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Interdisciplinary Family Intervention Program

2007· article· en· W2326450360 on OpenAlexaff
Hélène Lefebvre, Diane Pelchat, Marie‐Josée Levert

Bibliographic record

VenueJournal of Trauma Nursing · 2007
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsHEC MontréalUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsIntervention (counseling)General partnershipPsychologyTraumatic brain injuryQualitative researchNursingMedicineHealth careClinical psychologyMedical educationPsychiatry

Abstract

fetched live from OpenAlex

Throughout the delivery of care after traumatic brain injury, the type of relationship that develops between the family and the professionals has a major effect on the day-by-day adjustment of traumatic brain injury individuals and their relatives. Seventeen health professionals from different disciplines working with the traumatic brain injury clientele at different stages of the continuum of trauma care underwent training in the form of e-learning to apply the Interdisciplinary Family Intervention Program, or PRIFAM. The study methodology was mixed: participants' evaluation of the PRIFAM training was assessed through a quantitative questionnaire, whereas their experience and learning were documented in semiguided, qualitative interviews conducted before and after training. The results show that the training stimulated personal and professional reflective thought in participants and fostered the forging of an interdisciplinary partnership. The training had a positive impact on communication between professionals and with the families and helped to develop a sense of self-efficacy among health professionals.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0520.004

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 head0.107
GPT teacher head0.506
Teacher spread0.399 · 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 designObservational
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

Citations30
Published2007
Admission routes1
Has abstractyes

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