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Record W4387048652 · doi:10.2196/47586

The Ethical, Care, and Client-Caregiver Relationship Impacts Resulting From Introduction of Digital Communication and Surveillance Technologies in the Home Setting: Qualitative Inductive Study

2023· article· en· W4387048652 on OpenAlexvenueno aff
Hans‐Peter de Ruiter, David Clisbee, Rebecca Houston, Ingela Skärsäter

Bibliographic record

VenueJMIR Human Factors · 2023
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchPsychologyInternet privacyBusinessSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Embedding communication and surveillance technology into the home health care setting has demonstrated the capacity for increased data efficiency, assumptions of convenience, and smart solutions to pressing problems such as caregiver shortages amid a rise in the aging population. The race to develop and implement these technologies within home care and public health nursing often leaves several ethical questions needing to be answered. OBJECTIVE: The aim of this study was to understand the ethical and care implications of implementing digital communication and surveillance technologies in the home setting as perceived by health caregivers practicing in the region of Halland in Sweden with clients receiving home care services. METHODS: A questionnaire was completed by 1260 home health caregivers and the written responses were evaluated by qualitative inductive content analysis. The researchers reviewed data independently and consensus was used to determine themes. RESULTS: This study identified three main themes that illustrate ethical issues and unintended effects as perceived by caregivers of introducing digital communication and surveillance technologies in the home: (1) digital dependence vulnerability, (2) moral distress, and (3) interruptions to caregiving. This study highlights the consequences of technology developers and health systems leaders unintentionally ignoring the perspectives of caregivers who practice the intuitive artistry of providing care to other humans. CONCLUSIONS: Beyond the obtrusiveness of devices and impersonal data collection designed to emphasize health care system priorities, this study discovered a multifaceted shadow side of unintended consequences that arise from misalignment between system priorities and caregiver expertise, resulting in ethical issues. To develop communication and surveillance technologies that meet the needs of all stakeholders, it is important to involve caregivers who work with clients in the development process of new health care technology to improve both the quality of life of clients and the services offered by caregivers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.403
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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