Objectives: This study aimed to identify those at high risk of poor mental health among nursing students and to examine the relationships and consistency among five mental health assessments.
Design: A cross-sectional design with purposive sampling was used. Four mental health screening tools plus previous mental health history/information were conducted during June 2015 to October 2016.
Setting: A nursing major university in Taiwan.
Participants: A total of 2779 participants aged between 19 and 45 years were recruited.
Main outcome measures: Five mental health risks were identified: increased risk for ultra-high risk, putative prepsychosis states, high trait anxiety, high state anxiety with genetic risk and depression.
Results: Out of the 3395 collected questionnaire, 2779 (82%) were found valid and included in the study. 612 (22%) of the participants were identified to be at mental health risk. 12 of them appeared positive in four, 79 in three, 148 in two and 373 in one of the adopted mental health screening tools. 69 participants had the experience of seeking medical help due to mental health issues, and 58% of them were identified to be at risk of mental health during the screening. Trait and state anxiety scored the highest in correlation analysis (r(2620)=0.76, p<0.001). Correlations were observed in the scores on the subscales of Chinese Version of Schizotypal Personality Questionnaire-Brief (CSPQ-B) and those of Brief self-report Questionnaire for Screening Putative Prepsychotic States (BQSPS), and the highest correlation coefficients was (r(2740)=0.70, p<0.001). Although both of the screening tools are used to assess mental illness risk at its prodromal phase, but CSPQ-B in general appeared to have more rigorous screening criteria than BQSPS.
Conclusion: For expediting early identification high risk of poor mental health, easy-to-use screening questionnaires can be adopted to assess the mental health state of nursing students whose mental well-being and overall health are of vital importance to the entire healthcare industry.
Keywords: health economics; mental health; psychiatry; risk management.
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