This document discusses different types of research designs, including observational and intervention designs. It focuses on non-intervention designs like case reports, case series, and cross-sectional studies. Case reports describe the occurrence, diagnosis, treatment and follow-up of an individual patient, especially unusual cases. Case series describe aspects of a disease or treatment by following a group of patients with common characteristics. Both case reports and case series are useful for generating hypotheses but have limitations due to lack of a control group.

1. RESEARCH DESIGN
Prabesh Ghimire

2. Types of Research Design
Prabesh Ghimire, MPH 2

3. Types of Research Design
Non-Intervention
Observational
Design
Intervention Design
Population Based Individual Based
Descriptive
(Health
Survey)
Ecological
Study
Descriptive
Case Report/
Case Series
Analytical
Cross-sectional or
Prevalence Study
Case- Control Study Cohort Study
Randomized
Control Trial or
Clinical Trial
Non-randomized
Quasi Experimental
Field Trial
Cross-over
Design
Parallel
Design
Research
Designs
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4. Types of Research Design
• Observational/ Non-Intervention Design
• Observe both exposures and outcomes
• Intervention Design
• Assign exposures
• Observe outcomes
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5. Hierarchy of
Scientific
Evidence
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6. Observational Design
• Allows nature to take its course
• The investigator observes/ measures but does not intervene.
• Types
• Descriptive (Case report, case series, ecological, cross-sectional)
• Analytical (Cross-sectional, case-control, cohort)
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7. Case Report
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8. Case Report
• A case report is a detailed description of disease occurrence,
diagnosis, treatment, response to treatment, and follow-up after
treatment of an individual person.
• Case reports usually describe an unusual or novel occurrence
and as such, remain one of the cornerstones of public health
progress and provide many new ideas in public health.
• Unusual features of the case may suggest a new hypothesis
about the causes or mechanisms of disease.
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9. Case Report
Case reports often describe:
• Unique cases that cannot be explained by known diseases or
syndromes
• Cases that show an important variation of a disease or
condition
• Cases that show unexpected events that may yield new or
useful information
• Cases in which one patient has two or more unexpected
diseases or disorders
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10. Reasons for preparing case report
Case reports are prepared to keep record of
• an unexpected association between diseases or symptoms;
• an unexpected event in the course observing or treating a
patient;
• findings that shed new light on the possible pathogenesis of a
disease or an adverse effect;
• unique or rare features of a disease;
• unique therapeutic approaches; variation of anatomical
structures.
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11. Case Report
• Case reports are considered the lowest level of evidence, but
they are also the first line of evidence, because they are where
new issues and ideas emerge.
• If multiple case reports show something similar, the next step
might be a case-control study to determine if there is a
relationship between the relevant variables.
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12. Case Report
Case report should provide the following case details
• Case description (socio-demographic information)
• Case history
• Physical examination results
• Results of pathological tests and other investigations
• Treatment plan
• Expected outcome of the treatment plan
• Actual outcome
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13. Case Report
Strengths
• Can help in the identification of new trends or diseases
• Can help detect new drug side effects and potential uses
(adverse or beneficial)
• Educational -a way of sharing lessons learned
• Identifies rare manifestations of a disease (for example in covid-
19)
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14. Case Report
Limitations
• Cases may not be generalizable
• Not based on systematic studies
• Causes or associations may have other explanations
• Can be seen as emphasizing the bizarre or focusing on
misleading elements
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15. Case Series
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16. Case Series
• A case series is a descriptive study that follows a group of
patients with common characteristics used to describe some
clinical, pathophysiological or operational aspects of a disease,
treatment or diagnostic procedures.
• The primary purpose of a case series is generation of
hypotheses that subsequently can be tested in studies of
greater methodological rigor.
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17. Case Series
• It is most useful for describing the potential effectiveness of
new interventions, for describing the effectiveness of
interventions on unusual diagnoses, and for describing
unusual responses (either good or bad) to interventions.
• Case series can be conducted retrospectively or prospectively.
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18. When to consider a Case Series
• When a more cautious description of interventions in several
settings in required.
• To report on novel diagnostic or therapeutic strategies,
particularly when the option of waiting for comparative evidence
is considered unacceptable.
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19. Importance of Case Series
Clinical case-‐ series are of value in public health field for:
• Studying predictive symptoms, signs, and tests.
• Creating case definitions
• Clinical education, audit, and research
• Health services research
• Establishing safety profiles
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20. Types of Case Series
On the basis of recruitment
Consecutive case series:
• Includes all eligible patients identified by the researchers during the
study period.
• The patients are treated in the order in which they are identified.
• Consecutiveness increases the quality of the case series.
Non-consecutive case series:
• Includes some, but not all, of the eligible patients identified by the
researchers during the study period.
