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Record W3092018420 · doi:10.1097/rnj.0000000000000293

The Road to Family Resiliency: A Case Report of a Family’s Experiences Following Adolescent Stroke

2020· article· en· W3092018420 on OpenAlexaff
Zara Szigeti, Emily Nalder, Gillian King, Julie Farthing, Jérôme Gauvin‐Lepage

Bibliographic record

VenueRehabilitation Nursing · 2020
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalHolland Bloorview Kids Rehabilitation HospitalHEC MontréalToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsThematic analysisPsychologyIntervention (counseling)Qualitative researchNarrativePerceptionClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: This study generated an understanding of familial resiliency following an adolescent's stroke and what resiliency-related outcomes were important to this family. DESIGN AND METHODS: A qualitative case study design was used to collect data during an in-person interview. The interview was transcribed verbatim and analyzed using thematic analysis. FINDINGS: Participants' narratives revealed that reengaging and establishing new activities, reconstructing identities, and changing perceptions regarding health and life itself were important resiliency-related outcomes. CONCLUSIONS: The findings from this case study highlight innovative strategies that can be used to facilitate resiliency during strenuous times in a family's life, such as following an adolescent's stroke. CLINICAL RELEVANCE: Clinicians and service providers have the opportunity to help facilitate resiliency by identifying which protective factors and positive outcomes are most important to a family following an adolescent's stroke, allowing clinicians to assist in achieving these outcomes. This research illustrates ways for families to convert resources into personally meaningful resiliency-related outcomes. Further research is needed to study familial resiliency as a part of an intervention to promote occupational engagement.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.409
Teacher spread0.372 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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