The Potential Effectiveness of Medical Cannabis in the Treatment of Wellness Outcomes for Veterans with Depression
Notice bibliographique
Résumé
Depression is a pervasive mental illness with a prevalence of about nine percent of the Canadian population (Van Ameringen et al., 2008). Depression commonly presents with several chronic symptoms that can severely impact the quality of life and mental well-being, such as intrusive thoughts, flashbacks, irritability, anxiety, and sleep disturbances (Sharpless & Barber, 2011). Military veterans are notably present with much higher rates of depression than civilians (Veterans Affairs Canada, 2019). There is no single effective treatment, and persons with depression might receive multiple modes of treatment in combination. To date, few studies have characterized the demographic characteristics of medical marijuana patients or assessed them for pre-post changes in well-being. A mixed methods study was conducted to better understand therapeutic benefits for patients. Here, we aimed to describe physician authorization patterns of medical cannabis products and observe the self-reported effectiveness and wellness outcomes (depression and anxiety) of medical cannabis among Veterans from Avail Cannabis Clinic. Methods: A total of 34 patients were recruited for retrospective chart review. Researchers compared outcomes using the Patient-Health Questionnaire (PHQ-9) for the depression wellness scale. On intake and assessment, doctors interviewed patients on their lived experiences, and the questions were similar to the survey questions, with more opportunities for open-ended responses. Patients were asked to describe preconditions and treatment goals. Results: The average score before the administration of the treatment was 14.6, which according to the scoring guide, denotes moderate to moderately severe depression symptoms. After the treatment was administered, the average PHQ-9 total score decreased to 10.5, which according to the scoring guide highlights mild to moderate depression symptoms. A linear regression was also conducted to determine whether the dosage is a good predictor of the change in depression. The r2 value shows that the model explains roughly 23% (r2 -0.236) of the data. When asked to provide a percentage to characterize the change in symptoms, an average decline of 42% was verbally indicated by participants when asked to report the percentage of decreased pain. A similar self-reported improvement was seen with increased activity, where 38% of participants increased their activity. Conclusion: The interview and survey results indicate that patients seek medical cannabis to relieve medical ailments and have reported better-improved quality of life, mobility, and decreased pain. This finding aligned with previous studies which also found increased overall condition and energy as the most significant perceived benefits. The results may provide further clinical evidence to support the use of medical cannabis for depression symptoms and support more extensive research studies in the future.
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 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».