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Record W2062069139 · doi:10.2105/ajph.2013.301323

Relationship Between Adverse Childhood Experiences and Homelessness and the Impact of Axis I and II Disorders

2013· article· en· W2062069139 on OpenAlexafffund
Leslie E. Roos, Natalie Mota, Tracie O. Afifi, Laurence Y. Katz, Jino Distasio, Jitender Sareen

Bibliographic record

VenueAmerican Journal of Public Health · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMediationAdverse Childhood ExperiencesPsychological interventionPopulationPsychiatryPersonality disordersMedicinePsychologyGerontologyClinical psychologyMental healthDemographyPersonalityEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: We investigated the links between homelessness associated with serious mental and physical healthy disparities and adverse childhood experiences (ACEs) in nationally representative data, with Axis I and II disorders as potential mediators. METHODS: We examined data from the National Epidemiologic Survey of Alcohol and Related Conditions in 2001-2002 and 2004-2005, and included 34,653 participants representative of the noninstitutionalized US population who were 20 years old or older. We studied the variables related to 4 classes of Axis I disorders, all 10 Axis II personality disorders, a wide range of ACEs, and a lifetime history of homelessness. RESULTS: Analyses revealed high prevalences of each ACE in individuals experiencing lifetime homelessness (17%-60%). A mediation model with Axis I and II disorders determined that childhood adversities were significantly related to homelessness through direct effects (adjusted odd ratios = 2.04, 4.24) and indirect effects, indicating partial mediation. Population attributable fractions were also reported. CONCLUSIONS: Although Axis I and II disorders partially mediated the relationship between ACEs and homelessness, a strong direct association remained. This novel finding has implications for interventions and policy. Additional research is needed to understand relevant causal pathways.

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)0.001
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 score0.143
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.046
GPT teacher head0.400
Teacher spread0.354 · 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

Citations116
Published2013
Admission routes2
Has abstractyes

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