Primary care consultation predictors in men and women: a cohort study

Br J Gen Pract. 2005 Feb;55(511):108-13.

Abstract

Background: Women visit their doctors more than men, but comparatively few studies have explored gender differences in consultation in detail.

Aims: To identify the factors that predicted the number of primary care consultations in men and women over a 5-year period.

Design of study: Prospective cohort study with three waves of data collection by postal questionnaire.

Setting: A single suburban general practice in Greater Manchester, UK.

Method: Consultation data were sought from primary care records on a random sample of 800 adults. The main outcome measure was the number of consultations over the 5 years of the study. Questionnaire measures included the 12-item version of the General Health Questionnaire, the Illness Attitude Scales, a somatic symptom scale, a fatigue scale, and a functional assessment of disability.

Results: Consultation data were obtained on 738 patients (445 women, 293 men, 92% of selected subjects). Longitudinal models of consultation over 5 years showed that changes in psychological distress were more strongly associated with consultation in women than in men, whereas cognitive factors (negative illness attitudes) were more strongly associated with the consultation rate in men than women.

Conclusion: The predictors of consultation in primary care may be different for men and women. A fuller understanding of the reasons for consultation may enable primary care doctors to better help individual patients, as well as perhaps contributing more generally to the development of gender specific interventions for those who consult unusually frequently.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Cohort Studies
  • England
  • Family Practice / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Patient Acceptance of Health Care / psychology
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Primary Health Care
  • Sex Factors*
  • Surveys and Questionnaires