Commentary on Richardson <i>et al</i> . : Strategies to mitigate payment‐coincident drug‐related harms are urgently needed
Notice bibliographique
Résumé
Drug-related harms that coincide with synchronous income assistance payments are prevalent among people who use drugs. Given the global economic recessions precipitated by the COVID-19 pandemic, and the resulting unprecedented reliance on synchronous income assistance payments, strategies to mitigate these harms—while also disseminating necessary income assistance—are urgently needed. Richardson et al. [1] found that among people who use drugs (PWUD) and receive monthly income assistance, the majority (78%) of participants reported experiencing drug-related harm in the days surrounding receipt of income assistance. This research extends prior literature examining drug-related harm coinciding with synchronized income assistance payments [2-4], the so-called ‘check effect’, by quantifying the prevalence of these harms and identifying socio-economic and drug-related correlates. The high prevalence of payment-coincident drug-related harms identified by Richardson et al. underscores an urgent need to explore strategies that mitigate these harms while also disseminating necessary income assistance, particularly in light of international responses to the COVID-19 pandemic. COVID-19 has precipitated global economic recessions and unprecedented reliance upon synchronous income assistance payments. According to the World Bank, the global economy is expected to shrink by 5.2% in 2020 alone, representing the deepest global recession since the end of World War II [5]. In response, many countries have implemented direct support programs that provide synchronous income assistance payments to those who lost income due to COVID-19. Over the next year, an estimated 890 000 Canadians are expected to receive the Canada Recovery Benefit [6]. As of October, 10.2 million people in the United States received regular Pandemic Unemployment Assistance payments [7], and many other countries have expanded unemployment insurance programs for the foreseeable future. Depression, anxiety and substance use have also increased precipitously during the COVID-19 pandemic [8], and an unprecedented number of PWUD are receiving synchronous income assistance payments. The most common payment-coincident drug-related harms identified by Richardson et al. [1] were intensified drug and alcohol use. Many other payment-coincident harms were also identified, including non-fatal overdose, discontinuing substance use disorder treatment and being unable to access a health or social service or supervised injection facility due to increased demand. To mitigate risk of overdose and reduce barriers to critical services, supervised injection facilities and other harm reduction service providers (e.g. those who distribute naloxone, injecting equipment and fentanyl test strips) should consider expanding their operational capacities in the days surrounding synchronized income assistance payments when possible through increased staffing or expanded service hours. Other health and social service providers could also consider such expansions. While social distancing guidelines, shutdowns and fiscal challenges have complicated the delivery of harm reduction services [9], many programs have adopted less restrictive, needs-based models to increase service distribution [10]. Similar strategies could also be adapted to meet payment-coincident increases in demand. Expanded monetary support for harm reduction supplies and services will also be needed to ensure access to key services [11]. Alongside COVID-19 public health messaging that is tailored towards marginalized PWUD [11], harm reduction campaigns that address intensive alcohol and drug use during days surrounding payment distribution should also be developed and piloted. Directing resources and services to individuals at greatest risk of payment-coincident harms, such as those experiencing a high degree of socio-economic and structural marginalization or engaging in high-intensity drug use, will also be essential to mitigate harms. Richardson et al. [1] also found that residency in the Downtown Eastside, a neighborhood of Vancouver that is characterized by economic disadvantage, was associated with payment-coincident drug-related harm. As the authors note, prior research investigating the ‘check effect’ phenomenon at the neighborhood level in Rhode Island did not identify an association between the proportion of residents receiving monthly income assistance and excess payment-coincident overdose mortality, although it was associated with the proportion of residents living in unaffordable housing [12]. Correspondingly, in developing a robust response to reducing payment-coincident drug-related harms, other structural stressors that co-occur with synchronous income assistance payments—such as rent/mortgage payments and elevated evictions risks—should also be considered. COVID-19 has exacerbated a pre-existing global housing crisis which is already affecting millions, particularly PWUD [13]. Strategies that curtail housing-related stressors and reduce housing instability, such as expanded availability of temporary emergency housing [14], extending moratoriums on evictions [15], deferrals of mortgage and rental payments [16], rent stabilization and reduction measures [17] and an overall expansion of affordable housing, are also critically needed. As Richardson et al. [1] highlight, payment-coincident drug-related harms are prevalent among PWUD, and individuals who are marginalized or engaging in high-intensity drug use experience elevated risk. In the era of COVID-19, when reliance upon synchronous income assistance payments has never been greater, strategies to mitigate payment-coincident drug-related harms are urgently needed. None.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».