The Use of Mobile Health Technology and Behavioral Economics to Encourage Adherence in Adolescents

The Use of Mobile Health Technology and Behavioral Economics to Encourage Adherence to Statins in Adolescents With Familial Hypercholesterolemia

Familial hypercholesterolemia (FH) affects over one million Americans and increases the risk of cardiovascular disease (CVD) by as much as 20-fold. Although the use of statins can substantially reduce this risk, adherence to statins in adults and adolescence is poor. In adults, lower rates of adherence are associated with an increased rate of CVD events and all-cause mortality, as well as an additional $44 billion annually in health care costs. Novel interventions are needed to improve medication adherence in patients with FH, starting in adolescents. An underused strategy to improve medication adherence incorporates the principles of behavioral economics. Traditional economic theory suggests that providing an incentive to perform a behavior will increase the frequency of that behavior. However, two prominent theories in behavioral economics, Present Bias and Loss Aversion, suggest that not all types of incentives are effective and that poorly structured incentives can actually be negative enforcers. With novel mobile health technologies (mHealth), interventions based on behavioral economics can now be studied on a larger scale. In this proposal, the investigators will test the use of monetary incentives ($30 per 30 days) to improve medication adherence in eligible subjects. The investigators will test the subject's adherence prior to the use of incentives (using the Morisky Medication Adherence Scale and the Wellth Mobile Application) and during the period of time the incentives are provided. Lastly, the investigators will test the subject's adherence (using the Morisky Medication Adherence Scale and Wellth App) during the 60 days following discontinuation of the incentives to determine if any effect of the incentive persists after the incentive is discontinued.

