Behavioral Correlates for Quitting Opioids among Opioid-Dependent Pregnant and Non-Pregnant Women of Childbearing Age in Rural Appalachia
Notice bibliographique
Résumé
Background: The opioid epidemic is particularly worrisome in the pregnant population, wherein concerns are raised about the health of a mother and her child, resulting in an alarming incidence and prevalence of Neonatal Abstinence Syndrome (NAS). The 2016 National Survey on Drug Use and Health (NSDUH) show the rate of illicit psychoactive substance use among the females aged 12 or older was 15.5% in the past year. Among pregnant women aged 15 to 44, 6.3% were illicit psychoactive substance users. In Tennessee, the number of hospital discharged NAS cases from 2002 to 2013 increased from 1.50 to 16.6 cases per 1,000 live births. This number is triple the national incidence of NAS cases over the same time period. Between 2013 and 2016, at least 52.5% of children diagnosed with NAS in Tennessee have had exposure to one prescription drug, while 27.2% were exposed to a combination of prescribed medications and illicit substances. We examined the behavioral correlates that determine the wish to quit opioids or not to quit opioids among opioid-dependent pregnant and non-pregnant women in rural Appalachia. Methods: Ten women of childbearing age, whether pregnant or not, who were receiving prescribed opioids, were recruited to join the study. All the participating women were also receiving physician-managed Medication Assisted Treatment (MAT) therapy for the treatment of severe opioid use disorder, or are currently being prescribed an opioid medication. Study variables included age, Hamilton Depression Rating Scale (HAM-D), Visual Analogue Scale – Pain (VAS-P), the Modified Opiate Craving Scale (MOCS), the Visual Analog Commitment to Quit Opiates, the McGill Pain Index (MPI), prescriptions, tobacco and nicotine use, illicit substance use, the Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES), and the Adverse Childhood Experience (ACE) questionnaire. The HAM-D, MOCS, MPI, and SOCRATES scores were log-transformed to approximate a normal distribution. Descriptive statistics and the Spearman’s rank correlation (with a 95% Confidence Interval) were conducted to examine significant behavioral correlates for quitting opioids. Results: Descriptive statistics show that women with higher HAM-D and MOCS scores are not likely to express willingness to quit opioids. There is a statistically significant strong positive correlation of 0.679 (pppp Conclusion: Women who recognize the need to quit opioids or are “taking steps” to quit are more likely to quit opioids. Women with high depression and pain scores are not likely to quit opioids. Non-opioid medications may reduce the number of opioid-dependent pregnant and non-pregnant women of childbearing age, and, in turn, lower the currently high incidence and prevalence rates of NAS.
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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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».