title: Predictors of painkiller dependence among people with pain in the general population.
abstract: OBJECTIVE
  Self-medication with painkillers is widespread and increasing, and evidence about influences on painkiller dependence is needed to inform efforts to prevent and treat problem painkiller use.
  
  
  METHODS
  Online questionnaire survey.
  
  
  METHODS
  People in the general population who had pain and used painkillers in the last month (N = 112).
  
  
  METHODS
  Pain frequency and intensity, use of over-the-counter and prescription painkillers, risk of substance abuse (Screener and Opioid Assessment for Patients with Pain [SOAPP] scale), depression, anxiety, stress, alexithymia, pain catastrophizing, pain anxiety, pain self-efficacy, pain acceptance, mindfulness, self-compassion, and painkiller dependence (Leeds Dependence Questionnaire).
  
  
  RESULTS
  In multiple regression, the independent predictors of painkiller dependence were prescription painkiller use (β 0.21), SOAPP score (β 0.31), and pain acceptance (β -0.29). Prescription painkiller use mediated the influence of pain intensity. Alexithymia, anxiety, and pain acceptance all moderated the influence of pain.
  
  
  CONCLUSIONS
  The people most at risk of developing painkiller dependence are those who use prescription painkillers more frequently, who have a prior history of substance-related problems more generally, and who are less accepting of pain. Based on these findings, a preliminary model is presented with three types of influence on the development of painkiller dependence: 1) pain leading to painkiller use, 2) risk factors for substance-related problems irrespective of pain, and 3) psychological factors related to pain. The model could guide further research among the general population and high-risk groups, and acceptance-based interventions could be adapted and evaluated as methods to prevent and treat painkiller dependence.
authors.affiliation: University of Derby, Derby, UK.
authors.forename: James
authors.initials: J
authors.lastname: Elander
authors.forename: Joana
authors.initials: J
authors.lastname: Duarte
authors.forename: Frances A
authors.initials: FA
authors.lastname: Maratos
authors.forename: Paul
authors.initials: P
authors.lastname: Gilbert
mesh_terms: D000328:Adult; D000342:Affective Symptoms / Q000453:epidemiology; D000368:Aged; D000700:Analgesics / Q000627:therapeutic use; D000701:Analgesics, Opioid / Q000627:therapeutic use*; D001007:Anxiety / Q000453:epidemiology; D003863:Depression / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009293:Opioid-Related Disorders / Q000453:epidemiology*; D010146:Pain / Q000188:drug therapy*; D018570:Risk Assessment; D012307:Risk Factors; D013315:Stress, Psychological / Q000453:epidemiology; D019966:Substance-Related Disorders / Q000453:epidemiology; D011795:Surveys and Questionnaires; D055815:Young Adult
chemical_list: D000700:Analgesics; D000701:Analgesics, Opioid
keywords: Addiction; Analgesics; Dependence; Medication; Pain