Evidence map›Paper›PMID 35986284›Full record

ArticleBMC medical informatics and decision making2022

Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.

Huixian Zha, Kouying Liu, Ting Tang, Yue-Heng Yin, Bei Dou, Ling Jiang, Hongyun Yan, Xingyue Tian, Rong Wang, Weiping Xie

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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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

10 authors at 4 institutions in 1 country.

Huixian ZhaSchool of Nursing, Nanjing Medical University, Nanjing, 210000, People's Republic of China.
Kouying LiuSchool of Nursing, Nanjing Medical University, Nanjing, 210000, People's Republic of China. liuky188@126.com.
Ting TangThe First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China.
Yue-Heng YinSchool of Nursing, Nanjing Medical University, Nanjing, 210000, People's Republic of China.
Bei DouDepartment of Nursing, The Second Affiliated Hospital of Suzhou University, Suzhou, Jiangsu, 215000, People's Republic of China.
Ling JiangDepartment of Nursing, Suzhou Municipal Hospital, Suzhou, Jiangsu, 215008, People's Republic of China.
Hongyun YanDepartment of Nursing, Suzhou Municipal Hospital, Suzhou, Jiangsu, 215008, People's Republic of China.
Xingyue TianDepartment of Nursing, Suzhou Municipal Hospital, Suzhou, Jiangsu, 215008, People's Republic of China.
Rong WangSchool of Nursing, Nanjing Medical University, Nanjing, 210000, People's Republic of China.
Weiping XieThe First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China.
Nanjing Medical University · CNSuzhou Municipal Hospital · CNJiangsu Province Hospital · CNSecond Affiliated Hospital of Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVenous thromboembolism has been a major public health problem and caused a heavy disease burden. Venous thromboembolism clinical decision support system was proved to have a positive influence on the prevention and management of venous thromboembolism. As the direct users, nurses' acceptance of this system is of great importance to support the successful implementation of it. However, there are few relevant studies to investigate nurses' acceptance and the associated factors are still unclear.

objectiveTo investigate the determinant factors of nurses' acceptance of venous thromboembolism clinical decision support system with the modified Unified Theory of Acceptance and Use of Technology.

methodsWe designed a questionnaire based on the modified Unified Theory of Acceptance and Use of Technology and then a cross-sectional survey was conducted among nurses in a tertiary hospital in Nanjing, China. Statistically, a Structural Equation Modeling -Partial Least Squares path modeling approach was applied to examine the research model.

resultsA total of 1100 valid questionnaires were recycled. The modified model explained 74.7%, 83.0% and 86% of the variance in user satisfaction, behavioral intention and user behavior, respectively. The results showed that performance expectancy (β = 0.254, p = 0.000), social influence (β = 0.136, p = 0.047), facilitating conditions (β = 0.245, p = 0.000), self-efficacy (β = 0.121, p = 0.048) and user satisfaction (β = 0.193, p = 0.001) all had significant effects on nurses' intention. Although effort expectancy (β = 0.010, p = 0.785) did not have a direct effect on nurses' intention, it could indirectly influence nurses' intention with user satisfaction as the mediator (β = 0.296, p = 0.000). User behavior was significantly predicted by facilitating conditions (β = 0.298, p = 0.000) and user intention (β = 0.654, p = 0.001).

conclusionThe research enhances our understanding of the determinants of nurses' acceptance of venous thromboembolism clinical decision support system. Among these factors, performance expectancy was considered as the top priority. It highlights the importance of optimizing system performance to fit the users' needs. Generally, the findings in our research provide clinical technology designers and administrators with valuable information to better meet users' requirements and promote the implementation of venous thromboembolism clinical decision support system.

Indexed as

Decision Support Systems, ClinicalVenous ThromboembolismCross-Sectional StudiesHumansIntentionSurveys and QuestionnairesAcceptanceClinical decision support systemNursesVenous thromboembolism

Identifiers

PMID35986284
PMCPMC9392358
OpenAlexW4292677421

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.