Smartwatch acceptance among patients with chronic kidney disease: Development and content validation of a TAM-based questionnaire
José Javier Galán-Hernández, Ma Angeles Gómez González, Alberto Garcés-Jiménez, M. Victoria Soriano-Rodríguez, José Manuel Gómez-PulidoBackground
The acceptance of digital health technologies depends on multiple interrelated factors that should be understood before implementation. However, existing measurement instruments often lack a strong theoretical basis and a systematic development process adapted to healthcare settings. In chronic kidney disease (CKD), wearable devices such as smartwatches may support continuous monitoring and disease management.
Objective
This study aimed to develop a structured methodology for constructing Technology Acceptance Model (TAM)-based questionnaires for healthcare applications, using smartwatch acceptance among patients with CKD as a proof-of-concept case study.
Methods
A mixed methodological approach combined bibliometric analysis, expert content validation, and theoretical adaptation of the TAM framework. A total of 462 Scopus-indexed publications (2019–2024) were analyzed using VOSviewer term co-occurrence analysis. Thirty-nine high-centrality terms were refined into 35 unique factors and evaluated by nephrology healthcare professionals through individual review and structured consensus based on clinical relevance, clarity, and applicability. Expert review retained 18 factors, after which two pairs of conceptually overlapping factors were merged, resulting in 16 final factors organized into six TAM-aligned macroconstructs. Questionnaire items were then developed and linguistically reviewed.
Results
The methodology produced a concise questionnaire based on 16 clinically informed factors grouped into six TAM-aligned macroconstructs: perceived usefulness, perceived ease of use, attitude toward use, intention to use, personal factors, and trust/previous experience. The instrument was prepared for subsequent psychometric validation.
Conclusions
This study presents a structured and reproducible methodology for developing healthcare-specific TAM questionnaires. By integrating bibliometric evidence with expert content validation, it provides a methodological foundation for future psychometric evaluation and patient-based validation studies.