Sample size for regression analyses of theory of planned behaviour studies: case of prescribing in general practice.
OBJECTIVE
Interest has been growing in the use of the theory of planned behaviour (TBP) in health services research. The sample sizes range from less than 50 to more than 750 in published TPB studies without sample size calculations. We estimate the sample size for a multi-stage random survey of prescribing intention and actual prescribing for asthma in British general practice. To our knowledge, this is the first systematic attempt to determine sample size for a TPB survey.


METHODS
We use two different approaches: reported values of regression models' goodness-of-fit (the lambda method) and zero-order correlations (the variance inflation factor or VIF method). Intra-cluster correlation coefficient (ICC) is estimated and a socioeconomic variable is used for stratification. We perform sensitivity analysis to estimate the effects of our decisions on final sample size.


RESULTS
The VIF method is more sensitive to the requirements of a TPB study. Given a correlation of .25 between intention and behaviour, and of .4 between intention and perceived behavioural control, the proposed sample size is 148. We estimate the ICC for asthma prescribing to be around 0.07. If 10 general practitioners were sampled per cluster, the sample size would be 242.


CONCLUSIONS
It is feasible to perform sophisticated sample size calculations for a TPB study. The VIF is the appropriate method. Our approach can be used with adjustments in other settings and for other regression models.
Rashidian
Arash
A
Health Services Research Unit, Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, UK. arashidian@tums.ae.ir
Miles
Jeremy
J
Russell
Daphne
D
Russell
Ian
I
D001249:Asthma / Q000188:drug therapy*; D011307:Drug Prescriptions; D005194:Family Practice / Q000379:methods*; D006801:Humans; D033182:Intention; D011582:Psychological Theory; D011584:Psychology / Q000379:methods / Q000706:statistics & numerical data; D012044:Regression Analysis; D012919:Social Behavior