elicit a deeper discussion of each student's views. At the end of the interviews, students were asked to clearly state their mindset beliefs and explain why they hold such beliefs (“Do you think that people can change their intelligence in chemistry? How did you come to believe this?”).

A follow-up interview was requested during Fall 2021 from each of the case study participants. The interview protocol is provided in the ESI. † Questions in this interview focused more on students' experiences in chemistry classes, backgrounds, challenges, responses to challenges, and perceptions of others’ views about chemistry as a subject. Towards the end of the follow-up interview, each case study participant was directed to comment on one of their previously completed tasks. This involved sharing whether they still held the views they did at the time of task completion, explaining why they think they completed it that way, and providing what (if any) changes they would make.

Qualitative analysis

One final coder meeting was conducted to refine codes further and align the names of each theme more closely with terminology from the mindset literature. Additional details of the final codebook are available as ESI, † accompanying the online article (Table S1, ESI † ). Once the codebook and interrater reliability were inductively developed and established using other transcripts from the larger interview pool, all case study interviews were coded according to the three-pass method previously described. This coding scheme was applied to both initial interviews and follow-up interviews deductively.

After coding all interviews, coding frequencies were compared across cases. The transcripts were examined for relevant quotes to represent their expressed views on each aspect (mindset, behavior, and challenge), and summaries for each case were drafted. These summaries were sent to each participant for member-checking, or verification that the summaries accurately represented their views. Most participants replied that it was a correct representation or submitted minor corrections to explain in more detail.

Limitations

Results and discussion, case descriptions and mindset perspectives.

Chemistry mindset perspective	Description	Case
Interest	• Anyone can improve or develop chemistry intelligence in areas they naturally lack.	Yosef
Interest	• Interest is a key motivator for the effort required to improve.	Yosef

Confidence	• Anyone can improve any aspect of chemistry intelligence, but confidence is a key ingredient to realize that change is possible.	Natalie
Confidence	• Chemistry intelligence develops over time and naturally weak areas can be improved with effort and experience.	Teresa

Natural baseline	• Despite acknowledging that aspects of chemistry intelligence are naturally set at certain levels, they aren’t fixed and can improve to any level with the necessary effort.	Johnny
Natural baseline	• The effort required for different people to reach the same level will vary depending on natural strengths and weaknesses.	Kevin

Some abilities	• Some abilities are naturally weak and stable or naturally strong and can be improved with effort.	Camille
Some abilities	• Belief in the ability to improve is a significant factor in whether or not it is possible.	Camille

Most abilities	• If someone is naturally intelligent in chemistry, they are able to improve to a greater extent than someone who is not naturally intelligent in chemistry.	Raquel
Most abilities	• Both types of students are able to apply effort to improve their ability and achieve some level of success.	Raquel

All or nothing ability	• Tends to view chemistry intelligence as a single ability that is either naturally present or not.	Elle
All or nothing ability	• Someone who does not have this natural ability can apply effort to get by well enough but they won’t become more intelligent in that area.	Elle

Case	Background	Mindset beliefs	Challenges	Behaviors
Yosef	• Biochemistry major	• Interest is a driving force for change.	• Creativity is an ability in chemistry that Yosef feels he lacks naturally and must develop.	• Learns from mistakes rather than avoiding them.
	• Lifelong interest in science	• Interest and talent can be natural or developed.	• Earned a low grade on an exam in organic chemistry and used the experience to change habits.	• Desires improvement and welcomes feedback.
	• Family support for education and high grades	• External influences can spark interest.		• Focuses on small intrinsic rewards and avoids comparison with others.
		• Anything lacking naturally can be developed.		• Seeks help from the instructor.
		• Failure experiences drive improvement.

