Sample Size in Mental Health Research

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Questions and Answers

What is a primary reason for conducting sample size calculations in research?

To reduce the overall cost of the study

To ensure outcomes are statistically significant if a treatment effect exists (correct)

To speed up the recruitment process

To limit the number of participants in a study

Which of the following best defines a Type I error?

Failing to detect a true treatment effect

Finding no difference when one does exist

Detecting a treatment effect that does not exist (correct)

Incorrectly estimating the size of the treatment effect

Which factor does NOT impact the determination of sample size in a study?

The duration of the study (correct)

The desired level of statistical significance

The expected effect size

The variability in the outcome measure

What is a result of conducting a small study?

It may create publication bias for statistically significant results. Signup and view all the answers

What happens when a study is too small in sample size?

It may lead to inconclusive findings. Signup and view all the answers

How does trial size impact the credibility of results?

Very small trials may be regarded as unreliable. Signup and view all the answers

Why is it important to adjust sample sizes for loss to follow-up?

To ensure an adequate number of participants remain for analysis. Signup and view all the answers

In the context of sample size, what does 'risk ratio' indicate?

The comparison of death rates between treatment and control groups. Signup and view all the answers

What was the primary outcome measured in the clinical trial investigating CBT for reducing depression in adults with cancer?

Beck Depression Inventory II (BDI-II) Signup and view all the answers

What difference in BDI-II score did investigators consider necessary to recommend CBT for clinical practice?

6 points Signup and view all the answers

Which factor does NOT contribute to the power of a study?

Time duration of the study Signup and view all the answers

What is one way to increase the power of a clinical trial?

Increase the sample size Signup and view all the answers

In the context of the CBT study, what represents the expected treatment effect associated with CBT?

A score reduction of 6 points on the BDI-II Signup and view all the answers

What is the primary endpoint of the clinical trial investigating the effectiveness of cognitive behavioural therapy?

Beck Depression Inventory II score Signup and view all the answers

What is the expected mean BDI-II score in the control group following treatment?

20 points Signup and view all the answers

What treatment difference must be detected to implement CBT in clinical practice based on the study's criteria?

6 points Signup and view all the answers

What level of statistical significance is set for this trial?

5% Signup and view all the answers

What does a sample size calculation help determine in this clinical trial?

The required sample size per group Signup and view all the answers

With what degree of power is the trial designed to detect the treatment effect?

80% Signup and view all the answers

What variability is indicated by the standard deviation of the BDI-II scores in cancer patients?

12 points Signup and view all the answers

How many individual CBT sessions will the intervention group receive in addition to treatment as usual?

12 sessions Signup and view all the answers

What is the remaining percentage of participants after a 20% attrition from an initial 120 participants?

80% Signup and view all the answers

How is the adjusted sample size calculated when the attrition rate is 25%?

Sample size ÷ 0.75 Signup and view all the answers

What does a p-value greater than 0.05 indicate in the context of sample size calculations?

No difference exists between the groups tested. Signup and view all the answers

Why should post hoc power calculations be avoided according to the available guidelines?

They cannot help identify reasons for expected results not being found. Signup and view all the answers

What does the term 'Q' represent when calculating the adjustment for loss to follow-up?

Proportion lost Signup and view all the answers

Which of the following is NOT a reason for obtaining a p-value greater than 0.05?

Standard deviation is less than specified. Signup and view all the answers

What is an advisable method to report findings beyond post hoc power calculations?

95% confidence intervals Signup and view all the answers

Which statement is true about the relation between sample size and Type I and Type II errors?

Sample size impacts both Type I and II error rates. Signup and view all the answers

What is meant by the term 'clinically important effect' in sample size calculations?

The smallest difference between groups that needs to be detected Signup and view all the answers

Which factor is typically assumed to be the same between groups when determining sample size?

Standard deviation of the outcome Signup and view all the answers

What statistical power is commonly specified in sample size calculations?

80% or 90% Signup and view all the answers

In the context of binary outcomes, what does the variable `p1` represent?

The true proportion in the control group Signup and view all the answers

Which component is NOT part of the required sample size formula for comparing two means?

Proportion of the control group Signup and view all the answers

How is the required sample size for means and proportions generally related?

