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Related Experiment Videos

Effectiveness research and implications for study design: sample size and statistical power.

R Sturm1, J Unützer, W Katon

  • 1RAND, Santa Monica, California 90401, USA.

General Hospital Psychiatry
|October 9, 1999
PubMed
Summary
This summary is machine-generated.

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Clinical trials need larger sample sizes for quality of life and cost measures. Small studies with these outcomes risk exaggerating true effects due to publication bias.

Area of Science:

  • Health Services Research
  • Clinical Trial Design
  • Health Economics

Background:

  • Clinical trials increasingly use broad outcome measures like quality of life (QoL) and cost-effectiveness analyses alongside clinical status.
  • Prior mental health and primary care studies show variability in practice settings, patient populations, and geographic areas.

Purpose of the Study:

  • To analyze the implications of incorporating diverse outcome and cost measures on sample size requirements and study design.
  • To evaluate the impact of sample size on the detectability of differences in clinical status, QoL, and costs.

Main Methods:

  • Analysis of data from prior mental health and primary care studies.
  • Comparison of sample size needs for detecting clinical, QoL, and cost differences.

Related Experiment Videos

  • Examination of implications for study design and potential biases.

    • Main Results:

    • Detecting meaningful clinical differences often requires sample sizes under 100 per group.
    • Detecting large QoL changes typically necessitates several hundred observations per group.
    • Achieving precise cost estimates usually requires sample sizes in the thousands.

    Conclusions:

    • Many trials incorporating QoL or cost measures lack adequate sample sizes, leading to unreported null findings.
    • Publication bias favoring significant results can cause exaggeration of true effects in published literature.
    • Current practices raise concerns about the direction of clinical trials and the interpretation of findings from small studies on QoL and costs.