Evidence map›Paper›PMID 39291159›Full record

ArticleDigital health

Strengthening health monitoring: Intention and adoption of Internet of Things-enabled wearable healthcare devices.

Qing Yang, Abdullah Al Mamun, Mengling Wu, Farzana Naznen

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

4 authors.

Qing YangUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Selangor Darul Ehsan, Malaysia.
Abdullah Al MamunUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Selangor Darul Ehsan, Malaysia.ORCID https://orcid.org/0000-0002-9713-742X
Mengling WuUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, Selangor Darul Ehsan, Malaysia.
Farzana NaznenUCSI Graduate Business School, UCSI University, Kuala Lumpur, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Health self-monitoring technologies are gaining popularity worldwide, but they face low adoption rates in emerging countries. There is a deficiency in studies that have applied the value-belief-norm (VBN) model to understand the adoption of IoT-enabled wearable healthcare devices (WHDs). This study investigates the adoption of IoT-enabled WHDs among older adults in China, using the VBN model as a theoretical framework. Methods: Using a convenience sampling method and a web-based cross-sectional survey method, we collected data from 476 respondents, which we analyzed using partial least squares structural equation modeling using Smart PLS version 3.3.5. Results: The findings highlight the significance of health values and motivation in shaping personal health beliefs, which, in turn, influence personal norms and awareness of consequences. Particularly, awareness of consequences and attributions of responsibility significantly impact personal norms. Personal and social norms, in turn, strongly affect the intention to adopt IoT-enabled WHDs, ultimately driving their actual adoption. Conclusion: This research contributes novel insights into the behavioral dynamics surrounding the adoption of IoT-enabled WHDs, providing valuable guidance for marketers and policymakers. Marketers can leverage these insights to develop tailored marketing strategies within the IoT-enabled WHD industry. Additionally, policymakers are urged to prioritize campaigns aimed at enhancing awareness and understanding of self-healthcare monitoring, with a focus on promoting the unique health benefits of IoT-enabled WHDs.

Indexed as

health motivationhealth valuesIoT-enabled WHDsperceived product valuepersonal health beliefssenior adultsVBN model

Identifiers

PMID39291159
PMCPMC11406608

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.