# Acceptance and use of digital health technologies among physiotherapists in Germany: a web-based cross-sectional survey

**Authors:** Fatma Sahan, Anja Gutermuth, Jennifer A. Müller, Thomas Muth, Karin Panitz, Jennifer Apolinário-Hagen

PMC · DOI: 10.1186/s12913-026-14005-3 · BMC Health Services Research · 2026-01-10

## TL;DR

This study explores how German physiotherapists accept and use digital health tools, finding that younger therapists and those with formal training are more likely to adopt them.

## Contribution

The study identifies key factors influencing DHT acceptance among German physiotherapists using the UTAUT model and demographic variables.

## Key findings

- Younger physiotherapists and males reported higher DHT acceptance and use of digital tools like sensors and wearables.
- Formal education in digital health and UTAUT factors like performance expectancy significantly increase DHT acceptance.
- Prior DHT users showed lower acceptance than those who had never used them.

## Abstract

Digital health technologies (DHT) have the potential to improve physiotherapy efficiency, access, and patient engagement, yet their uptake among physiotherapists remains limited. However, research into the individual determinants of DHT acceptance and professional use in physiotherapy practice remains scarce in Germany.

This study investigates the acceptance of DHT among physiotherapists in Germany, identifying key factors influencing acceptance and actual use. Individual determinants such as demographic characteristics, eHealth literacy, technology readiness, and acceptance factors based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model are considered.

A cross-sectional online survey of physiotherapists in Germany was conducted from November to December 2023. The questionnaire assessed UTAUT scales, including performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), as well as eHealth literacy, technology readiness, demographic characteristics, knowledge about DHT, and exposure to digital health in formal education. Multiple linear regression analyses were performed using R.

Data from 297 physiotherapists (M = 44.56, SD = 12.26, female = 72.23%) were analyzed. Multiple regression analyses revealed that the UTAUT scales PE, FC, and SI, as well as the additional moderator formal education in digital health, were significantly associated with higher DHT acceptance (explained variance: R² = 0.79). Older age and prior DHT use negatively influenced acceptance, while knowledge, technology readiness, and eHealth literacy showed no significant influence. Younger physiotherapists used innovative digital tools (sensors: p = .002; wearables: p = .002; web apps: p = .008) more frequently. Male physiotherapists reported higher DHT acceptance than female professionals (p = .020). Notably, physiotherapists who had never used DHT showed greater acceptance than prior users (p < .001).

Acceptance of DHT is significantly shaped by key UTAUT constructs, notably PE, SI, and FC, with PE identified as the most influential determinant. Age-related differences were evident, as younger physiotherapists reported higher levels of digital tool acceptance. Training tailored to individual needs and technical support could enhance acceptance across age groups. Future research should investigate specific barriers to integration to help develop practical strategies for incorporating DHT in physiotherapy.

## Full-text entities

- **Diseases:** MSDs (MESH:D009140), stroke (MESH:D020521), cardiopulmonary diseases (MESH:D006323), movement disorders (MESH:D009069), Nervous system (MESH:D009422), chronic pain (MESH:D059350), MSD (MESH:D052517), impaired movement and physical function (MESH:D003291), shoulder lesions (MESH:D020069), Back pain (MESH:D001416), pain (MESH:D010146), knee disorders (MESH:D007718), multiple sclerosis (MESH:D009103)
- **Chemicals:** DHT (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12849112/full.md

## References

25 references — full list in the complete paper: https://tomesphere.com/paper/PMC12849112/full.md

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Source: https://tomesphere.com/paper/PMC12849112