Further Insights for Our Practice–Wishes for a Kinder 2024
Notice bibliographique
Résumé
As I draft this year-end editorial for submission, 3 months in advance of publication, I am currently reflecting on 2023 in the context of the last 50 years. I cannot recall a time when Mother Nature has tested us so drastically. From coast to coast to coast, we have experienced extensive scarring of our forests caused by wildfires, some resulting in significant population displacements (in the Northwest Territories and Interior British Columbia), as well as a succession of floods from our rivers and hurricanes pummeling our shores (in Quebec and the Maritimes). Right now, Hurricane Lee is heading toward New Brunswick, the twelfth storm in recent memory. The impacts of global warming are no longer to be denied. Will 2024 be kinder? I am unaware of any comprehensive Canadian study following the social impacts of repeated natural disasters, including the prevalence of addiction disorders in this context. This journal eagerly invites any submission exploring this. Meanwhile, this issue offers diverse publications on a range of insights to be addressed in our practices. Faced with the rising mortality from substance overdoses and the call for additional measures, policymakers are contemplating the potential benefits of implementing involuntary treatment for individuals with substance use disorder. The Policy Committee of the Canadian Society of Addiction Medicine has conducted a systematic literature review of the effectiveness of such measures. In fact, this is the second related review article published in the CJA.1 Apart from higher retention in treatment, the literature remains equivocal as to the therapeutic benefits of this approach. The next contribution, a commentary, is an observation that while residential treatment settings are increasingly advocated by some policymakers, only a marginal minority provide opioid agonist therapy to their clients with opioid use disorder, thus depriving them of a demonstrated gold-standard approach. In a similar vein, a survey of 58 secondary schools in Ontario about the availability of youth substance use prevention programs reports that about half are not offering any such program. Of those schools that do, global programs targeting multiple substances are more common than cannabis-specific programs, a year after the legalization of cannabis in Canada. This is despite the reported relatively high rate of cannabis use among students. A comprehensive, school-level strategy is advocated. Comparing the high prevalence of publications about opioid use disorders versus the scant number of articles addressing methamphetamine/stimulant use, the next 2 epidemiological surveys are welcome. The first is a chart review of methamphetamine-related emergency department visits in 2019 in Toronto. The second analyzes a cohort of people using methamphetamine with a history of hospitalizations in London, Ontario. Not surprisingly, both groups elicit high social and clinical needs for both substance use and mental health concerns. Of additional interest, the London sample reports a high in-hospital substance use, highlighting the need to address this issue in the hospital setting. A third population-based, retrospective cohort study in Southern Ontario of initiated buprenorphine/naloxone or methadone between October 2016 and December 2018 (N=15 724) concludes that treatment retention is lower among individuals treated with buprenorphine/naloxone relative to methadone, particularly among males. The last 2 articles are about the behavioural segments of our field. A secondary analysis of an online panel of 10 199 Canadian adults who had gambled at least monthly in the previous year elicited that those with Problem Gambling (N=909) are more likely to seek help from services other than professional treatment. Friends and family may be the only ones providing help. Professional counselling and casino self-exclusion are also perceived as valued. The final study, aimed at the neglected, concerned significant others of people with problematic internet use, identifies the set of dimensions to be taken into consideration when evaluating the specific needs of partners. Very best of the Season! Nady el-Guebaly CM, MD, FRCPC Editor-in-Chief, CJA
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».