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Title : An Introduction on Descriptive Analysis; Its advantages and disadvantages
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Study designs: Part 2 – Descriptive studies
Rakesh aggarwal.
Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
Priya Ranganathan
1 Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India
One of the first steps in planning a research study is the choice of study design. The available study designs are divided broadly into two types – observational and interventional. Of the various observational study designs, the descriptive design is the simplest. It allows the researcher to study and describe the distribution of one or more variables, without regard to any causal or other hypotheses. This article discusses the subtypes of descriptive study design, and their strengths and limitations.
INTRODUCTION
In our previous article in this series,[ 1 ] we introduced the concept of “study designs”– as “the set of methods and procedures used to collect and analyze data on variables specified in a particular research question.” Study designs are primarily of two types – observational and interventional, with the former being loosely divided into “descriptive” and “analytical.” In this article, we discuss the descriptive study designs.
WHAT IS A DESCRIPTIVE STUDY?
A descriptive study is one that is designed to describe the distribution of one or more variables, without regard to any causal or other hypothesis.
TYPES OF DESCRIPTIVE STUDIES
Descriptive studies can be of several types, namely, case reports, case series, cross-sectional studies, and ecological studies. In the first three of these, data are collected on individuals, whereas the last one uses aggregated data for groups.
Case reports and case series
A case report refers to the description of a patient with an unusual disease or with simultaneous occurrence of more than one condition. A case series is similar, except that it is an aggregation of multiple (often only a few) similar cases. Many case reports and case series are anecdotal and of limited value. However, some of these bring to the fore a hitherto unrecognized disease and play an important role in advancing medical science. For instance, HIV/AIDS was first recognized through a case report of disseminated Kaposi's sarcoma in a young homosexual man,[ 2 ] and a case series of such men with Pneumocystis carinii pneumonia.[ 3 ]
In other cases, description of a chance observation may open an entirely new line of investigation. Some examples include: fatal disseminated Bacillus Calmette–Guérin infection in a baby born to a mother taking infliximab for Crohn's disease suggesting that adminstration of infliximab may bring about reactivation of tuberculosis,[ 4 ] progressive multifocal leukoencephalopathy following natalizumab treatment – describing a new adverse effect of drugs that target cell adhesion molecule α4-integrin,[ 5 ] and demonstration of a tumor caused by invasive transformed cancer cells from a colonizing tapeworm in an HIV-infected person.[ 6 ]
Cross-sectional studies
Studies with a cross-sectional study design involve the collection of information on the presence or level of one or more variables of interest (health-related characteristic), whether exposure (e.g., a risk factor) or outcome (e.g., a disease) as they exist in a defined population at one particular time. If these data are analyzed only to determine the distribution of one or more variables, these are “descriptive.” However, often, in a cross-sectional study, the investigator also assesses the relationship between the presence of an exposure and that of an outcome. Such cross-sectional studies are referred to as “analytical” and will be discussed in the next article in this series.
Cross-sectional studies can be thought of as providing a “snapshot” of the frequency and characteristics of a disease in a population at a particular point in time. These are very good for measuring the prevalence of a disease or of a risk factor in a population. Thus, these are very helpful in assessing the disease burden and healthcare needs.
Let us look at a study that was aimed to assess the prevalence of myopia among Indian children.[ 7 ] In this study, trained health workers visited schools in Delhi and tested visual acuity in all children studying in classes 1–9. Of the 9884 children screened, 1297 (13.1%) had myopia (defined as spherical refractive error of −0.50 diopters (D) or worse in either or both eyes), and the mean myopic error was −1.86 ± 1.4 D. Furthermore, overall, 322 (3.3%), 247 (2.5%) and 3 children had mild, moderate, and severe visual impairment, respectively. These parts of the study looked at the prevalence and degree of myopia or of visual impairment, and did not assess the relationship of one variable with another or test a causative hypothesis – these qualify as a descriptive cross-sectional study. These data would be helpful to a health planner to assess the need for a school eye health program, and to know the proportion of children in her jurisdiction who would need corrective glasses.
The authors did, subsequently in the paper, look at the relationship of myopia (an outcome) with children's age, gender, socioeconomic status, type of school, mother's education, etc. (each of which qualifies as an exposure). Those parts of the paper look at the relationship between different variables and thus qualify as having “analytical” cross-sectional design.
Sometimes, cross-sectional studies are repeated after a time interval in the same population (using the same subjects as were included in the initial study, or a fresh sample) to identify temporal trends in the occurrence of one or more variables, and to determine the incidence of a disease (i.e., number of new cases) or its natural history. Indeed, the investigators in the myopia study above visited the same children and reassessed them a year later. This separate follow-up study[ 8 ] showed that “new” myopia had developed in 3.4% of children (incidence rate), with a mean change of −1.09 ± 0.55 D. Among those with myopia at the time of the initial survey, 49.2% showed progression of myopia with a mean change of −0.27 ± 0.42 D.
Cross-sectional studies are usually simple to do and inexpensive. Furthermore, these usually do not pose much of a challenge from an ethics viewpoint.
However, this design does carry a risk of bias, i.e., the results of the study may not represent the true situation in the population. This could arise from either selection bias or measurement bias. The former relates to differences between the population and the sample studied. The myopia study included only those children who attended school, and the prevalence of myopia could have been different in those did not attend school (e.g., those with severe myopia may not be able to see the blackboard and hence may have been more likely to drop out of school). The measurement bias in this study would relate to the accuracy of measurement and the cutoff used. If the investigators had used a cutoff of −0.25 D (instead of −0.50 D) to define myopia, the prevalence would have been higher. Furthermore, if the measurements were not done accurately, some cases with myopia could have been missed, or vice versa, affecting the study results.
Ecological studies
Ecological (also sometimes called as correlational) study design involves looking for association between an exposure and an outcome across populations rather than in individuals. For instance, a study in the United States found a relation between household firearm ownership in various states and the firearm death rates during the period 2007–2010.[ 9 ] Thus, in this study, the unit of assessment was a state and not an individual.