Preventing cardiovascular disease (CVD) in children and adolescents depend partly on the efficacy of the patients' self-management of their disease between clinic visits. One example of a health behavior that is particularly important for patients with CVD is medication adherence. Although the development of statins provides an opportunity to substantially reduce this risk of CVD, adherence to statins in both adults and adolescents is frequently inadequate. In recent study of youth prescribed a statin using claims data, nearly 75% of adolescents have at least one 90-day period of nonadherence. In adults, statin nonadherence is often as low as 50% and is associated with an increased risk for of CVD events and all-cause mortality, as well as almost $44 billion annually in additional health care costs. Unfortunately, successful interventions to improve statin adherence in adults are rare and there are no formally tested interventions to improve statin adherence in adolescents. It is critical novel interventions are developed that address medication adherence in adolescents with chronic diseases that increase the risk of CVD. Studies in adolescents with other diseases demonstrate that they appear to be particularly vulnerable to nonadherence across a wide-variety of conditions, including in adolescents with solid organ transplants and diabetes mellitus. Unfortunately, previous studies using text messaging reminders to take a medication or computerized action plans have not consistently shown positive results. Therefore, the significance of this proposal is that I will pilot a novel mobile health (mHealth) intervention that incorporates two theories in behavioral economics, Present Bias and Loss Aversion, to develop a better understanding of barriers to medication adherence in adolescents with cardiovascular risk factors. Traditional economic theory suggests that providing individuals with incentives to complete an action will lead to increased frequency of the occurrence of the desired action. However, behavioral economics studies in adult populations suggest that not all incentive structures are effective and that some incentives may act like negative enforcers. Studies suggest that patients are biased towards the present and often discount future risks, which is termed Present Bias. For instance, studies of Present Bias suggest that even small rewards, if provided frequently and immediately after a participant completes a desired task can improve adherence in adults. This strategy can be improved by using the principles of Loss Aversion, which suggest that individuals place more value on money or objects that they have than on new objects of the same value. Therefore, incentives framed as a loss can be more powerful than if it is framed as a gain. Unfortunately, only a few studies in adolescents have incorporated behavioral economics into interventions aimed at behavior change. One promising study in youth with type 1 diabetes mellitus found behavioral economics approaches could influence adherence to insulin regimens and glucose monitoring. Whereas diabetes mellitus is symptomatic if not properly managed, statins typically are used as primary prevention in asymptomatic patients with familial hypercholesterolemia (FH), which may require unique incentive structures. Although monetary incentives have been used with varying degrees of success in adults, it is unclear if these findings translate to adolescents. Adolescents may discount future events more, have different attitudes towards health, and have less mature cognitive function and capacities than adults. In addition, interventions that improve medication adherence are often resource intensive, which decreases the likelihood of larger scale implementation. Using an mHealth application may reduce costs by automating processes previously requiring human time and resources. Further, an mHealth intervention may be more successful as it uses a medium that is ubiquitous in adolescence. For instance, mobile applications that use gamification have demonstrated that adolescents find these health applications engaging and that they are interested in using mHealth in the management of their disease across a diverse set of socioeconomic and cultural backgrounds. As many health behaviors track into adulthood, establishing healthy behaviors early is crucial, which requires using developmentally appropriate interventions to promote adherence and ultimately minimize the risk of CVD. APPROACH Determine the efficacy of a monetary incentive to improve medication adherence. Aim 1.1 The investigators will determine the baseline adherence level in adolescents with FH prescribed a statin using the Morisky Medication Adherence Scale (MMAS). Aim 1.2 The investigators will determine the efficacy of a monetary incentive on medication adherence. Patients who are found to have low adherence according to the MMAS in Aim 1.1 will be enrolled into an intervention using the Wellth® mobile health application (Wellth App). Aim 1.3 Next, the investigators will determine adherence 60 days after the incentives have been discontinued using the tracking features in the Wellth App and the MMAS. Description of Wellth Application (Wellth App) The Wellth App has the following three features/functions: 1) it reminds users to take the prescribed medication through alerts/notifications on the smart phone; 2) it records medication adherence by determining whether the user takes the prescribed medication in the allotted time frame through photographic evidence termed a "check in"; and 3) it determines whether the predetermined reward is delivered to the patient instantly. The first function reminds the patient with an audible or haptic alert (i.e., vibration) using the phone's alert notification function. These alerts are not delivered through an email or text messaging service, but rather are similar to news alerts, alarms, or low battery notifications. The second function of the Wellth app is to document whether a patient takes the prescribed medication within the correct period of time. The Wellth App determines adherence by having the patient to take a photograph of the correct dose of medication out of the bottle/container and in the patient's hand using the Wellth app and smart phone's built-in camera. This will provide a time-stamped and individually-linked document of adherence. For example, a valid photograph in the current study would be a photograph of a statin tablet in the patient's hand during a calendar day that starts at 00:00 and ends at 23:59. If no photograph is captured within this time period, the subject is considered non-adherent. Taking more than one dose of the medication another day does not "make up" for previous missed days, even if it is recommended by a health care provider. Participants will be able to download the app to their smartphone without any additional software or encryption needed. In order to prevent patients from being excluded based on the costs of the necessary hardware, the investigators will provide a smartphone and data plan free of charge to patients based on an existing partnership if needed. Patients use the App to receive reminders, make check-ins, check their reward balance, and view their adherence history. Description of the reward system: In this proposal, subjects will receive money to incentivize adherence. Subjects will receive a $30 credit at 30-day intervals, which can only be spent at the end of the 30-day period. For each payout, the full $30 will be earned only if the individual submits all the required photos of his/her medications each day through the Wellth app. For each missed check-in, the subject loses $2 from the amount to be paid out at the end of the 30-day period. In this study, there will be two consecutive 30-day periods in which the subject can earn rewards. After this 60-day period, the subject will continue to use the Wellth App to document adherence for 60 days, but will not receive any rewards during this time period. The final 60-day period is used to determine if the reward period has influence on medication adherence after the incentive is stopped. Adherence will be measured by two methods. The first will be through the Morisky Medication Adherence Scale (MMAS) and the second will be using the proportion of prescribed pills taken. The choice to measure adherence with two methods is because the investigators only want to include patients who have poor adherence in the study. As self-reported adherence may be inaccurate, the investigators will use the validated Morisky Medication Adherence Scale (MMAS) to assess baseline adherence. However, during the study period, adherence will be measured much more accurately through the use of the Wellth App. As the score of the MMAS cannot be converted to the proportion of prescribed pills taken, the investors will simply measure changes in MMAS score throughout the study as well as measure changes in the proportion of prescribed days taken. The investigators provide power calculations for both scenarios below. Participants will complete the MMAS at the screening visit, after the 60-day intervention, and 60 days after the intervention ends. The investigators will measure adherence using the Wellth app continuously once the subject has access to the Wellth app. The adherence values used for analysis will be the proportion of pills prescribed in which the subjects completes a "checked in" during the three following periods: a) "pre-intervention period" of 14 days prior to the start of incentive period, b) the entirety of the Incentive Period, and c) the final 30 days after the Post-Incentive period. Sensitivity analysis will also compare adherence in the last 14 days of each period.

