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Record W4400056276 · doi:10.3389/fpsyg.2024.1437889

Editorial: Positive emotion dysregulation in eating disorders and dysregulated eating behaviors

2024· editorial· en· W4400056276 on OpenAlexaff
Edward A. Selby, Lindsay P. Bodell, Ann F. Haynos

Bibliographic record

VenueFrontiers in Psychology · 2024
Typeeditorial
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsWestern University
FundersNational Institute of Mental Health
KeywordsEating disordersPsychologyDisordered eatingClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Editorial on the Research Topic Positive emotion dysregulation in eating disorders and dysregulated eating behaviorsPositive emotions can play complex roles in eating disorders and dysregulated eating behaviors, influencing both the development and maintenance of these problems.However, research focused on the impact of positive emotions and their dysregulation in these conditions is notably lacking as compared to studies on negative emotion dysregulation.Positive emotions in these conditions should not be neglected, as a growing literature indicates that positive emotion dysregulation is implicated in various behaviors across the eating disorders spectrum, including overconsumption of palatable food, binge eating, restrictive eating, and excessive exercise (Selby et al., 2015;Coniglio et al., 2019).Positive emotional experience can also affect higher-order aspects of human functioning, such as happiness, life satisfaction, motivation, and fulfillment, all of which tend to be impaired in individuals with eating disorder symptoms.Key questions in the field revolve around whether dysregulated behaviors stem from diminished positive emotions and whether eating behaviors are reinforced by maladaptive emotional responses.Integration of positive emotion dysregulation into our theoretical models can improve our understanding of the onset and maintenance of eating disorders and dysfunctional eating behaviors (Selby and Coniglio, 2020; Bodell and Racine, 2023).Likewise, novel treatments for eating disorders may involve addressing the interplay between positive emotions, negative emotions, and maladaptive eating behaviors to promote healthier coping strategies and emotional regulation skills.Therefore, the better we can understand the key roles of positive emotion, the more precisely we can specify our treatments (Haynos et al., 2016(Haynos et al., , 2024)).This Research Topic aims to continue these lines of work and draw attention to ongoing research on positive emotion dysregulation in problematic eating behaviors.Included articles examined the role of positive emotion in disordered eating through factors such as emotion regulation, emotional reactivity traits, attachment patterns, and the dynamic interplay between psychosocial factors and eating behaviors.Collectively, these findings highlight that although positive emotions can serve adaptive functions at times, they can also contribute to the complexity and maintenance of eating disorders and dysregulated eating when they become dysregulated or become intertwined with disordered eating, weight loss, or social perception patterns.

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)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.001
Science and technology studies0.0030.002
Scholarly communication0.0070.004
Open science0.0040.002
Research integrity0.0180.014
Insufficient payload (model declined to judge)0.0300.014

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 head0.007
GPT teacher head0.316
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

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