Evidence map›Paper›PMID 32706684›Full record

ArticleJMIR mHealth and uHealth2020

Formative Evaluation of a Smartphone App for Monitoring Daily Meal Distribution and Food Selection in Adolescents: Acceptability and Usability Study.

Billy Langlet, Christos Maramis, Christos Diou, Nikolaos Maglaveras, Petter Fagerberg, Rachel Heimeier, Irini Lekka, Anastasios Delopoulos, Ioannis Ioakimidis

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 20 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

9 authors at 2 institutions in 2 countries.

Billy LangletThe Innovative Use of Mobile Phones to Promote Physical Activity and Nutrition Across the Lifespan Research Group, Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.ORCID 0000-0003-2806-6186
Christos MaramisLab of Computing, Medical Informatics and Biomedical Imaging Technologies, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID 0000-0002-6417-0784
Christos DiouDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID 0000-0002-2461-1928
Nikolaos MaglaverasLab of Computing, Medical Informatics and Biomedical Imaging Technologies, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID 0000-0002-4919-0664
Petter FagerbergThe Innovative Use of Mobile Phones to Promote Physical Activity and Nutrition Across the Lifespan Research Group, Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.ORCID 0000-0002-1443-3128
Rachel HeimeierInternationella Engelska Gymnasiet, Stockholm, Sweden.ORCID 0000-0003-4798-1312
Irini LekkaLab of Computing, Medical Informatics and Biomedical Imaging Technologies, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID 0000-0001-9305-6561
Anastasios DelopoulosDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID 0000-0001-8220-8486
Ioannis IoakimidisThe Innovative Use of Mobile Phones to Promote Physical Activity and Nutrition Across the Lifespan Research Group, Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.ORCID 0000-0002-7208-1722
Aristotle University of Thessaloniki · GRKarolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity interventions face the problem of weight regain after treatment as a result of low compliance. Mobile health (mHealth) technologies could potentially increase compliance and aid both health care providers and patients.

objectiveThis study aimed to evaluate the acceptability and usability and define system constraints of an mHealth system used to monitor dietary habits of adolescents in real life, as a first step in the development of a self-monitoring and lifestyle management system against adolescent obesity.

methodsWe recruited 26 students from a high school in Stockholm, Sweden. After a 30-minute information meeting and 5-minute individual instruction on how to use an mHealth system (smartphone with app and two external sensors), participants used it for 2-3 weeks to objectively collect dietary habits. The app and sensors were used by the participants, without supervision, to record as many main meals and snacks as possible in real life. Feasibility was assessed following the "mHealth evidence reporting and assessment checklist," and usability was assessed by questionnaires. Compliance was estimated based on system use, where a registration frequency of 3 main meals (breakfast, lunch, and dinner) per day for the period of the experiment, constituted 100% compliance.

resultsParticipants included in the analysis had a mean age of 16.8 years (SD 0.7 years) and BMI of 21.9 kg/m2 (SD 4.1 kg/m2). Due to deviations from study instructions, 2 participants were excluded from the analysis. During the study, 6 participants required additional information on system use. The system received a 'Good' grade (77.1 of 100 points) on the System Usability Scale, with most participants reporting that they were comfortable using the smartphone app. Participants expressed a willingness to use the app mostly at home, but also at school; most of their improvement suggestions concerned design choices for the app. Of all main meals, the registration frequency increased from 70% the first week to 76% the second week. Participants reported that 40% of the registered meals were home-prepared, while 34% of the reported drinks contained sugar. On average, breakfasts took place at 8:30 AM (from 5:00 AM to 2:00 PM), lunches took place at 12:15 PM (from 10:15 AM to 6:15 PM), and dinners took place at 7:30 PM (from 3:00 PM to 11:45 PM). When comparing meal occurrence during weekdays vs weekends, breakfasts and lunches were eaten 3 hours later during weekends, while dinner timing was unaffected.

conclusionsFrom an infrastructural and functional perspective, system use was feasible in the current context. The smartphone app appears to have high acceptability and usability in high school students, which are the intended end-users. The system appears promising as a relatively low-effort method to provide real-life dietary habit measurements associated with overweight and obesity risk.

Indexed as

Feeding BehaviorMobile ApplicationsSmartphoneTelemedicineAdolescentFeasibility StudiesFemaleFood PreferencesHumansMaleMealsPediatric ObesitySchoolsStudentsSwedendietary behavioreHealthlifestyle behavioral monitoringlifestyle interventionsmHealthmobile phoneobesityoverweightsmartphoneweight management

Identifiers

PMID32706684
PMCPMC7404017
OpenAlexW3024829084

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.