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Record W3115012913 · doi:10.1177/1049732320978202

Achieving Recovery Through Resilience: Insights From Adults in Midlife Living With Anorexia Nervosa

2020· article· en· W3115012913 on OpenAlexaff
Leslie McCallum, Ramona Alaggia

Bibliographic record

VenueQualitative Health Research · 2020
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConstructivist grounded theoryPsychologyPsychological resilienceAnorexia nervosaNarrativeContext (archaeology)Grounded theoryLife course approachYoung adultAdult developmentDevelopmental psychologyPsychotherapistQualitative researchGerontologyClinical psychologyEating disordersMedicineSociology

Abstract

fetched live from OpenAlex

Despite the high percentage of adults living with anorexia nervosa (AN) over the life course, there is limited understanding of what it means to be living with AN in midlife when the majority of research has focused on adolescents and young adults. As such, clinical practice for individuals in midlife is informed by a severe and enduring AN (SE-AN) framework, which assumes that recovery is not necessarily feasible past young adulthood. This study used constructivist grounded theory methodology to understand the experiences of adults in midlife living with AN. In-depth analyses of 19 participant narratives in midlife show that individuals face barriers to seeking help or remaining in recovery; however, midlife can also act as a significant catalyst toward recovery. Subsequently, there is merit in revisiting the utility of the SE-AN framework in the context of life course theory and exploring resilience-informed approaches in supporting recovery from AN.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.258
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.270
GPT teacher head0.530
Teacher spread0.259 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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