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Record W2969379373 · doi:10.5539/jedp.v9n2p74

Retrospective Reports of Parental Socialization of Physical Pain During Childhood Predicting Emerging Adults’ Current Coping With Pain

2019· article· en· W2969379373 on OpenAlexvenueno aff
Julie DiNuoscio, Vaishali V. Raval, Bethany L. Walker

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2019
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCoping (psychology)PsychologySocializationClinical psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Although a bulk of the literature has examined the methods by which people cope with physical pain, little attention has been devoted to how people learn to respond to pain. The current study examined the relation between college students’ reports of parental socialization of pain during childhood and their current coping with pain. One hundred twenty-four (65.3% female) college students reported on two methods of parental socialization they experienced during childhood: a) their mothers’ direct responses to their physical pain and b) mothers’ modeling of how they coped with their own pain. College students also reported on their own current coping strategies regarding physical pain. Results indicated that retrospective reports of mothers’ active coping with their own pain and mothers’ promotion responses to their child’s pain during childhood significantly positively predicted college students’ current active coping. These findings suggest the relevance of both methods of pain socialization (parental modeling and parents’ direct responses) for college-age children’s current coping with pain.

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)0.001
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 score0.004
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.301
Teacher spread0.293 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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