ArticleFrontiers in digital health2023
Acceptance of smart sensing: a barrier to implementation-results from a randomized controlled trial.
Article in Frontiers in digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Digital Therapeutics and Blended Care in Major Depressive Disorder: Current Evidence and Future Directions.Advances in experimental medicine and biology · 2026Review
- The relation between passively collected data and PTSD: a systematic review and meta-analysis.NPJ digital medicine · 2025Article
- Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study.Journal of medical Internet research · 2025Observational
- The predictive value of supervised machine learning models for insomnia symptoms through smartphone usage behavior.Sleep medicine: X · 2024Article
- Enhancing the acceptance of smart sensing in psychotherapy patients: findings from a randomized controlled trial.Frontiers in digital health · 2024Article
- Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial.Frontiers in digital health · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accurate and timely diagnostics are essential for effective mental healthcare. Given a resource- and time-limited mental healthcare system, novel digital and scalable diagnostic approaches such as smart sensing, which utilizes digital markers collected via sensors from digital devices, are explored. While the predictive accuracy of smart sensing is promising, its acceptance remains unclear. Based on the unified theory of acceptance and use of technology, the present study investigated (1) the effectiveness of an acceptance facilitating intervention (AFI), (2) the determinants of acceptance, and (3) the acceptance of adults toward smart sensing. Methods: The participants ( Results: The intervention did not affect the acceptance ( Discussion: The present AFI was not effective. The low to moderate acceptance of smart sensing poses a major barrier to its implementation. The performance expectancy, social influence, and trust should be targeted as the core factors of acceptance. Further studies are needed to identify effective ways to foster the acceptance of smart sensing and to develop successful implementation strategies. Clinical Trial Registration: identifier 10.17605/OSF.IO/GJTPH.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.