These studies are convenient to do since the data have often already been collected and are available from a reliable source. This design is particularly useful when the differences in exposure between individuals within a group are much smaller than the differences in exposure between groups. For instance, the intake of particular food items is likely to vary less between people in a particular group but can vary widely across groups, for example, people living in different countries.
However, the ecological study design has some important limitations.First, an association between exposure and outcome at the group level may not be true at the individual level (a phenomenon also referred to as “ecological fallacy”).[ 10 ] Second, the association may be related to a third factor which in turn is related to both the exposure and the outcome, the so-called “confounding”. For instance, an ecological association between higher income level and greater cardiovascular mortality across countries may be related to a higher prevalence of obesity. Third, migration of people between regions with different exposure levels may also introduce an error. A fourth consideration may be the use of differing definitions for exposure, outcome or both in different populations.
Descriptive studies, irrespective of the subtype, are often very easy to conduct. For case reports, case series, and ecological studies, the data are already available. For cross-sectional studies, these can be easily collected (usually in one encounter). Thus, these study designs are often inexpensive, quick and do not need too much effort. Furthermore, these studies often do not face serious ethics scrutiny, except if the information sought to be collected is of confidential nature (e.g., sexual practices, substance use, etc.).
Descriptive studies are useful for estimating the burden of disease (e.g., prevalence or incidence) in a population. This information is useful for resource planning. For instance, information on prevalence of cataract in a city may help the government decide on the appropriate number of ophthalmologic facilities. Data from descriptive studies done in different populations or done at different times in the same population may help identify geographic variation and temporal change in the frequency of disease. This may help generate hypotheses regarding the cause of the disease, which can then be verified using another, more complex design.
DISADVANTAGES
As with other study designs, descriptive studies have their own pitfalls. Case reports and case-series refer to a solitary patient or to only a few cases, who may represent a chance occurrence. Hence, conclusions based on these run the risk of being non-representative, and hence unreliable. In cross-sectional studies, the validity of results is highly dependent on whether the study sample is well representative of the population proposed to be studied, and whether all the individual measurements were made using an accurate and identical tool, or not. If the information on a variable cannot be obtained accurately, for instance in a study where the participants are asked about socially unacceptable (e.g., promiscuity) or illegal (e.g., substance use) behavior, the results are unlikely to be reliable.
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Descriptive Research Design – Overview
Published 16 October, 2023
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Descriptive research is an observational method that focuses on identifying patterns in data without making inferences about cause and effect relationships between variables. The purpose of this blog post is to provide a brief description of descriptive research design including its advantages and disadvantages and methods of conducting descriptive research.
What is Descriptive Research?
Descriptive research is a process of systematically describing and analyzing something’s features, properties or characteristics. Descriptive research provides numerical descriptions that identify what the thing being studied looks like in terms of its size, location, and frequency.
This type of research will help you in defining the characteristics of the population on which you have performed the study. A descriptive research design enables you to develop an in-depth understanding of the topic or subjects. In such a type of investigation, you can’t have control over variables.
By performing descriptive research, you will be able to study participants in a natural setting. Descriptive research basically includes describing the behavior of people to whom you have select as a participant in the research process .
In addition to this , descriptive research also allows you to describe the other various aspects of your investigation. An important feature is that you can employ different types of variables but you only need a single variable for performing the descriptive investigation. It is a type of study which includes observation as a technique for gathering facts about the study. You can perform descriptive research for analyzing the relationship between two different variables.
For example, A company whose sale of specific products such as home decor products is going down. Management, in order to analyze the reason for the same, needs to conduct descriptive research. Survey Research is the data collection technique that a research team in an organization can use for collecting the view of people about the decline in the sale of home décor products.
When to Use Descriptive Research Design
Descriptive research is suitable when the aim of the study is to identify characteristics, frequencies, trends, categories, and the behavior of people.
In addition to this, the descriptive research design is appropriate to use when you don’t have much knowledge about the research topics or problems.
This type of study can be used before you start researching why something happens so that we have an idea on how it occurs, where are most likely places this will happen at and who might experience these things more often than others.
Advantages of Descriptive Research
- One of the biggest advantages of descriptive research is that it allows you to analyze facts and helps you in developing an in-depth understanding of the research problem .
- Another benefit of descriptive research is that it enables you to determine the behavior of people in a natural setting.
- In such a type of investigation, you can utilize both qualitative and quantitative research methods for gathering facts.
- Descriptive research is cost-effective and quick. It can also be used for many different purposes, which makes it a very versatile method of gathering data.
- You need less time for performing such types of research .
- With descriptive research, you can get rich data that’s great for future studies. Use it to develop hypotheses or your research objective too!
Disadvantages of Descriptive Research
- The biggest disadvantage of descriptive research is that you cannot use statistical tools or techniques for verifying problems.
- Respondents can be affected by the presence of an observer and may engage in pretending. This is called the “observer effect.” In some cases, respondents are less likely to give accurate responses if they feel that a question will assess intimate matters.
- There are high chances of biases in the research findings .
- Due to the observational nature, it is quite difficult to repeat the research process .
- By performing descriptive research you can find the root cause of the problem.
Methods of Descriptive Research Design
You can utilize both Qualitative and Quantitative methods for performing descriptive research. It is very much essential for you to make the choice of a suitable research design for investigation as the reliability and validity of the research outcomes are completely based on it. There are three different methods that you can use in descriptive research are:
It is the method that includes a detailed description of the subject or topic. The survey is the method by utilizing which you can collect a huge volume of facts about the topic or subject.
You can use a survey technique for directly accumulating information about the perception of people about the topic. The methods which can be applied for performing a survey in descriptive research are questionnaires, telephonic and personal interviews . In descriptive studies, generally, open-ended questions are included in a questionnaire.
2. Observation
It is basically a technique that the researcher utilities for observing and recording participants. By utilizing this technique you can easily view the subject in a natural setting.
