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Record W4360956109 · doi:10.1016/j.ssmqr.2023.100261

'I just don't trust my pelvic floor': Examining the bio-social barriers to maternal health and physical activity participation in a sample of mothers' from New Zealand

2023· article· en· W4360956109 on OpenAlexaff
Marianne Clark, Holly Thorpe

Bibliographic record

VenueSSM - Qualitative Research in Health · 2023
Typearticle
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsAcadia University
Fundersnot available
KeywordsAotearoaChildbirthPsychologyBreastfeedingConceptual frameworkPostpartum periodNursingPregnancySocial psychologyMedicineSociologyGender studiesSocial science

Abstract

fetched live from OpenAlex

Maternal physical activity participation is associated with a range of positive mental and physical health outcomes. While a range of psycho-social and practical barriers to women's participation have been identified, little research has examined how these intersect with the physiological barriers posed by birthing injuries and the physical changes wrought by pregnancy and childbirth. In this study we address this gap using data collected through in-depth interviews with 20 women in Aotearoa New Zealand seeking to engage in regular exercise following childbirth. Guided by a socio-material conceptual framework, we examine women's physical activity engagement as bio-social phenomena. We pay particular attention to how women describe and navigate challenges posed by physiological considerations such as pelvic floor dysfunction, fatigue, the energetic demands of breastfeeding, and lingering birthing injuries. We argue these physical barriers are largely glossed over by policies, programmes and existing research that focus on motivating mothers to return to or become physically active. We suggest more sophisticated conceptual approaches are needed that explicitly acknowledge the overlapping biological and social dimensions of maternal physical activity in order to better support women through the complex postpartum period and beyond through enhanced resources, information, and general social awareness.

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)0.014
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.336
GPT teacher head0.586
Teacher spread0.251 · 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.

Study designQualitative
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

Citations6
Published2023
Admission routes1
Has abstractyes

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