Evidence map›Paper›PMID 29199630›Full record

ArticlePublic health nutrition2018

Adherence to self-monitoring healthy lifestyle behaviours through mobile phone-based ecological momentary assessments and photographic food records over 6 months in mostly ethnic minority mothers.

W Scott Comulada, Dallas Swendeman, Maryann K Koussa, Deborah Mindry, Melissa Medich, Deborah Estrin, Neil Mercer, Nithya Ramanathan

Open access · bronzeAbstract read
In one paragraph

Article in Public health nutrition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

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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

8 authors at 5 institutions in 1 country.

W Scott Comulada1Global Center for Children and Families,Department of Psychiatry & Biobehavioral Sciences,University of California,Los Angeles,10920 Wilshire Blvd,Suite 350,Los Angeles,CA 90024,USA.
Dallas Swendeman1Global Center for Children and Families,Department of Psychiatry & Biobehavioral Sciences,University of California,Los Angeles,10920 Wilshire Blvd,Suite 350,Los Angeles,CA 90024,USA.
Maryann K Koussa1Global Center for Children and Families,Department of Psychiatry & Biobehavioral Sciences,University of California,Los Angeles,10920 Wilshire Blvd,Suite 350,Los Angeles,CA 90024,USA.
Deborah Mindry2Center for Social Medicine and Humanities,Department of Psychiatry & Biobehavioral Sciences,University of California,Los Angeles,Los Angeles,CA,USA.
Melissa Medich3Department of Family Medicine,University of California,Los Angeles,Los Angeles,CA,USA.
Deborah Estrin4Computer Science Department,Cornell Tech,New York,NY,USA.
Neil Mercer5Department of Surgery,University of California,San Francisco,San Francisco,CA,USA.
Nithya Ramanathan6Nexleaf Analytics,Los Angeles,CA,USA.
University of California, Los Angeles · USCenter for Children · USCornell University · USNexleaf Analytics · USUniversity of California, San Francisco · US

Funding

UCLA Rapid, Relevant, Rigorous Implementation Science HubP30MH058107 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RAPHAEL J LANDOVITZ · 1997 to 2026
$53.5M
Self-monitoring using GPS- and accelerometer-equipped smartphonesRC1HL099556 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RAMANATHAN, NITHYA · 2009 to 2010
$971k
Predicting HIV-related Behaviors of Social Networks in a MPS EnvironmentK01MH089270 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COMULADA, WARREN SCOTT · 2010 to 2014
$736k
NHLBI NIH HHS RC1 HL099556NIMH NIH HHS K01 MH089270NIMH NIH HHS P30 MH058107
6 · The paper itself

Abstract

objectiveMobile phones can replace traditional self-monitoring tools through cell phone-based ecological momentary assessment (CEMA) of lifestyle behaviours and camera phone-based images of meals, i.e. photographic food records (PFR). Adherence to mobile self-monitoring needs to be evaluated in real-world treatment settings. Towards this goal, we examine CEMA and PFR adherence to the use of a mobile app designed to help mothers self-monitor lifestyle behaviours and stress. Design/Setting In 2012, forty-two mothers recorded CEMA of diet quality, exercise, sleep, stress and mood four times daily and PFR during meals over 6 months in Los Angeles, California, USA. SUBJECTS: A purposive sample of mothers from mixed ethnicities.

resultsAdherence to recording CEMA at least once daily was higher compared with recording PFR at least once daily over the study period (74 v. 11 %); adherence to both types of reports decreased over time. Participants who recorded PFR for more than a day (n 31) were more likely to be obese v. normal- to overweight and to have higher blood pressure, on average (all P<0·05). Based on random-effects regression, CEMA and PFR adherence was highest during weekdays (both P<0·01). Additionally, PFR adherence was associated with older age (P=0·04). CEMA adherence was highest in the morning (P<0·01). PFR recordings occurred throughout the day.

conclusionsVariations in population and temporal characteristics should be considered for mobile assessment schedules. Neither CEMA nor PFR alone is ideal over extended periods.

Indexed as

DietEcological Momentary AssessmentEthnicityFeeding BehaviorMothersPatient ComplianceAdultAge FactorsAsian PeopleBlack or African AmericanBlood PressureCell PhoneDiet RecordsFemaleHealthy LifestyleHispanic or LatinoCamera phone imageDietary intakeEcological momentary assessmentPhotographic food record

Identifiers

PMID29199630
PMCPMC5807077
OpenAlexW2773090345

What OpenQuestion holds

Textmetadata
LicenceTDM
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.