Evidence map›Paper›PMID 37976094›Full record

ArticleJMIR formative research2023

mHealth Intervention to Promote Physical Activity Among Employees Using a Deep Learning Model for Passive Monitoring of Depression and Anxiety: Single-Arm Feasibility Trial.

Kazuhiro Watanabe, Shoichi Okusa, Mitsuhiro Sato, Hideki Miura, Masahiro Morimoto, Akizumi Tsutsumi

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Trial
  2. Review
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  5. Article
  6. Article
  7. Article
  8. Quality assessment of mHealth apps: a scoping review.Frontiers in health services · 2024
    Article
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

6 authors.

Kazuhiro WatanabeDepartment of Public Health, Kitasato University School of Medicine, Sagamihara, Japan.ORCID https://orcid.org/0000-0002-3342-6142
Shoichi OkusaTOSHIBA Health Insurance Society, Kawasaki, Japan.ORCID https://orcid.org/0009-0009-8399-3004
Mitsuhiro SatoHealth & Productivity Management Promotion Division, Fujitsu General Limited, Kawasaki, Japan.ORCID https://orcid.org/0009-0006-8935-5327
Hideki MiuraNikkei Business Publications, Inc, Tokyo, Japan.ORCID https://orcid.org/0009-0006-7682-7495
Masahiro MorimotoMS & AD InterRisk Research & Consulting, Inc, Tokyo, Japan.ORCID https://orcid.org/0009-0009-6808-0936
Akizumi TsutsumiDepartment of Public Health, Kitasato University School of Medicine, Sagamihara, Japan.ORCID https://orcid.org/0000-0003-0966-4869

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysical activity effectively prevents depression and anxiety. Although mobile health (mHealth) technologies offer promising results in promoting physical activity and improving mental health, conflicting evidence exists on their effectiveness, and employees face barriers to using mHealth services. To address these problems, we recently developed a smartphone app named ASHARE to prevent depression and anxiety in the working population; it uses a deep learning model for passive monitoring of depression and anxiety from information about physical activity.

objectiveThis study aimed to preliminarily investigate (1) the effectiveness of the developed app in improving physical activity and reducing depression and anxiety and (2) the app's implementation outcomes (ie, its acceptability, appropriateness, feasibility, satisfaction, and potential harm).

methodsWe conducted a single-arm interventional study. From March to April 2023, employees aged ≥18 years who were not absent were recruited. The participants were asked to install and use the app for 1 month. The ideal usage of the app was for the participants to take about 5 minutes every day to open the app, check the physical activity patterns and results of an estimated score of psychological distress, and increase their physical activity. Self-reported physical activity (using the Global Physical Activity Questionnaire, version 2) and psychological distress (using the 6-item Kessler Psychological Distress Scale) were measured at baseline and after 1 month. The duration of physical activity was also recorded digitally. Paired t tests (two-tailed) and chi-square tests were performed to evaluate changes in these variables. Implementation Outcome Scales for Digital Mental Health were also measured for acceptability, appropriateness, feasibility, satisfaction, and harm. These average scores were assessed by comparing them with those reported in previous studies.

resultsThis study included 24 employees. On average, the app was used for 12.54 days (44.8% of this study's period). After using the app, no significant change was observed in physical activity (-12.59 metabolic equivalent hours per week, P=.31) or psychological distress (-0.43 metabolic equivalent hours per week, P=.93). However, the number of participants with severe psychological distress decreased significantly (P=.01). The digitally recorded duration of physical activity increased during the intervention period (+0.60 minutes per day, P=.08). The scores for acceptability, appropriateness, and satisfaction were lower than those in previous mHealth studies, whereas those for feasibility and harm were better.

conclusionsThe ASHARE app was insufficient in promoting physical activity or improving psychological distress. At this stage, the app has many issues that are to be addressed in terms of both implementation and effectiveness. The main reason for this low effectiveness might be the poor evaluation of the implementation outcomes by app users. Improving acceptability, appropriateness, and satisfaction are identified as key issues to be addressed in future implementation.

trial registrationUniversity Hospital Medical Information Network Clinical Trials Registry UMIN000050430; https://tinyurl.com/mrx5ntcmrecptno=R000057438.

Indexed as

acceptabilityanxietyappapplicationapplicationsappsbehavioral changedepressiondepressivedistresseHealthemployeeemployeesexercisefeasibilityfitnessmental healthmHealthmobile healthmobile phonemonitormonitoringoccupational healthphysical activitysatisfactionsmartphoneworkerworkersworkplace

Identifiers

PMID37976094
PMCPMC10692887

What OpenQuestion holds

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LicenceCC BY
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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.