Engagement With Personalized Feedback for Emotional Distress Among College Students at Elevated Suicide Risk

Mind Matters: Exploring the Intersection of Psychological Factors and Cognitive Abilities of University Students by Using ANN Model

Purpose

While previous studies have suggested close association of psychological variables of students withtheir higher-order cognitive abilities, such studies have largely been lacking for third world countries like India, with their unique socio-economic-cultural set of challenges. We aimed to investigate the relationship between psychological variables (depression, anxiety and stress) and cognitive functions among Indian students, and to predict cognitive performance as a function of these variables.

Patients and Methods

Four hundred and thirteen university students were systematically selected using purposive sampling. Widely used and validated offline questionnaires were used to assess their psychological and cognitive statuses. Correlational analyses were conducted to examine the associations between these variables. An Artificial Neural Network (ANN) model was applied to predict cognitive levels based on the scores of psychological variables.

Results

Correlational analyses revealed negative correlations between emotional distress and cognitive functioning. Principal Component Analysis (PCA) reduced the dimensionality of the input data, effectively capturing the variance with fewer features. The feature weight analysis indicated a balanced contribution of each mental health symptom, with particular emphasis on one of the symptoms. The ANN model demonstrated moderate predictive performance, explaining a portion of the variance in cognitive levels based on the psychological variables.

Conclusion

The study confirms significant associations between emotional statuses of university students with their cognitive abilities. Specifically, we provide evidence for the first time that in Indian students, self-reported higher levels of stress, anxiety, and depression are linked to lower performance in cognitive tests. The application of PCA and feature weight analysis provided deeper insights into the structure of the predictive model. Notably, use of the ANN model provided insights into predicting these cognitive domains as a function of the emotional attributes. Our results emphasize the importance of addressing mental health concerns and implementing interventions for the enhancement of cognitive functions in university students.

Suicide Ideation and Self-Harm Behaviors in First-Year Dormitory Students at a Public Midwestern University: A Pilot Study

Purpose: Currently, 1 in 5 college students struggle with suicidal ideation while 7% to 44% engage in nonsuicidal self-injury. Illinois has one of the highest teenage and college student suicide rates in the United States. This pilot study assessed suicide ideation and self-harm behaviors at a public Illinois university. This is the first study to use 5 standardized psychological instruments to investigate these 2 crises in freshmen college students who are all required to reside in dormitories. The main hypothesis was to determine if the independent effects of freshmen students' depression, Five-Factor Model, and Reasons for Living affected the dependent variables, self-harm behaviors and suicide ideation. Methods: Forty first-year college dormitory students completed the Beck Depression Inventory-II, Scale of Suicidal Ideation, Five-Factor Model, Inventory of Statements About Self-Injury, and Reasons for Living Scale in person. Results: Participants were 18 to 19 years old, predominantly female (65%), and non-White (62%). Forty percent reported self-harm behaviors and 19% reported suicidal ideation. The top reasons for contemplated suicide attempts included the inability to solve problems (33%) and attention/revenge (28%). Students experienced high levels of anxiety (55%), self-consciousness (43%), and depression (18%). Depression was associated with suicide ideation (β = 0.05, P = .006), while neuroticism and openness were associated with self-harm behaviors (aOR = 3.36, P = .02, aOR = 0.48, P = .047, respectively). Ninety-five percent reported "responsibility to family" as a Reason for Living. Conclusions: Preliminary evidence necessitates an examination of self-harm and suicide ideation among all freshmen, investigating both risk and protective factors. In the future, a prevention intervention should be implemented campus-wide (and eventually nationwide) for all first-year dormitory students to enhance their mental well-being.

Characteristics and statistical analysis of university accidents in China from 2017 to 2021

University accidents in China are frequent, and to find out the relationship pattern of factors influencing accidents, 248 university accidents occurring within 2017-2021 were studied using difference analysis (Independent-samples T-test, Mann-Whitney U test), logistic regression analysis, and diagnostic analysis of receiver operating characteristic curves. The results show: The variability in time, space, and qualifications was statistically significant (p < 0.05), and when the number of university safety policies ≥77 would significantly reduce the frequency of university accidents, with an influence strength value of 0.884 and a diagnostic accuracy of 79.8 %. In addition, the perpetrators, the time and the location of the accidents were usually undergraduate students, first semester of university, and economically developed and educationally rich provinces, respectively, with influence strength value and diagnostic accuracy of greater than 1 and 70%, respectively. Finally, specific suggestions are offered for the future prevention and reduction of accidents at the University based on the findings of the studies.

A Web-Based Stratified Stepped Care Platform for Mental Well-being (TourHeart+): User-Centered Research and Design

BACKGROUND

Internet-based mental health interventions have been demonstrated to be effective in alleviating psychological distress and promoting mental well-being. However, real-world uptake and engagement of such interventions have been low. Rather than being stand-alone interventions, situating internet-based interventions under a stratified stepped care system can support users to continue with mental health practice and monitor their mental health status for timely services that are commensurate with their needs. A user-centered approach should be used in the development of such web-based platforms to understand the facilitators and barriers in user engagement to enhance platform uptake, usability, and adherence so it can support the users' continued adoption and practice of self-care for their mental health.

OBJECTIVE

The aim of this study was to describe the design process taken to develop a web-based stratified stepped care mental health platform, TourHeart+, using a user-centered approach that gathers target users' perceptions on mental self-care and feedback on the platform design and incorporates them into the design.

METHODS

The process involved a design workshop with the interdisciplinary development team, user interviews, and 2 usability testing sessions on the flow of registration and mental health assessment and the web-based self-help interventions of the platform. The data collected were summarized as descriptive statistics if appropriate and insights are extracted inductively. Qualitative data were extracted using a thematic coding approach.

RESULTS

In the design workshop, the team generated empathy maps and point-of-view statements related to the possible mental health needs of target users. Four user personas and related processes in the mental health self-care journey were developed based on user interviews. Design considerations were derived based on the insights drawn from the personas and mental health self-care journey. Survey results from 104 users during usability testing showed that the overall experience during registration and mental health assessment was friendly, and they felt cared for, although no statistically significant differences on preference ratings were found between using a web-based questionnaire tool and through an interactive chatbot, except that chatbot format was deemed more interesting. Facilitators of and barriers to registering the platform and completing the mental health assessment were identified through user feedback during simulation with mock-ups. In the usability testing for guided self-help interventions, users expressed pain points in course adherence, and corresponding amendments were made in the flow and design of the web-based courses.

CONCLUSIONS

The design process and findings presented in the study are important in developing a user-centric platform to optimize users' acceptance and usability of a web-based stratified stepped care platform with guided self-help interventions for mental well-being. Accounting for users' perceptions and needs toward mental health self-care and their experiences in the design process can enhance the usability of an evidence-based mental health platform on the web.