Evidence map›Paper›PMID 29513683›Full record

Trial reportPloS one2018

Individual differences in regulatory mode moderate the effectiveness of a pilot mHealth trial for diabetes management among older veterans.

Michelle Dugas, Kenyon Crowley, Guodong Gordon Gao, Timothy Xu, Ritu Agarwal, Arie W Kruglanski, Nanette Steinle

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 8 pooled it
11.9field-weighted citation impact, top 1% of its field
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, 8 syntheses or guidelines pooled it, 61 citations in OpenAlex.

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  10. Home blood pressure-lowering effect of digital therapeutics in hypertension: impact of body weight and salt intake.Hypertension research : official journal of the Japanese Society of Hypertension · 2023
    Trial
  11. Article
  12. Article
  13. Staying engaged: a scoping review of psychological and motivational drivers of adherence to technology-supported physical activity in older adults.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2025
    Review
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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

7 authors at 4 institutions in 1 country.

Michelle DugasDepartment of Psychology, University of Maryland, College Park, Maryland, United States of America.ORCID 0000-0003-1400-4515
Kenyon CrowleyCenter for Health Information & Decision Systems, Robert H Smith School of Business, University of Maryland, College Park, Maryland, United States of America.
Guodong Gordon GaoCenter for Health Information & Decision Systems, Robert H Smith School of Business, University of Maryland, College Park, Maryland, United States of America.
Timothy XuDepartment of Biology, Emory University, Atlanta, Georgia, United States of America.
Ritu AgarwalCenter for Health Information & Decision Systems, Robert H Smith School of Business, University of Maryland, College Park, Maryland, United States of America.
Arie W KruglanskiDepartment of Psychology, University of Maryland, College Park, Maryland, United States of America.
Nanette SteinleMaryland Veterans Administration Health Care Center, Baltimore, Maryland, United States of America.
Decision Systems (United States) · USEmory University · USUniversity of Maryland, Baltimore · USUniversity of Maryland, College Park · US

Funding

Research BaseP30DK072488 · NIDDK · UNIVERSITY OF MARYLAND BALTIMORE · PI MITCHELL, BRAXTON D · 2005 to 2019
$17.3M
NIDDK NIH HHS P30 DK072488
6 · The paper itself

Abstract

mHealth tools to help people manage chronic illnesses have surged in popularity, but evidence of their effectiveness remains mixed. The aim of this study was to address a gap in the mHealth and health psychology literatures by investigating how individual differences in psychological traits are associated with mHealth effectiveness. Drawing from regulatory mode theory, we tested the role of locomotion and assessment in explaining why mHealth tools are effective for some but not everyone. A 13-week pilot study investigated the effectiveness of an mHealth app in improving health behaviors among older veterans (n = 27) with poorly controlled Type 2 diabetes. We developed a gamified mHealth tool (DiaSocial) aimed at encouraging tracking of glucose control, exercise, nutrition, and medication adherence. Important individual differences in longitudinal trends of adherence, operationalized as points earned for healthy behavior, over the course of the 13-week study period were found. Specifically, low locomotion was associated with unchanging levels of adherence during the course of the study. In contrast, high locomotion was associated with generally stronger adherence although it exhibited a quadratic longitudinal trend. In addition, high assessment was associated with a marginal, positive trend in adherence over time while low assessment was associated with a marginal, negative trend. Next, we examined the relationship between greater adherence and improved clinical outcomes, finding that greater adherence was associated with greater reductions in glycated hemoglobin (HbA1c) levels. Findings from the pilot study suggest that mHealth technologies can help older adults improve their diabetes management, but a "one size fits all" approach may yield suboptimal outcomes.

Indexed as

Drug MonitoringAgedAged, 80 and overDiabetes Mellitus, Type 2ExerciseGlycated HemoglobinHealth BehaviorHumansIndividualityMiddle AgedOutcome Assessment, Health CarePilot ProjectsSelf CareTelemedicineVeteransGlycated Hemoglobin

Identifiers

PMID29513683
PMCPMC5841664
OpenAlexW2794421602

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.