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Narrative Methods and Children: Theoretical Explanations and Practice Issues

2008· review· en· W2148357031 on OpenAlexaff
Lorna Bennett

Bibliographic record

VenueJournal of Child and Adolescent Psychiatric Nursing · 2008
Typereview
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNarrativePsychologyMental healthPsychotherapist

Abstract

fetched live from OpenAlex

TOPIC: The Narrative approach is an innovative way of working with children and adolescents experiencing mental health problems. This approach can be effectively integrated with the expressive arts and other nonverbal ways of accessing the life world of children. In addition, the approach promotes respect for and collaboration with the child in working towards healing and growth. PURPOSE: In this paper core features of the narrative approach are described; the theoretical and philosophical and evidence base for this approach as well as its congruence with the special nature and needs of children will be explored. Finally, the benefits and challenges of this approach in relation to a specific clinical situation will be highlighted. SOURCES USED: Published literature and the author's clinical experiences. CONCLUSION: Narrative methods are ideally suited for addressing needs of children experiencing mental health problems and can enhance therapeutic effectiveness. Some of the challenges associated with its use include: finding creative ways to apply specific narrative concepts and methods with diverse clinical issues/problems; learning to collaborate with children and respect them as experts in their own lives; and shifting the nursing focus from a problem-focused orientation to a strength-oriented and child-centered approach.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.431
Teacher spread0.405 · 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 designOther design
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

Citations40
Published2008
Admission routes1
Has abstractyes

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