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Cultural adaptation to Shawi and psychometric analysis of the Patient Health Questionnaire (PHQ-9) in adults from the Alto Amazonas, Peru

Medwave. 2026 May 8;26(4):e3176. doi: 10.5867/medwave.2026.04.3176.

ABSTRACT

INTRODUCTION: Depression is currently one of the most impactful mental health conditions worldwide, with more than 280 million reported cases. However, there is a critical lack of data on Indigenous populations due to language barriers and the absence of culturally adapted assessment tools, limiting timely diagnosis and appropriate care. The aim of this work is to culturally and linguistically adapt the Patient Health Questionnaire-9 (PHQ-9) into the Shawi language and to evaluate its psychometric properties among Indigenous adults in Alto Amazonas, Peru.

METHODS: A rigorous cultural adaptation process was carried out, including translation by bilingual experts and back-translation. Validation involved expert technical review and a pilot phase conducted within the participating community. Content validity was assessed using Aiken’s V coefficient as a statistical indicator. The internal structure was evaluated using confirmatory factor analysis and structural equation modeling.

RESULTS: The sample consisted of 432 members of the Shawi community. The instrument showed excellent content validity (V = 0.90 to 1.00). Confirmatory factor analysis supported a unidimensional model with good fit (comparative fit index: 0.98; root mean square error of approximation: 0.06) and adequate internal consistency (α = 0.80; ω = 0.81). In addition, invariance of the PHQ-9 was demonstrated across age, sex, educational level, and marital status, supporting its applicability across different population subgroups.

CONCLUSIONS: The Shawi version of the Patient Health Questionnaire-9 has proven to be a reliable and valid tool for detecting depressive symptoms in this Indigenous population. This advancement represents a significant contribution to reducing mental health disparities by facilitating culturally appropriate diagnoses and improving care in historically underserved Amazonian communities.

PMID:42102351 | DOI:10.5867/medwave.2026.04.3176

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