Making Research Count: Dealing with Bias and Uncertainty

Question 1

Outline the aims and objectives of quantitative research in the clinical, healthcare and biomedical sciences

Answer 1

1) Establishing Efficacy and Effectiveness:

• One major aim is to determine the effectiveness of treatments, interventions, or preventative measures.
• This is typically achieved through randomised controlled trials, where treatments are tested under controlled conditions.

2) Identifying Risk Factors and Correlations:

• Quantitative research aims to identify potential risk factors for diseases and health conditions, and to explore correlations between various factors.
• This is often done through observational studies, such as cohort studies or case-control studies.

3) Understanding Prevalence and Incidence:

• Quantitative research helps establish the prevalence (how common a condition is in a population at a specific time)
• and incidence (how many new cases occur in a population over a specific time period) of health conditions.

4) Exploring Relationships Between Variables:

• Quantitative research can explore the relationships between different variables, such as how a specific behavior impacts health outcomes, or how demographic factors relate to health disparities.

5) Informing Clinical Practice Guidelines:

• The results of quantitative research form the basis for evidence-based clinical practice guidelines, which guide healthcare providers in making informed decisions about patient care.

6) Developing and Testing Hypotheses:

• A core objective of quantitative research is to develop and test hypotheses about potential cause-and-effect relationships.
• This is often done through experimental research in laboratory settings, or through observational research in natural settings.

7) Measuring Health Outcomes:

• Quantitative research allows for the standardized measurement of health outcomes, facilitating comparisons across different populations or time periods.

8) Informing Health Policy:

• Quantitative research plays a vital role in informing health policy by providing robust, generalisable data that can guide decision-making

Question 2

Describe briefly the design and purpose of experimental and observational clinical studies

Answer 2

Experimental Clinical Studies:

Design:

• Experimental studies are characterised by the researcher having control over the assignment of participants to different conditions
• The most common example is a randomized controlled trial (RCT) in which participants are randomly assigned to either the treatment group (which receives the intervention) or the control group (which does not)
• This design helps ensure any observed effects are due to the intervention and not some other variable
• Experimental studies often also include blinding (where participants, clinicians, or researchers don’t know which group a participant is in) to further reduce bias

Purpose:

• The primary purpose of experimental clinical studies is to establish causal relationships
• I.e. to determine whether an intervention causes a change in outcomes. This is particularly useful in testing new treatments, interventions, or medical procedures

Observational Clinical Studies:

Design:

• In observational studies, the researcher does not control the assignment of participants to different conditions
• Instead, they observe and measure variables as they naturally occur
• This category includes cohort studies (where a group of individuals is followed over time), case-control studies (where individuals with a condition are compared to those without), and cross-sectional studies (where data is collected at a single point in time)

Purpose:

• The main purpose of observational studies is to explore associations between variables
• They are often used to identify risk factors for diseases or health outcomes, assess the prevalence or incidence of a disease, or generate hypotheses for further research
• While they can indicate correlations, they cannot definitively establish causation due to potential confounding variables

Question 3

Outline the rationale for, and approaches to sampling in order to make inferences about a population

Question 4

Discuss the effects of biases in research

Answer 4

1. Distortion of Results: overestimation or underestimation of the true effect, giving a false impression of the association between variables
2. Misleading Conclusions: Biased results can lead to incorrect conclusions being drawn
3. Reduction in Validity: Bias can reduce the validity of a study, making the results less trustworthy. Internal validity (the degree to which the results are true for the participants in the study) can be compromised by biases like selection bias, measurement bias, or confounding. External validity (the degree to which the results can be generalized to the wider population) can be compromised by biases like sampling bias
4. Wasted Resources: including time, money, and human effort
5. Ethical Concerns: Bias in research can also raise ethical issues. For example, if bias leads to the overestimation of the effectiveness of a treatment, patients may be exposed to unnecessary risks or burdens.