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Record W2969782900 · doi:10.1111/jpm.12557

Influences on mental health and health services accessibility in immigrant women with post‐partum depression: An interpretive descriptive study

2019· article· en· W2969782900 on OpenAlexafffundabout
Rebecca Ganann, Wendy Sword, K. Bruce Newbold, Lehana Thabane, Leigh Armour, Bernadette Kint

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2019
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Public HealthChild and Family Research InstituteImpactMcMaster University
FundersCanadian Institutes of Health ResearchMcMaster University
KeywordsMental healthDescriptive researchPost partumImmigrationDepression (economics)Postpartum depressionPsychologyPsychiatryMedicineClinical psychologySociologyPregnancyPolitical science

Abstract

fetched live from OpenAlex

WHAT IS KNOWN ABOUT THE SUBJECT?: Immigrant women in Canada are at greater risk for post-partum depression (PPD) than native-born women. Immigrant women are less likely to have their care needs met as they face multiple barriers to care at both individual and system levels. To date, most PPD research has focused on individual barriers to care, with limited research examining organizational and system level barriers and the uniqueness of immigrant women's post-partum health experiences. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: This study provides unique insights into immigrant women's perceptions of what influences their post-partum mental health and ability to access services for PPD. Factors contributing to immigrant women's PPD included several social determinants of health, particularly a lack of social support and limited knowledge about PPD and available services. Most helpful services acknowledge women's concerns, build trust, enact cultural competence and help with system navigation. Assessment approaches and organizational wait times created barriers to accessing care. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Relationship building by providers is foundational to effective care for immigrant women with PPD. Findings highlight the need for mental health practitioners to improve cultural competence when working with diverse ethno-cultural communities and for more effective assistance with system navigation, service integration and timely, flexible and accessible services. Findings have implications for the development of healthy public policy to address perinatal mental health issues amongst immigrant women. Abstract Introduction Immigrant women in Canada are at greater risk for post-partum depression (PPD) than native-born women yet face multiple barriers to care at individual and system levels. Aim To explore factors that contribute to PPD and health service accessibility, and the role of health services in supporting immigrant women with PPD. Methods A qualitative interpretive descriptive design was used. Individual interviews were conducted with 11 immigrant women who had delivered a baby within the previous year and had experienced PPD. Inductive thematic content analysis was conducted. Results Factors contributing to immigrant women's PPD included several social health determinants. Services were most helpful and accessible when providers acknowledged women's concerns, allowed time to build trust, provided culturally competent care and helped with navigating services. Assessment approaches and organizational wait times created barriers to care. Discussion Immigrant women with PPD see relationship building by providers as foundational to providing effective support, enhancing coping and facilitating access to services. Improved communication with diverse ethno-cultural communities and assistance with system navigation, service integration and timely, accessible services are needed. Implications for Practice Findings can inform health service delivery models and the development of healthy public policy to address perinatal mental health issues amongst immigrant women.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.372
Teacher spread0.358 · 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 designObservational
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

Citations41
Published2019
Admission routes3
Has abstractyes

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