They share a similar structure in their formulas. Signup and view all the answers

What does the significance level typically represent in sample size calculations?

0.05 Signup and view all the answers

Which of the following can be affected by the standard deviation in sample size calculations?

All of the above Signup and view all the answers

What is the primary effect of larger sample sizes in hypothesis testing?

They enhance the ability to detect smaller differences between groups. Signup and view all the answers

How does an increase in variability of outcomes between groups affect sample size requirements?

It necessitates larger sample sizes. Signup and view all the answers

What is the significance of 'power' in sample size calculations?

It represents the likelihood of detecting a true effect. Signup and view all the answers

What is the impact of a smaller significance level on sample size requirements?

It increases the required sample size. Signup and view all the answers

In the context of anticipating loss to follow-up, what should researchers do?

Recruit additional participants to counteract potential loss. Signup and view all the answers

What method is typically used to estimate required sample size for continuous outcomes adjusting for baseline?

Specifying correlations between baseline and follow-up. Signup and view all the answers

Which factor is likely to increase sample size requirements when conducting a hierarchical study?

Increased intraclass correlation (ICC). Signup and view all the answers

What must researchers consider when conducting time to event analysis?

The timing of events must be carefully recorded. Signup and view all the answers

What effect does a significant loss to follow up have on a study’s power?

It reduces the power to detect the specified effect. Signup and view all the answers

Study Notes

Power and Sample Size in Mental Health Research

Sample size calculations are crucial for mental health research.
Understanding Type I and Type II errors is vital.
Key factors determining sample size include:
- The magnitude of the expected effect.
- The variability in the data.
- The desired level of statistical power.
- The significance level (alpha).
Calculating sample size for continuous and binary outcomes is important in the study design.
Loss to follow-up must be considered in adjusting sample size.
Sample sizes should be large enough to detect clinically important effects, but not so large that resources are wasted.

Approaches to Sample Size Determination

Statistical/Scientific Approach: Determine the number of patients needed to reliably detect a treatment effect (if one exists).
Economic/Pragmatic Approach: Assess the availability of patients, recruitment time, and cost. Consider how many patients are available, how long recruitment will take and what the cost of the trial will be.
Ethical Considerations: Establish how soon a trial should be stopped given an inferior treatment.
Credibility Considerations: Ensure the size of the trial is sufficient to create reliable results.
Important to consider ethical implications and limitations of the available resources, such as patient numbers.

Small Studies

Small studies often fail to detect clinically important and realistically sized treatment effects.
They may show a clinically significant but not statistically significant effect.
Small studies frequently yield imprecise estimates.
Wide confidence intervals for effect estimates are common in small studies.
Findings from small studies are less likely to be representative of the population as a whole.
Publication bias favours small studies with statistically significant (p<0.05) results over those that are not. This can lead to misleading conclusions. Therefore, small studies with statistically significant results are more often published compared to small studies with non-significant results.
Unethical when participants' time is spent in a study with a low chance of producing useful outcomes.

Results from Trials of Different Sizes

Examples of trials (1st Australian and ISIS-2) illustrate how different sample sizes can lead to varying results.
Analysis of trials of the drug streptokinase showed varying results depending on sample size, with the larger trial yielding a more reliable result.

Sample Size: Too Small vs. Too Large

Too Small:
- Lack of precision in results.
- Difficulty distinguishing real improvements from chance variation.
- Ethical issues may arise if the study is too small to detect a true effect, wasting resources and participants' time.
Too Large:
- Waste of resources (patients, funding, time).
- Ethical issues, especially for trials that involve treatments that may be inferior, wasting resources and participants' time.

Drawing the Wrong Conclusions

Type I Error: False positive; concluding an effect exists when none exists in reality. This is a false positive result.
Type II Error: False negative; concluding no effect exists when one does. This is a false negative result.
Alpha (α)—Probability of a Type I error.
Beta (β)—Probability of a Type II error.
Power (1-β)—Probability of detecting an effect when one exists.
Important to consider Type I and Type II errors in the context of sample size decisions.

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Description

This quiz explores the critical aspects of sample size calculations in mental health research. It covers essential topics such as Type I and Type II errors, statistical power, and factors influencing sample size determination. Gain insight into both statistical and pragmatic approaches to ensure effective study designs.