ArticleProceedings of the ACM on human-computer interaction2022
Burnout and the Quantified Workplace: Tensions around Personal Sensing Interventions for Stress in Resident Physicians.
Article in Proceedings of the ACM on human-computer interaction, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 55 citations in OpenAlex.
- Offline Reinforcement Learning for Adaptive Support in AI-Assisted Decision-Making.ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery · 2026Article
- Predicting Emotional Exhaustion with Multimodal Sensor Data During Return-to-Work Trajectories: A 6-Month Longitudinal Study.Journal of occupational rehabilitation · 2026Article
- Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2024Article
- Understanding Mental Health Clinicians' Perceptions and Concerns Regarding Using Passive Patient-Generated Health Data for Clinical Decision-Making: Qualitative Semistructured Interview Study.JMIR formative research · 2023Article
- "All Day, Every Day, Listening to Trauma": Investigating Features of Digital Interventions for Empathy-Based Stress and Burnout.Proceedings of the SIGCHI conference on human factors in computing systems. CHI ConferenceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
Recent research has explored computational tools to manage workplace stress via personal sensing, a measurement paradigm in which behavioral data streams are collected from technologies including smartphones, wearables, and personal computers. As these tools develop, they invite inquiry into how they can be appropriately implemented towards improving workers' well-being. In this study, we explored this proposition through formative interviews followed by a design provocation centered around measuring burnout in a U.S. resident physician program. Residents and their supervising attending physicians were presented with medium-fidelity mockups of a dashboard providing behavioral data on residents' sleep, activity and time working; self-reported data on residents' levels of burnout; and a free text box where residents could further contextualize their well-being. Our findings uncover tensions around how best to measure workplace well-being, who within a workplace is accountable for worker stress, and how the introduction of such tools remakes the boundaries of appropriate information flows between worker and workplace. We conclude by charting future work confronting these tensions, to ensure personal sensing is leveraged to truly improve worker well-being.
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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.