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Record W2900301493 · doi:10.1371/journal.pone.0205673

Nuestras Historias- Designing a novel digital story intervention through participatory methods to improve maternal and child health in the Peruvian Amazon

2018· article· en· W2900301493 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
FundersOffice of Research on Women's HealthFogarty International CenterNIH Office of the DirectorNational Institute of General Medical SciencesNational Institute of Mental HealthNational Institutes of HealthConsejo Nacional de Ciencia, Tecnología e Innovación TecnológicaGrand Challenges Canada
KeywordsPhotovoicePsychological interventionCommunity-based participatory researchDigital storytellingMedicineParticipatory action researchThematic analysisNarrativeIntervention (counseling)Medical educationNursingFamily medicinePsychologyQualitative researchSociologyPedagogySocial scienceVisual arts

Abstract

fetched live from OpenAlex

BACKGROUND: In rural areas of the Loreto region within the Peruvian Amazon, maternal mortality rate is above the national average and the majority of women deliver at home without care from a trained health care provider. METHODS: To develop community-tailored videos that could be used for future interventions, we conducted Photovoice and digital storytelling workshops with community health workers (CHW) and mothers from 13 rural communities in the Parinari district. Through Photovoice we recognized local barriers to healthy pregnancies. Participants (n = 28) were trained in basic photography skills and ethics. They captured photos representing perceived pregnancy-related road-blocks and supports, and these photos identified central themes. Participants recorded personal stories and "storyboarded" to develop digital stories around these themes, and a Digital Story Curriculum called Nuestras Historias (Our Stories), was created. An acceptability survey of the digital stories was then conducted including 47 men (M) and 60 women (F). RESULTS: According to the PhotoVoice workshops, pregnancy-related problems included: lack of partner support, domestic violence, early pregnancies, difficulty attending prenatal appointments, and complications during pregnancy and delivery. Over 30 stories on these themes were recorded. Seven were selected based on clarity, thematic relevance, and narrative quality and were edited by a professional filmmaker. The acceptability survey showed that local participants found the digital stories novel (M = 89.4%, F = 83.3%), relatable (M = 89.4%, F = 93.2%), educational (M = 91.5%, F = 93.3%) and shareable (M = 100%, F = 100%). Over 90% of respondents rated the digital stories as "Excellent" or "Good", found the videos "Useful" and considered them "Relevant" to their communities. CONCLUSIONS: The digital stories address community-specific problems through narrative persuasion using local voices and photography. This combination had a high acceptability among the target population and can serve as a model for developing educational strategies in a community-tailored manner. This package of seven videos will be further evaluated through a cluster randomized trial.

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.

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)0.010
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.600
GPT teacher head0.589
Teacher spread0.011 · 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