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Older adult report of change in depressive symptoms as a treatment decision tool
Catherine J Datto1, Richard Thompson, Kathryn Knott
1Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA. cdatto@mail.med.upenn.edu
Objectives:
To evaluate patient reports of changes in depressive symptoms as information that can be used in treatment decision-making.
Design:
Longitudinal cohort study.
Setting:
The Prevention of Suicide in Primary Care Elderly: Collaborative Trial and the Primary Care Research in Substance Abuse and Mental Health for the Elderly trial, multisite studies investigating the effect of depression interventions on outcomes in primary care.
Participants:
Fifty-six patients aged 60 and older.
Measurements:
Patient demographics were collected from patient reports. Symptoms of depression were measured using the Centers for Epidemiologic Studies Depression Scale (CES-D) and Hamilton Depression Scale (HAM-D). Changes in depressive symptoms were also measured using the Clinical Global Impressions of Change (CGI-C) as rated by patients in ongoing treatment.
Results:
Patient ratings of CGI-C were significantly correlated with percentage improvement on the HAM-D as rated by the depression care manager (correlation coefficient (r)=0.44, P<.001) and percentage improvement on the CES-D (r=0.38, P=.005). The patient report of at least "much improved" predicted at least 50% treatment response based on HAM-D scale scores, with a sensitivity of 87.5% and a specificity of 74.2%.
Conclusion:
These findings suggest that patients are able to accurately report their degree of improvement in depressive symptoms. Patient report of at least "much improved" can be used as an estimate of at least 50% depression treatment response. In an era of increasingly fragmented clinical care, these findings demonstrate that older adult primary care patients can accurately self-report overall change in depressive symptoms. When results of repeated depression instruments are not available, patient report of depression treatment response can be used to inform depression treatment decision-making.
