Behavior analysis, technology, and the super-convergence. Jesse Dallery, Ph.D. Professor Dept of Psychology University of Florida
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1 Behavior analysis, technology, and the super-convergence Jesse Dallery, Ph.D. Professor Dept of Psychology University of Florida
2 Cyborg An organism to which exogenous components have been added for the purposes of adapting to new environments.
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4 Technology and health behavior Health behavior - Cigarette smoking, physical inactivity, alcohol abuse, unhealthy diet, medication adherence
5 Morbidity associated with unhealthy behavior
6 Technology and health behavior Automated hovering over health behavior during every activities (Asch, Muller, & Volpp, 2012)
7 Automated Hovering Behavior Presence/absence of behavior Ecological Momentary Assessment Physical activity/inactivity Accelerometers Medication adherence Medication Event Monitoring Systems Illicit and licit drug use Fluid- or breath-based detection
8 Automated nudging Behavior Presence/absence of behavior EMA Physical activity/inactivity accelerometers Medication adherence MEMs Drug taking fluid- or breath-based detection
9 Automated nudging Antecedents Prompts Goals Instructions Encouragement mobile-phones, Internet, wearable devices Behavior Presence/absence of behavior EMA Physical activity/inactivity accelerometers Medication adherence MEMs Drug taking fluid- or breath-based detection
10 Automated nudging Antecedents Prompts Goals Instructions Encouragement mobile-phones, Internet, wearable devices Behavior Presence/absence of behavior EMA Physical activity/inactivity accelerometers Medication adherence MEMs Drug taking fluid- or breath-based detection Consequences Monetary consequences Social consequences Conditioned reinforcers (points, badges, graphed progress) mobile-phones, Internet, wearable devices, gaming devices
11 We have the science, we have the technology, we can re-build a repertoire Contingency Management + Information Technology = Smoking cessation CHOICE Drug Use Abstinence
12 Contingency management (CM) Consequences contingent on objective evidence (breath carbon monoxide, CO) of smoking abstinence Negative CO Sample $ Voucher $ Goods and services
13 Potential barriers Response effort: home visits or clinic visits High rate of CO sampling (half- life of breath CO 6 hr) Treatment duration Financial cost Access and dissemination
14 One Solution Internet-based contingency management - CO monitoring via a web-camera from the participant s home - Low response effort - Sampling can continue on a frequent, sustained basis (2/day, 7/week)
15 Timeline of experimental conditions Baseline Shaping Abstinence Induction Thinning Return to Baseline Voucher Value ($) Ascending, reset, bonuses Consecutive Negative CO samples
16 Internet-based contingency management Dallery, J., Glenn, I., & Raiff, B. R. (2007). An Internet-based voucher reinforcement program for smoking cessation. Drug and Alcohol Dependence, 86,
17 Conclusions Feasible: Over 97% of the 1,120 CO samples were collected Efficacy: Over 65% negative CO samples during abstinence induction condition (out of 400) Dallery & Glenn, 2005; Dallery, Glenn, Raiff, 2007; Glenn & Dallery, 2007,
18 Technological Enhancements Mike Grabinski, developer Secure, user-friendly website Participants can logon from any computer that has Internet access Only necessary to loan CO monitors and webcameras if needed
19 Video Submissions Video stream is sent directly to the study server over a secure, encrypted connection Video stream Server in NYC
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24 100 Median percent negative samples Contingent (n= 39) Noncontingent (n = 38) Group
25 Participants
26 Treatment Acceptability Questionnaire 100 How was the Internet Program? VAS (0= not at all, 100 = very much) Mean + SEM Easy Helpful Convenient Effective Fair Question Contingent Noncontingent
27 Adolescent Smokers Reynolds, Dallery, Shroff, Patak, Leras (2008). A web-based contingency management program with adolescent smokers. JABA.