Adolescents, Medication adherence, Familial hypercholesterolemia, Behavioral economics, Mobile health technology

This is a pre-post study design. The intervention group will have medication adherence measured prior to receiving incentives, medication adherence while receiving incentives, and medication adherence after discontinuation of the incentives.

All subjects in this trial will receive the following interventions: Pre-Intervention (Days 0-14): Subjects given access to Wellth application reminders, no incentives provided. A virtual "check in" with the study team will occur at the end of the pre-intervention period (14 days). Intervention (Days 15-74): Subjects will use Wellth app for 60 days, with incentives provided at the 30- and 60-day mark. At the end of the intervention period (Day 60), the subject will attend a clinic visit with the medical provider and a fasting lipid panel and MMAS will also be collected at this time. Post-intervention (Days 74-134): Subjects will continue to use the Wellth app and receive reminders, but with no incentives provided, for 60 days. A clinic visit, fasting lipid profile, and MMAS will also be collected following the post-intervention period.

This intervention will assess the efficacy of subjects using the Wellth mobile phone application to provide reminders to take their statin medication, and receiving monetary incentives for taking their medication as prescribed.

Change in statin adherence in enrolled subjects following an intervention that includes access to the Wellth mobile phone application with reminders to take their medication, and will receive monetary incentives for taking medication as prescribed.

Change in statin adherence in enrolled subjects following an intervention that includes access to the Wellth application with reminders to take their medication, but with no monetary incentives.

Inclusion Criteria: Diagnosis of FH based on National Lipid Association (NLA) criteria and/or genetic testing Prescribed a statin Be able to provide written, informed consent or have a parent/guardian provide written, informed consent Be able to use a mobile phone and application Morisky Medication Adherence Scale score of ≤ 6 Exclusion Criteria: Diagnosis of Homozygous FH Residence in a long-term care facility where medications are administered May become pregnant History of adverse effect or allergy to a statin, or any ingredient in a statin

1. National Institute for Health and Clinical Excellence. Statins for the prevention of cardiovascular events. Technology Appraisal. London: National Institute for Health and Clinical Excellence, 2006.

Mortality in treated heterozygous familial hypercholesterolaemia: implications for clinical management. Scientific Steering Committee on behalf of the Simon Broome Register Group. Atherosclerosis. 1999 Jan;142(1):105-12.

Baigent C, Keech A, Kearney PM, Blackwell L, Buck G, Pollicino C, Kirby A, Sourjina T, Peto R, Collins R, Simes R; Cholesterol Treatment Trialists' (CTT) Collaborators. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet. 2005 Oct 8;366(9493):1267-78. doi: 10.1016/S0140-6736(05)67394-1. Epub 2005 Sep 27. Erratum In: Lancet. 2005 Oct 15-21;366(9494):1358. Lancet. 2008 Jun 21;371(9630):2084.

Braamskamp MJAM, Kastelein JJP, Kusters DM, Hutten BA, Wiegman A. Statin Initiation During Childhood in Patients With Familial Hypercholesterolemia: Consequences for Cardiovascular Risk. J Am Coll Cardiol. 2016 Feb 2;67(4):455-456. doi: 10.1016/j.jacc.2015.11.021. No abstract available.

Braamskamp MJAM, Langslet G, McCrindle BW, Cassiman D, Francis GA, Gagne C, Gaudet D, Morrison KM, Wiegman A, Turner T, Kusters DM, Miller E, Raichlen JS, Wissmar J, Martin PD, Stein EA, Kastelein JJP. Efficacy and safety of rosuvastatin therapy in children and adolescents with familial hypercholesterolemia: Results from the CHARON study. J Clin Lipidol. 2015 Nov-Dec;9(6):741-750. doi: 10.1016/j.jacl.2015.07.011. Epub 2015 Aug 1.

de Jongh S, Ose L, Szamosi T, Gagne C, Lambert M, Scott R, Perron P, Dobbelaere D, Saborio M, Tuohy MB, Stepanavage M, Sapre A, Gumbiner B, Mercuri M, van Trotsenburg AS, Bakker HD, Kastelein JJ; Simvastatin in Children Study Group. Efficacy and safety of statin therapy in children with familial hypercholesterolemia: a randomized, double-blind, placebo-controlled trial with simvastatin. Circulation. 2002 Oct 22;106(17):2231-7. doi: 10.1161/01.cir.0000035247.42888.82.