Natalie	• Post-baccalaureate	• Shifted beliefs about improvability of chemistry-specific abilities to include all aspects after seeing significant self-improvement in weak areas.	• Challenges managing time with external pressures.	• Grades have come to signify alignment of understanding with expectations rather than a measure of ability and are used for self-evaluation.
	• Threatening academic environment discouraged medical pursuit	• Defines intelligence as a willingness to learn from mistakes.	• Remote learning presented challenges during complex theoretical content segments.	• Often seeks help.
	• Wrestled with imposter syndrome	• Intelligence develops over time and can be improved by anyone in any area.	• Feelings of challenge are a good indicator that ability needs to improve in an area.	• Mistakes are valuable if they are overcome and produce change.
	• Renewed intention to pursue medicine
	• Fear of chemistry has turned to enjoyment

Teresa	• Premedical	• Anything can be improved with effort.	• Perception of challenges has shifted with confidence levels and now leads to increased effort and help seeking.	• Changes to her confidence in chemistry dramatically affected behaviors.
	• First-STEM major in family	• Chemistry intelligence develops with experience.	• Previously, challenges confirmed beliefs that chemistry intelligence was not natural for her.	• Low grades used to imply low ability, but now motivate effort.
	• Initially intimidated by reputation of organic chemistry	• Natural abilities are not genetic but developed early on.		• Previously allowed negative self-perceptions based on comparisons.
	• Grown to enjoy chemistry			• Now regularly seeks help.

Johnny	• Premedical non-traditional student	• Willingness to put forth effort is key to improving chemistry intelligence.	• It is challenging to read chemistry problems and not know how to begin solving them.	• Understanding is more important than the grade, but the grade measures understanding.
	• Family history in science and medicine	• Any aspect of chemistry intelligence can be improved.	• Another challenge is not knowing how to check the work done to solve a problem.	• He boosts his confidence in chemistry by developing creative explanations and helping others.
	• Always learned quickly	• Accumulation and application of knowledge are the definitions of intelligence he used to explain his own improvement in chemistry.	• New content can be overwhelming, but repeated practice can help problems feel more natural.	• Comparison with others isn’t helpful and mistakes are useful for learning.
	• Doesn’t view math and science as his natural abilities	• Has improved his mathematical thinking in chemistry over time.
	• Negative feelings toward chemistry in high school that have become positive in college

Kevin	• Neuroscience major	• Different aspects of chemistry intelligence are more (or less) easily changed, but no ability is static.	• Does not experience challenges with grades in chemistry.	• Holds self to high standards and uses grades as a measure of understanding.
	• Lifelong passion for science	• Individuals begin with various ability levels as a “baseline” but can improve to any level desired with effort.	• Described challenges with distinctions in complex applications of chiral synthesis.	• Would ask for help if challenged, but more often helps others.
	• Experiences of success in school from childhood	• The rate of change can vary drastically between people.	• The stress of feeling lost with the content was something he used to motivate seeking understanding.	• Views learning chemistry as a collaborative activity.
	• Self-perception as smart
	• Failure experiences applying to college
	• Re-evaluated beliefs about the necessity of effort

Camille	• Pursuing a career in neurosurgery	• Some abilities in chemistry can be changed more easily than others.	• Has challenges with the language aspect of chemistry (applying correct terminology).	• Grades are important for the evaluation of your abilities by others.
	• Interest in medicine since childhood	• “Mindset” affects a person's ability to succeed in chemistry, but also the natural abilities that person has.	• Describes having challenges with believing she can improve in certain areas and it fluctuates on different days.	• Tends to procrastinate when her grades are high.
	• Gifted education	• If some abilities are naturally weak, they are stable.		• Mistakes allow her to see that she is improving and can be motivating to try harder.
	• Family emphasis on grades	• Some abilities can only be developed.		• Willing to ask for help and enjoys helping others.
	• Previously disliked chemistry
	• Now enjoys explaining chemistry to others

Raquel	• Medical career aspirations	• Makes a distinction between chemistry ability and chemistry intelligence and believes that chemistry ability is more changeable through effort.	• Faced visualization challenges when learning about crystal structures.	• Doesn’t avoid challenging problems and uses them to learn and improve.
	• Values chemistry and finds it interesting	• Natural abilities can improve if a person has them.	• Overcame this challenge by examining various representations until she was able to visualize better.	• Compares her grades with others to feel better about her own grades.
	• Family is supportive of education	• Someone who doesn’t have a natural ability can’t do much to improve it.		• Describes competing with herself in performance expectations.
	• Self-perception as smart	• Values effort over “direct intelligence.”		• Will listen to constructive feedback but tends to avoid negative feedback and mistakes.
	• Tends to earn A grades in chemistry

