Evidence map›Paper›PMID 33104517›Full record

ArticleJMIR mHealth and uHealth2020

Comparison of Mobile Health Technology Use for Self-Tracking Between Older Adults and the General Adult Population in Canada: Cross-Sectional Survey.

Mirou Jaana, Guy Paré

Abstract 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 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 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

44 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Digital Cognitive Rehabilitation Platforms for Older Adults in Portugal: A Systematic Review.International journal of environmental research and public health · 2026
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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

2 authors.

Mirou JaanaTelfer School of Management, University of Ottawa, Ottawa, ON, Canada.ORCID 0000-0002-9795-6281
Guy ParéResearch Chair in Digital Health, HEC Montreal, Montreal, QC, Canada.ORCID 0000-0001-7425-1994

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe burden of population aging and chronic conditions has been reported worldwide. Older adults, especially those with high needs, experience social isolation and have high rates of emergency visits and limited satisfaction with the care they receive. Mobile health (mHealth) technologies present opportunities to address these challenges. To date, limited information is available on Canadian older adults' attitudes toward and use of mHealth technologies for self-tracking purposes-an area that is increasingly important and relevant during the COVID-19 era.

objectiveThis study presents contributions to an underresearched area on older adults and mHealth technology use. The aim of this study was to compare older adults' use of mHealth technologies to that of the general adult population in Canada and to investigate the factors that affect their use.

methodsA cross-sectional survey on mHealth and digital self-tracking was conducted. A web-based questionnaire was administered to a national sample of 4109 Canadian residents who spoke either English or French. The survey instrument consisted of 3 sections assessing the following items: (1) demographic characteristics, health status, and comorbidities; (2) familiarity with and use of mHealth technologies (ie, mobile apps, consumer smart devices/wearables such as vital signs monitors, bathroom scales, fitness trackers, intelligent clothing); and (3) factors influencing the continued use of mHealth technologies.

resultsSignificant differences were observed between the older adults and the general adult population in the use of smart technologies and internet (P<.001). Approximately 47.4% (323/682) of the older adults in the community reported using smartphones and 49.8% (340/682) indicated using digital tablets. Only 19.6% (91/463) of the older adults using smartphones/digital tablets reported downloading mobile apps, and 12.3% (47/383) of the older adults who heard of smart devices/wearables indicated using them. The majority of the mobile apps downloaded by older adults was health-related; interestingly, their use was sustained over a longer period of time (P=.007) by the older adults compared to that by the general population. Approximately 62.7% (428/682) of the older adults reported tracking their health measures, but the majority did so manually. Older adults with one or more chronic conditions were mostly nontrackers (odds ratio 0.439 and 0.431 for traditional trackers and digital trackers, respectively). No significant differences were observed between the older adults and the general adult population with regard to satisfaction with mHealth technologies and their intention to continue using them.

conclusionsLeveraging mHealth technologies in partnership with health care providers and sharing of health/well-being data with health care professionals and family members remain very limited. A culture shift in the provision of care to older adults is deemed necessary to keep up with the development of mHealth technologies and the changing demographics and expectations of patients and their caregivers.

Indexed as

Age FactorsAdolescentAdultAgedAged, 80 and overBiomedical TechnologyCanadaCOVID-19Cross-Sectional StudiesFemaleHumansMaleMiddle AgedPatient Acceptance of Health CareSARS-CoV-2Self Careelderlymobile appsmobile healthmobile phoneolder adultsself-trackingseniorssmart devicessurveywearable technology

Identifiers

PMID33104517
PMCPMC7717921

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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.