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Record W7115176825 · doi:10.5281/zenodo.17929396

"Take a minute (or 60) to focus on yourself": Using autophotography to explore postpartum physical activity experiences and associated psychological constructs

2024· article· W7115176825 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Language
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingFocus groupPhysical activityDownloadFocus (optics)PermissionPostpartum period

Abstract

fetched live from OpenAlex

The demands of motherhood have been shown to negatively impact physical activity (PA) engagement. Participants in a larger PA-based study in British Columbia, Canada were invited to participate in this sub study. Forty-eight photos and descriptions were provided by 9 participants with infants 3–7 months of age. Photos depicted challenges with PA, PA self-efficacy, body image and self-compassion in motherhood. We noted four themes that reflected the complex and gendered nature of postpartum PA engagement. First, gendered expectations of motherhood placed demands on time and space for PA engagement. Second, how mothers felt about their bodies both positively and negatively impacted their sense of self and PA engagement. Third, moments of self-compassion illustrated how navigating feelings of self-compassion about PA was messy. Fourth, PA self-efficacy was essential and required reimagining PA within the constraints of motherhood. In conclusion, PA postpartum is complex and impacted by broader concepts related to the expected duties of motherhood.Iris Lesser et al, "Take a minute (or 60) to focus on yourself": Using autophotography to explore postpartum physical activity experiences and associated psychological constructs, Journal of Health Psychology (, ) pp. . Copyright © 2024. DOI: 10.1177/13591053241284032. Users who receive access to an article through a repository are reminded that the article is protected by copyright and reuse is restricted to non-commercial and no derivative uses. Users may also download and save a local copy of an article accessed in an institutional repository for the user's personal reference. For permission to reuse an article, please follow our Process for Requesting Permission. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@openaccessbutton.org.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.124
GPT teacher head0.364
Teacher spread0.239 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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