Elle	• Nutrition science major	• Makes a distinction between chemistry ability and chemistry intelligence and believes that chemistry ability is more changeable through effort and memorization.	• Study and learning strategies to be successful in chemistry have been the greatest challenge.	• Uses grades as a primary gauge of success.
	• Pursuing a career in endocrinology	• Natural abilities are the key determinant in whether someone will be good at chemistry.	• Motivation is also a major challenge.	• Believes she should learn from mistakes and shouldn’t avoid paying attention to feedback.
	• Experience with a diabetic parent	• Doesn’t make distinctions between overall chemistry intelligence and aspects of it that could come naturally to different people.	• Describes only doing enough to get by in chemistry, which is not something she does in other classes.	• Has worked with a tutor to improve in chemistry.
	• Parents work in and value education		• The tutor and changes to study strategies have helped to overcome some of these challenges.	• Tends to skip challenging problems and doesn’t feel like trying when she can’t solve a problem.
	• Naturally good at math and science (not chemistry)			• Competes with others in her mind, but often this makes her feel inadequate.
	• Does not like chemistry

Chemistry mindset perspectives as a continuum

Elle and Yosef expressed views that represent the far ends of the mindset spectrum from one another, Elle being the most fixed in mindset and Yosef holding the strongest growth beliefs. A possible explanation for the strength of Yosef's growth convictions is his high ability in chemistry, which he doesn’t attribute to natural ability, but rather effort and interest. He believes he developed chemistry intelligence through combined effort and interest, so he must think that to be true for anyone. Yosef shares his beliefs about people's ability to improve with the following statement, “I know for a fact, based off of experience that if you put in effort for any small thing – if you really want to put in effort, you can definitely change that. There's like nothing that's impossible to change – unless you're like, not biologically capable of doing it, I think an average person has the ability to change no matter what it is.”

Elle has had the opposite experience of Yosef's. She has low interest and low perceived ability. She thinks the ability portion is natural and thus does not have an interest in chemistry because it's not easy or relatable. She does believe effort makes a difference in her performance, but not as much in her chemistry intelligence, which she doesn’t care as much about regardless. Elle expresses her frustration with learning chemistry in the following:

“Sometimes chemistry will just push me to a point where I just do not want to even try because it just tests me so much and I just don't know what else to do. And challenging problems are…I'm not saying I don't do them at all, but I definitely don't do as many as I should – because I think if I did, I would really be trying to, like, get A's on tests and I really don't do that. I really just try to get a B. And that's just so weird to even say, ‘cause that is really not who I am, to try to get a B, but that's who I am in chemistry…I don't want to be burned when I don't get an A. Because I don't expect it because I know I'm not putting in the effort that is required of an A in chemistry. And just all the different factors – Not naturally being good at it, not really wanting to work at it, wanting to do the bare minimum just to try to get good enough. – It's like an internal issue.”

None of the students’ perspectives completely overlapped, but a few students had sufficient similarities in their views to be categorized within the same mindset theme. First, both Kevin and Johnny seemed convinced that natural abilities are important to how easily you can understand chemistry, but both also expressed that any ability can be developed and equated that to increasing chemistry intelligence. For example, Johnny says,

“I would contrast it as, the natural ability would be like the clay and developed with effort is when you take that clay and mold it into something with edges and, like, corners and, you know, so it becomes something more defined, as opposed to just this big blob of material or matter…I feel like you can have these natural abilities but you still need to do something to shape them and hone them…if you don't, then you could have all the natural ability in the world – It's almost like raw potential. Somebody could have potential, but never meet that potential or meet that promise.”

Second, both Teresa and Natalie expressed confidence that chemistry intelligence is improvable through effort but required performance feedback to create a sense of confidence that growth is possible for themselves as well. To provide evidence for this belief, Natalie shared her experience with improving in visualization skills in organic chemistry: “The ability to rotate models in my head, I've gotten a lot better at that…It feels like a silly small thing, but it's been really rewarding…I used to not be able to do this at all or understand what it is. And now I feel like I kind of know what's happening.”

