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Record W2057666613 · doi:10.1002/imhj.10025

Affect expression in prenatally psychotropic exposed and nonexposed mother–infant dyads

2002· article· en· W2057666613 on OpenAlexaff
Pratibha Reebye, Sara J. Morison, Hira Panikkar, Shaila Misri, Ruth E. Grunau

Bibliographic record

VenueInfant Mental Health Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsChildren's & Women's Health Centre of British ColumbiaBC Research (Canada)University of British Columbia
Fundersnot available
KeywordsAnxietyAffect (linguistics)PsychologyTemperamentPregnancyDepression (economics)PsychiatryClinical psychologyPediatricsMedicinePersonality

Abstract

fetched live from OpenAlex

Abstract This prospective study examined infant, maternal, and dyadic affective profiles at three months postpartum in infant–mother dyads that were exposed to psychotropic medications in utero compared with nonexposed control dyads. Control dyads of nondepressed mothers and their infants showed many similarities in affect expression with mother–infant dyads who were exposed to selective serotonin reuptake inhibitors (SSRIs) alone for treatment of maternal depression. In contrast, mothers who received SSRIs and Rivotril (Benzodiazepine derivative) for treatment of depression and anxiety expressed both positive and negative affect towards their infants. Clinical implications regarding use of psychotropic medications such as SSRIs alone or in combination with other drugs for treatment of maternal anxiety and depression during pregnancy are discussed. Clinicians should be aware of the possible differential response in maternal–infant interaction in a mixed diagnosis group (i.e., depression and anxiety) regarding infant temperament, possibly suggesting latent behavioral teratogenicity with psychotropics. ©2002 Michigan Association for Infant Mental Health.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.315
Teacher spread0.287 · 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 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

Citations29
Published2002
Admission routes1
Has abstractyes

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