Evidence map›Paper›PMID 30609985›Full record

ArticleJMIR mHealth and uHealth2019

Usefulness of Wearable Cameras as a Tool to Enhance Chronic Disease Self-Management: Scoping Review.

Ralph Maddison, Susie Cartledge, Michelle Rogerson, Nicole Sylvia Goedhart, Tarveen Ragbir Singh, Christopher Neil, Dinh Phung, Kylie Ball

Open access · goldAbstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
5.5field-weighted citation impact, top 4% 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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 46 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 2 institutions in 1 country.

Ralph MaddisonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID 0000-0001-8564-5518
Susie CartledgeInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID 0000-0002-6837-2244
Michelle RogersonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID 0000-0002-2558-3535
Nicole Sylvia GoedhartAthena Institute for Research on Innovation and Communication in Health and Life Sciences, Faculty of Science, VU University, Amsterdam, Netherlands.ORCID 0000-0001-5975-9749
Tarveen Ragbir SinghInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID 0000-0001-7510-7433
Christopher NeilDepartment of Medicine, Western Health, University of Melbourne, Melbourne, Australia.ORCID 0000-0002-1546-4022
Dinh PhungCentre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia.ORCID 0000-0002-9977-8247
Kylie BallInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID 0000-0003-2893-8415
Deakin University · AUThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-management is a critical component of chronic disease management and can include a host of activities, such as adhering to prescribed medications, undertaking daily care activities, managing dietary intake and body weight, and proactively contacting medical practitioners. The rise of technologies (mobile phones, wearable cameras) for health care use offers potential support for people to better manage their disease in collaboration with their treating health professionals. Wearable cameras can be used to provide rich contextual data and insight into everyday activities and aid in recall. This information can then be used to prompt memory recall or guide the development of interventions to support self-management. Application of wearable cameras to better understand and augment self-management by people with chronic disease has yet to be investigated.

objectiveThe objective of our review was to ascertain the scope of the literature on the use of wearable cameras for self-management by people with chronic disease and to determine the potential of wearable cameras to assist people to better manage their disease.

methodsWe conducted a scoping review, which involved a comprehensive electronic literature search of 9 databases in July 2017. The search strategy focused on studies that used wearable cameras to capture one or more modifiable lifestyle risk factors associated with chronic disease or to capture typical self-management behaviors, or studies that involved a chronic disease population. We then categorized and described included studies according to their characteristics (eg, behaviors measured, study design or type, characteristics of the sample).

resultsWe identified 31 studies: 25 studies involved primary or secondary data analysis, and 6 were review, discussion, or descriptive articles. Wearable cameras were predominantly used to capture dietary intake, physical activity, activities of daily living, and sedentary behavior. Populations studied were predominantly healthy volunteers, school students, and sports people, with only 1 study examining an intervention using wearable cameras for people with an acquired brain injury. Most studies highlighted technical or ethical issues associated with using wearable cameras, many of which were overcome.

conclusionsThis scoping review highlighted the potential of wearable cameras to capture health-related behaviors and risk factors of chronic disease, such as diet, exercise, and sedentary behaviors. Data collected from wearable cameras can be used as an adjunct to traditional data collection methods such as self-reported diaries in addition to providing valuable contextual information. While most studies to date have focused on healthy populations, wearable cameras offer promise to better understand self-management of chronic disease and its context.

Indexed as

AdultChronic DiseaseFemaleHumansMaleSelf-ManagementVideo RecordingWearable Electronic Devicescameraschronic diseaseeHealthlife-logginglifestyle behaviorreview

Identifiers

PMID30609985
PMCPMC6682294
OpenAlexW2888839493

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.