Another similarity was the strength of emphasis placed on natural abilities by both Camille and Raquel. Nevertheless, they were able to believe themselves capable of growth in chemistry due to their own natural abilities for STEM subjects. Despite this similarity, Camille expressed that increasing chemistry intelligence is possible through effort focused on developing relevant abilities, though she felt that not all abilities were changeable. Her belief about stable abilities is apparent in the following quote: “I think it's just differences that we all have as humans. There are people that are always going to be able to have a better memory than most. Like, I have a terrible memory.

No matter what I do I can't necessarily change it. The only thing I can do is improve on how I try to relate the information that I'm trying to remember to things that I've – Things that I know, things that just come naturally to me.” Raquel expressed a higher number of abilities as difficult to change, showing a belief that natural abilities are mostly stable.

Based on the similarities and differences discussed above, different categories of mindset perspectives can be defined. These mindset perspectives are presented in Fig. 3 along a hypothetical continuum. Elle carries the traditional implications of fixed beliefs, in that, if a person doesn’t have natural ability for chemistry, then there is not much that can be done other than to protect one's ego through avoidant behaviors. Raquel is a bit more open to the idea of improving chemistry intelligence but much more for those who have the natural ability to begin with. Camille has a slightly more flexible view on overall chemistry intelligence but emphasized specific abilities as unchangeable and the need to leverage the natural abilities you do have to improve. Kevin and Johnny both believe that development of any ability is possible, yet state that natural ability plays a role in how easily one can learn. They were placed at the same point on the continuum in Fig. 3 because their views are similar, yet Kevin has more confidence because he views himself as having natural ability for chemistry and Johnny does not. Johnny instead has a natural interest (or curiosity) and thus is willing to develop his weak areas. Teresa and Natalie both believe that anything can be developed yet were hesitant to believe this about their own chemistry intelligence without evidence supporting that they could improve. Teresa's shift from lack of confidence in general chemistry to complete enjoyment of the success she found in organic chemistry is more substantial than the changes Natalie experienced. This could suggest that Natalie's mindset beliefs are more deeply ingrained and drive her effort to improve, while Teresa has exerted effort out of a desire to succeed and her mindset beliefs followed her improvement. Finally, Yosef expressed very optimistic views regarding anyone developing abilities if they have interest in that domain. He did acknowledge that some people have a “God-given talent” for certain subjects, but also said that everyone must work hard to be good at chemistry. His main comparison between students who do well in chemistry and those who do not was based on the amount of effort they apply as driven by their personal interests. He also stated that educators play a significant role in how personally interesting a course is through their own enthusiasm for the content.


	Case participants’ mindset perspectives organized along a continuum from most fixed to most growth mindset. The colors along the continuum represent the degree of growth or fixedness of a given mindset perspective theme.

Chemistry mindset perspectives in two-dimensions


	Qualitative placement of each case along two dimensions of mindset: myself and others. The same colors for each case are used from to indicate the degree of growth or fixedness of each mindset perspective uncovered when considering a single mindset dimension.

Results from the survey measures indicate that the case study participants tended to have more fixed mindsets about others’ chemistry intelligence compared to their own. Aligning with the interview findings, Yosef was shown to have the highest growth mindset about his own chemistry intelligence as well as that of other students. Raquel and Elle both scored the lowest on their chemistry mindset beliefs as well as their beliefs about others, with Raquel reporting the most fixed chemistry mindset about others. Johnny and Teresa both reported a more growth mindset about others compared to themselves, aligning with the expressions of self-doubt and lack of natural ability in the area of chemistry described in their interviews. All participants reported a chemistry mindset on the growth end of the scale, but the degree of growth chemistry mindset about self and others aligned well with the interview findings.

