Promoting Stress Management among Students in Higher Education: Evaluating the Effectiveness of a Persuasive Time Management Mobile App
Bibliographic record
Abstract
In recent years, there has been a notable rise in the development of mobile apps to deliver stress management interventions. However, the prevailing design of most available stress management apps leans towards an emotion-focused coping approach, primarily targeting the regulation of stress-induced negative emotions. Given that the perception of time shortage is a major source of stress among students in higher education, we adopted a problem-focused coping approach that targets tackling student stress via time management. Our work evolved through four main phases. First, we previously conducted a large-scale study involving 502 students, constructing five structural equation models (SEMs) to pinpoint the most effective time management factor in promoting the perception of control over time. Second, based on the findings, we designed and developed a persuasive mobile app (SortOut) to promote effective time management behavior among the target users. Before the development phase, the initial app prototype was evaluated and refined with students (n = 69). In the final phase, this paper focuses on the culmination of our work, wherein we assessed the app’s effectiveness through a 4-week field study involving 34 students. Subsequently, we conducted one-on-one interviews with 11 students to delve into their experiences and feedback. The results revealed that, after using the app, students demonstrated improvement in time management behavior, higher academic self-confidence, and lower stress compared to the baseline. Students in the early and later stages of behavior change (based on the Transtheoretical Model (TTM)) reported similar positive outcomes. Moreover, students perceived the app as straightforward and easy to use; they were not tense or pressured while using the app, which is especially vital for stress management interventions. Thematic analysis showed that the app encouraged organizational thought and behavior and aided students in managing their time and workload, increasing the commitment toward task completion. The study findings suggest that the app helped students engage in effective time management behavior with an improved perception of control over time. Such improved perception is instrumental in promoting student confidence and well-being. Guided by the study findings, we provided actionable design recommendations and future research directions to facilitate the development of impactful persuasive time and stress management interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".