Evidence map›Paper›PMID 32449688›Full record

ArticleJMIR mHealth and uHealth2020

Understanding and Preventing Health Concerns About Emerging Mobile Health Technologies.

Frank T Materia, Kate Faasse, Joshua M Smyth

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 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
6.5field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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  10. Health Communication in COVID-19 Era: Experiences from the Italian VaccinarSì Network Websites.International journal of environmental research and public health · 2021
    Article
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  12. Review
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

3 authors at 2 institutions in 2 countries.

Frank T MateriaThe Pennsylvania State University, University Park, PA, United States.ORCID 0000-0002-8015-1743
Kate FaasseUniversity of New South Wales, Sydney, Australia.ORCID 0000-0003-3073-3718
Joshua M SmythThe Pennsylvania State University, University Park, PA, United States.ORCID 0000-0002-0904-5390
Pennsylvania State University · USUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New technologies and innovations have often improved population well-being and societal function; however, these are also often initially accompanied by worry and fear. In some cases, such worries can impede, or even prevent entirely, the adoption of the technology. Mobile health (mHealth), a discipline broadly focused on employing ambulatory technologies to improve the affordability, reach, and effectiveness of health promotion and clinical intervention approaches, offers new innovations and opportunities. Despite emerging evidence supporting mHealth efficacy (eg, for improving health outcomes), some individuals have concerns about mHealth technology that may impede scalability, efficacy, and, ultimately, the public health benefits of mHealth. We present a review and conceptual framework to examine these issues, focusing on three overarching themes: biophysiological, psychological, and societal concerns. There are features of mHealth that lead to worries about the potential negative effects on an individual's health (eg, due to exposure to electromagnetic or radio waves), despite evidence supporting the safety of these technologies. When present, such beliefs can lead to worry that gives rise to the experience of unpleasant and concerning physical symptoms-the nocebo effect. This may represent an important implementational barrier because of apprehension toward beneficial mHealth products (or features thereof, such as wireless charging, wearable or implantable sensors, etc) and may also have broader ramifications (eg, leading to economic, governmental, and legislative actions). In addition to reviewing evidence on these points, we provide a broad three-step model of implementation research in mHealth that focuses on understanding and preventing health concerns to facilitate the safe and effective scalability of mHealth (and that may be generalizable and applied to similar technologies): (1) evaluating and better discerning public perceptions and misperceptions (and how these may differ between populations), (2) developing theory-based public health communication strategies regarding the safety of mHealth, and (3) disseminating this messaging using evidence-based methods. Collectively, these steps converge on reviewing evidence regarding the potential role of worry and nocebo in mHealth and providing a model for understanding and changing attitudes and preventing unfounded negative perceptions related to mHealth technology.

Indexed as

TelemedicineAmbulatory Care FacilitiesBiomedical TechnologyHealth PromotionHumansimplementation sciencemedically unexplained symptomsmHealthnocebo effecttechnology

Identifiers

PMID32449688
PMCPMC7281144
OpenAlexW3005992664

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.