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Record W4416235536 · doi:10.1080/14681811.2025.2582812

Congruence and discrepancies in mothers’ and adolescents’ reports of the extent of sexual communication

2025· article· en· W4416235536 on OpenAlexafffundabout
E. Sandra Byers, Heather A. Sears, Amanda Bockaj

Bibliographic record

VenueSex Education · 2025
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of New Brunswick
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCongruence (geometry)Human sexualitySexual behaviorSexual identityInterpersonal communicationHeterosexualityQualitative research

Abstract

fetched live from OpenAlex

Researchers have found that, on average, parents report more frequent parent-adolescent sexual communication than do their adolescents, but they have not considered that this informant discrepancy in perceptions likely does not occur in all families. We examined the proportion of mother-adolescent dyads who showed three patterns of congruence and discrepancy in the extent of sexual communication: Mother > Adolescent, Mother = Adolescent, and Adolescent > Mother. Participants were 254 Canadian adolescents (134 girls, 120 boys; 12–14 years) and their mothers. The analyses showed that, overall, 56% of dyads fell into the Mother = Adolescent group, 35% into the Mother > Adolescent group, and 9% into the Adolescent > Mother group. This was also the pattern for most specific sexual health topics assessed. Discriminant function analysis showed that only adolescents’ perceptions of the quality of communication (sexual and general) separated the groups. These results demonstrate that the most common pattern was for mothers and adolescents to be congruent, not discrepant, in their perceptions of their sexual communication. They also suggest that these patterns of congruence and discrepancy are linked to adolescents’ but not mothers’ perceptions of the quality of their sexual and general communication.

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 score0.013
Threshold uncertainty score0.140

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 science0.0000.000
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 head0.013
GPT teacher head0.299
Teacher spread0.286 · 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
Published2025
Admission routes3
Has abstractyes

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