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Record W2049730323 · doi:10.1002/eat.22033

Preferred therapist characteristics in treatment of anorexia nervosa: The patient's perspective

2012· article· en· W2049730323 on OpenAlexaff
Kjersti S. Gulliksen, Ester M. S. Espeset, Ragnfrid H. S. Nordbø, Finn Skårderud, Josie Geller, Arne Holte

Bibliographic record

VenueInternational Journal of Eating Disorders · 2012
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsAnorexia nervosaPsychologyPerspective (graphical)VitalityPsychotherapistAllianceEating disordersClinical psychologySet (abstract data type)PopulationBulimia nervosaMedicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Previous research in eating disorders suggests that treatment satisfaction is closely related to the manner in which care is delivered. The present research is a systematic in depth study of health professional characteristics preferred by AN-patients. METHOD: Thirty-eight women with AN aged 18-51 were interviewed in depth using a phenomenological study design. Interviews were tape-recorded, transcribed, and analyzed using the QSR-NVivo7 software program. RESULTS: Four factors associated with patients' satisfaction with their therapists were identified: "acceptance," "vitality," "challenge," and "expertise." Patients' responses suggested that treatment of AN requires therapists who are capable of using a complex set of behaviors when interacting with their patients. DISCUSSION: There is accumulating evidence that across treatment modality, the manner in which treatment is delivered is critical to therapeutic change. Our findings increase the understanding of factors that may be associated with treatment retention, further help seeking, and overall treatment outcome. These exploratory and informant-centered results could guide clinicians in developing a strong therapeutic alliance with AN-patients and promote increased knowledge about the mechanisms that engage this population.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.024
GPT teacher head0.338
Teacher spread0.314 · 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 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

Citations82
Published2012
Admission routes1
Has abstractyes

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