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Record W2023078462 · doi:10.1002/erv.937

Caring for a sibling with anorexia nervosa: A qualitative study

2009· article· en· W2023078462 on OpenAlexaff
Gina Dimitropoulos, Kristina Klopfer, Lorena Lazar, Reva Schacter

Bibliographic record

VenueEuropean Eating Disorders Review · 2009
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsAnorexia nervosaSiblingEating disordersPsychologyQualitative researchAnorexiaPsychiatryClinical psychologyPsychotherapistDevelopmental psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Few studies have explored eating disorders from the perspective of non-affected siblings. The aim of this investigation was to explore the unique experiences and challenges of siblings of women with anorexia nervosa (AN). METHOD: Twelve semi-structured qualitative interviews were conducted with sibling participants to ascertain their perspective of caring for a sister with chronic AN. RESULTS: Qualitative analyses gleaned six themes: (1) the sibling role as protector and mediator; (2) familial factors that influence and reinforce these sibling roles; (3) consequences and benefits of AN to non-affected sibling; (4) coping strategies; (5) current and future intentions of caregiving and (6) professional and informal support. DISCUSSION: The findings from this qualitative study provide a window into the perceptions, feelings, and roles of siblings of women afflicted with AN. An intervention guided by the elicited themes may facilitate family functioning that is more adaptive for both siblings.

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)0.008
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0010.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.398
Teacher spread0.344 · 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

Citations61
Published2009
Admission routes1
Has abstractyes

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