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Record W4318344441 · doi:10.1177/09697330221134983

Moral distress and patients who forego care due to cost

2023· article· en· W4318344441 on OpenAlexaff
Linda J. Keilman, Soudabeh Jolaei, Douglas P. Olsen

Bibliographic record

VenueNursing Ethics · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsFraser Health
Fundersnot available
KeywordsContext (archaeology)CompromiseNursingDistressHealth careQualitative researchPsychologyMedicineSociologyClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: In the US, many patients forgo recommended care due to cost. The ANA Code of Ethics requires nurses to give care based on need. Therefore, US nurses are compelled to practice in a context which breaches their professional ethical code. RESEARCH OBJECTIVES: This study sought to determine if nurses do care for patients who forgo treatment due to cost (PFTDC) and if so, does this result in an experience of moral distress (MD). RESEARCH DESIGN: Semi-structured interviews were transcribed and analyzed using a qualitative content analysis. PARTICIPANTS AND RESEARCH CONTEXT: A convenience sample of 20 nurses in practice for at least one year from a variety of health care setting participated. ETHICAL CONSIDERATIONS: This project was approved by the Michigan State University Biomedical Institutional Review Board. RESULTS: There were 19 female and one male nurse-participants, averaging 47 years old with an average of 10 years in practice. 18 reported caring for PFTDC. These 17 nurse-participants experienced a moderate degree of MD as a result, averaging 5.4 of 10 on the Moral Distress Thermometer. In the interviews, the following themes were identified, strategies to help PFTDC, and the broken US health care system which had the subthemes of preference for business over patient-oriented benefit, PFTDC using the emergency department, and limited support for treatment/management of PFTDC. CONCLUSIONS: The existence of this phenomenon places the profession of nursing in the US in a position of moral compromise and threatens to corrupt the institution of nursing in the US.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.784
GPT teacher head0.633
Teacher spread0.151 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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