Evidence map›Paper›PMID 32845553›Full record

Trial reportJournal of occupational health2020

Can self-monitoring mobile health apps reduce sedentary behavior? A randomized controlled trial.

Kojiro Yamamoto, Takeshi Ebara, Fumiko Matsuda, Tsuyoshi Matsukawa, Nao Yamamoto, Kenji Ishii, Takahiro Kurihara, Shota Yamada, Taro Matsuki, Naomichi Tani and 1 more

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of occupational health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. 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

11 authors.

Kojiro YamamotoNagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0002-4388-2854
Takeshi EbaraNagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0003-3342-1058
Fumiko MatsudaThe Ohara Memorial Institute for Science of Labour, Tokyo, Japan.
Tsuyoshi MatsukawaFaculty of Information Science, Aichi Institute of Technology, Toyota, Japan.
Nao YamamotoNagoya City University Graduate School of Economics, Nagoya, Japan.
Kenji IshiiThe Ohara Memorial Institute for Science of Labour, Tokyo, Japan.
Takahiro KuriharaNagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Shota YamadaNagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Taro MatsukiNagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0003-2935-3064
Naomichi TaniThe Association for Preventive Medicine of Japan, Fukuoka, Japan.
Michihiro KamijimaNagoya City University Graduate School of Medical Sciences, Nagoya, Japan.ORCID https://orcid.org/0000-0003-0670-8790

Funding

Japan Society for the Promotion of Science 19H01609
6 · The paper itself

Abstract

objectiveTo examine whether the self-monitoring interventions of a mobile health app reduce sedentary behavior in the short and long terms.

methodWe designed a double-blind randomized control trial. Participants were selected from among the staff of a medical institution and registrants of an online research firm. Forty-nine participants were randomly assigned to either a control group (n = 25) or an intervention group (n = 24). The control group was given only the latest information about sedentary behavior, and the intervention was provided real-time feedback for self-monitoring in addition to the information. These interventions provided for 5 weeks (to measure the short-term effect) and 13 weeks (to measure the long-term effect) via the smartphone app. Measurements were as follows: subjective total sedentary time (SST), objective total sedentary time (OST), mean sedentary bout duration (MSB), and the number of sedentary breaks (SB). Only SST was measured by self-report based on the standardized International Physical Activity Questionnaire and others were measured with the smartphone.

resultsNo significant results were observed in the short term. In the long term, while no significant results were also observed in objective sedentary behavior (OST, MSB, SB), the significant differences were observed in subjective sedentary behavior (SST, β

conclusionsReal-time feedback for self-monitoring with smartphone did not significantly affect objective sedentary behavior. However, providing only information about sedentary behavior to users with smartphones may make misperception on the amount of their subjective sedentary behavior.

Indexed as

Health BehaviorMobile ApplicationsMonitoring, AmbulatorySedentary BehaviorSmartphoneAdultDouble-Blind MethodFemaleHumansMaleMiddle Agedmobile health technologysedentary behaviorself-monitoring intervention

Identifiers

PMID32845553
PMCPMC7448798

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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.