Abstract
The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care. It was, however, originally designed as a diagnostic screening tool, and not for measuring change in response to antidepressant treatment. Although the Quick Inventory of Depressive Symptomology (QIDS-SR-16) has been extensively validated for outcome measurement, it is poorly adopted in UK primary care, and, although free for clinicians, has licensing restrictions for healthcare organisation use. We aimed to develop a modified version of the PHQ-9, the Maudsley Modified PHQ-9 (MM-PHQ-9), for tracking symptom changes in primary care. We tested the measure's validity, reliability and factor structure. A sample of 121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. MM-PHQ-9 scores were compared with the QIDS-SR-16 and Clinical Global Impressions improvement scale, for concurrent validity. Internal consistency of the scale was assessed, and principal component analysis was conducted to determine the items' factor structure. The MM-PHQ-9 demonstrated good concurrent validity with the QIDS-SR-16, and excellent internal consistency. Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16. Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67. These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, although further validation is required. The measure was sensitive to change, demonstrating suitability for use in routine outcome assessment.
Highlights
The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care
Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16
Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67. These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, further validation is required
Summary
Method A sample of121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. Secondary data analysis was conducted on data from the Antidepressant Advisor Study (ADeSS), Neurofeedback in Depression (NeuroMooD)and Sadness is Good (SiG) studies (see Table 1). ADeSS study 3 aimed to provide the proof of concept for using functional magnetic resonance imaging (fMRI) biomarkers to prospectively predict which patients would not benefit from standard SSRI treatment, and comparing fMRI measures with participants without depression.[23] For the purpose of this analysis, participants from ADeSS studies 1 and 2 were included in the MDD sample, and controls from ADeSS study 3 were included in the control sample. The NeuroMooD trial examined a novel real-time fMRI neurofeedback method in MDD, and included a case–control crosssectional study recruiting healthy controls.[24] Both MDD and control samples were included in this analysis. The SiG study aimed to use a method of emotion reappraisal to train healthy participants with a tendency for self-blame to convert their self-blame to sadness, as a more adaptive emotion
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