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Enregistrement W7104288981 · doi:10.17605/osf.io/ehbcy

Pharmacological Interventions for Alcohol Use Disorder in Older Adults: A Scoping Review

2025· other· W7104288981 sur OpenAlexaboutno aff

Notice bibliographique

RevueOSF Preprints (OSF Preprints) · 2025
Typeother
Langue
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPolypharmacyPsychological interventionPsychosocialContext (archaeology)DistressSocial isolationPopulationAlcohol use disorder

Résumé

récupéré en direct d'OpenAlex

Substance use disorders (SUDs) are a growing, yet underrecognized problem amongst the older adult population. SUDs are defined by patterns of substance use that can develop clinically significant impairment or distress - a significant burden for individuals, families, and societies. Relevant substances that will be explored in this study include alcohol. In Canada, despite national surveys, there is limited data on DSM-diagnosed substance use disorders in older adults. This becomes particularly concerning in the context of a growing global aging population. The proportion of individuals aged 50 and older with substance use disorders is increasing due to an aging population. In the United States, the 2024 National Survey on Drug Use and Health reported that approximately 2.9 million adults aged 65 or older met the criteria for past-year alcohol use disorder. SUD research defines older adults as 50 and older to capture midlife adults alongside traditionally defined older adult populations as individuals by 50 may already experience age-related changes that influence substance use behaviours. Due to differing physiological, neurobiological, and psychosocial changes associated with aging, the effectiveness and safety of pharmacological interventions for SUDs should be considered. For example, age-associated reduction in liver and kidney function impact drug metabolism and clearance, neurobiological alterations in terms of changes to neurotransmitter systems may influence efficacy of treatment, and polypharmacy or other social factors such as isolation may impact adherence to treatment. These trends and population differences highlight the need for appropriate evidence-based pharmacological strategies tailored to older adults. In this review, adults aged 50 years and older will be included to ensure sufficient evidence, while a subgroup of adults aged 65 years and above will be examined separately to explore findings relevant to traditionally defined older adults. This threshold aligns with prior literature examining substance use in midlife and older adults, which often defines older populations as those aged ≥50 years. Pharmacological interventions for AUDs include medications approved to assist with cessation, relapse prevention, and or withdrawal management. Medications commonly utilized to treat include naltrexone, acamprosate, disulfiram, and benzodiazepines. Common adverse effects associated with these medications include nausea, vomiting, diarrhea, loss of appetite, skin rashes, acne, drowsiness, dizziness, anxiety, constipation, headache, and weight gain. Substance use disorders in older adults are increasing in prevalence yet continue to be understudied. Most pharmacological research on SUDs focus on younger adults, thus possibly missing out on data that may indicate alterations in efficacy and safety in an older adult population. Preliminary searches of databases such as MEDLINE suggest a moderate number of studies that address pharmacological treatment of AUD in adults; however, many of them either restrict the inclusion criteria from ages 18 to 65, or do not focus on older adults as a primary interest group. In addition to this, many of the studies that do address pharmacological treatment of AUD in adults aged 50 and above are limited by small sample sizes, heterogeneity in intervention or outcome, or a lack of age-specific analyses. Given these constraints, a systematic review would not be appropriate as the focus of synthesizing evidence to determine intervention effectiveness would be difficult with limited rigorous eligible studies. Due to this, there is evidence that a scoping review is needed to map the literature while identifying any gaps to guide future research. This approach allows for inclusion of a diverse set of sources, including randomized studies, non-randomized (quasi-experimental) studies, and observational (non-experimental) studies. A previous review by Tampi et al. has explored pharmacological interventions for AUDs in older adults, but there are several limitations that justify the need for an updated scoping review. Firstly, the review was restricted to randomized controlled trials, excluding other study designs such as non-randomized or observational, that could be relevant and offer evidence on the intervention in older adults. The review found a total of two trials. Additionally, the study did not investigate a subgroup of adults aged 65 and older, potentially missing a distinct population with differing efficacy and safety of the pharmacological interventions. The review did not follow a formal scoping review methodology, and is now over four years old, which may be missing any new insights into this topic. Thus, with a broader range of study designs, focus on updated literature, subgroup analysis within the 65 and older group, this review will be a more comprehensive and methodologically robust coverage of current evidence. Objective: To explore the pharmacological interventions for AUD in older adults aged ≥50 years, including prevalence of use, patient characteristics, outcomes, adverse events and costs. We will include a subgroup analysis of those aged ≥65 years. Expected outcomes: A synthesis of evidence will clarify the certainty of evidence supporting pharmacological treatments for AUD in older adults as direct evidence in this population remains limited. This review will identify gaps in existing literature and inform future research and guideline development.

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)0,019
score de la tête « metaresearch » (Gemma)0,041
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Science ouverte, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMéta-épidémiologie (sens strict), Science ouverte, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,496
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0190,041
Méta-épidémiologie (sens strict)0,0030,003
Méta-épidémiologie (sens large)0,0050,005
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0060,009
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,9550,911

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 Opus0,050
Tête enseignante GPT0,379
Écart entre enseignants0,329 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeRevue systématique
Domainenon disponible
GenreAutre

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

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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