6/27/2016 Acknowledgments & disclosure Merrill‐Palmer Skillman Institute Maximizing reach via computer‐delivered screening & brief intervention for substance use I gratefully acknowledge my colleagues (Dace Svikis, Robert Sokol, Kim Yonkers, Funding for this research is from the NIH (DA000516, Emily Grekin, Grace Chang, Golfo Tzilos, Ken Resnicow, Ronald Strickler, James among pregnant & LeBreton, Gregory Goyert, James Janisse, George Divine), lab students and DA014621, DA021329, DA018975, DA021668, DA021329, The speaker is part owner of a company marketing authorable postpartum women staff (Jessi Beatty, Casey Thacker, Lucy McGoron, Amy Loree, Amy Graham, DA029050, AA020056, DA036788) the CDC (CE001078, Ebonie Guyton, Shatoya Rice, Erica Montgomery, Peter Preonas, Erica DANSK SELSKAB computerized intervention software. DP006082), and Joe Young Sr./Helene Lycacki funds from the FOR PSYKOSOCIAL Hohentanner), the participants who shared their time, the Detroit Medical MEDICIN Steven J. Ondersma, PhD, Professor State of Michigan. Center, the Henry Ford Health System, and the Wayne State University Department of Psychiatry & Behavioral Neurosciences JUNE 6, 2016 Physician’s Group. Merrill‐Palmer Skillman Institute 1. Why technology matters WHY TECHNOLOGY MATTERS 2. Empathic technology? (Hint: REACH is crucial) 3. e‐SBIRT trial data The problem? We’re missing far too many 3.5% Of 22.5 million 11.6% people in the U.S. Population impact needing treatment for = Effect size X reach drug or alcohol 84.9% use in 2014… Did not receive treatment and felt didn't need it Received specialty treatment Did not receive treatment, but felt needed it 1
6/27/2016 Screening, Brief Intervention, & 57% Referral to Treatment (SBIRT) Proactive screening and brief intervention …proportion of participants randomized to the brief counseling group who actually received the intervention (SIPS trial; Kaner et al., 2013) Does anyone have time? 4.4 hours per working day …for a primary care physician to conduct all recommended screening and prevention activities (Yarnall et al., 2004) And what do they do while waiting…? THE GOAL is to turn patient use of interactive technology, in the waiting area, into a routine part of health services; and to use that window to deliver evidence‐based screening and behavioral health interventions. 2
6/27/2016 But isn’t that a little cold? “Users can be induced to Dr. Clifford Nass Dr. Clifford Nass behave as if computers Stanford University were human, even though Stanford University 1958‐2013 users know that the 1958‐2013 machines do not actually “…I discovered people possess “selves” or human were interacting with motivations. We refer to THE FACTORS that make all therapies computers using such assignment of human the same social rules attitudes, intentions, or and expectations that effective (i.e., the common factors) are ones motives to non‐human they use when they entities as ethopoeia , the interact with other that are uniquely human. classical Greek word for people.” such attributions. “ Bruce Wampold, 2012 ( New Scientist , 2010) (Nass et al., 1993) Social responses to computers 10 Generic Flattery 8 e‐SBIRT 6 4 Electronic screening and brief intervention 2 with pregnant and postpartum women 0 Positive Enjoyment Rating of Willing to affect computer continue Fogg & Nass, 1997 e‐SBIRT for alcohol use in pregnancy: Pilot trial (Ondersma et al., 2015) Question 1: PARTICIPANTS Can a technology‐delivered brief intervention Total of 48 pregnant women screening positive for alcohol use reduce alcohol use in pregnancy? risk at intake prenatal care appointment (mean ≈ 12 weeks gestation) Most were African‐American and of low to low‐moderate SES; few had a history of treatment for alcohol use disorders 3