Observations are a way of gathering data that can be used to understand how people act in real-life situations. These observations give researchers the opportunity to see behaviors and phenomena without having them rely on honesty or accuracy from respondents, which is often useful for psychologists, social scientists, and market research companies. Furthermore, observations play an important role in understanding things such as physical entities before developing models hypotheses, or theories – because they provide systematic descriptions of what’s being investigated
For example, an investigation is performed for gathering information about the buying decision-making procedure by customers. The investigator for collecting the facts about the topic has observed people in shopping malls while they are making the purchase of specific products or services. By using the observation technique you can ensure the accuracy and honesty in the information provided by respondents.
3. Case study
You can use the case study methods in research for gathering an in-depth understanding of specific phenomena. It is the method that would enable you to study the situation which takes place rarely
Case studies are a great way to provide detailed information about an individual (such as yourself), group, event, or organization. Instead of gathering data across time and space in order to identify patterns, case studies gather extensive detailed data to identify the characteristics of a narrowly defined subject.
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Bridging the Gap: Overcome these 7 flaws in descriptive research design
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Descriptive research design is a powerful tool used by scientists and researchers to gather information about a particular group or phenomenon. This type of research provides a detailed and accurate picture of the characteristics and behaviors of a particular population or subject. By observing and collecting data on a given topic, descriptive research helps researchers gain a deeper understanding of a specific issue and provides valuable insights that can inform future studies.
In this blog, we will explore the definition, characteristics, and common flaws in descriptive research design, and provide tips on how to avoid these pitfalls to produce high-quality results. Whether you are a seasoned researcher or a student just starting, understanding the fundamentals of descriptive research design is essential to conducting successful scientific studies.
Table of Contents
What Is Descriptive Research Design?
The descriptive research design involves observing and collecting data on a given topic without attempting to infer cause-and-effect relationships. The goal of descriptive research is to provide a comprehensive and accurate picture of the population or phenomenon being studied and to describe the relationships, patterns, and trends that exist within the data.
Descriptive research methods can include surveys, observational studies , and case studies, and the data collected can be qualitative or quantitative . The findings from descriptive research provide valuable insights and inform future research, but do not establish cause-and-effect relationships.
Importance of Descriptive Research in Scientific Studies
1. understanding of a population or phenomenon.
Descriptive research provides a comprehensive picture of the characteristics and behaviors of a particular population or phenomenon, allowing researchers to gain a deeper understanding of the topic.
2. Baseline Information
The information gathered through descriptive research can serve as a baseline for future research and provide a foundation for further studies.
3. Informative Data
Descriptive research can provide valuable information and insights into a particular topic, which can inform future research, policy decisions, and programs.
4. Sampling Validation
Descriptive research can be used to validate sampling methods and to help researchers determine the best approach for their study.
5. Cost Effective
Descriptive research is often less expensive and less time-consuming than other research methods , making it a cost-effective way to gather information about a particular population or phenomenon.
6. Easy to Replicate
Descriptive research is straightforward to replicate, making it a reliable way to gather and compare information from multiple sources.
Key Characteristics of Descriptive Research Design
The primary purpose of descriptive research is to describe the characteristics, behaviors, and attributes of a particular population or phenomenon.
2. Participants and Sampling
Descriptive research studies a particular population or sample that is representative of the larger population being studied. Furthermore, sampling methods can include convenience, stratified, or random sampling.
3. Data Collection Techniques
Descriptive research typically involves the collection of both qualitative and quantitative data through methods such as surveys, observational studies, case studies, or focus groups.
4. Data Analysis
Descriptive research data is analyzed to identify patterns, relationships, and trends within the data. Statistical techniques , such as frequency distributions and descriptive statistics, are commonly used to summarize and describe the data.
5. Focus on Description
Descriptive research is focused on describing and summarizing the characteristics of a particular population or phenomenon. It does not make causal inferences.
6. Non-Experimental
Descriptive research is non-experimental, meaning that the researcher does not manipulate variables or control conditions. The researcher simply observes and collects data on the population or phenomenon being studied.
When Can a Researcher Conduct Descriptive Research?
A researcher can conduct descriptive research in the following situations:
- To better understand a particular population or phenomenon
- To describe the relationships between variables
- To describe patterns and trends
- To validate sampling methods and determine the best approach for a study
- To compare data from multiple sources.
Types of Descriptive Research Design
1. survey research.
Surveys are a type of descriptive research that involves collecting data through self-administered or interviewer-administered questionnaires. Additionally, they can be administered in-person, by mail, or online, and can collect both qualitative and quantitative data.
2. Observational Research
Observational research involves observing and collecting data on a particular population or phenomenon without manipulating variables or controlling conditions. It can be conducted in naturalistic settings or controlled laboratory settings.
3. Case Study Research
Case study research is a type of descriptive research that focuses on a single individual, group, or event. It involves collecting detailed information on the subject through a variety of methods, including interviews, observations, and examination of documents.
4. Focus Group Research
Focus group research involves bringing together a small group of people to discuss a particular topic or product. Furthermore, the group is usually moderated by a researcher and the discussion is recorded for later analysis.
5. Ethnographic Research
Ethnographic research involves conducting detailed observations of a particular culture or community. It is often used to gain a deep understanding of the beliefs, behaviors, and practices of a particular group.
Advantages of Descriptive Research Design
1. provides a comprehensive understanding.
Descriptive research provides a comprehensive picture of the characteristics, behaviors, and attributes of a particular population or phenomenon, which can be useful in informing future research and policy decisions.
2. Non-invasive
Descriptive research is non-invasive and does not manipulate variables or control conditions, making it a suitable method for sensitive or ethical concerns.
3. Flexibility
Descriptive research allows for a wide range of data collection methods , including surveys, observational studies, case studies, and focus groups, making it a flexible and versatile research method.
4. Cost-effective
Descriptive research is often less expensive and less time-consuming than other research methods. Moreover, it gives a cost-effective option to many researchers.
5. Easy to Replicate
Descriptive research is easy to replicate, making it a reliable way to gather and compare information from multiple sources.
