Browsing by Author "Phalen, Peter"

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    Consumer factors predicting level of treatment response to illness management and recovery
    (American Psychological Association, 2017-12) White, Dominique A.; McGuire, Alan B.; Roudebush, Richard L.; Luther, Lauren; Anderson, Adrienne; Phalen, Peter; McGrew, John H.; Psychology, School of Science
    OBJECTIVE: This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. METHOD: Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. RESULTS: Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p < .001, R2 = .248, R2 change = .05. Additionally, we found that higher levels of maladaptive coping at baseline were predictive of higher levels of adaptive coping at follow-up, F(2, 180) = 5.29, p < .02, R2 = .38, R2 change = .02. Evidence did not support additional predictors. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Previously, consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record
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    Evaluation of post-discharge engagement for emergency department patients with opioid use history who received telehealth recovery coaching services
    (BMC, 2023-02-11) Watson, Dennis P.; Phalen, Peter; Medcalf, Spencer; Messmer, Sarah; McGuire, Alan; Social and Behavioral Sciences, School of Public Health
    Background: In recent years, emergency departments (EDs) across the nation have implemented peer recovery coach (PRC) services to support patients who use opioids. The majority of such interventions discussed in the literature follow an in-person modality where PRCs engage patients directly at the ED bedside. However, the use of telehealth services in EDs is becoming more popular. These services connect PRCs with ED patients in real-time via secure communications technology, and very little is known about the service- and clinical-based outcomes with which they are associated. The current study sought to assess factors associated with successful post-discharge follow-up of patients with a history of opioid use who received PRC telehealth services while in the ED. Method: Data come from records for 917 patients who engaged with a telehealth PRC one or more times (1208 total engagements) at 1 of 13 EDs within the same health system. A multilevel Poisson regression model was used to assess the degree to which variables predicted successful post-discharge follow-up, defined as the number of times a PRC successfully spoke with the patient each month after ED discharge. Results: At least one follow-up was successfully completed by a PRC for 23% of enrolled patients. Significant predictors of successful follow-up included patient employment at baseline (Incidence Rate Ratio [IRR]: 2.8, CI: 2.05-3.9), living in a rural area (IRR: 1.8, CI: 1.04-3.2), PRC provision of referrals (IRR: 1.7, CI: 1.2-2.2), number of ED encounters in the previous 365 days (IRR: 0.99, CI: 0.98-0.99), and duration of the initial PRC telehealth interaction (IRR: 0.87, CI: 0.85-0.88). Conclusion: Given that relationship development is a key tool in the PRC profession, understanding successful follow-up associated with telehealth engagement has unique importance. The results have potential utility for planning and implementing peer telehealth services in EDs and other locations, which is needed for the development of the PRC profession and the likely expansion of peer telehealth services.
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    Fentanyl related overdose in Indianapolis: Estimating trends using multilevel Bayesian models
    (Addictive Behaviors, 2018-03-20) Phalen, Peter; Ray, Bradley; Watson, Dennis P.; Huynh, Phillip; Green, Marion S.
    Introduction: The opioid epidemic has been largely attributed to changes in prescribing practices over the past 20 years. Although current overdose trends appear driven by the opioid fentanyl, heroin has remained the focus of overdose fatality assessments. We obtained full toxicology screens on lethal overdose cases in a major US city, allowing more accurate assessment of the time-course of fentanyl-related deaths. Methods: We used coroner data from Marion County, Indiana comprising 1583 overdose deaths recorded between January 1, 2010 and April 30, 2017. Bayesian multilevel models were fitted to predict likelihood of lethal fentanyl-related overdose using information about the victim's age, race, sex, zip code, and date of death. Results: Three hundred and seventy-seven (23.8%) overdose deaths contained fentanyl across the seven-year period. Rates rose exponentially over time, beginning well below 15% from 2010 through 2013 before rising to approximately 50% by 2017. At the beginning of the study period, rates of fentanyl overdose were lowest among Black persons but increased more rapidly, eventually surpassing Whites. Currently, White females may be at particularly low risk of fentanyl overdose and Black females at high risk. Rates were highest for younger and middle-aged groups. Over time, fentanyl was more likely detected without the presence of other opioids. Conclusions: Fentanyl has increasingly been detected in fatal overdose deaths in Marion County. Policy and program responses must focus on education for those at highest risk of fentanyl exposure and death. These responses should also be tailored to meet the unique needs of high-risk demographics.