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Record W4394827264 · doi:10.1177/23333936241245588

Listening to the Voices of Mothers Who Participated in a Video Feedback Intervention for Postpartum Depression

2024· article· en· W4394827264 on OpenAlexafffund
Jennifer Bernard, Nancy J. Moules, Suzanne Tough, Panagiota Tryphonopoulos, Nicole Létourneau

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsWestern UniversityUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsActive listeningIntervention (counseling)Postpartum depressionPsychologyDepression (economics)Video feedbackClinical psychologyAudiologyPsychotherapistDevelopmental psychologyMedicinePsychiatryPregnancy

Abstract

fetched live from OpenAlex

Postpartum depression (PPD) symptoms can negatively influence mother-infant interactions. Video-Feedback Interaction Guidance for Improving Interactions Between Depressed Mothers and their Infants (VID-KIDS) is a parenting intervention that allows mothers experiencing PPD symptoms to observe and improve their interactions with their infants. VID-KIDS has also positively influenced infants' stress (cortisol) patterns. There is limited research on maternal perspectives of interventions like VID-KIDS. In this hermeneutic study, four mothers were interviewed to increase understanding of the VID-KIDS experience. Key findings included: 1) VID-KIDS provided an opportunity for mothers with PPD symptoms to positively transform their identity; 2) VID-KIDS provided a chance to witness the mother-infant relationship forming and improve maternal mental health t, and; 3) VID-KIDS provided a space for mothers to dialogue about their experience with PPD symptoms authentically. VID-KIDS promoted healing from PPD as mothers experienced a transformation in how they perceived themselves and their relationships with their infants.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.127
GPT teacher head0.541
Teacher spread0.413 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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