Construct validation of measures of depression, anxiety, and functionality in Northern Haiti - Michael Galvin; Ann Scheunemann; Guesly Michel; Edny Pierre; Eurine Manguira (Elsevier, 2022)
Background: Mental illness represents an increasing burden of disease and disability in low- and middle-income countries (LMICs). With high levels of poverty, violence, and natural disasters, the population of Haiti is confronted with significant mental health challenges. In spite of this, few validated and culturally adapted tools exist to measure mental distress in Haitian Creole (Kreyòl). Methods: This study applied exploratory factor analysis to examine the factor structure of three measures - the Zanmi Lasante Depression Symptom Inventory (ZLDSI) for depression, Beck Anxiety Inventory (BAI) for anxiety, and the Kreyòl Functional Assessment (KFA) for functionality - using cross-sectional responses collected from 96 patients at Sant Sante Mantal Mòn Pele (SSMMP), the first mental health clinic in northern Haiti, between August 2020 and February 2021. Results: All measures displayed good internal consistencies for the entire scale and all subscales, as measured using Cronbach's alpha. The model fit was acceptable for the KFA, marginally acceptable for the ZLDSI, and low for the BAI. The findings of this analysis suggest a one symptom category for the depression scale, two symptom categories for anxiety - somatic and affective - and three categories for functionality - agriculture, social, and caretaking. The results of this study highlight instruments which are sensitive to culturally informed diagnoses within the Haitian context. Conclusion: This study represents a promising step towards the validation of culturally-adapted measures of mental distress in Kreyòl which are needed to advance the standardization of psychometrics and diagnostics in Haiti. These efforts will not only improve identification and diagnosis of mental illness but can also help to expand biomedical services and mental health treatment throughout the country.