Methodology series module 2: Case-control studies

Case-Control study design is a type of observational study. In this design, participants are selected for the study based on their outcome status. Thus, some participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. The investigator should define the cases as specifically as possible. Sometimes, definition of a disease may be based on multiple criteria; thus, all these points should be explicitly stated in case definition. An important aspect of selecting a control is that they should be from the same 'study base' as that of the cases. We can select controls from a variety of groups. Some of them are: General population; relatives or friends; and hospital patients. Matching is often used in case-control control studies to ensure that the cases and controls are similar in certain characteristics, and it is a useful technique to increase the efficiency of the study. Case-Control studies can usually be conducted relatively faster and are inexpensive – particularly when compared with cohort studies (prospective). It is useful to study rare outcomes and outcomes with long latent periods. This design is not very useful to study rare exposures. Furthermore, they may also be prone to certain biases – selection bias and recall bias

Methodology series module 7: Ecologic studies and natural experiments

In this module, we have discussed study designs that have not been covered in the previous modules – ecologic studies and natural experiments. In an ecologic study, the unit of analysis is a group or aggregate rather than the individual. It may be the characteristics of districts, states, or countries. For example, per capita income across countries, income quintiles across districts, and proportion of college graduates in states. If the data already exist (such as global measures and prevalence of diseases, data sets such as the National Family Health Survey, census data), then ecologic studies are cheap and data are easy to collect. However, one needs to be aware of the “ecologic fallacy.” The researcher should not interpret ecologic level results at the individual level. In “natural experiments,” the researcher does not assign the exposure (as is the case in interventional studies) to the groups in the study. The exposure is assigned by a natural process. This may be due to existing policies or services (example, one city has laws against specific vehicles and the other city does not); changes in services or policies; or introduction of new laws (such helmet for bikers and seat-belts for cars). We would like to encourage researchers to explore the possibility of using these study designs to conduct studies

Methodology series module 8: Designing questionnaires andclinical record forms

As researchers, we often collect data on a clinical record form or a questionnaire. It is an important part of study design. If the questionnaire is not well designed, the data collected will not be useful. In this section of the module, we have discussed some practical aspects of designing a questionnaire. It is useful to make a list of all the variables that will be assessed in the study before preparing the questionnaire. The researcher should review all the existing questionnaires. It may be efficient to use an existing standardized questionnaire or scale. Many of these scales are freely available and may be used with an appropriate reference. However, some may be under copyright protection and permissions may be required to use the same questionnaire. While designing their own questionnaire, researchers may use open- or close-ended questions. It is important to design the responses appropriately as the format of responses will influence the analysis. Sometimes, one can collect the same information in multiple ways - continuous or categorical response. Besides these, the researcher can also use visual analog scales or Likert's scale in the questionnaire. Some practical take-home points are: (1) Use specific language while framing the questions; (2) write detailed instructions in the questionnaire; (3) use mutually exclusive response categories; (4) use skip patterns; (5) avoid double-barreled questions; and (6) anchor the time period if required

Methodology series module 6: Systematic reviews and meta-analysis

Systematic reviews and meta-analysis have become an important of biomedical literature, and they provide the "highest level of evidence" for various clinical questions. There are a lot of studies - sometimes with contradictory conclusions - on a particular topic in literature. Hence, as a clinician, which results will you believe? What will you tell your patient? Which drug is better? A systematic review or a meta-analysis may help us answer these questions. In addition, it may also help us understand the quality of the articles in literature or the type of studies that have been conducted and published (example, randomized trials or observational studies). The first step it to identify a research question for systematic review or meta-analysis. The next step is to identify the articles that will be included in the study. This will be done by searching various databases; it is important that the researcher should search for articles in more than one database. It will also be useful to form a group of researchers and statisticians that have expertise in conducting systematic reviews and meta-analysis before initiating them. We strongly encourage the readers to register their proposed review/meta-analysis with PROSPERO. Finally, these studies should be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis checklist

Methodology series module 5: Sampling strategies

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the 'Sampling Method'. There are essentially two types of sampling methods: 1) probability sampling – based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term 'random sample' when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the 'generalizability' of these results. In such a scenario, the researcher may want to use 'purposive sampling' for the study

Men who have sex with men and transgenders in Mumbai, India: An emerging risk group for STIs and HIV

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