Evidence map›Paper›PMID 39324148›Full record

ArticleBiomedical engineering and computational biology2024

Conceptualizing Patient as an Organization With the Adoption of Digital Health.

Atantra Das Gupta

Abstract read
In one paragraph

Article in Biomedical engineering and computational biology, 2024. 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
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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

1 author.

Atantra Das GuptaMarketing Research, Management Development Institute Gurgaon, Gurgaon, Haryana, India.ORCID https://orcid.org/0000-0002-0593-2582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The concept of viewing a patient as an organization within the context of digital healthcare is an innovative and evolving concept. Traditionally, the patient-doctor relationship has been centered around the individual patient and their interactions with healthcare providers. However, with the advent of technology and digital healthcare solutions, the dynamics of this relationship are changing. Digital healthcare platforms and technologies enable patients to have more control and active participation in managing their health and healthcare processes. This shift empowers patients to take on a more proactive role, similar to how an organization functions with various stakeholders, goals, and strategies. The prevalence of mobile phones and wearables is regarded as an important factor in the acceptance of digital health. Objective: This study aimed to identify the factors affecting adoption intention using the TAM (Technology Acceptance Model), HB (Health Belief model), and the UTAUT (Unified Theory of Acceptance and Use of Technology). The argument is made that the adoption of the technology enables patients to create resources (ie, data), transforming patients from mere consumers to producers as well. Results: PLS analysis showed that health beliefs and perceived ease of use had positive effects on the perceived usefulness of digital healthcare, and system capabilities positively impacted perceived ease of use. Furthermore, perceived service, the customer's willingness to change and reference group influence significantly impacted adoption intention ( Conclusions: Perceived usefulness, the customer's willingness to change, and the influence of the reference group are decisive variables affecting adoption intention among the general population, whereas privacy protection and data security are indecisive variables. Online resources and user guides do not support adoption intentions.

Indexed as

conceptdigital healthcarePatient

Identifiers

PMID39324148
PMCPMC11423387

What OpenQuestion holds

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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.