Measuring post-adoption user evaluations in wearable fitness technology: evidence from Fitbit reviews and surveys

Wearable fitness technology has transformed consumer engagement with health monitoring, yet factors influencing user satisfaction and dissatisfaction remain underexplored. This study employed a mixed-methods approach, which integrated text mining of 50,000 Fitbit user reviews with survey-based psychometric validation. Text analysis techniques, including sentiment analysis, topic modelling, co-occurrence networks, and word embeddings, identified key satisfiers (e.g. tracking accuracy, motivation) and dissatisfiers (e.g. syncing issues, software malfunctions). A structured questionnaire was developed and administered to 683 Fitbit users, with exploratory and confirmatory factor analyses ensuring measurement validity. The empirical findings contribute to wearable technology research by offering a validated, empirically grounded scale for assessing consumer experience. This study provides actionable insights for improving wearable device functionality and enhancing user retention through data-driven design and customer service improvements.