Psychometric properties of the positive mental health instrument among people with mental disorders: A cross-sectional study

Abstract

Background: The Positive Mental Health (PMH) instrument was developed and validated to assess the level of PMH and its six dimensions in a multi-ethnic general population sample. This cross-sectional study examines the psychometric properties of the instrument for assessing the level of PMH among help-seeking patients with mental disorders. Methods: The PMH instrument was tested among 360 out-patients with schizophrenia, depression or anxiety spectrum disorders, seeking treatment at a tertiary psychiatric hospital and its affiliated clinics in Singapore. All participants completed the PMH instrument along with measures of life satisfaction, mental and overall health and happiness. Reliability (internal consistency), construct (Exploratory Structural Equation Modeling (ESEM)) and criterion (convergent and divergent) validity of the PMH instrument were tested in this population. Items were also tested for item response theory and differential item functioning (IRT-DIF). Results: ESEM on the PMH instrument showed good fit with the model reflecting six factors (general coping, personal growth and autonomy, spirituality, interpersonal skills, emotional support, and global affect). Internal consistency was high (Cronbach's alpha >0.85) for the instrument and its six subscales. The PMH instrument fulfilled expected correlations with related constructs and demonstrated adequate item discrimination and difficulty estimates; however, significant DIF was noted for few items for age, gender and ethnicity groups. Conclusions: The PMH instrument is a reliable and valid instrument for measuring PMH dimensions in patients with mental disorders. Further studies in larger samples are needed to assess the impact of DIF on PMH scores. The implications for the shift in focus from just the negative aspects of mental disorders to including positive components in the assessment of patients with mental disorders are immense, and can be applied in routine mental health practice and policy making.