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- All Subjects: public health
- All Subjects: Naloxone
- Creators: Hruschka, Daniel
Methods: Parents of children six months to five years old (N = 975) were randomly exposed to one of four high-threat/high-efficacy messages (narrative, statistical, combined, control) and completed a follow-up survey. Differences between message conditions were assessed with one-way ANOVAs, and binary logistic regressions were used to show how constructs predicted intentions.
Results: There were no significant differences in the ANOVA results at p = .05 for EPPM variables or risk EPPM variables. There was a significant difference between message conditions for perceived manipulation (p = 0.026), authority, (p = 0.024), character (p = 0.037), attention (p < .000), and emotion (p < .000). The EPPM model and perceptions of message model (positively), and the risk EPPM model and fear control model (negatively), predicted intentions to vaccinate. Significant predictor variables in each model at p < .05 were severity (aOR = 1.83), response efficacy (aOR = 4.33), risk susceptibility (aOR = 0.53), risk fear (aOR = 0.74), issue derogation (aOR = 0.63), perceived manipulation (aOR = 0.64), character (aOR = 2.00), and personal relevance (aOR = 1.88). In a multivariate model of the significant predictors, only response efficacy significantly predicted intentions to vaccinate (aOR = 3.43). Compared to the control, none of the experimental messages significantly predicted intentions to vaccinate. The narrative and combined conditions significantly predicted intentions to search online (aOR = 2.37), and the combined condition significantly predicted intentions to talk to family/friends (aOR = 2.66).
Conclusions: The EPPM may not be effective in context of a two-way threat. Additional constructs that may be useful in the EPPM model are perceptions of the message and fear control variables. One-shot flu vaccine messages will be unlikely to directly influence vaccination rates; however they may increase information-seeking behavior. The impact of seeking more information on vaccination uptake requires further research. Flu vaccine messages should be presented in combined form. Future studies should focus on strategies to increase perceptions of the effectiveness of the flu vaccine.
Abstract
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs)
towards opioid overdose management and to assess the effect of online training on opioid
overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and
respond to opioid overdose situations.
Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid
Overdose Attitude Scale (OOAS) surveys were administered electronically to five BHTs in
2020. Data obtained were de-identified. Comparisons between responses to pre-and post-surveys questions were carried out using the standardized Wilcoxon signed-rank statistical test(z). This study was conducted in a residential treatment center (RTC) with the institutional review board's approval from Arizona State University. BHTs aged 18 years and above, working at this RTC were included in the study.
Interventions: An online training was provided on opioid overdose response (OOR) and
naloxone administration and on when to refer patients with opioid use disorder (OUD) for
medication-assisted treatment.
Results: Compared to the pre-intervention surveys, the BHTs showed significant improvements
in attitudes on the overall score on the OOAS (mean= 26.4 ± 13.1; 95% CI = 10.1 - 42.7; z =
2.02; p = 0.043) and significant improvement in knowledge on the OOKS (mean= 10.6 ± 6.5;
95% CI = 2.5 – 18.7; z =2.02, p = 0.043).
Conclusions and Relevance: Training BHTs working in an RTC on opioid overdose response is
effective in increasing attitudes and knowledge related to opioid overdose management. opioid
overdose reversal in RTCs.
Keywords: Naloxone, opioid overdose, overdose education, overdose response program
Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.