e–Mental Health Program to Prevent Psychological Distress Among French-Speaking International Students in a Linguistic-Cultural Minority Context (Ottawa, Alberta, and Quebec): Protocol for the Implementation and Evaluation of Psy-Web (Preprint)
Bibliographic record
Abstract
BACKGROUND Based on experiences with the COVID-19 pandemic, postsecondary institutions were most affected by the restrictions. Students, especially international students, have borne the brunt associated with in-person learning restrictions imposed by public health recommendations. Canada is among the top 3 countries hosting international students (ISs), including Francophone students in provinces such as Quebec and other anglophone regions. Academic restrictions were accompanied by other measures such as quarantine, self-isolation, social distancing, and travel ban, to cite some. This has had a wide-ranging impact on these ISs. The resulting psychological distress and burden may have a much greater impact on Francophone ISs in anglophone settings, many of whom had ordinarily limited access to active offers of care in French in addition to cultural barriers and low literacy of the health care system. In order to take advantage of the effectiveness of eHealth as a pertinent and promising avenue, our project intends to build a web-based application that is cost-effective, user-friendly, anonymous, and capable to prompt interactive interventions as a first-line resource for psychological distress. In fact, internet applications have been increasingly used for the management of psychological distresses, and internet-based cognitive behavioral therapy is one of the preferred methods to prevent or control them. OBJECTIVE The aims of this study are to (1) design, implement, and maintain Psy-Web for the psychological support of ISs and (2) analyze the results of the implementation of the Psy-Web platform, the additional resources solicited, and the results obtained. METHODS This interventional project will use a sequential mixed design in the exploratory phase (phase 1) including the construction of the Psy-Web platform. A quantitative prospective component (phase 2) will include the intervention content of the Psy-Web platform. In total, 105 ISs participants (study group) and 52 ISs (control group), based on a ratio of 1:2, will be considered. The control group participants include those who did not use the web platform. RESULTS The project is at the data collection stage (phase 1). Psy-Web will be built in accordance with the DMAIC (Define, Measure, Analyze, Improve and Control) model with the perspective of boosting its robustness. As a first-line resource to prevent psychological distress and ultimately improve their academic performance, Psy-Web is an innovative opportunity for high education managers. The project involves a multisectoral and a multidisciplinary partnership. CONCLUSIONS The project will develop a promising web-based solution to prevent psychological distress. Ultimately, Psy-Web will be operable in multiple languages including French. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/47059
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.064 | 0.006 |
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".