Dataset Information

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.

ABSTRACT:

Objectives

The 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.

Design

Cross-sectional study.

Setting

Rural county in the Appalachian region of the USA.

Participants

A 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 measure

Opioid addiction helping behaviour.

Results

The regression model was significant (F _{(6, 180)}=26.191, p<0.001) and explained 44.8% of the variance in opioid addiction helping behaviour (R²=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.

Conclusions

PRECEDE-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.

SUBMITTER: Wilkerson AH

PROVIDER: S-EPMC10193052 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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.

Wilkerson Amanda H AH Sharma Manoj M Davis Robert E RE Stephens Philip M PM Kim Richard W RW Bhati Deepak D Nahar Vinayak K VK

BMJ open 20230516 5

<h4>Objectives</h4>The 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 ad ...[more]

PMID: 37192792

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Project description:BackgroundThe prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective.ObjectiveThe aim of this study was to identify existing obesity-related mHealth apps in India and evaluate the potential of the apps' contents to promote health behavior change. This study also aimed to discover the general quality of obesity-related mHealth apps.MethodsA systematic search for obesity-related mHealth apps was conducted in both the Google Play Store and the Apple App Store. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) and the potential of the sample apps' contents to promote health behavior change was assessed using the PRECEDE-PROCEED Model (PPM).ResultsA total of 13 apps (11 from the Google Play Store and 2 from the Apple App Store) were considered eligible for the study. The general quality of the 13 apps assessed using MARS resulted in mean scores ranging from 1.8 to 3.7. The bivariate Pearson correlation between the MARS rating and app user rating failed to establish statistically significant results. The multivariate regression analysis result indicated that the PPM factors are significant determinants of health behavior change (F3,9=63.186; P<.001) and 95.5% of the variance (R2=0.955; P<.001) in the dependent variable (health behavior change) can be explained by the independent variables (PPM factors).ConclusionsIn general, mHealth apps are found to be more effective when they are based on theory. The presence of PPM factors in an mHealth app can greatly influence the likelihood of health behavior change among users. So, we suggest mHealth app developers consider this to develop efficient apps. Also, mHealth app developers should consider providing health information from credible sources and indicating the sources of the information, which will increase the perceived credibility of the apps among the users. We strongly recommend health professionals and health organizations be involved in the development of mHealth apps. Future research should include mHealth app users to understand better the apps' effectiveness in bringing about health behavior change.

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Dataset Information

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.

Objectives

Design

Setting

Participants

Primary outcome measure

Results

Conclusions

Publications

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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