An investigation of the dual continua model of mental health in the context of eating disorder symptomatology using latent profile analysis.

OBJECTIVE: The dual continua model of mental health suggests that mental well-being and mental illness are two distinct continua that are interrelated in their contributions to overall mental health. This study investigated the dual continua model in individuals with eating disorder symptoms. METHOD: Female university students (N = 346) completed measures of mental well-being, eating disorder symptomatology, clinical impairment and psychological distress. Confirmatory factor and latent profile analyses were used to derive underlying mental health profiles. RESULTS: Results revealed two oblique factors representing the mental well-being and eating disorder symptomatology constructs and four unique mental health profiles that were partially consistent with the dual continua model emerged: 'flourishing', 'vulnerable', 'partially symptomatic and content', and 'languishing'. The derived mental health profiles had unique characteristics described by psychological distress and clinical impairment. CONCLUSIONS: The results did not provide conclusive evidence for the dual continua model as they could also be interpreted in a manner consistent with the unidimensional approach. While the dual continua model is a promising avenue to understand mental health in a way that looks beyond symptoms, these results caution against its rapid adoption and encourage future research to understand how eating disorder symptomatology and positive mental health assets contribute to overall mental health.

The influence of trust and social identity in farmers' intentions to report suspected emergency disease outbreaks.

This study examines the influence of trust on farmers' intentions to report suspected disease on their farm. Disease reporting is essential to detect and respond to disease early, thereby minimising its impacts on agriculture businesses, the economy, and the environment. Trust has been identified as an important factor influencing farmers' disease reporting intentions but has not been quantitatively investigated. We use an established model of trust-the Integrative Model of Organisational Trust (IMOT)-to conceptualise how trust influences disease reporting intentions. We also examine how social identity is related to trust and disease reporting. Australian plant, livestock, and aquaculture farmers (N = 41) completed an online questionnaire developed from existing validated measures and we also developed two new measures for disease reporting intentions. Trust in government positively and significantly predicted farmer intentions to report suspected disease outbreaks, explaining 26% of the variance. For every one-unit increase in trust, disease reporting intentions increased by over four times. Results also support the role of shared values and group membership as aspects of social identity that influence trust and disease reporting. These results highlight the importance of government decision-makers developing and maintaining trust with farmers to support early detection and response to emergency disease outbreaks.