A Guided, Internet-Based Stress Management Intervention for University Students With High Levels of Stress: Feasibility and Acceptability Study
Notice bibliographique
Résumé
BACKGROUND: Transitioning to adulthood and challenges in university life can result in increased stress levels among university students. Chronic and severe stress is associated with deleterious psychological and physiological effects. Digital interventions could succeed in approaching and helping university students who might be at risk; however, the experiences of students with internet-based stress management interventions are insufficiently understood. OBJECTIVE: This study aims to explore the feasibility; acceptability; and changes in perceived stress, depressive symptoms, and quality of life from baseline to posttest assessment of a 5-session, internet-based stress management intervention guided by an e-coach, developed for university students experiencing high levels of stress. METHODS: A single-arm study was conducted. Students were recruited from different channels, mainly from a web survey. Students were eligible if they (1) scored ≥20 on the Perceived Stress Scale-10, (2) were aged ≥18 years, and (3) were studying at one of the participating universities. Feasibility and acceptability of the intervention were investigated using several indications, including satisfaction (Client Satisfaction Questionnaire-8) and usability (System Usability Scale-10). We also investigated the indicators of intervention adherence using use metrics (eg, the number of completed sessions). Our secondary goal was to explore the changes in perceived stress (Perceived Stress Scale-10), depressive symptoms (Patient Health Questionnaire-9), and quality of life (EQ-5D-5L scale) from baseline to posttest assessment. In addition, we conducted semistructured interviews with intervention completers and noncompleters to understand user experiences in depth. For all primary outcomes, descriptive statistics were calculated. Changes from baseline to posttest assessment were examined using 2-tailed paired sample t tests or the Wilcoxon signed rank test. Qualitative data were analyzed using thematic analysis. RESULTS: Of 436 eligible students, 307 (70.4%) students started using the intervention. Overall, 25.7% (79/307) completed the core sessions (ie, sessions 1-3) and posttest assessment. A substantial proportion of the students (228/307, 74.3%) did not complete the core sessions or the posttest assessment. Students who completed the core sessions reported high satisfaction (mean 25.78, SD 3.30) and high usability of the intervention (mean 86.01, SD 10.25). Moreover, this group showed large reductions in perceived stress (Cohen d=0.80) and moderate improvements in depression score (Cohen d=0.47) and quality of life (Cohen d=-0.35) from baseline to posttest assessment. Qualitative findings highlight that several personal and intervention-related factors play a role in user experience. CONCLUSIONS: The internet-based stress management intervention seems to be feasible, acceptable, and possibly effective for some university students with elevated stress levels. However, given the high dropout rate and qualitative findings, several adjustments in the content and features of the intervention are needed to maximize the user experience and the impact of the intervention. TRIAL REGISTRATION: Netherlands Trial Register 8686; https://onderzoekmetmensen.nl/nl/trial/20889. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.invent.2021.100369.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».