Gidding SS, Champagne MA, de Ferranti SD, Defesche J, Ito MK, Knowles JW, McCrindle B, Raal F, Rader D, Santos RD, Lopes-Virella M, Watts GF, Wierzbicki AS; American Heart Association Atherosclerosis, Hypertension, and Obesity in Young Committee of Council on Cardiovascular Disease in Young, Council on Cardiovascular and Stroke Nursing, Council on Functional Genomics and Translational Biology, and Council on Lifestyle and Cardiometabolic Health. The Agenda for Familial Hypercholesterolemia: A Scientific Statement From the American Heart Association. Circulation. 2015 Dec 1;132(22):2167-92. doi: 10.1161/CIR.0000000000000297. Epub 2015 Oct 28. No abstract available. Erratum In: Circulation. 2015 Dec 22;132(25):e397.

Jacobson TA, Maki KC, Orringer CE, Jones PH, Kris-Etherton P, Sikand G, La Forge R, Daniels SR, Wilson DP, Morris PB, Wild RA, Grundy SM, Daviglus M, Ferdinand KC, Vijayaraghavan K, Deedwania PC, Aberg JA, Liao KP, McKenney JM, Ross JL, Braun LT, Ito MK, Bays HE, Brown WV, Underberg JA; NLA Expert Panel. National Lipid Association Recommendations for Patient-Centered Management of Dyslipidemia: Part 2. J Clin Lipidol. 2015 Nov-Dec;9(6 Suppl):S1-122.e1. doi: 10.1016/j.jacl.2015.09.002. Epub 2015 Sep 18. Erratum In: J Clin Lipidol. 2016 Jan-Feb;10(1):211. Underberg, James A [added].

Kavey RE, Allada V, Daniels SR, Hayman LL, McCrindle BW, Newburger JW, Parekh RS, Steinberger J; American Heart Association Expert Panel on Population and Prevention Science; American Heart Association Council on Cardiovascular Disease in the Young; American Heart Association Council on Epidemiology and Prevention; American Heart Association Council on Nutrition, Physical Activity and Metabolism; American Heart Association Council on High Blood Pressure Research; American Heart Association Council on Cardiovascular Nursing; American Heart Association Council on the Kidney in Heart Disease; Interdisciplinary Working Group on Quality of Care and Outcomes Research. Cardiovascular risk reduction in high-risk pediatric patients: a scientific statement from the American Heart Association Expert Panel on Population and Prevention Science; the Councils on Cardiovascular Disease in the Young, Epidemiology and Prevention, Nutrition, Physical Activity and Metabolism, High Blood Pressure Research, Cardiovascular Nursing, and the Kidney in Heart Disease; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research: endorsed by the American Academy of Pediatrics. Circulation. 2006 Dec 12;114(24):2710-38. doi: 10.1161/CIRCULATIONAHA.106.179568. Epub 2006 Nov 27.

Nawrocki JW, Weiss SR, Davidson MH, Sprecher DL, Schwartz SL, Lupien PJ, Jones PH, Haber HE, Black DM. Reduction of LDL cholesterol by 25% to 60% in patients with primary hypercholesterolemia by atorvastatin, a new HMG-CoA reductase inhibitor. Arterioscler Thromb Vasc Biol. 1995 May;15(5):678-82. doi: 10.1161/01.atv.15.5.678.

Neil A, Cooper J, Betteridge J, Capps N, McDowell I, Durrington P, Seed M, Humphries SE. Reductions in all-cause, cancer, and coronary mortality in statin-treated patients with heterozygous familial hypercholesterolaemia: a prospective registry study. Eur Heart J. 2008 Nov;29(21):2625-33. doi: 10.1093/eurheartj/ehn422. Epub 2008 Oct 7.

Rodenburg J, Vissers MN, Wiegman A, van Trotsenburg AS, van der Graaf A, de Groot E, Wijburg FA, Kastelein JJ, Hutten BA. Statin treatment in children with familial hypercholesterolemia: the younger, the better. Circulation. 2007 Aug 7;116(6):664-8. doi: 10.1161/CIRCULATIONAHA.106.671016. Epub 2007 Jul 30.

Wiegman A, Gidding SS, Watts GF, Chapman MJ, Ginsberg HN, Cuchel M, Ose L, Averna M, Boileau C, Boren J, Bruckert E, Catapano AL, Defesche JC, Descamps OS, Hegele RA, Hovingh GK, Humphries SE, Kovanen PT, Kuivenhoven JA, Masana L, Nordestgaard BG, Pajukanta P, Parhofer KG, Raal FJ, Ray KK, Santos RD, Stalenhoef AF, Steinhagen-Thiessen E, Stroes ES, Taskinen MR, Tybjaerg-Hansen A, Wiklund O; European Atherosclerosis Society Consensus Panel. Familial hypercholesterolaemia in children and adolescents: gaining decades of life by optimizing detection and treatment. Eur Heart J. 2015 Sep 21;36(36):2425-37. doi: 10.1093/eurheartj/ehv157. Epub 2015 May 25.

