ArticleDigital health
Research on user's highly sensitive privacy disclosure intention in home intelligent health service system: A perspective from trust enhancement mechanism.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The aim is to investigate the determinants and mechanisms that influence user's highly sensitive privacy disclosure intention (HSPDI) in home intelligent health service system (HIHSS). Methods: This study improves the privacy calculus theory by considering the influence of service providers' trust enhancement mechanism besides benefit and risk factors and investigates their impact on users' HSPDIs. This study takes perceived valence and perceived security as the trade-off result among perceived benefits, perceived risks, financial trust enhancement mechanism, and the technical trust enhancement mechanism and suggests that perceived valence and perceived security further affect users' HSPDI in HIHSS. Moreover, the common and differential effects of the perceived justice of privacy violation compensation (PJOPVC) and the perceived effectiveness of privacy protection technologies (PEOPPTs) are studied. The structural equation model is used to analyze 204 valid samples to test the proposed model. Results: The results show that perceived benefits and perceived risks are important predictors of perceived valence and perceived security, and further affect users' HSPDI. We find PJOPVC has a greater impact on perceived valence while PEOPPT has a greater impact on perceived security. Conclusions: We recommend that the HSPDI of users with low perceived valence can be improved by providing privacy violation compensation while the HSPDI of users with low perceived security can be enhanced by popularizing relevant knowledge of privacy protection technologies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.