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Predisposing, enabling and reinforcing factors associated with opioid addiction helping behaviour in tri-state Appalachian counties: application of the PRECEDE-PROCEED model-cross-sectional analysis

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dc.contributor.authorWilkerson, Amanda H.
dc.contributor.authorSharma, Manoj
dc.contributor.authorDavis, Robert E.
dc.contributor.authorStephens, Philip M.
dc.contributor.authorKim, Richard W.
dc.contributor.authorBhati, Deepak
dc.contributor.authorNahar, Vinayak K.
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.contributor.otherUniversity of Nevada Las Vegas
dc.contributor.otherUniversity of Arkansas Fayetteville
dc.contributor.otherUniversity of Pittsburgh
dc.contributor.otherLincoln Memorial University
dc.contributor.otherColumbia University
dc.contributor.otherNewYork-Presbyterian Hospital
dc.contributor.otherCornell University
dc.contributor.otherWeill Cornell Medicine
dc.contributor.otherUniversity of Mississippi
dc.contributor.otherUniversity of Mississippi Medical Center
dc.date.accessioned2023-09-28T19:05:48Z
dc.date.available2023-09-28T19:05:48Z
dc.date.issued2023
dc.description.abstractObjectivesThe overdose epidemic was designated a 'Public Health Emergency' in the USA on 26 October 2017, bringing attention to the severity of this public health problem. The Appalachian region remains substantially impacted by the effects from years of overprescription of opioids, and subsequently opioid non-medical use and addiction. This study aims to examine the utility of the PRECEDE-PROCEED model constructs (ie, predisposing, reinforcing and enabling factors) to explain opioid addiction helping behaviour (ie, helping someone who has an opioid addiction) among members of the public living in tri-state Appalachian counties.DesignCross-sectional study.SettingRural county in the Appalachian region of the USA.ParticipantsA total of 213 participants from a retail mall in a rural Appalachian Kentucky county completed the survey. Most participants were between the ages of 18 and 30 years (n=68; 31.9%) and identified as men (n=139; 65.3%).Primary outcome measureOpioid addiction helping behaviour.ResultsThe regression model was significant (F-(6,F- 180)=26.191, p<0.001) and explained 44.8% of the variance in opioid addiction helping behaviour (R-2=0.448). Attitude towards helping someone with opioid addiction (B=0.335; p<0.001), behavioural skills (B=0.208; p=0.003), reinforcing factors (B=0.190; p=0.015) and enabling factors (B=0.195; p=0.009) were all significantly associated with opioid addiction helping behaviour.ConclusionsPRECEDE-PROCEED model constructs have utility to explain opioid addiction helping behaviour among individuals in a region greatly impacted by the overdose epidemic. This study provides an empirically tested framework for future programmes addressing helping behaviour related to opioid non-medical use.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationWilkerson, A. H., Sharma, M., Davis, R. E., Stephens, P. M., Kim, R. W., Bhati, D., & Nahar, V. K. (2023). Predisposing, enabling and reinforcing factors associated with opioid addiction helping behaviour in tri-state Appalachian counties: application of the PRECEDE–PROCEED model–cross-sectional analysis. In BMJ Open (Vol. 13, Issue 5, p. e066147). BMJ. https://doi.org/10.1136/bmjopen-2022-066147
dc.identifier.doi10.1136/bmjopen-2022-066147
dc.identifier.urihttps://ir.ua.edu/handle/123456789/10850
dc.languageEnglish
dc.language.isoen_US
dc.publisherBMJ
dc.rights.licenseAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectPUBLIC HEALTH
dc.subjectPREVENTIVE MEDICINE
dc.subjectEPIDEMIOLOGY
dc.subjectUNITED-STATES
dc.subjectCHRONIC PAIN
dc.subjectATTITUDES
dc.subjectOVERDOSE
dc.subjectSTIGMA
dc.subjectABUSE
dc.subjectRATES
dc.subjectMedicine, General & Internal
dc.titlePredisposing, enabling and reinforcing factors associated with opioid addiction helping behaviour in tri-state Appalachian counties: application of the PRECEDE-PROCEED model-cross-sectional analysisen_US
dc.typeArticle
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