Predictors of refusal to participate: a longitudinal health survey of the elderly in Australia.
BACKGROUND
The loss of participants in longitudinal studies due to non-contact, refusal or death can introduce bias into the results of such studies. The study described here examines reasons for refusal over three waves of a survey of persons aged >or=70 years.


METHODS
In a longitudinal study involving three waves, participants were compared to those who refused to participate but allowed an informant to be interviewed and to those who refused any participation.


RESULTS
At Wave 1 both groups of Wave 2 non-participants had reported lower occupational status and fewer years of education, had achieved lower verbal IQ scores and cognitive performance scores and experienced some distress from the interview. Those with an informant interview only were in poorer physical health than those who participated and those who refused. Depression and anxiety symptoms were not associated with non-participation. Multivariate analyses found that verbal IQ and cognitive impairment predicted refusal. Results were very similar for refusers at both Waves 2 and 3.


CONCLUSIONS
Longitudinal studies of the elderly may over estimate cognitive performance because of the greater refusal rate of those with poorer performance. However, there is no evidence of bias with respect to anxiety or depression.
Jacomb
Patricia A
PA
The Centre for Mental Health Research, The Australian National University, Canberra, Australia.
Jorm
Anthony F
AF
Korten
Ailsa E
AE
Christensen
Helen
H
Henderson
A Scott
AS
D000203:Activities of Daily Living; D000368:Aged / Q000523:psychology*; D020958:Australian Capital Territory; D015982:Bias; D003071:Cognition / Q000145:classification; D003256:Community Participation; D003299:Cooperative Behavior; D005260:Female; D006306:Health Surveys; D006801:Humans; D007360:Intelligence / Q000145:classification; D007407:Interviews as Topic; D008137:Longitudinal Studies; D008297:Male; D015999:Multivariate Analysis; D012959:Socioeconomic Factors