Evidence map›Paper›PMID 37052996›Full record

ArticleJournal of medical Internet research2023

Investigating Employees' Concerns and Wishes Regarding Digital Stress Management Interventions With Value Sensitive Design: Mixed Methods Study.

Jasmine I Kerr, Mara Naegelin, Michaela Benk, Florian V Wangenheim, Erika Meins, Eleonora Viganò, Andrea Ferrario

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
5.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Jasmine I Kerr *Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland.ORCID 0000-0001-5093-3835
Mara Naegelin *Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland.ORCID 0000-0002-0490-7510
Michaela BenkMobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland.ORCID 0000-0002-8171-320X
Florian V WangenheimChair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.ORCID 0000-0003-3964-2353
Erika MeinsMobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland.ORCID 0009-0003-4750-6228
Eleonora ViganòInstitute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-1640-2763
Andrea FerrarioMobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland.ORCID 0000-0001-9968-9474
ETH Zurich · CHUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWork stress places a heavy economic and disease burden on society. Recent technological advances include digital health interventions for helping employees prevent and manage their stress at work effectively. Although such digital solutions come with an array of ethical risks, especially if they involve biomedical big data, the incorporation of employees' values in their design and deployment has been widely overlooked.

objectiveTo bridge this gap, we used the value sensitive design (VSD) framework to identify relevant values concerning a digital stress management intervention (dSMI) at the workplace, assess how users comprehend these values, and derive specific requirements for an ethics-informed design of dSMIs. VSD is a theoretically grounded framework that front-loads ethics by accounting for values throughout the design process of a technology.

methodsWe conducted a literature search to identify relevant values of dSMIs at the workplace. To understand how potential users comprehend these values and derive design requirements, we conducted a web-based study that contained closed and open questions with employees of a Swiss company, allowing both quantitative and qualitative analyses.

resultsThe values health and well-being, privacy, autonomy, accountability, and identity were identified through our literature search. Statistical analysis of 170 responses from the web-based study revealed that the intention to use and perceived usefulness of a dSMI were moderate to high. Employees' moderate to high health and well-being concerns included worries that a dSMI would not be effective or would even amplify their stress levels. Privacy concerns were also rated on the higher end of the score range, whereas concerns regarding autonomy, accountability, and identity were rated lower. Moreover, a personalized dSMI with a monitoring system involving a machine learning-based analysis of data led to significantly higher privacy (P=.009) and accountability concerns (P=.04) than a dSMI without a monitoring system. In addition, integrability, user-friendliness, and digital independence emerged as novel values from the qualitative analysis of 85 text responses.

conclusionsAlthough most surveyed employees were willing to use a dSMI at the workplace, there were considerable health and well-being concerns with regard to effectiveness and problem perpetuation. For a minority of employees who value digital independence, a nondigital offer might be more suitable. In terms of the type of dSMI, privacy and accountability concerns must be particularly well addressed if a machine learning-based monitoring component is included. To help mitigate these concerns, we propose specific requirements to support the VSD of a dSMI at the workplace. The results of this work and our research protocol will inform future research on VSD-based interventions and further advance the integration of ethics in digital health.

Indexed as

Occupational StressWorkplaceCell PhoneDigital TechnologyHumansMachine Learningdigital health interventionemployee well-beingethicsmachine learningmobile phonemonitoringstressvalue sensitive design

Identifiers

PMID37052996
PMCPMC10141316
OpenAlexW4324011586

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.