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Record W7116734467 · doi:10.1186/s12912-025-04195-2

The process of nurses’ confrontation with ethical conflicts in home care: a grounded theory study

2025· article· en· W7116734467 on OpenAlexaff
Mostafa Gholami, Tahereh Najafi Ghezeljeh, Forough Rafii, Soodabeh Joolaee

Bibliographic record

VenueBMC Nursing · 2025
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsFraser Health
Fundersnot available
KeywordsGrounded theoryTheoretical samplingQualitative researchVariety (cybernetics)Process (computing)Nursing researchSnowball sampling

Abstract

fetched live from OpenAlex

BACKGROUND: Ethical conflicts (ECs) are an inseparable part of nursing care, particularly home care (HC). Nurses’ inability to effectively manage ECs may lead to occupational stress, job burnout, and low patient care quality. Despite various studies on ECs, there is limited research regarding the process of nurses’ confrontation with them in HC settings. AIM: This study aimed to explore the process of nurses’ confrontation with ECs in HC. RESEARCH DESIGN: This qualitative study was conducted from February 2023 to August 2025 using Corbin and Strauss’s approach to grounded theory. METHODS: Twenty-two unstructured and semi-structured interviews were held with sixteen nurses recruited through purposeful and theoretical sampling from HC centers in Tehran, Iran. Data were analyzed using Corbin and Strauss’s approach to grounded theory. RESULTS: The main concern of participants was fear of harming patients, and their four strategies to manage it were expedient thinking, persuading, self-justifying, and disclosing. They used these strategies to balance the interests of all parties involved in the EC situation, including patients, families, colleagues, and HC center authorities. Therefore, the core category of the theory formulated in this study was “Balancing the interests”. CONCLUSION: Nurses’ confrontation with ECs in HC is a complex process influenced by a variety of contextual factors. Study findings can be used to develop purposeful educational and supportive programs for improving nurses’ ethical decision-making.

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)0.007
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.005
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 head0.058
GPT teacher head0.526
Teacher spread0.468 · 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 designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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