Jhpiego Resource Package for Journal Manuscript Development: Support Materials

Jhpiego Resource Package for Journal Manuscript Development Support Materials

Tool 32: Types of Quantitative Study Designs

Study designs can be divided into three types, as shown in the table below, based on whether they: 1. Randomly assign subjects to groups, and 2. Include a control group or multiple waves of measurement.

The sections below describe and provide examples of experimental, quasi-experimental, and non- experimental study designs.

QUASI- NON - STUDY DESIGN EXPERIMENTAL EXPERIMENTAL EXPERIMENTAL Random assignment of subjects to Yes No No group(s) Control group or multiple waves of Yes Yes No measurement

EXPERIMENTAL DESIGNS Experiments manipulate an independent variable and examine what the consequences are on another variable, the so-called dependent variable or outcome. In contrast, ‘‘natural experiments’’ assess the patterns between naturally occurring variables. Experimental designs vary in their rigor and ability to make causal inferences. The hallmark of experimental design is the random assignment of subjects to intervention and control groups.

Example of an experimental study

QUASI-EXPERIMENTAL DESIGNS Like experimental designs, quasi-experimental study designs involve the manipulation of an independent variable to examine the consequence on another, dependent variable. Unlike experimental designs, however, subjects are not randomly assigned to groups.

Example of a quasi-experimental study

NON-EXPERIMENTAL DESIGNS Non-experimental designs (which are also known as observational designs) do not involve random assignment of subjects to groups, nor is there a control or comparison group. Non-experimental designs also do not involve multiple waves of measurement. This type of design is very useful for descriptive research questions.

Observational study designs are used when it is not feasible or not ethical to randomize groups to receive a certain exposure and determine whether it causes a particular outcome. For example, a classic example of an observational study design involves cigarette smoking: it would be unethical to designate certain people to begin smoking and then measure how many developed cancer.

Observational studies may provide information to:

 Explain the causes of disease incidence and the determinants of disease progression,

 Predict the future health care needs of a population, and

 Control disease by studying ways to prevent disease and prolong life while living with disease.

The main limitation of observational studies is that investigators do not have complete control over other variables related to the exposure and outcome, such as environmental factors or events that occur in the research area. As a result, observational study designs cannot be used to establish causality.

The sub-sections below describe four non-experimental study designs that are often used in public health research:

 Descriptive cross-sectional studies,

 Cohort studies,

 Case-control studies, and

 Case-crossover studies.

Descriptive Cross-Sectional Studies Descriptive cross-sectional studies are a simple but common form of observational study design. For example, a researcher might survey patients about their opinions of health care services. Alternatively, a researcher might survey patients’ attitudes after providers have undergone specialized training (the intervention). This limitation of this post-test only design is that it lacks a comparison group and therefore the ability to conclude that the outcome was the result of the intervention.

Example of a descriptive study

Cohort Studies This type of observational study follows a defined group------called the cohort------over time. The primary advantage of cohort studies is their ability to establish a temporal association between a particular exposure and a particular outcome. The choice of cohort depends on the hypothesis being tested, along with feasibility issues, such as the availability of records and ease of follow-up. Cohort studies are most feasible when the exposure and outcome of interest are relatively common. However, special cohorts have been used to study the health effects of rare exposures such as uncommon workplace chemicals, unusual diets, and uncommon lifestyles.

Groups may be formed prospectively or retrospectively. In a prospective cohort study, participants are grouped on predetermined criteria (for example, smokers) and then followed into the future to observe outcomes of interest (for example, cancer). When the study commences, the outcomes have not yet developed and the investigator must wait for them to occur. In contrast, when a retrospective cohort study begins, both the exposures and outcomes have already occurred. The decision to conduct a retrospective or prospective study depends on the research question, practical constraints such as time and money, and the availability of suitable study populations and records.

Cohorts may be closed or open. Members of a closed (or fixed) cohort are all enrolled at the same time and followed until a predetermined endpoint, such as death or diagnosis with a particular disease. In an open cohort, members may enter the study at different times.

Example of a cohort study

Case-Control Studies This type of observational study compares subjects who have a disease (called cases) with those who do not have that disease (called controls). The first step in case-control studies is formulating a disease or case definition based on a combination of signs and symptoms, physical and pathological examinations, and results of diagnostic tests. Cases are typically identified from hospital or clinic patient rosters, death certificates, special surveys, and reporting systems such as cancer or birth defects registries. Investigators consider both accuracy and efficiency when selecting a source for case identification, with the goal of identifying as many true cases of disease as quickly and cheaply as possible. Researchers who study the causes of disease prefer to select incident cases of disease, because they are interested in the factors that lead to the development of a disease rather than factors that affect its duration. However, epidemiologists sometimes have no choice but to rely on prevalent cases, for example, when studying an insidious disease whose exact onset is difficult to pinpoint. Studies using prevalent cases must be interpreted cautiously, because it is impossible to determine if the exposure is related to the inception of the disease, its duration, or a combination of the two.

Controls come from the same population that produced the cases and may be matched with cases on particular characteristics. Investigators use several sources to identify controls. Investigators may sample:

 Individuals from the general population,

 Individuals attending a hospital or clinic,

 Friends or relatives identified by the cases, or

 Individuals who have died.

Population controls are typically selected when cases are identified from a well-defined population, such as residents of a geographic area.

After cases and controls are identified, their exposure histories are obtained and compared. If cases are found to have higher exposure than controls, after controlling for other important factors, the study’s hypothesis may merit testing through a more rigorous design, such as a cohort study or randomized controlled trial.

Example of a case-control study

Case-Crossover Study This type of observational study is a variant of the case-control study. Case-crossover studies were developed for settings in which the risk of the outcome is increased for only a brief time following the exposure. The period of increased risk following the exposure is termed the hazard period. In the case-crossover study, cases serve as their own controls, and the exposure frequency during the hazard period is compared to that from a control period. Because cases serve as their own controls, this design has several advantages. It eliminates confounding by characteristics such as gender and race and the bias that results from selecting unrepresentative controls. In addition, because variability is reduced, this design requires fewer subjects than a traditional case-control study.

Example of a case-crossover study

Recommended reading: Aschengrau, Serge 2008