METHODS: In the current study, 2074 students (706 males), filled out the Meaning in Life Questionnaire, with subscales of Search for Meaning (MLQ-S) and Presence of Meaning (MLQ-P); the Future Disposition Inventory-24 (FDI-24), with subscales of Positive Focus (PF), Suicide Orientation (SO), and Negative Focus (NF); and the Beck Hopelessness Scale (BHS). These scales measure protective and risk factors that are linked to suicidal behaviors; while suicidal behaviors were measured by the Suicidal Behaviors Questionnaire-Revised (SBQ-R). Mediation analyses were performed to test the models with both the MLQ-S and MLQ-P as the mediators between a) hopelessness, as measured by BHS and suicidal behaviors; and b) PF, SO, and NF, as measured by FDI-24, and suicidal behaviors.
RESULTS: We found that only MLQ-P mediated the relation between hopelessness and suicidal behaviors; while both MLQ-P and MLQ-S mediated PF, SO, and NF (as measured by FDI-24), and suicidal behaviors, respectively.
CONCLUSION: Meaning in life, including both the presence of meaning in life and search for meaning, can be good protective factors against suicidal behaviors.
OBJECTIVE: To examine the risk and protective factors contributing to suicidality among undergraduate college students in seven provinces in China.
METHODS: We conducted a cross-sectional study involving 13,387 college students from seven universities in Ningxia, Shandong, Shanghai, Jilin, Qinghai, Shaanxi, and Xinjiang. Data were collected using self-report questionnaires.
RESULTS: Higher scores in the psychological strain, depression, anxiety, stress, and psychache (psychological risk factors for suicidality) and lower scores in self-esteem and purpose in life (psychological protective factors against suicidality) were associated with increased suicidality among undergraduate students in China. Demographic factors which were associated with higher risks of suicidality were female gender, younger age, bad academic results, were an only child, non-participation in school associations, and had an urban household registration. Perceived good health was protective against suicidality.
CONCLUSIONS: Knowing the common risk and protective factors for suicidality among Chinese undergraduate students is useful in developing interventions targeted at this population and to guide public health policies on suicide in China.
OBJECTIVE: The current study examines the association between religious affiliation and suicidality among college students in six provinces in China.
METHODS: We conducted a cross-sectional study involving 11,407 college students from six universities in Ningxia, Shandong, Shanghai, Jilin, Qinghai, and Shaanxi. We collected the data between October 2017 and March 2018 using self-report questionnaires. They included self-report measures of depression, psychache, hopelessness, self-esteem, social support, and life purpose.
RESULTS: Participants with a Christian affiliation had 1.5 times (95% CI: 1.14, 1.99, p = 0.004) higher odds of indicating an elevated suicide risk, 3.1 times (95% CI: 1.90, 5.04, p<0.001) higher odds of indicating a previous suicide attempt, and increased overall suicidality (B = 0.105, p < 0.001) after accounting for demographic and risk/protective factors. Christians also scored the highest in depression, psychache, hopelessness, and the lowest social support, self-esteem, and purpose in life. Muslims reported decreased suicidality (B = -0.034, p = 0.031). Buddhism/Daoism yielded non-significant results in the multivariate analyses.
CONCLUSIONS: Christian college students reported increased suicidality levels, perhaps due to public policies on religion. The decreased suicidality levels among Muslims may be attributed to higher perceived social support. The associations between religious affiliation and suicidality, depression, and hopelessness contrast sharply with US samples. This finding may be influenced by interactions between the religious denomination, individual, and social/political factors. This conclusion includes the possibility of anti-religious discrimination, which this paper did not investigate as a possible mediator and therefore remains a conjecture worthy of future investigation.
MATERIALS AND METHODS: We propose a mixed-method study of mental health assessment that combines psychological questionnaires with facial emotion analysis to comprehensively evaluate the mental health of students on a large scale. The Depression Anxiety and Stress Scale-21(DASS-21) is used for the psychological questionnaire. The facial emotion recognition model is implemented by transfer learning based on neural networks, and the model is pre-trained using FER2013 and CFEE datasets. Among them, the FER2013 dataset consists of 48 × 48-pixel face gray images, a total of 35,887 face images. The CFEE dataset contains 950,000 facial images with annotated action units (au). Using a random sampling strategy, we sent online questionnaires to 400 college students and received 374 responses, and the response rate was 93.5%. After pre-processing, 350 results were available, including 187 male and 153 female students. First, the facial emotion data of students were collected in an online questionnaire test. Then, a pre-trained model was used for emotion recognition. Finally, the online psychological questionnaire scores and the facial emotion recognition model scores were collated to give a comprehensive psychological evaluation score.
RESULTS: The experimental results of the facial emotion recognition model proposed to show that its classification results are broadly consistent with the mental health survey results. This model can be used to improve efficiency. In particular, the accuracy of the facial emotion recognition model proposed in this paper is higher than that of the general mental health model, which only uses the traditional single questionnaire. Furthermore, the absolute errors of this study in the three symptoms of depression, anxiety, and stress are lower than other mental health survey results and are only 0.8%, 8.1%, 3.5%, and 1.8%, respectively.
CONCLUSION: The mixed method combining intelligent methods and scales for mental health assessment has high recognition accuracy. Therefore, it can support efficient large-scale screening of students' psychological problems.
METHODS: In a cross-sectional survey, the undergraduate students in Universiti Sains Malaysia were invited to complete the self-administered questionnaires. Participants were selected using a purposive sampling method. The proposed hypothesised model was analysed using a structural equation modelling with Mplus 7.3 program. A total of 788 (70.7% female) undergraduate students with a mean age of 20.2 (SD = 1.02) participated in the study. The primary outcome of knowledge, health beliefs, and health-promoting behaviours related to CVD were measured by questionnaires namely: Knowledge of Heart Disease, Health Beliefs Related to CVD, and Health Promoting Lifestyle Profiles-II.
RESULTS: The final hypothetical structural model showed a good fit to the data based on several fit indices: with comparative fit index (CFI) at .921, standardised root mean square residual (SRMR) at .037, and root mean square error of approximation (RMSEA) at .044 (90% CI: .032, .054). The final structural model supported 13 significant path estimates. These variables explained 12% of the total variance in health-promoting behaviours. Through perceived benefits, total knowledge had an indirect effect on health-promoting behaviours.
CONCLUSION: The results suggest that perceived barriers, perceived benefits, family history of CVD, and screening intention enable young adults to engage in health-promoting behaviours.