Perceived need for care and stigma experiences among individuals with methamphetamine-related admissions to inpatient mental health wards
Notice bibliographique
Résumé
BACKGROUND: There are gaps in our understanding of treatment needs among people who use methamphetamine. We examined the demographics, perceived treatment needs, barriers to accessing care, and stigma experienced by an inpatient sample of people who use methamphetamine. METHODS: This study surveyed a convenience sample of patients admitted to psychiatry wards with a history of methamphetamine use in Winnipeg, Canada, between May 1 and July 31, 2019. The Perceived Need for Care Questionnaire (PNCQ-9) was used to assess treatment needs and barriers to care, and the Substance Use Stigma Mechanisms Scale (SU-SMS) was used to assess enacted, anticipated, and internalized stigma. Prevalence rates of perceived need, stigma, and demographic variables were determined. RESULTS: A total of 103 potential participants were identified, with 34 completing the survey. The most common age group was 21-30 years of age (41.2%); an approximate equal number of men and women; and almost all were single and never married (91.1%). Rates of perceived need for care were very high across all treatment types, including 91% identifying a need for medication treatment for their mental health or substance use. Despite the majority receiving care across the seven types of care described in the PNCQ-9, most felt they did not receive enough care. Unmet need for care was therefore high in many categories, including rates of 87% for counselling and skills training. The most common barriers to having needs met were a desire to self-manage substance use, and not receiving care after asking for help. Almost all participants reported experiencing stigma (94%). Stigma from family was endorsed significantly more than stigma from health care providers (p = 0.005). CONCLUSIONS: The average hospitalized person who uses methamphetamine in this sample is young, single, and has not completed any post-secondary education. High rates of perceived treatment need suggest an awareness of problems with methamphetamine, yet most interventions are perceived as inadequate. People who used methamphetamine felt highly stigmatized, particularly by their family members. Trial registration Registered with the Health Research Ethics Board at the University of Manitoba (Number HS22605 (H2019:072), renewed February 14, 2022).
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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) | 0,000 | 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 | 0,000 |
| 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 ».