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21. Types of Case Series
On the basis of sampling
Exposure-based sampling
• Include all patients treated and have specific outcomes or adverse events.
• Sampling is based on both a specific outcome and presence of a specific
exposure.
Outcome-based sampling
• Includes patients with the specific outcome regardless of exposure.
• Thus neither absolute risk nor relative risk can be calculated.
• Selection is based only on a specific outcome, and data are collected on
previous exposures.
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22. Designing a good case series
Research Question
• The study question should list its study population, the intervention,
and the primary outcome.
Setting
• Select a suitable observation period and identify cases with events in
this period.
• It may be tempting to include patients seen over a large period of
time to increase sample size.
• However, the use of a short inclusion period minimizes known and
unknown changes over time in co-interventions, prognosis, and even
in the intervention under study
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23. Designing a good case series
Number of Cases
• The general number of cases reported in a case series range from
20 to 50.
• But may vary from as few as 2 or 3 to as many as more than 100 or
even thousands.
Data collection
• Reports of case series usually contain detailed information about the
individual patients.
• This includes demographic information (for example, age, gender,
ethnic origin) and information on diagnosis, treatment, response to
treatment, and follow-up after treatment
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24. Designing a good case series
What
• The diagnosis or case definition should be clear and applied
equally to all individuals in the series.
• The case definition should mention the inclusion and exclusion
criteria, which should be based on widely used validated
definitions.
• When: The date when the disease or death occurred (time).
• Where: The place where the person lived, worked etc (place).
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25. Designing a good case series
Who
• The characteristics of the population (person).
• Noting the socio-demographic characteristics of a series of
cases, as well as the temporal and spatial distributions can
sometimes provide a clue to risk factors and hence help
generate a hypothesis.
• This can be tested subsequently with more elaborate analytic
studies.
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26. Designing a good case series
• A detailed description of the intervention and the co-intervention
should be stated. This will ensure repeatability of the study by
other investigators.
• It is very important to thoroughly describe co-interventions (for
example, physical therapy)
• The most important outcomes in care are those that measure
patient satisfaction, relief of symptoms, and a feeling of well-
being.
• An example is the Short Form-36 questionnaire, which not only
measures physical function but also mental well-being.
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27. Designing a good case series
Methods of data collection
• The method of data acquisition (telephone interview, clinical
measurement, or chart review) should be addressed in the study
report
Analysis
• Only descriptive statistics should be used.
• Findings can be presented as proportions (%) of the study
populations with the outcome, confidence intervals; means,
standard deviations for continuous variables
• No comparative tests yielding p values should be done.
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28. Designing a good case series
Reporting
• A statement of the external validity of the obtained data should be
given. This includes patient characteristics and completeness of
follow-up.
• The follow-up rates and reasons for loss to follow-up should be
stated.
• No absolute conclusions on the studied treatment should be stated.
As mentioned before, the lack of a comparison group prohibits any
hypothesis from being tested.
• Valid conclusion: “Patients treated by treatment X showed good outcome Y
after Z months of follow-up.”
• Stating that “treatment X is better than treatment Y” or even that “treatment X
is effective” would be invalid.
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29. Strengths and Limitations
Strengths
• High external validity: the study results are closer to those obtained in
routine clinical practice and may, therefore, be considered more relevant.
• It could be useful when a randomized controlled trial is not appropriate or
possible.
• No interference in the treatment decision process
• Wide range of patients can be studied
• In-expensive
• Conduction of study take little time
• Useful for hypothesis generation
• Informative for very rare disease with few established risk factors.
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30. Strengths and Limitations
Limitations
• Lack of a control (or comparison) group
• Lack of a denominator to calculate rates of disease.
• Causal inferences cannot be made
• Data collection often incomplete
• Susceptible to bias (selection bias, measurement bias)
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31. For further reading
• https://asploro.com/what-is-case-
series/#:~:text=Non%2DConsecutive%20Case%20Series%3A%20%5B,quality%20of%20
the%20case%20series.
• Mathes, T., & Pieper, D. (2017). Clarifying the distinction between case series and cohort
studies in systematic reviews of comparative studies: potential impact on body of
evidence and workload. BMC medical research methodology, 17(1), 107.
https://doi.org/10.1186/s12874-017-0391-8
• Abu-Zidan, F. M., Abbas, A. K., & Hefny, A. F. (2012). Clinical "case series": a concept
analysis. African health sciences, 12(4), 557–562.
• https://www.researchgate.net/publication/327449197_What_is_case_series
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32. Ecological Study Design
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33. Ecological Study
• Observational study in which data are analyzed at the
population or community level rather than individual level.
• Disease rates and exposures are measured in each of a series
of populations and their relations is examined.
• Often the information about disease and exposure is abstracted
from published statistics and therefore does not require
expensive or time consuming data collection.
