Medical and psychological predictors of prescription opioids dependence during chronic pain treatment
| Autor: | Carlos Alonso-Garrido, José Luis Carballo, Ainhoa Coloma-Carmona, Jesús Rodríguez-Marín, Ana Pérez-Carbonell |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
medicine.medical_specialty
business.industry Chronic pain medicine.disease 03 medical and health sciences 0302 clinical medicine Sample size determination Physical therapy medicine 030212 general & internal medicine Medical prescription Radiation treatment planning Prescribed drugs business Psychoactive substance dependence 030217 neurology & neurosurgery Applied Psychology Depression (differential diagnoses) |
| Zdroj: | European Review of Applied Psychology. 68:199-204 |
| ISSN: | 1162-9088 |
| DOI: | 10.1016/j.erap.2018.10.002 |
| Popis: | Introduction Due to the increasing rates of prescription opioids (PO) dependence, there is a need for designing evaluations that detect, before initiating treatment, those patients with a greater probability of developing PO dependence. Objective To develop a mathematical model for predicting PO dependence in chronic pain patients using medical and psychological variables. Method Participants were 210 consumers of PO, of which 47.1% met three or more DSM-IV-TR criteria for psychoactive substance dependence. Socio-demographic, medical and psychological variables were assessed. Results The number of prescribed drugs, years in treatment, PO consumed and specialists visited is significantly higher in opioid-dependent patients, which consume more anxiolytics and have a greater pain intensity and interference. The predictive model created with the variables number of prescribed drugs and opioids consumed, depression, use of anxiolytics and pain intensity correctly classifies 71.5% of opioid-dependent patients. Conclusions Medical as well as psychological variables seem to be involved in the development of PO dependence, so they both should be considered in the treatment planning. Further studies with a bigger sample size are needed to analyze the applicability of the model to identify PO-dependent patients. |
| Databáze: | OpenAIRE |
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