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Record W4400013471 · doi:10.1177/10870547241261826

Positive Childhood Experiences and the Indirect Relationship With Improved Emotion Regulation in Adults With ADHD Through Social Support

2024· article· en· W4400013471 on OpenAlexafffund
Catherine Lowe, Alexandra C. Bath, Brandy L. Callahan, Emma A. Climie

Bibliographic record

VenueJournal of Attention Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial supportDevelopmental psychologySocial functioningClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Individuals with ADHD report diminished emotion regulation capacities and adversity in childhood detrimentally affects emotion regulation development; however, how positive childhood experiences (PCEs) and whether and how social support are related to PCEs and emotion regulation for those with ADHD is unknown. Objective: To identify direct and indirect associations between PCEs and social support to emotion regulation outcomes in adults with ADHD. Method: Adults with ADHD ( n = 81) reported PCEs, current social support, and emotion regulation. Conditional effects modeling examined the direct and indirect relationships between PCEs and emotion dysregulation through social support. Results: Higher PCEs were indirectly related to improved emotion regulation through increased social support generally (β = −.70, 95% CI [−1.32, −0.17], and specifically through belonging (β = −.43, 95% CI [ −0.87, −0.05], self-esteem (β = −.61, 95% CI [−1.08, −0.27], and tangible social support (β = −.50, 95% CI [−1.07, −0.02]. Conclusions: PCEs may protect emotion regulation in adults with ADHD through social support, possibly through facilitating social connections, increasing access to social support, and sustaining emotion regulation strategies.

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 score0.380
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.283
Teacher spread0.269 · 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

Citations14
Published2024
Admission routes2
Has abstractyes

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