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Record W2170212886 · doi:10.1177/1049732307306921

Learning to Care for Spiritual Needs: Connecting Spiritually

2007· article· en· W2170212886 on OpenAlexaff
L. Elizabeth Hood, Joanne Olson, Marion Allen

Bibliographic record

VenueQualitative Health Research · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of AlbertaAlberta Hospital Edmonton
Fundersnot available
KeywordsSpiritualityGrounded theoryPsychologyExperiential learningSpiritual careExperiential knowledgeConfusionProcess (computing)NursingSocial psychologyQualitative researchPedagogySociologyMedicineEpistemologyPsychoanalysis

Abstract

fetched live from OpenAlex

Despite mandates to provide spiritual care, confusion persists among nurses about spirituality, spiritual needs, and related roles. To discover how practicing nurses acquire knowledge for spiritual care, the authors chose a grounded theory design. They constantly compared and analyzed verbatim transcribed interview data to find the core variable, categories, and properties. Connection, manifesting as a state, act, or process, appeared throughout the data. Categories emerged as Needing Connection, Nurturing Connection, Learning Connection, and Living Connection. Nurses used a cyclical, intertwined, and progressive learning process of opening to, struggling with, and making connections between numerous discrete personal and professional experiences. Shifting attention between these interconnected experiences fueled knowledge acquisition. Whether referring to how nurses learn, what they do, or with whom, the theory Connecting Spiritually joined categories into a cumulative experiential learning process that explained how nurses learn to care for spiritual needs.

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)0.058
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.367
GPT teacher head0.620
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2007
Admission routes1
Has abstractyes

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