6. Informs Future Research
The insights gained from a descriptive research can inform future research and inform policy decisions and programs.
Disadvantages of Descriptive Research Design
1. limited scope.
Descriptive research only provides a snapshot of the current situation and cannot establish cause-and-effect relationships.
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2. Dependence on Existing Data
Descriptive research relies on existing data, which may not always be comprehensive or accurate.
3. Lack of Control
Researchers have no control over the variables in descriptive research, which can limit the conclusions that can be drawn.
The researcher’s own biases and preconceptions can influence the interpretation of the data.
5. Lack of Generalizability
Descriptive research findings may not be applicable to other populations or situations.
6. Lack of Depth
Descriptive research provides a surface-level understanding of a phenomenon, rather than a deep understanding.
7. Time-consuming
Descriptive research often requires a large amount of data collection and analysis, which can be time-consuming and resource-intensive.
7 Ways to Avoid Common Flaws While Designing Descriptive Research
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1. Clearly define the research question
A clearly defined research question is the foundation of any research study, and it is important to ensure that the question is both specific and relevant to the topic being studied.
2. Choose the appropriate research design
Choosing the appropriate research design for a study is crucial to the success of the study. Moreover, researchers should choose a design that best fits the research question and the type of data needed to answer it.
3. Select a representative sample
Selecting a representative sample is important to ensure that the findings of the study are generalizable to the population being studied. Researchers should use a sampling method that provides a random and representative sample of the population.
4. Use valid and reliable data collection methods
Using valid and reliable data collection methods is important to ensure that the data collected is accurate and can be used to answer the research question. Researchers should choose methods that are appropriate for the study and that can be administered consistently and systematically.
5. Minimize bias
Bias can significantly impact the validity and reliability of research findings. Furthermore, it is important to minimize bias in all aspects of the study, from the selection of participants to the analysis of data.
6. Ensure adequate sample size
An adequate sample size is important to ensure that the results of the study are statistically significant and can be generalized to the population being studied.
7. Use appropriate data analysis techniques
The appropriate data analysis technique depends on the type of data collected and the research question being asked. Researchers should choose techniques that are appropriate for the data and the question being asked.
Have you worked on descriptive research designs? How was your experience creating a descriptive design? What challenges did you face? Do write to us or leave a comment below and share your insights on descriptive research designs!
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extremely very educative
Indeed very educative and useful. Well explained. Thank you
Simple,easy to understand
Excellent and easy to understand queries and questions get answered easily. Its rather clear than any confusion. Thanks a million Shritika Sirisilla.
Easy to understand. Well written , educative and informative
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Descriptive Studies- Types, Applications, Advantages, Limitations
- A simple description of the health status of a community, based on routinely available data or on data obtained in special surveys, is often the first step in an epidemiological investigation. Such a study is termed as a descriptive study.
- A descriptive study – as the name implies – describes the distributions of disease, injury or health in a population, outlining the burden of disease or the extent of exposure.
- Pure descriptive studies make no attempt to analyze the links between exposure and effect.
- They summarize patterns of disease or of disease determinants in terms of time, place and person.
- They are usually based on mortality statistics and may examine patterns of death by age, sex, race or ethnicity during specified time periods or in various countries.
- They describe a health outcome by different characteristics of a person (race, age, or sex, for example), place (geographic location), and time (a specific year or a span of time). For example, the case fatality of cholera in 1854 in London was 40% (John Snow, the cholera outbreak in London).
- The results are used to understand a population’s health status, generate hypotheses about the causes of diseases, and inform program planning and evaluation. In other words, descriptive epidemiology describes the distribution of disease.
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Types of Descriptive Studies
The types of descriptive studies include:
- Case reports or case series
- Correlational or ecologic studies
- Cross-sectional studies
- Prevalence surveys
Descriptive studies that examine individuals can take the form of case reports (a report of a single case of an unusual disease or association), case series (a description of several similar cases) and cross-sectional studies. Descriptive studies that examine populations, or groups, as the unit of observation, are known as ecological studies.
Applications of Descriptive Studies
- Descriptive epidemiology identifies non-random variation in the distribution of disease, injury or health.
- Their function is to describe the “who, what, why, when, where” without regard to the hypothesis, highlighting patterns of disease and associated factors.
- This allows the public health practitioner to generate testable hypotheses regarding why such variation occurs.
- Descriptive epidemiology identifies who is affected, when, and where the situation is occurring in the community or population of interest. This is an important tool for health services planning and programming.
- Pure descriptive studies are rare, but descriptive data in reports of health statistics are a useful source of ideas for epidemiological studies.
- Limited descriptive information (such as that provided in a case series) in which the characteristics of several patients with a specific disease are described but are not compared with those of a reference population, often stimulates the initiation of a more detailed epidemiological study.
For example, the description in 1981 of four young men with a previously rare form of pneumonia was the first in a wide range of epidemiological studies on the condition that became known as the acquired immunodeficiency syndrome (AIDS).
Advantages of Descriptive Studies
- Descriptive (including ecological) studies are generally relatively quick, easy and cheap to conduct.
- Exposure data often only available at the area level.
- Differences in exposure between areas may be bigger than at the individual level, and so are more easily examined.
- Utilization of geographical information systems to examine the spatial framework of disease and exposure.
Limitations
- A descriptive study is limited to a description of the occurrence of a disease in a population.
- It is unable to test hypotheses.
- Weaknesses of case reports and case series are that they have no comparison (control) group, they cannot be tested for statistical associations, and they are especially prone to publication bias (especially where case reports/series describe the effectiveness of an intervention).
- Park, K. (n.d.). Park’s textbook of preventive and social medicine.
- Gordis, L. (2014). Epidemiology (Fifth edition.). Philadelphia, PA: Elsevier Saunders.
