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Enregistrement W4284663309 · doi:10.1002/cl2.1246

PROTOCOL: The effectiveness of abstinence‐based and harm reduction‐based interventions in reducing problematic substance use in adults who are experiencing severe and multiple disadvantage homelessness: A systematic review and meta‐analysis

2022· review· en· W4284663309 sur OpenAlexfundno aff
Chris O’Leary, Robert Ralphs, Jennifer C. Stevenson, Andrew Smith, Jordan Harrison, Zsolt Kiss

Notice bibliographique

RevueCampbell Systematic Reviews · 2022
Typereview
Langueen
DomaineHealth Professions
ThématiqueHomelessness and Social Issues
Établissements canadiensnon disponible
Organismes subventionnairesQueen's UniversityQueen's University Belfast
Mots-clésPsychological interventionAbstinencePsychiatryMental healthPsychologyHarm reductionPopulationPublic healthMedicineSubstance abuseEnvironmental healthNursing

Résumé

récupéré en direct d'OpenAlex

Background: Homelessness is a major social and public health concern. It is a traumatic experience, and can have a devastating effect on those experiencing it. People who are homeless often face significant barriers when accessing public services, and those experiencing more visible and extreme forms of homelessness have often faced adverse childhood events, extreme social disadvantage, physical, emotional and sexual abuse, neglect, low self-esteem, poor physical and mental health, and much lower life expectancy compared to the general population. Problematic substance use is disproportionately high amongst people experiencing homelessness, with many using drugs and alcohol to deal with the stress of living on the street, to keep warm, or to block out memories of previous abuse or trauma. Drug overdose is a major cause of death for people experiencing street homelessness. Substance dependency can also create barriers to successful transition to stable housing. There is ongoing policy interest in the effectiveness of different interventions that aim to stop, reduce or prevent problematic substance use, and there is specific interest in the relative effectiveness of interventions that adopt harm reduction or abstinence-based approaches. Objectives: The objective of this review is to understand the effectiveness of different substance use interventions. The review will consider the effectiveness of harm reduction-based interventions, and abstinence-based interventions, for adults experiencing homelessness. The focus of the review is on high-income countries. Search Methods: The primary source of studies for potential inclusion in this review is the Homelessness Effectiveness Studies Evidence and Gaps Maps (EGM). The first of these was published in 2018, with updates published in 2019 and 2020. A further update is due to be published in the summer of 2022. It is this update that provides the final list of studies from which this review will draw. The search for this update (EGM 4th edition) was completed in September 2021. Other potential studies will be identified through a call for grey evidence and hand-searching key journals. Selection Criteria: Eligible studies will be impact evaluations with designs at levels, 3, 4 and 5 of the Maryland Scientific Methods scale. This therefore includes all studies categorised as either 'Randomised Controlled Trials' or 'nonexperimental designs with a comparison group' from the studies which form the basis of the Homelessness Effectiveness Studies Evidence and Gap Maps (EGM) created by CHI and the Campbell Collaboration. We are interested in studies that examine the effect of interventions on substance use outcomes. Studies to be excluded are those with designs at levels 1 and 2 of the Maryland Scientific Methods scale, for example, studies without a control or comparison group, 'before vs. after' designs (without an untreated comparison group), and cross-sectional regressions. Data Collection and Analysis: Descriptive characteristics and statistical information in included studies will be coded and checked by at least two members of the review team. Studies selected for the review will be assessed for confidence in the findings using a critical appraisal tool for determining confidence in primary studies. Standardised effect sizes will be calculated and, if a study does not provide sufficient raw data for the calculation of an effect size, we will attempt to contact the author(s) to obtain this data. We will aim to use random-effects meta-analysis and robust-variance estimation procedures to synthesise effect sizes. If a study includes multiple effects, we will carry out a critical assessment to determine (even if only theoretically) whether the effects are likely to be dependent. Where we suspect dependent effects, we will determine whether we can account for these by robust variance estimation. We will explore the moderating influence of participant and study characteristics, such as gender, race, substances targeted and length of follow-up. Where effect sizes are converted from a binary to continuous measure (or vice versa), we will undertake a sensitivity analysis to investigate the effect of the inclusion of studies with a converted effect size in the meta-analysis by running an additional analysis with these studies omitted. We will also assess the sensitivity of results to inclusion of non-randomised studies and studies classified as low confidence in findings. All analyses will include an assessment of statistical heterogeneity. Finally, we will undertake analysis to assess whether publication bias is likely to be a factor in our findings.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,020
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Méta-épidémiologie (sens large)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,136
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0200,006
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0240,002
Bibliométrie0,0010,003
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,231
Tête enseignante GPT0,461
Écart entre enseignants0,230 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2022
Routes d'admission1
Résumé présentoui

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