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Record W4393379484 · doi:10.1377/hlthaff.2023.01449

A Strategy To Support Perinatal Mental Health By Collaborating With Tribal Communities In Montana

2024· article· en· W4393379484 on OpenAlexaff
Amy Stiffarm, Stephanie Morton, Dawn Gunderson, Brie MacLaurin, Nicole Redvers, Maridee Shogren, T.D. Wright, Andrew Williams

Bibliographic record

VenueHealth Affairs · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsWestern University
Fundersnot available
KeywordsIndigenousMental healthPsychological interventionResource (disambiguation)PopulationNursingPsychologyMedicinePublic relationsEconomic growthPolitical scienceEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

Among Indigenous women and birthing people, reported rates of perinatal mental health complications are consistently higher than in the general US population. However, perinatal mental health programs and interventions tend to focus on the general population and do not account for the unique experiences and worldviews of Indigenous Peoples. We highlight a collaborative strategy employed by a Montana nonprofit to engage Tribal communities in completing a statewide online resource guide designed to help pregnant and parenting families find resources, including mental health and substance use treatment options, within and beyond their local communities. Based on this strategy, cultural resources relevant to Tribal communities were added to the resource guide. Agencies committed to addressing perinatal mental health disparities among Indigenous populations should consider similar strategies to share power with Tribal communities and collaboratively create culturally congruent programs and interventions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.023
GPT teacher head0.337
Teacher spread0.314 · 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 designNot applicable
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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