A Mobile Health Intervention for Mental Health Promotion Among University Students: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: High positive mental health, including the ability to cope with the normal stresses of life, work productively, and be able to contribute to one's community, has been associated with various health outcomes. The role of positive mental health is therefore increasingly recognized in national mental health promotion programs and policies. Mobile health (mHealth) interventions could be a cost-effective way to disseminate positive psychological interventions to the general population. OBJECTIVE: The aim of this study was to estimate the effect of a fully automated mHealth intervention on positive mental health, and anxiety and depression symptomology among Swedish university students using a randomized controlled trial design. METHODS: A 2-arm, single-blind (researchers), parallel-groups randomized controlled trial with an mHealth positive psychology program intervention group and a relevant online mental health information control group was employed to estimate the effect of the novel intervention. Participants were recruited using digital advertising through student health care centers in Sweden. Inclusion criteria were (1) university students, (2) able to read and understand Swedish, (3) and have access to a mobile phone. Exclusion criteria were high positive mental health, as assessed by the Mental Health Continuum Short Form (MHC-SF), or high depression and anxiety symptomology, as assessed by the Hospital Anxiety Depression Scale (HADS). The primary outcome was positive mental health (MHC-SF), and the secondary outcomes were depression and anxiety symptomatology (HADS). The subscales of MHC-SF were also analyzed as exploratory outcomes. Outcomes were measured 3 months after randomization through questionnaires completed on the participants' mobile phones. RESULTS: A total of 654 participants (median age 25 years), including 510 (78.0%) identifying as female, were randomized to either the intervention (n=348) or control group (n=306). At follow-up, positive mental health was significantly higher in the intervention group compared with the control group (incidence rate ratio [IRR]=1.067, 95% CI 1.024-1.112, P=.002). For both depression and anxiety symptomatology, the intervention group showed significantly lower scores at follow-up compared with the control group (depression: IRR=0.820, 95% CI 0.714-0.942, P=.005; anxiety: IRR=0.899, 95% CI 0.840-0.962, P=.002). Follow-up rates were lower than expected (58.3% for primary outcomes and 52.3% for secondary outcomes); however, attrition analyses did not identify any systematic attrition with respect to baseline variables. CONCLUSIONS: The mHealth intervention was estimated to be superior to usual care in increasing positive mental health among university students. A protective effect of the intervention was also found on depressive and anxiety symptoms. These findings demonstrate the feasibility of using an automated mobile phone format to enhance positive mental health, which offers promise for the use of mHealth solutions in public mental health promotion. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Registry ISRCTN54748632; http://www.isrctn.com/ISRCTN54748632.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".