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Record W3012103240 · doi:10.2196/17208

A Mobile Health Intervention for Mental Health Promotion Among University Students: Randomized Controlled Trial

2020· article· en· W3012103240 on OpenAlexvenueno aff
Marcus Bendtsen, Ulrika Müssener, Catharina Linderoth, Kristin Thomas

Bibliographic record

VenueJMIR mhealth and uhealth · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthmHealthPsychological interventionRandomized controlled trialAnxietyHospital Anxiety and Depression ScaleMedicinePopulationClinical psychologyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.444
Teacher spread0.385 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations68
Published2020
Admission routes1
Has abstractyes

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