28 Adolescent smokers in rural Appalachia Contingent: n = 29 CO ppm: Control: n = 23 CO ppm: NIH Grant: RC1CA PI: B. Reynolds
29 Adolescent smokers in rural Appalachia Contingent: n = 29 * * CO ppm: * 5.13 * 6.22 Control: n = 23 CO ppm: * * Baseline Shaping Abstinence Thinning Return to Baseline * Significant difference from baseline Significant difference from control group NIH Grant: RC1CA PI: B. Reynolds
30 Adult smokers in Appalachian Kentucky N=68 Stoops, Dallery, Schoenberg, Fields, Martin, Casey, Nuzzo, Wong (2009). An Internet- Based Smoking Cessation Intervention in Appalachian Kentucky Smokers. Drug and Alcohol Dependence, 105,
31 Previous work at UF Internet-based CM feasible, acceptable, and efficacious Locally-derived samples of participants Grant-funded vouchers Except: Dallery, Meredith, Glenn (2008). A deposit contract method to deliver abstinence reinforcement for cigarette smoking. JABA, 41
32 Ongoing effectiveness trial Capitalizing on the reach of the Internet: providing access to any qualified smoker in the US Incorporating a deposit contract Possible roles of deposit - Motivational - Deterrent to non-smokers - Cost-offsets
33 ~ufsmokelab
34 Deposit and vouchers All participants pay a $50 deposit via PayPal, recouped based on abstinence or CO submissions After $50 has been earned, vouchers are provided for remainder of treatment All vouchers go to participants PayPal accounts
35 Median 11/10/2011
36 Participant
37 11/10/2011
38 Access
39 Internet-based group contingencies Social network procedure using small groups (e.g., n=4) of smokers Integrated discussion board into Mōtiv8 architecture All members of a network must meet criteria to receive vouchers shared goals, social support, and potential for sustainability Meredith, S., Grabinski, M., & Dallery, J. (2011). Internet-based group contingencies to promote abstinence from cigarette smoking. Drug and Alcohol Dependence, 118,
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44 Results Meredith, S., Grabinski, M., & Dallery, J. (2011). Internetbased group contingencies to promote abstinence from cigarette smoking. Drug and Alcohol Dependence, 118, Posts on support forum total (mean # posts/participant = 9.8, S.D. ± 5.7) - 65% rated positive, 34% neutral, 1% negative (Speltz et al., 1982)
45 CB MB KK CB: I am positive we can do this---- one step at a time. CO level % of bonuses earned MB: Let's Make Some Money!!!!!!!!!!!!!!!!!!!!!!!!!!! KK: Great job people! For once we all made it # of Posts Day
46 MC KT BB MC: First day in about 3 years I have left the house without a lighter. CO level % of bonuses earned KT (in reply to above comment): that's really good! BB: Haven't smoked yet today but got the anxiety and craving...congrats to everyone so far # of Posts Day
47 JY KM ER CO Level # of Posts % of bonuses earned JY (didn t hit a tapering goal): Well I suck, missed my goal by one friggin number. I apologize teammates. I really put forth my best efforts today. You guys are doing great! Tomorrow is a new day, and Q-Day, I have no smokes so I wont smoke any. KM: ER, your graph is looking good!! (although a little group participation would be nice ) I only mean that JY and Myself would love to hear from you about how you are doing it and how well you are handling the change. What methods are you using?? Just drop a line from time to time!!! Day
48 Growth of the treatment Other behavior - Self-monitoring of blood glucose - Exercise (Kurti & Dallery, 2013) - Medication Adherence - Alcohol Raiff & Dallery (2010). Internet-based contingency management to improve adherence with blood glucose testing recommendations for teens diagnosed with Type 1 diabetes. JABA
49 Evolution of the treatment R 2 =1.0 Accessibility Time
50 Future - Making access easier Building prototypes to collect breath CO or salivary cotinine, transmitted via mobile phone User authentication via face recognition or radio frequency identification (RFID)
51 Selfdeposits Sponsor deposits Individual CM Group CM
52 Cost Access Contingency Management
53 Information Technology Internet Mobile phone Access Cost Behavioral Technology Deposit Contracts Social contingencies Other Contingency Management
54 Dissemination Potential Social Support Tailoring Anonymity Linking Behavioral Science with Technology Temporal Flexibility Treatment Fidelity Cost effectiveness Access
55 The super-convergence
56 The super-convergence Digital and Information Technology Health Behavior Behavioral Technology
57 Behavior analysis, technology, and the superconvergence
58 Behavior analysis, technology, and the superconvergence Resistance is futile
59 C4TBH.ORG
60 Acknowledgments Collaborators Darragh Devine, Ph.D. Mark Gold, M.D. Michael Grabinski, B.A., MCSD Brady Reynolds, Ph.D. Lisa Marsch, Ph.D. Kenneth Silverman, Ph.D. Maxine Stitzer, Ph.D Paul Soto, Ph.D. Conrad Wong, Ph.D. Graduate Students Rachel Cassidy Philip Erb Brantley Jarvis Allison Kurti Matthew Locey Julie Marusich Steven Meredith Bethany Raiff Alana Rojewski Undergraduate Students Tia Bolivar Aaron Dumas Taryn Manders Zaday Sanchez Marissa Turturicci UF Grant Support College of Liberal Arts and Sciences NIH Grant Support R03DA (Dallery) R03DA15373 (Dallery) R21DA (Dallery) R21CA (Wong) R01DA (Dallery) R01DA (Dallery)
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