The other important result from the survey measures included in the case study was the relationship between chemistry mindset about self and the participants’ self-report of mindset-related behaviors. Behaviors were consistently slightly less growth mindset compared to the measured chemistry mindset belief. This meant that the students with the highest reported mindset-related behaviors were those who also held the most growth beliefs about their own chemistry intelligence. Combined with the observation that mindset beliefs about self and others do not always align, this finding suggests that chemistry mindset beliefs about the self most strongly predict a student's mindset-related behaviors ( i.e. avoidance, persistence, reception of critique, etc. ). It should be noted that only qualitative observations can be made about these survey results with a sample size of 8 participants and generalizations cannot be made based on this evidence alone.

To address the second research question, rather than considering three categories of mindset (growth, middle, and fixed) as the traditional mindset literature suggests ( Dweck et al. , 1995a ; Hong et al. , 1999 ), we can consider the four quadrants of the two-dimensional conception of mindset ( Kalender et al. , 2022 ; Malespina et al. , 2022 ). The upper right and bottom left quadrant represent the growth and fixed labels as previously defined; however, with a richer measurement distinction as a combination of two dimensions. In contrast, the bottom right and upper left quadrants may shed additional light on the messy middle described in the mindset literature ( Hong et al. , 1999 ).

Alignment of chemistry mindset with general mindset

It must be acknowledged that the academic environment in which all students in this study were enrolled places a general emphasis on performance above mastery and the primary tool provided for diagnosing one's mastery is performance scores. If academic environments aim to promote mastery and growth beliefs, the performance focus may need to be reconsidered due to its impact on students’ interpretations of their own success.

Based on the criteria described for a growth mindset, Yosef, Kevin, Johnny, and Natalie would all be considered to have a growth mindset. In the case analyses described here, Yosef, Teresa, and Natalie were all considered to have chemistry mindsets aligning with growth beliefs and Johnny and Kevin were considered to lie on the growth end of the spectrum. Some caveats to this classification process were misalignment of beliefs about oneself relative to others and some emphasis on natural abilities or an innate interest in chemistry. Thus, a growth chemistry mindset appears to be more complex in nature than a theoretical general growth mindset.

Raquel meets two of these fixed mindset criteria. She explains the differences between people's achievement in chemistry by way of their natural abilities. She also admits to using some degree of competitive behavior in comparing her grades to others to boost her self-esteem. However, she does not give up in the face of challenges and rather becomes more motivated when challenges arise because she believes herself capable of overcoming them due to her high natural ability. Camille meets the first criterion (natural abilities) to some degree, but is a bit more flexible in that view, and does not meet any of the others. Teresa met the third criterion to some degree in her first interview (performance and competition) but attempts to minimize these comparisons to maintain her confidence and does not meet the others. Classifying a chemistry fixed mindset, as indicated by these cases, is complex. Some of the criteria from a theoretical fixed general mindset aligned with students whose views approached a growth chemistry mindset. This is due to misalignment of beliefs about the self and others in chemistry because of perceived self-competence.

Furthermore, evidence for multiple dimensions of chemistry mindset beliefs was uncovered in this case study as a function of who is being considered (self versus others). Similar dimensions have been uncovered for undergraduate students’ physics mindset beliefs ( Kalender et al. , 2022 ; Malespina et al. , 2022 ). Moreover, the degree of ingrained beliefs about oneself was found to correspond to interpretations of challenge and behavioral responses to challenge. This suggests that although there is substantial alignment of chemistry mindset, behaviors, and challenges observed in these case participants with extant literature findings, the object of mindset items (me or someone else) are critical to predictive measures of an individual's behaviors (RQ2).

Implications for research and teaching

The multiple aspects involved in a rich description of a students’ chemistry mindset could be considered for better triangulation of their true beliefs and the depth to which they hold such beliefs. The more accurate our description of a student's mindset, the more appropriate predictions could be made regarding their success in chemistry courses. One method to resolve this concern for large-scale mindset classification would be to create a multidimensional mindset instrument, specific to chemistry, that addresses each construct as a subfactor: (1) chemistry mindset about self, (2) chemistry mindset about everyone, (3) interpretation of challenge in chemistry, and (4) behavioral response to challenge in chemistry. These additional factors can allow for the creation of many mindset categories that could each be evaluated for their relative contribution to the predictive relationship of mindset with student success outcomes.

