Evidence map›Paper›PMID 37523226›Full record

ArticleJournal of medical Internet research2023

Investigating Factors Influencing Medical Practitioners' Resistance to and Adoption of Internet Hospitals in China: Mixed Methods Study.

Wenhao Deng, Tianan Yang, Jianwei Deng, Ran Liu, Xueqin Sun, Gang Li, Xinmei Wen

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

7 authors.

Wenhao Deng *School of Management and Economics, Beijing Institute of Technology, Beijing, China.ORCID 0000-0003-3316-6691
Tianan Yang *School of Management and Economics, Beijing Institute of Technology, Beijing, China.ORCID 0000-0001-6994-354X
Jianwei DengSchool of Management and Economics, Beijing Institute of Technology, Beijing, China.ORCID 0000-0001-5846-9715
Ran LiuSchool of Public Health and Management, Wenzhou Medical University, Wenzhou, China.ORCID 0009-0006-9412-8815
Xueqin SunDepartment of Medical Insurance Management, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.ORCID 0009-0002-0162-9356
Gang LiTongJi Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0003-0988-962X
Xinmei WenDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0009-0006-7260-2248

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe swift shift toward internet hospitals has relied on the willingness of medical practitioners to embrace new systems and workflows. Low engagement or acceptance by medical practitioners leads to difficulties in patient access. However, few investigations have focused on barriers and facilitators of adoption of internet hospitals from the perspective of medical practitioners.

objectiveThis study aims to identify both enabling and inhibiting predictors associated with resistance and behavioral intentions of medical practitioners to use internet hospitals by combining the conservation of resources theory with the Unified Theory of Acceptance and Use of Technology and technostress framework.

methodsA mixed methods research design was conducted to qualitatively identify the factors that enable and inhibit resistance and behavioral intention to use internet hospitals, followed by a quantitative survey-based study that empirically tested the effects of the identified factors. The qualitative phase involved conducting in-depth interviews with 16 experts in China from June to August 2022. Thematic analysis was performed using the qualitative data analysis software NVivo version 10 (QSR International). On the basis of the findings and conceptual framework gained from the qualitative interviews, a cross-sectional, anonymous, web-based survey of 593 medical practitioners in 28 provincial administrative regions of China was conducted. The data collected were analyzed using the partial least squares method, with the assistance of SPSS 27.0 (IBM Corp) and Mplus 7.0 (Muthen and Muthen), to measure and validate the proposed model.

resultsOn the basis of qualitative results, this study identified 4 facilitators and inhibitors, namely performance expectancy, social influence, work overload, and role ambiguity. Of the 593 medical practitioners surveyed in the quantitative research, most were female (n=364, 61.4%), had a middle title (n=211, 35.6%) or primary title (n=212, 35.8%), and had an average use experience of 6 months every year. By conducting structural equation modeling, we found that performance expectancy (β=-.55; P<.001) and work overload (β=.16; P=.005) had the most significant impact on resistance to change. Resistance to change fully mediated the influence of performance expectancy and partially mediated the influences of social influence (variance accounted for [VAF]=43.3%; P=.002), work overload (VAF=37.2%; P=.03), and role ambiguity (VAF=12.2%; P<.001) on behavioral intentions to use internet hospitals. In addition, this study found that the sex, age, professional title, and use experience of medical practitioners significantly moderated the aforementioned influencing mechanisms.

conclusionsThis study investigated the factors that facilitate or hinder medical practitioners' resistance to change and their behavioral intentions to use internet hospitals. The findings suggest that policy makers avoid the resistance and further promote the adoption of internet hospitals by ensuring performance expectancy and social influence and eliminating work overload and role ambiguity.

Indexed as

HospitalsPhysiciansAttitude of Health PersonnelChinaHealth Knowledge, Attitudes, PracticeHumansIntentionInternetbehavioral intention to useconservation of resource theoryinternet hospitalmedical practitionerresistance to changetechnostressUnified Theory of Acceptance and Use of Technology

Identifiers

PMID37523226
PMCPMC10425818

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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.