Background: Despite recognition of the burden of disease due to mood disorders in low- and middle-income countries, there is a lack of consensus on best practices for detecting depression. Self-report screening tools, such as the Patient Health Questionnaire (PHQ-9), require modification for low literacy populations and to assure cultural and clinical validity. An alternative approach is to employ idioms of distress that are locally salient, but these are not synonymous with psychiatric categories. Therefore, our objectives were to evaluate the validity of the PHQ-9, assess the added value of using idioms of distress, and develop an algorithm for depression detection in primary care.
Methods: We conducted a transcultural translation of the PHQ-9 in Nepal using qualitative methods to achieve semantic, content, technical, and criterion equivalence. Researchers administered the Nepali PHQ-9 to randomly selected patients in a rural primary health care center. Trained psychosocial counselors administered a validated Nepali depression module of the Composite International Diagnostic Interview (CIDI) to validate the Nepali PHQ-9. Patients were also assessed for local idioms of distress including heart-mind problems (Nepali, manko samasya).
Results: Among 125 primary care patients, 17 (14 %) were positive for a major depressive episode in the prior 2 weeks based on CIDI administration. With a Nepali PHQ-9 cutoff ≥ 10: sensitivity = 0.94, specificity = 0.80, positive predictive value (PPV) =0.42, negative predictive value (NPV) =0.99, positive likelihood ratio = 4.62, and negative likelihood ratio = 0.07. For heart-mind problems: sensitivity = 0.94, specificity = 0.27, PPV = 0.17, NPV = 0.97. With an algorithm comprising two screening questions (1. presence of heart-mind problems and 2. function impairment due to heart-mind problems) to determine who should receive the full PHQ-9, the number of patients requiring administration of the PHQ-9 could be reduced by 50 %, PHQ-9 false positives would be reduced by 18 %, and 88 % of patients with depression would be correctly identified.
Conclusion: Combining idioms of distress with a transculturally-translated depression screener increases efficiency and maintains accuracy for high levels of detection. The algorithm reduces the time needed for primary healthcare staff to verbally administer the tool for patients with limited literacy. The burden of false positives is comparable to rates in high-income countries and is a limitation for universal primary care screening.