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Record W2741333610 · doi:10.1080/15295192.2017.1333789

Mothers’ Knowledge of What Reduces Distress in Their Adolescents: Impact on the Development of Adolescent Approach Coping

2017· article· en· W2741333610 on OpenAlexafffund
Amanda Sherman, Joan E. Grusec, Alisa N. Almas

Bibliographic record

VenueParenting · 2017
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCoping (psychology)PsychologyDevelopmental psychologyDistressLongitudinal studyPsychological distressAdolescent developmentCoping behaviorClinical psychologyAnxietyMedicinePsychiatry

Abstract

fetched live from OpenAlex

SYNOPSISObjective. This longitudinal study assessed the role of mothers’ knowledge of what is comforting to their adolescents when they are distressed. The authors proposed that the adolescents of mothers who were knowledgeable but dissatisfied with their adolescent would have adolescents who coped better than those whose mothers were less dissatisfied; dissatisfied mothers would be more likely to draw on their knowledge to engage in “not-too-nice” parenting, thereby allowing their adolescents to find their own means of self-comfort. Design. Participants were 111 early adolescents and their mothers. At the first time-point adolescents were assessed for approach coping and asked to rate what they would find comforting when they were upset; mothers were asked to predict those ratings and assessed for the extent of their dissatisfaction with their adolescent’s behavior. Adolescents were assessed again for approach coping 2 years later. Results. Mothers’ knowledge positively predicted adolescent approach coping, but only when mothers were high in dissatisfaction. Conclusions. The findings underscore the importance of parents’ knowledge of their adolescents in promoting coping, as well as the role that maternal dissatisfaction plays in adolescents’ ability to cope on their own.

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 score0.421
Threshold uncertainty score0.527

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 science0.0010.000
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 head0.059
GPT teacher head0.337
Teacher spread0.278 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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