ArticleJMIR formative research2022
Shared Autonomy to Reduce Sedentary Behavior Among Sit-Stand Desk Users in the United States and India: Web-Based Study.
Article in JMIR formative research, 2022. 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, 5 citations in OpenAlex.
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
6 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundFitness technologies such as wearables and sit-stand desks are increasingly being used to fight sedentary lifestyles by encouraging physical activity. However, adherence to such technologies decreases over time because of apathy and increased dismissal of behavioral nudges.
objectiveTo address this problem, we introduced shared autonomy in the context of sit-stand desks, where user input is integrated with robot autonomy to control the desk and reduce sedentary behavior and investigated user reactions and preferences for levels of automation with a sit-stand desk. As demographics affect user acceptance of robotic technology, we also studied how perceptions of nonvolitional behavior change differ across cultures (United States and India), sex, familiarity, dispositional factors, and health priming messages.
methodsWe conducted a web-based vignette study in the United States and India where a total of 279 participants watched video vignettes of a person interacting with sit-stand desks of various levels of automation and answered questions about their perceptions of the desks such as ranking of the different levels of automation.
resultsParticipants generally preferred either manual or semiautonomous desks over the fully autonomous option (P<.001). However, participants in India were generally more amenable to the idea of nonvolitional interventions from the desk than participants in the United States (P<.001). Male participants had a stronger desire for having control over the desk than female participants (P=.01). Participants who were more familiar with sit-stand desks were more likely to adopt autonomous sit-stand desks (P=.001). No effects of health priming messages were observed. We estimated the projected health outcome by combining ranking data and hazard ratios from previous work and found that the semiautonomous desk led to the highest projected health outcome.
conclusionsThese results suggest that the shared autonomy desk is the optimal level of automation in terms of both user preferences and estimated projected health outcomes. Demographics such as culture and sex had significant effects on how receptive users were to autonomous intervention. As familiarity improves the likelihood of adoption, we propose a gradual behavior change intervention to increase acceptance and adherence, especially for populations with a high desire for control.
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.