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Hope and interpersonal psychiatric/mental health nursing: a systematic review of the literature – part one

2007· review· en· W2149233567 on OpenAlexaff
Corinne V. Koehn, John R. Cutcliffe

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2007
Typereview
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsMental healthContext (archaeology)Interpersonal communicationPsychologyAcknowledgementThematic analysisNursingSystematic reviewPsychiatryPsychotherapistMedicineQualitative researchMEDLINESocial psychologySociologySocial science

Abstract

fetched live from OpenAlex

Psychiatric/mental health (P/MH) nursing is inherently an interpersonal endeavour; one that includes a broad range of 'helping activities'. The interpersonal activities and skills are enshrined in our underpinning philosophy, explored and learned in our curricula (all around the world) and enacted in our everyday clinical practice. Within this interpersonal context and framework, it is heartening to see that understated, abstract and yet-lasting concepts such as hope are gaining more acknowledgement, recognition and subsequently attention. While it is recognized that hope in mental health care is increasingly becoming the focal point of disciplined inquiry, the authors believe it is perhaps necessary and timely to re-examine these two concepts, namely: interpersonal P/MH nursing and hope/inspiring hope in people with mental health problems. Accordingly, this two-part article reports on a systematic review of the literature that focuses on hope (inspiring hope) within interpersonal (counselling) focused P/MH nursing. Part one focuses on the method used and the results, indicating that a total of 57 articles were included in the review: 39 were categorized as empirical studies involving either a quantitative or qualitative methodological design, and 18 were considered theoretical/clinical/review articles. Though not a product of an empirical investigation per se, it was clear that many of the articles shared and covered common ground. Thus, these were arranged into six 'loose' thematic groupings. The first three of these areas, schizophrenia, suicidality and depression form the remainder of part one of this article, and the remaining areas are included in part two.

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)0.012
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0230.023
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.403
Teacher spread0.373 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations45
Published2007
Admission routes1
Has abstractyes

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