- https://wiki.ecdc.europa.eu/fem/w/wiki/descriptive-studies
- https://cursos.campusvirtualsp.org/mod/tab/view.php?id=34133&forceview=1
- http://sphweb.bumc.bu.edu/otlt/MPH-Modules/EP/EP713_DescriptiveEpi/EP713_DescriptiveEpi_print.html
- https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/descriptive-studies-ecological-studies
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Advantages and disadvantages of descriptive research
Descriptive research
Descriptive research is a type of research that is responsible for describing the population situation or phenomenon around which his study focuses. It seeks to provide information about the what, how, when, and where of the research problem, without giving priority to answering the “why” of the problem. As its name says, this way of investigating “describes”, it does not explain. Advantages and disadvantages of descriptive research
In addition, it obtains information on the phenomenon or situation to be studied, using techniques such as observation and survey, among others. For example, research studying the morphology and mechanism of action of SARS-CoV-2 is descriptive. Answer the “what”, not the “why”.
This type of research is very useful when conducting studies, for example, when you want to know which brand of soda is most consumed in a supermarket, where you only want to know which is the most consumed, and not why it is the most consumed. consumed.
Descriptive investigations, unlike other types of investigations, carry out their study without altering or manipulating any of the variables of the phenomenon, limiting themselves only to their measurement and description. Additionally, it is possible to make future forecasts, although they are considered premature or basic.
Descriptive research characteristics
Here are some of the most important characteristics of descriptive research :
Has no control over variables
In descriptive research, the researcher has no control over any of the variables that affect the event or problem under investigation. Advantages and disadvantages of descriptive research
Existence of variables
To carry out a descriptive research , it is necessary to know in advance the variables that will be analyzed, since this type of research is not dedicated to the search for variables, but to their study.
Although, when obtaining data on the variables , it is possible to make forecasts, these are not entirely reliable, since they are considered premature.
Quantitative information
In most cases, descriptive research gets data on quantities, not qualities . It is for this reason that it can be said that a descriptive research is quantitative. Advantages and disadvantages of descriptive research
Even so, there is also the possibility of obtaining qualitative data.
As in all types of research , the data provided by descriptive research must be both accurate and reliable.
Information classification
Descriptive research can be used to classify the data collected in the study that is being carried out, separating them into different categories of description.
Usually, the cross-sectional or transectional design is the most used to carry out this type of research , although it is also possible to use the pre-experimental design. Advantages and disadvantages of descriptive research
Descriptive research design
The research design is used to draw up the work plan to follow in the research. It is where the conceptual phase of the research, such as the statement of the problem , meets the operational phase, such as the method and instruments of the investigation.
For the case of the design of a descriptive investigation, most of the time it is necessary to obtain data that refers to the quantity. To achieve this task, the researcher can choose between two different types of research designs, which have specific characteristics that differentiate them from each other.
The two types of designs used in descriptive research are described below:
Cross-sectional or transectional design
In cross-sectional designs, the variables are not affected by any type of process, which is why they only dedicate themselves to observing the event as it happens, limiting themselves only to analyzing them. Advantages and disadvantages of descriptive research
They basically consist of making a description of the variables to be measured in a phenomenon, and analyzing the incidence at the time that event occurs.
Pre-experimental design
There are occasions where the pre- experimental design is used as a test to get a first contact with the research problem in a real way, being used, on some occasions, as a test of experiments with a greater degree of control.
This type of design does not allow to establish causal relationships, since they do not have the possibility of controlling variables , and their internal validity is not very reliable. Furthermore, it is applied only to a group, over which it has no control whatsoever.
There are two ways to carry out a pre- experimental design, which are as follows:
- Case study with a single measurement : in this type of design, a stimulus is applied to a group and then the data obtained from the variable or variables to be measured are taken. The simplicity of the design makes it unreliable, since there is no reference to the level of the variable (s) before the stimulus is applied, as well as no control over them.
- Test and post-test design with a single group : for this type of design, a test is carried out before and after applying the stimulus to the group, thus allowing the visualization of the differences that may exist between the measurements of the studied variable (s) . Although, using this design it is possible to differentiate the levels of the variables , before and after the stimulus is applied, it does not allow to visualize causality, since there is no comparison group, nor is there the possibility of manipulating the variables. Advantages and disadvantages of descriptive research
Techniques used in descriptive research
In the case of descriptive research , there are three techniques to carry it out:
Observation
Observation is one of the most used information, of the quantitative or qualitative type:
- To obtain quantitative information , statistical and numerical study methodologies are used, where information about values such as weight, scale and years, among others, is obtained. So it can be said that fundamentally numerical values are obtained.
- On the other hand, to obtain qualitative information, the type of data obtained does not have to do with numbers or statistics , but with the dynamics that occur in the group on which the research is being developed. Advantages and disadvantages of descriptive research
Using the case study it is possible to carry out a slightly more detailed analysis of the event, as well as to study in detail groups or subjects separately.
In addition, it is possible to present a hypothesis and to expand the degree of knowledge about the event under investigation. However, due to its low precision in forecasting, it is not possible to specify the causes and effects of the phenomenon studied.
Research survey
The research survey is one of the most widely used instruments when conducting descriptive research, where the number of samples to be taken is large. Advantages and disadvantages of descriptive research
The selection of questions should include both open and closed questions, thus guaranteeing a balance between them and making it possible to collect good quality information.
Like all different types of research , descriptive research has both advantages and disadvantages. Some of the most important are listed below.
- The brevity by which descriptive investigations are carried out means that their costs are not high, compared to other types of investigations.
- It enables both the collection of quantitative data and qualitative data.
- They allow to formulate hypotheses, as well as provide a large amount of valuable data for the development of future investigations. Advantages and disadvantages of descriptive research
- By using descriptive research , the data is collected in the place where it occurs, without any type of alteration, ensuring the quality and integrity of the same.
Disadvantages
- If the questions are not well formulated, the answers obtained may not be entirely reliable, which makes it difficult to carry out a credible investigation.
- The types of variables that allow the study of descriptive investigations make it impossible to visualize the causes and effects of the event.
- The data obtained by conducting a descriptive research , being collected randomly, make it impossible to obtain valid data that represent the entire population.
