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Background <p>Telerehabilitation is considered a promising way to address the gap between supply and demand for rehabilitation services. To sure that telerehabilitation will be widely applied in clinical, a comprehensive and thorough understanding of the extent of usage intention for telerehabilitation is needed. This study aimed to identify the use intention and the barriers and facilitators factors to telerehabilitation utilization among people with rehabilitation needs.</p> Methods <p>This study is a cross-sectional study. A structured survey questionnaire on the usage intention of telerehabilitation was designed by the research team based on the extended UTAUT theoretical model. This survey recruited a total of 386 participants with rehabilitation needs from May 2022 to July 2023. The partial least squares structural equation model (PLS-SEM) to analyze the data and test the research hypotheses to determine the factors that influence the public’s intention to use telerehabilitation.</p> Results <p>A total of 327 valid questionnaires were collected. The model of this study explained 62.0% of the variance in behavioral intention, 39.1% of the variance of perceived trust, and 36.7% of the variance of performance expectations. The results of the structural model analysis indicated that performance expectancy (β = 0.220, <i>P</i> &lt; 0.001), social influence (β = 0.108, <i>P</i> = 0.011), perceived trust (β = 0.265, <i>P</i> &lt; 0.001) and self-efficacy (β = 0.185, <i>P</i> = 0.009) had significant effects on behavioral intention to use telerehabilitation; performance expectancy (β = 0.402, <i>P</i> &lt; 0.001) and effort expectancy (β = 0.208, <i>P</i> = 0.010) had a significant effect on perceived trust; self-efficacy had a significant effect on performance expectancy (β = 0.608, <i>P</i> &lt; 0.001); performance expectancy and effort expectancy had indirect effect on behavioral intention with perceived trust as the mediator, and self-efficacy also had significant indirect influences with performance expectancy as the mediator.</p> Conclusions <p>This study applied an extended UTAUT model to investigated the intention of and influencing factors for using telerehabilitation service among individuals with rehabilitation needs. The results indicate that performance expectancy, social influence, perceived trust and self-efficacy are important factors influencing the use intention of telerehabilitation in individuals with rehabilitation needs.</p>

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Determining the adoption intention and influencing factors of telerehabilitation by people with rehabilitation needs: a cross-sectional survey

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月22日

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  • Hong Chen,
  • Shi Chen,
  • Yang Zhou,
  • Mao-Yuan Wang,
  • Yong-Qiang Wu,
  • Chun-Mei Wu

摘要

Background

Telerehabilitation is considered a promising way to address the gap between supply and demand for rehabilitation services. To sure that telerehabilitation will be widely applied in clinical, a comprehensive and thorough understanding of the extent of usage intention for telerehabilitation is needed. This study aimed to identify the use intention and the barriers and facilitators factors to telerehabilitation utilization among people with rehabilitation needs.

Methods

This study is a cross-sectional study. A structured survey questionnaire on the usage intention of telerehabilitation was designed by the research team based on the extended UTAUT theoretical model. This survey recruited a total of 386 participants with rehabilitation needs from May 2022 to July 2023. The partial least squares structural equation model (PLS-SEM) to analyze the data and test the research hypotheses to determine the factors that influence the public’s intention to use telerehabilitation.

Results

A total of 327 valid questionnaires were collected. The model of this study explained 62.0% of the variance in behavioral intention, 39.1% of the variance of perceived trust, and 36.7% of the variance of performance expectations. The results of the structural model analysis indicated that performance expectancy (β = 0.220, P < 0.001), social influence (β = 0.108, P = 0.011), perceived trust (β = 0.265, P < 0.001) and self-efficacy (β = 0.185, P = 0.009) had significant effects on behavioral intention to use telerehabilitation; performance expectancy (β = 0.402, P < 0.001) and effort expectancy (β = 0.208, P = 0.010) had a significant effect on perceived trust; self-efficacy had a significant effect on performance expectancy (β = 0.608, P < 0.001); performance expectancy and effort expectancy had indirect effect on behavioral intention with perceived trust as the mediator, and self-efficacy also had significant indirect influences with performance expectancy as the mediator.

Conclusions

This study applied an extended UTAUT model to investigated the intention of and influencing factors for using telerehabilitation service among individuals with rehabilitation needs. The results indicate that performance expectancy, social influence, perceived trust and self-efficacy are important factors influencing the use intention of telerehabilitation in individuals with rehabilitation needs.