Do primary care physicians have particular difficulty identifying late-life depression? A meta-analysis stratified by age

Psychother Psychosom. 2010;79(5):285-94. doi: 10.1159/000318295. Epub 2010 Jul 9.


Background: There is long-standing concern regarding poor recognition of depression in primary care, especially in older people.

Methods: Studies that examined the unassisted (clinical) ability of general practitioners (GPs; primary care physicians) to identify depression were divided into those of older adults, younger adults and mixed populations. Data were extracted by 3 reviewers independently and pooled using a Bayesian meta-analysis.

Results: We identified 31 valid studies that examined both sensitivity and specificity (or rule-in and rule-out accuracy), involving 52,513 individuals. Twelve studies recruited older individuals, 12 recruited younger adults and 7 recruited both younger and older adults (mixed populations). In the most robust studies the point prevalence of depression in late life was 13.2% (95% CI = 7.9-19.6). GPs were able to correctly identify 47.3% of the late-life depressions and 78.6% of the non-cases (71.0% overall accuracy). In younger adults GPs were able to identify 39.7% of the mid-life depressions and 85.1% of the non-depressed (77.8% overall accuracy). In mixed aged groups GPs we able to correctly identify 46.6% of the depressed individuals and 86.2% of the non-depressed (79.6% overall accuracy). The overall fraction correctly identified was significantly lower in older compared with younger adults. Correcting for differences in prevalence showed a statistically lower rule-in performance for older compared with younger adults. There was no difference in ability to identify non-depressed (healthy) individuals by age.

Conclusions: In clinical practice GPs appear to be less successful in identifying depression in older people than in younger adults, however there have been few head-to-head studies stratified by age from one centre.

Publication types

  • Meta-Analysis

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Bayes Theorem
  • Depressive Disorder / diagnosis*
  • Diagnostic Errors / statistics & numerical data
  • Humans
  • Physicians, Primary Care* / standards
  • Physicians, Primary Care* / statistics & numerical data