6/27/2016 e‐SBIRT for alcohol use in pregnancy: Pilot trial e‐SBIRT for alcohol use in pregnancy: Pilot trial (Ondersma et al., 2015) (Ondersma et al., 2015) METHOD INTERVENTION Women were screened and randomized to intervention vs. The initial 20‐minute brief intervention was largely based on time control conditions immediately following recruitment MI principles, tailored to current quit status, health beliefs, and reactivity Follow‐up was completed during the postpartum hospital stay, after the participant had slept but before leaving the Intervention participants also received three subsequent hospital. Primary outcome = any drinking, past 90 days (TLFB) tailored mailings, each a single page e‐SBIRT for alcohol use in pregnancy: Pilot trial e‐SBIRT for alcohol use in pregnancy: Pilot trial (Ondersma et al., 2015) (Ondersma et al., 2015) e‐SBIRT for alcohol use in pregnancy: Pilot trial e‐SBIRT for alcohol use in pregnancy: Pilot trial (Ondersma et al., 2015) (Ondersma et al., 2015) Candace, you said that you had quit drinking even before we talked to you. You made that decision mostly because quitting drinking would improve the health of your baby. Your decision to stop drinking could also save you up to 400 dollars over the course of your pregnancy! 4
6/27/2016 e‐SBIRT for alcohol use in pregnancy: Pilot trial e‐SBIRT for alcohol use in pregnancy: Pilot trial (Ondersma et al., 2015) (Ondersma et al., 2015) Control Intervention Variable (n = 24) (n = 24) ANALYSIS African‐American 21 (88%) 18 (75%) The primary outcome (any drinking in the past 90 days) was HS graduate 14 (58%) 18 (75%) examined as a function of experimental condition, using a logistic model controlling for prior drinking. Any public assistance 20 (83%) 19 (79%) 81.3% of participants were successfully evaluated at follow‐ Alcohol use disorder 5 (21%) 7 (29.2) up. Loss did not differ between conditions, and was due to miscarriage (44%), delivering outside of the targeted health Prior treatment 0 (0%) 2 (8%) system (33%), and inability to contact (22%) A pilot RCT of e‐SBIRT for e‐SBIRT for alcohol use in pregnancy: Pilot trial alcohol use in pregnancy (Ondersma et al., 2015) 30% 45% Any drinking, past 90 days Miscarriage, LBW, or NICU stay 40% 25% 35% 20% 30% OR= 3.2 OR= 3.3 25% ( p = .20) ( p = .09) 15% 20% 10% 15% 10% 5% 5% 0% 0% e‐SBIRT Control e‐SBIRT Control e‐SBI for smoking in pregnancy (N = 107; Ondersma et al., 2012) Question 2: SAMPLE N = 110 primarily African‐American pregnant Can a technology‐delivered brief intervention women reporting active smoking, proactively reduce tobacco use in pregnancy? recruited from a Detroit prenatal care clinic 5
6/27/2016 e‐SBI for smoking in pregnancy e‐SBI for smoking in pregnancy (N = 107; Ondersma et al., 2012) (N = 107; Ondersma et al., 2012) 35% 30% * 25% INTERVENTION 20% Intervention was a single 20‐minute session Control 15% following the “5As” approach (Ask, Advise, e‐SBI 10% Assess, Assist, Arrange) plus 5Rs (motivational 5% elements); it included tailored video clips of a 0% physician and women who had quit 7‐day abstinence per Abstinent per cotinine breath CO/self‐report Help‐seeking following brief intervention 70% * 60% 50% e‐SBI 40% Control 30% Question 3: 20% 10% Can a technology‐delivered brief 0% intervention reduce postpartum drug use? Called Quitline Talked to MD/RN e‐SBIRT for postpartum drug use e‐SBIRT for postpartum drug use (Ondersma et al., 2007, 2013) (Ondersma et al., 2007, 2013) SAMPLES SAMPLES INTERVENTION Postpartum women (N = 107 and N = 143) in Postpartum women (N = 107 and N = 143) in Based primarily on brief intervention private hospital rooms, after having slept; private hospital rooms, after having slept; principles; provided information, feedback, primarily African‐American and low‐income, primarily African‐American and low‐income, and optional goal setting sections with heavy all reporting drug use prior to becoming all reporting drug use prior to becoming use of synchronous interactivity, reflections, pregnant. pregnant. empathy, affirmations, & humor. 6
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