Descriptive Research Examples
Some examples of descriptive investigations may be the following:
Penguin census
Studying the penguin population that exists in the South Georgia Islands is a descriptive investigation that answers the what and where. Advantages and disadvantages of descriptive research
National census
The research carried out in a national census is descriptive, since it is only interested in data such as the number of population, the salary they receive, or what class the household is, without making any kind of analogy between these. .
Carrying out a descriptive investigation that collects data about the political party that people will choose in the next elections, it is possible to predict, with a margin of error , the result that will be obtained in them.
Supermarket
Using observation, qualitative data can be collected on the habits of supermarket customers regarding the purchases they make in it. Advantages and disadvantages of descriptive research
Kids playtime
Through the resource of the survey , it is possible to carry out a descriptive investigation that yields information about the number of hours per day that children in a particular population play. Being able to make a forecast of the weather that a particular child of that city plays.
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Research on the dynamic evaluation of the competitiveness of listed seed enterprises in china.
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1. Introduction
2. research design, 2.1. indicator system construction, 2.1.1. scale strength, 2.1.2. benefit strength, 2.1.3. operational capacity, 2.1.4. technological innovation capability, 2.2. research methodology and sample selection, 2.2.1. global principal component analysis, 2.2.2. cluster analysis, 2.2.3. sample selection and data source, 3. evaluation and classification of the competitiveness of listed seed enterprises, 3.1. descriptive statistics analysis, 3.2. global principal component analysis, 3.2.1. applicability analysis, 3.2.2. principal component extraction, 3.2.3. principal component naming, 3.2.4. principal component scores and ranking, 3.3. cluster analysis, 4. a vertical and horizontal comparative analysis of the competitiveness of listed seed enterprises, 4.1. comparison of the dynamic competitiveness of seed enterprises, 4.2. comparison of the static competitiveness of seed enterprises, 4.3. industry heterogeneity of seed enterprises’ competitiveness, 4.3.1. criteria for classifying industry differences in seed enterprises, 4.3.2. comparison of seed enterprises’ competitiveness, 4.4. competitiveness comparison between chinese listed seed enterprises and multinational seed industry giants, 5. discussion, 6. conclusions and policy implications, 6.1. conclusions, 6.2. recommendations, author contributions, institutional review board statement, data availability statement, conflicts of interest.
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Click here to enlarge figure
Overall Target | Level 1 Indicators | Secondary Indicators | Tertiary Indicators | Indicator Code |
---|---|---|---|---|
Competitiveness of listed seed enterprises | Explicit Competitiveness | Scale Strength | Revenues | x1 |
Enterprise scale | x2 | |||
Net assets | x3 | |||
Benefits Strength | Return on net assets | x4 | ||
Return on total assets | x5 | |||
Gross profit margin | x6 | |||
Output per employee | x7 | |||
Year-on-year growth in basic earnings per share | x8 | |||
Potential Competitiveness | Operating Capacity | Total asset turnover | x9 | |
Current asset turnover ratio | x10 | |||
Inventory turnover | x11 | |||
Technological Innovation Capacity | R&D capital investment | x12 | ||
R&D labor investment | x13 |
Secondary Indicator Variables | Third-Level Indicator Variables | Mean | S.D. | Min | p50 | Max |
---|---|---|---|---|---|---|
Scale Strength | Revenues | 12.39 | 34.28 | 0.0184 | 1.773 | 324.0 |
Enterprise size | 17.75 | 37.22 | 0.0849 | 3.514 | 311.7 | |
Net assets | 9.911 | 20.23 | −0.0216 | 1.868 | 130.4 | |
Benefits Strength | Return on net assets | 7.961 | 16.69 | −98.30 | 7.415 | 91.44 |
Net interest rate on total assets | 5.379 | 9.195 | −26.32 | 4.129 | 62.40 | |
Gross sales margin | 28.89 | 16.67 | −32.92 | 27.88 | 85.86 | |
Output per employee | 0.0142 | 0.0131 | 0 | 0.0113 | 0.109 | |
Year-on-year growth in basic earnings per share | −38.90 | 69.82 | −96 | 5.882 | 41.50 | |
Operating Capacity | Total asset turnover | 0.635 | 0.387 | 0.0299 | 0.543 | 3.113 |
Current asset turnover ratio | 1.071 | 0.636 | 0.0657 | 0.933 | 4.522 | |
Inventory turnover | 2.290 | 3.061 | 0.208 | 1.538 | 40.94 | |
Technological Innovation Capacity | R&D capital investment | 4.410 | 4.764 | 0.0300 | 3.725 | 55.02 |
R&D labor investment | 11.94 | 7.716 | 0.0917 | 12.73 | 30.52 |
Test Methods | Indicator Variables | Results |
---|---|---|
KMO test | KMO statistic | 0.662 |
Bartlett’s test | approximate chi-square (math.) | 1558.519 |
Df | 78 | |
Sig | 0.000 |
Principal Component | Eigenvalue (Math.) | Contribution (%) | Cumulative Contribution (%) |
---|---|---|---|
F1 | 4.357 | 33.515 | 33.515 |
F2 | 2.968 | 22.833 | 56.348 |
F3 | 2.077 | 15.976 | 72.325 |
F4 | 1.443 | 11.1 | 83.425 |
Principal Component Name | Variables | F1 | F2 | F3 | F4 |
---|---|---|---|---|---|
operational capability | Current asset turnover ratio | 0.893 | −0.011 | 0.244 | −0.016 |
Revenues | 0.856 | 0.133 | −0.362 | 0.195 | |
