Evidence map›Paper›PMID 28500020›Full record

Trial reportJournal of medical Internet research2017

Efficacy of a Web-Based Guided Recommendation Service for a Curated List of Readily Available Mental Health and Well-Being Mobile Apps for Young People: Randomized Controlled Trial.

Niranjan Bidargaddi, Peter Musiat, Megan Winsall, Gillian Vogl, Victoria Blake, Stephen Quinn, Simone Orlowski, Gaston Antezana, Geoffrey Schrader

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Health Recommender Systems: Systematic Review.Journal of medical Internet research · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Niranjan BidargaddiDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0003-2868-9260
Peter MusiatDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0001-7439-0441
Megan WinsallDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0001-5696-0578
Gillian VoglReachOut.com, Sydney, Australia.ORCID 0000-0002-4958-5789
Victoria BlakeReachOut.com, Sydney, Australia.ORCID 0000-0002-5832-6324
Stephen QuinnDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0002-1306-9686
Simone OrlowskiDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0001-8395-1087
Gaston AntezanaDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0002-4257-0779
Geoffrey SchraderDigital Psychiatry & Personal Health Informatics Group, School of Medicine, Flinders University, Clovelly Park, Australia.ORCID 0000-0002-2504-8102

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental disorders are highly prevalent for the people who are aged between 16 and 25 years and can permanently disrupt the development of these individuals. Easily available mobile health (mHealth) apps for mobile phones have great potential for the prevention and early intervention of mental disorders in young adults, but interventions are required that can help individuals to both identify high-quality mobile apps and use them to change health and lifestyle behavior.

objectivesThe study aimed to assess the efficacy of a Web-based self-guided app recommendation service ("The Toolbox") in improving the well-being of young Australians aged between 16 and 25 years. The intervention was developed in collaboration with young adults and consists of a curated list of 46 readily available health and well-being apps, assessed and rated by professionals and young people. Participants are guided by an interactive quiz and subsequently receive recommendations for particular apps to download and use based on their personal goals.

methodsThe study was a waitlist, parallel-arm, randomized controlled trial. Our primary outcome measure was change in well-being as measured by the Mental Health Continuum-Short Form (MHC-SF). We also employed ecological momentary assessments (EMAs) to track mood, energy, rest, and sleep. Participants were recruited from the general Australian population, via several Web-based and community strategies. The study was conducted through a Web-based platform consisting of a landing Web page and capabilities to administer study measures at different time points. Web-based measurements were self-assessed at baseline and 4 weeks, and EMAs were collected repeatedly at regular weekly intervals or ad hoc when participants interacted with the study platform. Primary outcomes were analyzed using linear mixed-models and intention-to-treat (ITT) analysis.

resultsA total of 387 participants completed baseline scores and were randomized into the trial. Results demonstrated no significant effect of "The Toolbox" intervention on participant well-being at 4 weeks compared with the control group (P=.66). There were also no significant differences between the intervention and control groups at 4 weeks on any of the subscales of the MHC-SF (psychological: P=.95, social: P=.42, emotional: P=.95). Repeat engagement with the study platform resulted in a significant difference in mood, energy, rest, and sleep trajectories between intervention and control groups as measured by EMAs (P<.01).

conclusionsThis was the first study to assess the effectiveness of a Web-based well-being intervention in a sample of young adults. The design of the intervention utilized expert rating of existing apps and end-user codesign approaches resulting in an app recommendation service. Our finding suggests that recommended readily available mental health and well-being apps may not lead to improvements in the well-being of a nonclinical sample of young people, but might halt a decline in mood, energy, rest, and sleep.

trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12614000710628; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366145 (Archived by WebCite at http://www.webcitation.org/ 6pWDsnKme).

Indexed as

AdolescentAdultCell PhoneFemaleHumansInternetMaleMental HealthMobile ApplicationsYoung Adultappsengagementmental healthonline interventionwell-beingyoung people

Identifiers

PMID28500020
PMCPMC5446666

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.