The Role of Mental Health Stigma in University Students’ Satisfaction With Web-Based Stress Management Resources: Intervention Study
Bibliographic record
Abstract
BACKGROUND: University students frequently report elevated levels of stress and mental health difficulties. Thus, the need to build coping capacity on university campuses has been highlighted as critical to mitigating the negative effects of prolonged stress and distress among students. Since the COVID-19 pandemic, web-based stress management resources such as infographics and web-based workshops have been central to supporting university students' mental health and well-being. However, there is a lack of research on students' satisfaction with and uptake of these approaches. Furthermore, mental health stigma has been suggested to have not only fueled the emergence of these web-based approaches to stress management but may also influence students' help-seeking behaviors and their satisfaction with and uptake of these resources. OBJECTIVE: This study explored potential differences in students' satisfaction and strategy use in response to an interactive infographic (an emerging resource delivery modality) presenting stress management strategies and a web-based workshop (a more common modality) presenting identical strategies. This study also examined the relative contribution of students' strategy use and family-based mental health stigma in predicting their sustained satisfaction with the 2 web-based stress management approaches. METHODS: University students (N=113; mean age 20.93, SD 1.53 years; 100/113, 88.5% women) completed our web-based self-report measure of family-based mental health stigma at baseline and were randomly assigned to either independently review an interactive infographic (n=60) or attend a synchronous web-based workshop (n=53). All participants reported their satisfaction with their assigned modality at postintervention (T1) and follow-up (T2) and their strategy use at T2. RESULTS: Interestingly, a 2-way mixed ANOVA revealed no significant group × time interaction or main effect of group on satisfaction. However, there was a significant decrease in satisfaction from T1 to T2, despite relatively high levels of satisfaction being reported at both time points. In addition, a 1-way ANOVA revealed no significant difference in strategy use between groups. Results from a hierarchical multiple regression revealed that students' strategy use positively predicted T2 satisfaction in both groups. However, only in the web-based workshop group did family-based mental health stigma predict T2 satisfaction over and above strategy use. CONCLUSIONS: While both approaches were highly satisfactory over time, findings highlight the potential utility of interactive infographics since they are less resource-intensive than web-based workshops and students' satisfaction with them is not impacted by family-based mental health stigma. Moreover, although numerous intervention studies measure satisfaction at a single time point, this study highlights the need for tracking satisfaction over time following intervention delivery. These findings have implications for student service units in the higher education context, emphasizing the need to consider student perceptions of family-based mental health stigma and preferences regarding delivery format when designing programming aimed at bolstering students' coping capacity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".