Smartphone apps talk given at the International Conference for Behavioral medicine

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Smartphone apps talk given at the International Conference for Behavioral medicine

  1. 1. Presenting on behalf of: Abby C. King, PhDStanford Prevention Research Center Stanford University Eric B. Hekler, PhD School of Nutrition and Health Promotion Arizona State University
  2. 2. Collaborators: Abby King Tom Robinson Matt Buman Lauren Grieco Frank Chen Jesse Cirimele Beth Mezias Banny Banerjee Martin Alonso
  3. 3. Health promotion interventions Evidence-based Cost-effective Tailored Easy to disseminate Promote maintenance
  4. 4. Introduction Mobile Interventions for Lifestyle Exercise and Eating at Stanford (MILES) NHLBI-funded Challenge Grant (10/09 – 08/12)  PI- King, 1RC1HL099340-01 Status: Ran wave 1 with 36 older adults; iterated on design and almost complete with second wave of data collection for final sample of 80.
  5. 5. Purpose Develop theoretically meaningful smartphone apps for midlife & older adults Physical activity & sedentary behavior Passively assess PA & SB Provide just-in-time feedback for behavior change
  6. 6. Activity Algorithm Validation N=15, Men & Women, Mean Age=55 12 laboratory-based activities 3-4 min each Hip- and pocket-worn Android phones Compared to Actigraph & Zephyr Bioharness Hekler, Buman, et al, 2010, November
  7. 7. Validation Results Comparison of Phone to Actigraph "Counts" Minute-level "counts" 1000Phone AUC m/s3 800 600 y = 0.09x + 55.1 400 R² = 0.83 200 0 0 2000 4000 6000 8000 10000 12000 Actigraph "counts" Hekler, Buman, et al, 2010, November
  8. 8. The “Apps” Control:mTrack mSmiles mConnect Calofiric King, Hekler, et al. April, 2012, Hekler, et al. 2012, Hekler et al. 2011
  9. 9. Components study arms mTrack mSmiles mConnect CalorificPush component X X X XPull component X X X X"Glance-able" display X X X XPassive activity assessment X X X XReal-time feedback X X X XSelf-monitoring X X X X“Help” tab X X X X King, Hekler, et al. April, 2012, Hekler, et al. 2012, Hekler et al. 2011
  10. 10. Components study arms mTrack mSmiles mConnect CalorificPush component X X X XPull component X X X X"Glance-able" display X X X XPassive activity assessment X X X XReal-time feedback X X X XSelf-monitoring X X X X“Help” tab X X X XGoal-setting X XFeedback about goals X XProblem-solving X XReinforcement X X XVariable reinforcement schedule X XAttachment X"Play" X"Jack pot" random reinforcement XSocial norm comparison XCompetition/collaboration X King, Hekler, et al. April, 2012, Hekler, et al. 2012, Hekler et al. 2011
  11. 11. MILES Study Design Pre- Baseline Feedback Follow up study Week1 Week2 Week8 Visit1 Visit2, check in Visit3 mTrack (Cognitive App, n=20)Randomize mSmiles (Affect App, n=20) mConnect (Social App, n=20) Diet Tracker Control App (n=20)Assess: Assess: Activity Assessment, ContinuousModerators Ecological Momentary Assessment, Daily AcceptabilitySelf-report Self-reportPA, Sed Beh Real-time use of phone features PA, Sed Beh King, Hekler, et al. April, 2012, Hekler, et al. 2012, Hekler et al. 2011
  12. 12. Preliminary Activity Results (n = 30 inactive, smartphone-naive adults ages > 45 yrs) 2-mos Daily Increases in MVPA vs. Control (Calorific) 20 MVPA Net Increase Minutes/Day - Smartphone Accelerometer P < .01 15 P < .01 10 5 P = .39 ??? ??? ???King, Hekler, Grieco, Winter, Buman, et al., Ann Behav Med, 2012 (abstract)
  13. 13. Preliminary Activity Results (n = 30 inactive, smartphone-naive adults ages > 45 yrs) 2-mos Daily Increases in MVPA vs. Control (Calorific) 20 MVPA Net Increase Minutes/Day - Smartphone Accelerometer P < .01 15 P < .01 10 5 P = .39 Cognitive Affect SocialKing, Hekler, Grieco, Winter, Buman, et al., Ann Behav Med, 2012 (abstract) Which App for WHOM?
  14. 14. Preliminary Eating Results 12 10∆Consumption servings/wk 8 6 4 2 0 -2 -4 -6 Food-tracking App Average of Activity Hekler, King, et al. April, 2012 (N=30) Apps
  15. 15. Conclusions & Next Steps Game dynamics/operant conditioning and social comparison appear more influential than goal- setting and feedback  May be due to specificity of data Redesigned apps, running a second wave now Exploring the use of other research methods for testing (e.g., Multiphase Optimization Strategy, Linda Collins et al., 2010).
  16. 16. Thank you! Abby King king@stanford.edu Eric Heklerdesiginghealth.lab.asu.edu Twitter: @ehekler ehekler@asu.edu

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