Validating mental health assessment in Kenya using an innovative gold standard. (17th June 2019)

• Record Type: Journal Article
• Authors: Watson, Leah K.; Kaiser, Bonnie N.; Giusto, Ali M.; Ayuku, David; Puffer, Eve S.
• Is Part Of: International journal of psychology. Volume 55:Number 3(2020)
• Page Start: 425
• Page End: 434
• Publication Date: 2019-06-17
• Subjects: Family functioning -- Validation -- Measure development -- Mental health -- Kenya; Psychology -- Periodicals; Psychologie -- Périodiques; 150.5
• DOI: 10.1002/ijop.12604
• Languages: English
• ISSNs: 0020-7594

Abstract

Abstract : With the growing burden of mental health disorders worldwide, alongside efforts to expand availability of evidence‐based interventions, strategies are needed to ensure accurate identification of individuals suffering from mental disorders. Efforts to locally validate mental health assessments are of particular value, yet gold‐standard clinical validation is costly, time‐intensive, and reliant on available professionals. This study aimed to validate assessment items for mental distress in Kenya, using an innovative gold standard and a combination of culturally adapted and locally developed items. The mixed‐method study drew on surveys and semi‐structured interviews, conducted by lay interviewers, with 48 caregivers. Interviews were used to designate mental health "cases" or "non‐cases" based on emotional health problems, identified through a collaborative clinical rating process with local input. Individual mental health survey items were evaluated for their ability to discriminate between cases and non‐cases. Discriminant survey items included 23 items adapted from existing mental health assessment tools, as well as 6 new items developed for the specific cultural context. When items were combined into a scale, results showed good psychometric properties. The use of clinically rated semi‐structured interviews provides a promising alternative gold standard that can help address the challenges of conducting diagnostic clinical validation in low‐resource settings.