Total asset turnover | 0.836 | −0.048 | 0.469 | 0.056 | |
Inventory turnover | 0.738 | −0.184 | 0.182 | −0.011 | |
net assets | 0.718 | 0.306 | −0.572 | 0.123 | |
asset size | 0.714 | 0.216 | −0.591 | 0.226 | |
growth capacity | Net interest rate on total assets | 0.108 | 0.894 | 0.244 | −0.219 |
return on net assets | 0.113 | 0.884 | 0.297 | −0.131 | |
Gross sales margin | −0.335 | 0.74 | −0.227 | −0.2 | |
Year-on-year growth in basic earnings per share | 0.087 | 0.643 | 0.38 | −0.019 | |
production efficiency | Output per employee | 0.262 | −0.195 | 0.7 | 0.439 |
Technological innovation capacity | R&D labor intensity | −0.344 | 0.306 | 0.231 | 0.766 |
R&D capital investment intensity | −0.476 | 0.316 | −0.262 | 0.671 |
Indicator | F1 | F2 | F3 | F4 |
---|---|---|---|---|
Current asset turnover ratio | 0.205 | −0.004 | 0.118 | −0.011 |
revenues | 0.197 | 0.045 | −0.175 | 0.135 |
Total asset turnover | 0.192 | −0.016 | 0.226 | 0.039 |
Inventory turnover | 0.169 | −0.062 | 0.088 | −0.007 |
net assets | 0.165 | 0.103 | −0.275 | 0.086 |
asset size | 0.164 | 0.073 | −0.284 | 0.156 |
Net interest rate on total assets | 0.025 | 0.301 | 0.118 | −0.152 |
return on net assets | 0.026 | 0.298 | 0.143 | −0.091 |
Gross sales margin | −0.077 | 0.249 | −0.109 | −0.139 |
Year-on-year growth in basic earnings per share | 0.02 | 0.217 | 0.183 | −0.013 |
Output per employee | 0.06 | −0.066 | 0.337 | 0.304 |
R&D labor intensity | −0.079 | 0.103 | 0.111 | 0.531 |
R&D capital investment intensity | −0.476 | 0.316 | −0.262 | 0.671 |
Rankings | Operational Capability | Growth Capacity | Production Efficiency | Technological Innovation Capacity | Enterprise Competitiveness | |||||
---|---|---|---|---|---|---|---|---|---|---|
Corporations | F1 Score | Corporations | F2 Score | Corporations | F3 Score | Corporations | F4 Score | Corporations | F Score | |
1 | A1 | 10.36 | B1 | 2.2 | C1 | 3.86 | D1 | 3.72 | E1 | 3.88 |
2 | A2 | 4.7 | B2 | 1.79 | C2 | 2.29 | D2 | 2.01 | E2 | 2.09 |
3 | A3 | 3.64 | B3 | 1.73 | C3 | 0.83 | D3 | 1.63 | E3 | 1.56 |
4 | A4 | 3.42 | B4 | 1.01 | C4 | 0.53 | D4 | 1.46 | E4 | 1.34 |
5 | A5 | 1.99 | B5 | 1 | C5 | 0.11 | D5 | 0.86 | E5 | 1.08 |
6 | A6 | 1.51 | B6 | 0.61 | C6 | −1.07 | D6 | 0.53 | E6 | 0.82 |
7 | A7 | 1.04 | B7 | 0.57 | C7 | −2.13 | D7 | 0.26 | E7 | 0.7 |
8 | A8 | 1.01 | B8 | −0.03 | C8 | −2.76 | D8 | 0.06 | E8 | 0.56 |
9 | A9 | 0.58 | B9 | −0.05 | C9 | −3.79 | D9 | −1.18 | E9 | 0.45 |
10 | A10 | −0.3 | B10 | −1.52 | C10 | −6.54 | D10 | −1.2 | E10 | 0.17 |
Type of Seed Enterprise | Number of Seed Enterprises | Name of the Seed Company |
---|---|---|
Type I | 2 | F1 and F2 |
Type II | 6 | F3–F8 |
Type III | 19 | F9–F27 and 19 other seed enterprises |
Type IV | 22 | F28–49 and 22 other seed enterprises |
Seed Enterprises | Operational Capability | Growth Capacity | Production Efficiency | Technological Innovation Capacity | Enterprise Competitiveness |
---|---|---|---|---|---|
G1 | 1.99 | −1.52 | 3.86 | 1.63 | 1.34 |
G2 | 1.85 | −0.73 | 0.73 | 0.96 | 0.81 |
G3 | 0.69 | −0.63 | −4.2 | 2.6 | −0.35 |
G4 | −0.41 | 0.74 | −0.98 | 1.03 | −0.01 |
G5 | 1.01 | 0.57 | 0.11 | 0.86 | 0.7 |
G6 | 3.64 | −0.03 | 2.29 | 1.46 | 2.09 |
G7 | 4.7 | 0.61 | −2.76 | 0.26 | 1.56 |
G8 | −0.33 | 0.46 | −0.18 | −0.85 | −0.15 |
G9 | 10.36 | 1.73 | −6.54 | 3.72 | 3.88 |
G10 | 3.42 | 1 | −2.13 | −1.18 | 1.08 |
Rankings | Enterprise Abbreviation | Country | Operating Income for 2018 | Rankings | Enterprise Abbreviation | Operating Income for 2018 |
---|---|---|---|---|---|---|
1 | Bayer Monsanto | German | 741.75 | 1 | H1 | 193.02 |
2 | Cordova Agricultural Technology | America | 551.31 | 2 | H2 | 48.84 |
3 | Syngenta (ChemChina) | China | 206.83 | 3 | H3 | 35.80 |
4 | BASF | German | 137.71 | 4 | H4 | 34.46 |
5 | Limagrain | French | 125.38 | 5 | H5 | 32.65 |
6 | Covos (brand) | German | 108.31 | 6 | H6 | 19.27 |
7 | Dannon | Denmark | 46.68 | 7 | H7 | 16.52 |
8 | Sakata Seedling Co. | Japan | 39.52 | 8 | H8 | 12.84 |
9 | Long Ping High-Tech | China | 35.80 | 9 | H9 | 9.10 |
10 | Rijk Zwaan | Holland | 33.26 | 10 | H10 | 8.49 |
11 | TAKII SEED | Japan | 32.43 | 11 | H11 | 7.67 |
12 | Floremont I Depay Breeding Co. | French | NA | 12 | H12 | 7.61 |
13 | Bejo | Holland | 22.17 | 13 | H13 | 6.27 |
14 | Barenburg | Holland | 20.93 | 14 | H14 | 3.24 |
15 | Enza Zaden | Holland | NA | 15 | H15 | 2.78 |
16 | RAGT Semences | French | 17.70 | 16 | H16 | 2.64 |
17 | Andean Seeds (United Phosphorus) | India | NA | 17 | H17 | 2.55 |
18 | Heilongjiang Agriculture Company Limited | China | 16.52 | 18 | H18 | 2.48 |
19 | Euralis | French | 15.63 | 19 | H19 | 2.43 |
20 | invivo | French | 9.91 | 20 | H20 | 2.07 |
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Li, L.; Zhang, L.; Wang, X. Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China. Agriculture 2024 , 14 , 1213. https://doi.org/10.3390/agriculture14081213
Li L, Zhang L, Wang X. Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China. Agriculture . 2024; 14(8):1213. https://doi.org/10.3390/agriculture14081213
Li, Lanlan, Lu Zhang, and Xiudong Wang. 2024. "Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China" Agriculture 14, no. 8: 1213. https://doi.org/10.3390/agriculture14081213
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A descriptive correlation study was a research method that observes and characterizes the behavior of participants from a scientific standpoint in relation to factors in a setting. It seeks to ...
