Factors Predicting Abnormal Mental Health Status of Admission-Passed Students in the First Year Class of Bachelor Degree of Nursing Science Program, Faculty of Nursing, One Studied University
Keywords:
Mental health, Students, Nursing program, Symptom Distress Checklist-90Abstract
This cross-sectional descriptive study aimed to examine mental health conditions and predictive factors of abnormal mental health among first-year students admitted to the Bachelor of Nursing Science program at a faculty of nursing in a university. The sample consisted of 206 selected students. The research instruments included a personal information questionnaire and the Symptom Distress Checklist-90 (SCL-90), which had a reliability coefficient of .96. Data were collected via Google Forms and analyzed using descriptive statistics and inferential statistics, including chi-square, odds ratio, and binary logistic regression.
The results revealed that a minority of participants (14.08%) had abnormal mental health conditions. All participants experienced some level of mental health issues according to various subscales of the SCL-90, ranging from 14.08% to 16.50%. The factors found to predict abnormal mental health included: interest in enrolling in the program (β = 1.31, p-value = .006), living with family (β = 1.25, p-value = .011), family relationships (β = 1.40, p-value = .004), and the number of hours spent using mobile phones per week (β = 1.64, p-value = .001). These factors collectively explained 31.80% of the variance in abnormal mental health conditions (Nagelkerke R2 = .318). From the results of this study, it is recommended that students at risk of mental health problems should receive appropriate initial support. Educational institutions should establish systems for screening, counseling, and mental health promotion services to help students effectively manage mental health issues.
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