• In ecological studies health outcomes are aggregates of
individual health data. E.g. prevalence, incidence, rate of
diseases.
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34. Years of education Teenage pregnancy
(Yes/No)
Prevalence/ Rate of
Teenage Pregnancy
Association
Avg. no. of years of
education
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35. Purpose of ecological study
• To monitor population health so that public health strategies may be
developed and directed.
• To make large scale comparisons, e.g. comparisons between
countries;
• To study the relationship between population-level exposure to risk
factors and diseases or in-order to look at the contextual effect of
risk factors on the population
• When disease under investigation is rare, requiring aggregation of
data for any analysis to be carried out.
• When measurement at individual level are not available. E.g.
confidentiality might require that individuals are anonymized by
aggregation of data to small area level.
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36. Types of Ecological Study
Geographical
• One common approach is to look for geographical correlations
between disease incidence or mortality and the prevalence of
risk factors.
• For example, mortality from coronary heart disease in local
authority areas of England and Wales has been correlated with
neonatal mortality in the same places 70 and more years
earlier.
• This observation generated the hypothesis that coronary heart
disease may result from the impaired development of blood
vessels and other tissues in fetal life and infancy.
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37. Types of Ecological Study
Longitudinal/Time trends
• Many diseases show remarkable fluctuations in incidence over time.
• Epidemics of chronic disorders such as lung cancer and coronary
heart disease evolve over decades.
• If time or secular trends in disease incidence correlate with changes
in a community’s environment or way of life then the trends may
provide important clues to aetiology.
• Example: In Britain, successive rises and falls in mortality from
cervical cancer have been related to varying levels of sexual
promiscuity, as evidenced by notification rates for gonorrhoea.
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38. Types of Ecological Study
Migrant studies
• In migrant studies, the disease rate among persons who have
migrated from one location to another is compared with the
disease rate in persons who did not migrate.
• Second generation Japanese migrants to the USA have
substantially lower rates of stomach cancer than Japanese
people in Japan, indicating that the high incidence of the
disease in Japan is environmental in origin.
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39. Ecological Study
• Advantage
• Inexpensive and easy to carry-out using routinely collected data
• Useful for performing international comparisons and studying group-
level effects (correlation between rates from CVD and cigarette sales
per capita)
• Disadvantage
• Prone to bias and confounding
• Caution is needed when applying grouped results to the individual level
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40. Ecological Study Examples
• Assessment of various dietary factors and cancer mortality and
incidence by country.
• Incidence rates for 27 cancers in 23 countries and mortality rates for 14
cancers in 32 countries have been correlated with a wide range of
dietary and other variables.
• Source: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ijc.2910150411
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41. Ecological Fallacy
• Type of confounding specific to ecological studies.
• Occurs when relationships which exists for groups are assumed to
also be true for groups.
• It is an error in the interpretation of the results of an ecological study,
where conclusions are inappropriately inferred about individuals from
the results of aggregate data.
• The fallacy assumes that individual members of a group all have the
average characteristics of the group as whole, when in fact any
association observed between variables at the group level does not
necessarily mean that the same association exists for any given
individual selected from the group.
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42. Ecological Fallacy
• For example, it has been observed that the number of
televisions per capita is negatively associated with the rate of
deaths from heart disease.
• However, it would be an ecological fallacy to infer that people
who don’t own televisions die from heart disease.
• Indeed, in this scenario there are other potentially causative
factors that could be common to both, such as reduced physical
activity or a poorer diet associated with less affluent societies.
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43. Ecological Fallacy
• In ecologic studies, only information on aggregate measures,
such as the average exposure in City A and the death rate in
City A can be known.
• At the individual level, however, we can, for example, determine
the proportion of people who died within each of the categories
of exposure (low or high).
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44. Example of ecological fallacy
• Suppose indoor air pollution is higher in Bajura than in Achham, but
mortality from COPD is lower in Bajura than in Achham.
• It would be fallacious to conclude that indoor air pollution protects against
COPD deaths.
• It is possible that persons dying of COPD in Achham may have moved
from cities with high indoor air pollution or that another risk factor for
COPD – such as smoking – is more prevalent in Achham than Bajura.
• We do not know the cumulative exposures of cases and non-cases in
either district.
• The heterogeneity of lifetime air pollution exposure among individuals in
each district makes the average exposure unrepresentative of the
distribution of exposure among individuals in the population.
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45. Criteria for ecological fallacy
Ecological fallacy exists if it meets all of these three criteria
• Results must be obtained with ecological data
• Data must be inferred to individuals.
• Results obtained with individual data are contradictory
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46. Reasons for ecological fallacy
• It is not possible to link exposure with disease in individuals -
those with disease may not be the same people in the
population who are exposed.
• The data used may have originally been collected for other
purposes.
• Inability to control for confounding.
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47. THANK YOU
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