A descriptive research aims to describe a phenomena the ways it is, for example, describing social systems or relationships between events (Adams et al., 2007). This paper attempts to introduce descriptive analysis; its advantages, disadvantages an example of Descriptive Analysis and conclusion. The next section introduces Descriptive Analysis ...
INTRODUCTION. In our previous article in this series, [ 1] we introduced the concept of "study designs"- as "the set of methods and procedures used to collect and analyze data on variables specified in a particular research question.". Study designs are primarily of two types - observational and interventional, with the former being ...
Box 1. Descriptive Analysis Is a Critical Component of Research Box 2. Examples of Using Descriptive Analyses to Diagnose Need and Target Intervention on the Topic of "Summer Melt" Box 3. An Example of Using Descriptive Analysis to Evaluate Plausible Causes and Generate Hypotheses Box 4.
One of the biggest advantages of descriptive research is that it allows you to analyze facts and helps you in developing an in-depth understanding of the research problem. Another benefit of descriptive research is that it enables you to determine the behavior of people in a natural setting. In such a type of investigation, you can utilize both ...
Descriptive studies have several important roles in medical research.They are often the first foray into a new disease or area of inquiry—the first scientific "toe in the water".1 They document the health of populations and often prompt more rigorous studies. Since descriptive studies are often reported,2 clinicians need to know their
classified either as descriptive versus analytical study designs or as observational versus interventional. Study designs are arranged in a hierarchy starting from the basic 'Case Report' to the highly valued 'Randomised Clinical Trial'[4] as shown in Table 1. Before discussing the advantages and disadvantages of each study design,
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medical research. They are often the first foray into a new disease or area of inquiry-the first scientific "toe in the ... we provide an overview of the advantages and disadvantages of descriptive studies, provide examples of several types of descriptive study, examine their clinical uses, and show how they can be misinterpreted. ...
Beck S.: Designing a study, in Mateo MA, Kirchhoff KT (eds): Conducting and Using Nursing Research in the Clinical Setting. Baltimore, MD, Williams and Wilkins, 1991 Baltimore, MD, Williams and Wilkins, 1991
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Over the years, many techniques have been developed to meet different objectives and applications, each with their own advantages and disadvantages. Traditional techniques include Flavour Profiling, Texture Profiling, Spectrum TM Method and Quantitative Descriptive Analysis. These are more time consuming and costly due to the extensive training ...
DATA COLLECTION METHODS: SOME TIPS AND COMPARISONS. In the previous chapter, we identified two broad types of evaluation methodologies: quantitative and qualitative. In this section, we talk more about the debate over the relative virtues of these approaches and discuss some of the advantages and disadvantages of different types of instruments.
Types of Descriptive Studies. The types of descriptive studies include: Case reports or case series. Correlational or ecologic studies. Cross-sectional studies. Prevalence surveys. Descriptive studies that examine individuals can take the form of case reports (a report of a single case of an unusual disease or association), case series (a ...
They allow to formulate hypotheses, as well as provide a large amount of valuable data for the development of future investigations. Advantages and disadvantages of descriptive research. By using descriptive research, the data is collected in the place where it occurs, without any type of alteration, ensuring the quality and integrity of the same.
Keywords: descriptive evaluation, strength, weakness, school. 1. Introduction. During the past few years, there have been extensive arguments over educational reforms in schools. The evaluation of students is considered as a key factor in school reformation and improvement in education and learning (Seif, 2010).
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Descriptive research provides a broad picture of a phenomenon you might be interested in exploring. Current employment rates, census of any country, number of working single parents are examples of descriptive research. 4.3.3 Correlational Research Descriptive and historical research provides a picture of events that are currently
Descriptive studies have several important roles in medical research. They are often the first foray into a new disease or area of inquiry—the first scientific "toe in the water". 1. They document the health of populations and often prompt more rigorous studies. Since descriptive studies are often reported, 2.
s tend to have higher internal validity and lower external validity. Finally, case studies as a sc. entific method is highly disputed but even so it is a well-used method. Simply put, the case study as a scientific method has both advantages and disadvantages, like all research methods, and should be used when it'. ropriate plan fo.
summary that can aid in decision-making. The paper explains the importance of descriptive. visualization, analysis, interpretation, and reporting. The paper also mentions the advantages of. data ...
Seed enterprises are crucial for ensuring national food security, the driving force behind the seed industry's advancement, and the core entity in constructing a modern seed industry system. At the micro and macro levels, agricultural seed enterprises face challenges and pressures in earning excess profits, enhancing their competitive edge, and resisting the incursion of multinational seed ...
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