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Record W2782272415 · doi:10.1111/dar.12649

How do people with homelessness and alcohol dependence cope when alcohol is unaffordable? A comparison of residents of Canadian managed alcohol programs and locally recruited controls

2018· article· en· W2782272415 on OpenAlexafffundabout
Rebekah A. Erickson, Tim Stockwell, Bernie Pauly, Clifton Chow, Audra Roemer, Jinhui Zhao, Kate Vallance, Ashley Wettlaufer

Bibliographic record

VenueDrug and Alcohol Review · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Victoria
FundersCanadian Institutes of Health ResearchSystembolagetMichael Smith Health Research BC
KeywordsAlcoholCoping (psychology)Logistic regressionEthnic groupAlcohol dependenceOddsDemographyMedicineOdds ratioPsychologyPsychiatryGerontologyInternal medicineSociology

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: We investigated coping strategies used by alcohol-dependent and unstably housed people when they could not afford alcohol, and how managed alcohol program (MAP) participation influenced these. The aim of this study was to investigate potential negative unintended consequences of alcohol being unaffordable. DESIGN AND METHODS: A total of 175 MAP residents in five Canadian cities and 189 control participants from nearby shelters were interviewed about the frequency they used 10 coping strategies when unable to afford alcohol. Length of stay in a MAP was examined as a predictor of negative coping while controlling for age, sex, ethnicity, housing stability, spending money and drinks per day. Multivariate binary logistic and linear regression models were used. RESULTS: Most commonly reported strategies were re-budgeting (53%), waiting for money (49%) or going without alcohol (48%). A significant proportion used illicit drugs (41%) and/or drank non-beverage alcohol (41%). Stealing alcohol or property was less common. Long-term MAP participants (>2 months) exhibited lower negative coping scores than controls (8.76 vs. 10.63, P < 0.001) and were less likely to use illicit drugs [odds ratio (OR) 0.50, P = 0.02], steal from liquor stores (OR 0.50, P = 0.04), re-budget (OR 0.36, P < 0.001) or steal property (OR 0.40, P = 0.07). Long-term MAP participants were also more likely to seek treatment (OR 1.91, P = 0.03) and less likely to go without alcohol (OR 0.47, P = 0.01). DISCUSSION AND CONCLUSIONS: People experiencing alcohol dependence and housing instability more often reduced their alcohol consumption than used harmful coping when alcohol was unaffordable. MAP participation was associated with fewer potentially harmful coping strategies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.076
GPT teacher head0.384
Teacher spread0.308 · 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.

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

Citations42
Published2018
Admission routes3
Has abstractyes

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