In chemistry classrooms, a variety of student affective profiles are present. Feedback carries different meaning to each student as a function of their mindset beliefs and self-perceptions of chemistry ability. Chemistry instructors should be aware of this when providing feedback to students and emphasize the ways in which it is beneficial to their improvement rather than evaluative of their ability. Also, students may place different degrees of emphasis on the effects of effort toward impacting their intelligence or just their “ability.” Noticeable improvements in mastery or skills can be emphasized by instructors over simple grade improvements or “native abilities.” Because students were more likely to exhibit mastery behaviors when they had high ability self-perceptions, instructors can impact students’ mindset beliefs about the self by placing emphasis on improvements over the scores themselves, which is likely to increase ability perceptions and thus foster growth beliefs about the self.

Another avenue for impacting students was suggested by one of the case participants, Yosef. He perceived his instructors as impacting his interest through their enthusiasm and passion for the subject of chemistry. It is important for instructors to remember that they serve as role models for students. Instructors can share how they improved their own intelligence in chemistry through effort and that they believe this to be possible for any student who is willing to engage in it. This can be specifically targeted as individual skills, such as visualization, mathematical thinking, and disciplinary language usage. Instructors can also share topics of personal interest related to course content and provide opportunities for students to see how the concepts being covered are relevant to them.

Data availability

Conflicts of interest, appendix a. initial in-depth semi-structured interview protocol with tasks developed based on general mindset literature.

Description of phases and questions students will be asked to respond to using think aloud:

Phase 1: Beginning questions to practice talking:

• How is the current semester of chemistry going?

• What course are you in, how are your grades, do you feel challenged currently in chemistry?

• What do you notice about someone in chemistry class that makes you think they are smart/intelligent?

• Do you recall family members praising you more for your ability or for your effort in school?

• Do you think your chemistry intelligence is the main factor determining your chemistry performance?

• Why or why not? (How would you define it?)

• Can you tell me about a time when you faced a challenge in chemistry? What happened, how did you respond, and what was the end result?

Phase 2: Behaviors in challenging chemistry scenarios selection activity (Appendix A Fig. 5 and 6 )


	Entity behavior item task.


	Incremental behavior item task.

• Which of these items can you see yourself doing this semester when you experience challenges in chemistry? Circle the ones you think are relevant to you and cross out those that you don’t think you would do.

• For some of the circled responses: Can you give an example of a time you did that in a class?

• For some of the crossed out responses: Why did you cross that out (social desirability?)? Why don’t you think you would do that?

Phase 3a: Beliefs about cognitive abilities important to chemistry intelligence selection activity (Appendix A Fig. 7 )


	Chemistry intelligence aspects task.

• Which of these items are the most important aspects of chemistry intelligence? Circle the ones you agree with and cross out those you don’t agree with.

• Are there any other aspects you would like to add to this list?

• Which of these are aspects you feel like you are good at vs not good at? Why?

Phase 3b: Beliefs about chemistry intelligence cognitive abilities origins sorting activity (Appendix A Fig. 8 )


	Natural and developed chemistry intelligence aspects sorting task.

• Out of the items you circled, how do you think you get those abilities? Are they developed or natural abilities?

• What do you think “natural ability” means?

• Why do you think these are developed? Can you give an example?

• Why do you think these are natural abilities? Can you give an example?

Phase 3c: Beliefs about chemistry intelligence cognitive abilities malleability within origin sorting activity (Appendix A Fig. 9 )


	Malleability of chemistry intelligence aspects sorting task.

• Can you sort each of these into those that you can change versus those that you cannot change?

• How would you define “change” in this case?

• What evidence of change would you look at to verify that it had happened?

• Why do you think these can change?

• Why do you think these cannot change?

Phase 4: Discussion of survey response reasons and discrepancies with currently stated beliefs

• Here are the responses you selected from the survey earlier this semester.

• Why did you choose this answer before? What were you thinking when you read the question? (social desirability?)

• Today, you said this behavior/answer, but/and on the survey you said this. Why do you think they were different/the same?

