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Record W7128178683 · doi:10.1080/10530789.2025.2515632

Preventing homelessness in pregnant youth and young mothers: a review of key turning points

2025· article· en· W7128178683 on OpenAlexafffund
Devin Nihill, Laurence Roy, Cécile Arbaud, Christine Stich

Bibliographic record

VenueJournal of Social Distress and the Homeless · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill University
FundersNetworks of Centres of Excellence of Canada
KeywordsKey (lock)PregnancyQualitative researchMEDLINE

Abstract

fetched live from OpenAlex

Background Pregnancy and motherhood in youth experiencing homelessness is a critical public health issue. Understanding key turning points (KTPs) and pathways into, during, and out of homelessness for this group is vital for enhancing prevention and intervention efforts.We conducted a scoping review to synthesize existing knowledge on the topic in scientific and grey literature for pregnant youth and young mothers aged 13 to 30.Methods The review involved an extensive search in eight scientific and three grey literature databases, and a Google Scholar search, leading to the thematic analysis of 45 studies.Results Nine themes were identified: 1. History of experiencing violence, abuse, and victimization; 2. Involvement with the child welfare system; 3. Transition periods; 4. Lack of supportive relationships; 5. Pro-pregnancy attitudes; 6. Pregnancy and motherhood as opportunity and challenge; 7. Fear of child protective services and custody loss; 8. Challenges in accessing resources; 9. Pregnancy and motherhood as a facilitator for exiting homelessness. The review also highlighted unique aspects of homelessness and pregnancy for LGBTQIA + and BIPOC youth.Conclusions The scoping review revealed complex, interconnected pathways and KTPs for pregnant youth and young mothers experiencing homelessness. Effective support requires tailored interventions addressing their specific needs, with a focus on trauma-informed care.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.450

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 communication0.0000.000
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 head0.023
GPT teacher head0.356
Teacher spread0.333 · 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 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
Published2025
Admission routes2
Has abstractyes

Explore more

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