Are nursing home employees ready for the technical evolution? German-wide survey on the status quo of affinity for technology and technology interaction

Author:

Barisch-Fritz Bettina1ORCID,Krafft Jelena1,Rayling Sabine1,Diener Jonathan1,Möller Tobias1,Wunsch Kathrin1,Riedel Norman2,Maia Maria3ORCID,Weinberger Nora3,Lefint Jérémy3,Asfour Tamim4,Krell-Rösch Janina1,Woll Alexander1

Affiliation:

1. Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany

2. Institute of Ergonomics & Business Organization, Karlsruhe Institute of Technology, Karlsruhe, Germany

3. Institute of Technology Assessment and Systems Analysis, Karlsruhe Institute of Technology, Karlsruhe, Germany

4. Institut for Anthropomatics and Robotics – High Performance Humanoid Technologies, Karlsruhe Institute of Technology, Karlsruhe, Germany

Abstract

Background Technological devices can support nursing home employees; however, their perspective is not sufficiently studied. Our aims were thus to (a) examine affinity for technology and technology interaction and related sociodemographic confounders, as well as (b) detect possible requirements and boundary conditions relevant for the development and implementation of assistive technologies among nursing home employees. Methods We conducted an online survey between May and July of 2022 among 200 nursing home employees in Germany. The survey included two questionnaires, that is, Affinity for Technology Interaction (ATI) and Affinity for Technology—Electronic Devices (TA-EG; subscales TA-EG-Enthusiasm, TA-EG-Competence, TA-EG-Positive Consequences, and TA-EG-Negative Consequences), as well as sociodemographic variables, that is, age, gender, professional groups, education/graduation level. We carried out factorial variance and multiple regression analyses. Results There were differences between age groups in ATI (lower score with increasing age) and between gender, age, and professional group in TA-EG (lower score for females, participants with higher ages, and nursing home managers). Predictors of ATI were age and professional group, predictors of TA-EG, TA-EG-Enthusiasm, and TA-EG-Competence were gender, age, and professional group. Predictors of TA-EG-Positive Consequences were education and professional group. Conclusions We observed rather high affinity for technology and technology interaction values overall, and particularly for nursing home employees compared to managers. Significant predictors for technology affinity and interaction may have important implications, for example the perspectives of nursing home employees and managers should be considered separately in the technological design, development, and implementation process. Furthermore, an open dialogue between all stakeholders should be encouraged to increase the probability of actual technology use.

Funder

Carl-Zeiss-Stiftung

Publisher

SAGE Publications

Subject

Health Information Management,Computer Science Applications,Health Informatics,Health Policy

Reference42 articles.

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