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Record W3013410878 · doi:10.1080/07481187.2020.1744201

Learning from clinicians’ positive inclination to suicidal patients: A grounded theory model

2020· article· en· W3013410878 on OpenAlexaff
Tess Soulié, William Levack, Gabrielle Jenkin, Sunny Collings, Elliot Bell

Bibliographic record

VenueDeath Studies · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsEthica (Canada)Université du Québec à Montréal
FundersUniversity of Otago
KeywordsGrounded theoryInterdependenceDistressPsychologyEmotional distressPsychotherapistPatient satisfactionClinical psychologyMedicinePsychiatryQualitative researchNursingAnxiety

Abstract

fetched live from OpenAlex

Despite experts' contention that clinicians' positive inclination is essential to successful treatment of patients at risk for suicide (PRS), research in the area is lacking. This study used grounded theory to develop a model of clinicians' positive inclination based on interviews with 12 clinicians who "liked" working with PRS. The core process identified, a state of emotional synchrony through deep connection between clinicians and PRS, appeared to provide an intersubjective emotion regulation, associated with distress reduction in patients and deep satisfaction in clinicians. Findings suggest clinicians' deep sense of satisfaction and PRS' clinical improvement in treatment could be interdependent.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.016
Scholarly communication0.0070.005
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.127
GPT teacher head0.420
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2020
Admission routes1
Has abstractyes

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