Phase 5: Graphing of intelligence over lifetime activity (Appendix A Fig. 10 )


	Intelligence level over lifetime graphing task.

• How do you define intelligence as a whole?

• What do you think a graph of intelligence vs. time looks from birth, through childhood, adolescence, adulthood, and elderly stages until death for the average person?

• How should the graph look for the average chemist?

• Can you explain why you drew each graph the way you did?

• Why is the graph for the average person the same/different from the average chemist?

• Can you compare the max intelligence you drew and the shape of each graph?

Phase 6: Final questions

• Do you think that people can change their intelligence in chemistry? How did you come to believe this?

• Throughout your chemistry courses, has your confidence in your chemistry ability changed? How and why?

• Have you ever dropped, withdrawn, or failed a chemistry course? If so, what factors influenced that decision/event?

• Do you often doubt your ability to succeed in chemistry? If so, what causes you to think that way?

• Have you ever said (or believed) that you aren’t good at chemistry? Why?

Appendix B. Follow-up semi-structured interview protocol.

Phase 1: Beginning questions to practice talking and reflecting on past experiences and what brought them to this point.

• What class are you currently in and what is your major/reason for taking chemistry?

• What led you to select your major? What are your career goals?

• Can you tell me a bit about your background? What were some influences on your academic/career goals?

• What were some influences on what you value as demonstrating intelligence?

• Can you discuss your experiences with chemistry before college? What is your history with chemistry?

Phase 2: How does the student view their identity with regards to science and/or chemistry?

• How well do you feel that you fit in as a science major? What about in a chemistry class? Why do you see yourself that way?

• What kind of person do you think becomes a chemist?

Phase 3: What are external factors affecting the student's beliefs about chemistry?

• How do your family and friends talk about chemistry and/or your major? Do they seem to think it requires natural ability or very smart people?

• How do you think your chemistry instructors view your intelligence in chemistry? Do they seem to think it can change?

• How does society/our culture/everyday person view chemistry in terms of difficulty/ability?

• Do you agree with these different perspectives about chemistry? Why or why not?

Phase 4: What are the student's internal beliefs about chemistry and challenge experiences?

• How challenging do you believe chemistry is? Is it more or less challenging to you compared to your peers? Why do you think this is? Were there differences between organic and general chemistry in terms of difficulty?

• What is the most challenging aspect of chemistry to you?

• What are some specific challenges you have faced in chemistry classes? How big of a challenge was it? When did it happen and how did you feel? What did you do?

• What does encountering a challenge in chemistry mean to you (low ability or more effort)? How does that make you feel? What do you do when there's a challenge?

Phase 5: What are some behaviors the student acknowledges being important to their success?

• What is something you achieved in chemistry that you are very proud of?

• What is something you did in chemistry that you are not so proud of?

Phase 6: Previous interview activity results

• Show either the categorization of chemistry abilities, the natural ability vs developed abilities, or the plot for intelligence and ask further questions to clarify perspective and gauge changes in beliefs.

Phase 7: Final questions (What is the student's mindset toward chemistry and has it changed?)

• Is your ability to do chemistry something that you could improve in? How would that happen? What are some aspects that could be improved?

• Has the way you feel about your ability to do chemistry changed over time? How and why?

• Do your feelings about your ability to do chemistry change in certain scenarios? Can you give examples?

• Is chemistry something that you could see a career in? Why or why not?

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Integrating the complexity of healthcare improvement with implementation science: a longitudinal qualitative case study

Tracy Robinson

Ian Mcloughlin

Rick Iedema

Helena Teede

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Characteristics of the case study

Case study outcomes

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Main theme – leadership: characteristics of the implementation team leading and engaging with target clinicians with improvement work

Capability for engagement

Teamwork and collaboration

Main theme - process of improvement and implementation

Method of improvement and change process (planning, execution and evaluation)

Project management

Main theme - navigating context

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The complexity of chemistry mindset beliefs: a multiple case study approach †

Introduction

Theoretical framework

Behavior-aligned mindset model

Theoretical model interpretation

Science domain-specific mindset theory

Multiple case study design

Data sources and collection

Qualitative analysis