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Record W3024715916 · doi:10.1080/0167482x.2020.1761320

The relationship of trait mindfulness to physical and psychological health during pregnancy

2020· article· en· W3024715916 on OpenAlexafffundabout

Bibliographic record

VenueJournal of Psychosomatic Obstetrics & Gynecology · 2020
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsMindfulnessPregnancyTraitAnxietyPsychological interventionTrait anxietyMental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Research on mindfulness has extended to the prevention of psychopathology and physical conditions during pregnancy. The purpose of this study was to investigate the relationship between trait mindfulness assessed in the first or early second trimester to health outcomes throughout pregnancy. METHODS: A total of 510 women were recruited at McGill University-affiliated obstetrics clinics (average gestational age: 13.43 weeks, sd = 1.2). The Mindful Awareness and Attention Scale (MAAS) was administered at baseline. At three timepoints during pregnancy, participants completed the Perceived Stress Scale (PSS-10), the Edinburgh Postnatal Depression Scale (EPDS), the Prenatal Distress Questionnaire-revised (PDQR) and a measure of pregnancy symptom intensity and indicated whether they had been diagnosed with gestational diabetes or high blood pressure. RESULTS: Higher MAAS scores predicted lower PSS, EPDS and PDQR scores and less severe physical discomforts throughout pregnancy. MAAS scores were a stronger predictor of PSS scores earlier in pregnancy. Logistic regressions found that trait mindfulness did not predict the presence of physical discomforts, diabetes or high blood pressure. CONCLUSIONS: These results indicate that trait mindfulness is an important predictor of subjective stress, depression, anxiety and the severity of physical discomforts during pregnancy. These findings suggest that interventions earlier in pregnancy may increase the impact of mindfulness on maternal 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 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)0.003
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 score0.281
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.062
GPT teacher head0.357
Teacher spread0.296 · 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
Published2020
Admission routes3
Has abstractyes

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