Wiegman A, Hutten BA, de Groot E, Rodenburg J, Bakker HD, Buller HR, Sijbrands EJ, Kastelein JJ. Efficacy and safety of statin therapy in children with familial hypercholesterolemia: a randomized controlled trial. JAMA. 2004 Jul 21;292(3):331-7. doi: 10.1001/jama.292.3.331.

Chi MD, Vansomphone SS, Liu IL, Cheetham C, Green KR, Scott RD, Reynolds K. Adherence to statins and LDL-cholesterol goal attainment. Am J Manag Care. 2014 Apr 1;20(4):e105-12.

De Vera MA, Bhole V, Burns LC, Lacaille D. Impact of statin adherence on cardiovascular disease and mortality outcomes: a systematic review. Br J Clin Pharmacol. 2014 Oct;78(4):684-98. doi: 10.1111/bcp.12339.

Fung V, Graetz I, Reed M, Jaffe MG. Patient-reported adherence to statin therapy, barriers to adherence, and perceptions of cardiovascular risk. PLoS One. 2018 Feb 8;13(2):e0191817. doi: 10.1371/journal.pone.0191817. eCollection 2018.

Pittman DG, Chen W, Bowlin SJ, Foody JM. Adherence to statins, subsequent healthcare costs, and cardiovascular hospitalizations. Am J Cardiol. 2011 Jun 1;107(11):1662-6. doi: 10.1016/j.amjcard.2011.01.052. Epub 2011 Mar 23.

Braamskamp MJ, Kusters DM, Avis HJ, Smets EM, Wijburg FA, Kastelein JJ, Wiegman A, Hutten BA. Long-term statin treatment in children with familial hypercholesterolemia: more insight into tolerability and adherence. Paediatr Drugs. 2015 Apr;17(2):159-66. doi: 10.1007/s40272-014-0116-y.

Joyce NR, Wellenius GA, Eaton CB, Trivedi AN, Zachariah JP. Patterns and predictors of medication adherence to lipid-lowering therapy in children aged 8 to 20 years. J Clin Lipidol. 2016 Jul-Aug;10(4):824-832.e2. doi: 10.1016/j.jacl.2016.03.002. Epub 2016 Mar 10.

Wei L, Wang J, Thompson P, Wong S, Struthers AD, MacDonald TM. Adherence to statin treatment and readmission of patients after myocardial infarction: a six year follow up study. Heart. 2002 Sep;88(3):229-33. doi: 10.1136/heart.88.3.229.

Gatwood J, Bailey JE. Improving medication adherence in hypercholesterolemia: challenges and solutions. Vasc Health Risk Manag. 2014 Nov 6;10:615-25. doi: 10.2147/VHRM.S56056. eCollection 2014.

Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005 Aug 4;353(5):487-97. doi: 10.1056/NEJMra050100. No abstract available.

Normansell R, Kew KM, Stovold E. Interventions to improve adherence to inhaled steroids for asthma. Cochrane Database Syst Rev. 2017 Apr 18;4(4):CD012226. doi: 10.1002/14651858.CD012226.pub2.

Taddeo D, Egedy M, Frappier JY. Adherence to treatment in adolescents. Paediatr Child Health. 2008 Jan;13(1):19-24. doi: 10.1093/pch/13.1.19.

Falkenstein K, Flynn L, Kirkpatrick B, Casa-Melley A, Dunn S. Non-compliance in children post-liver transplant. Who are the culprits? Pediatr Transplant. 2004 Jun;8(3):233-6. doi: 10.1111/j.1399-3046.2004.00136.x.

Rausch JR, Hood KK, Delamater A, Shroff Pendley J, Rohan JM, Reeves G, Dolan L, Drotar D. Changes in treatment adherence and glycemic control during the transition to adolescence in type 1 diabetes. Diabetes Care. 2012 Jun;35(6):1219-24. doi: 10.2337/dc11-2163. Epub 2012 Apr 3.

Badawy SM, Kuhns LM. Texting and Mobile Phone App Interventions for Improving Adherence to Preventive Behavior in Adolescents: A Systematic Review. JMIR Mhealth Uhealth. 2017 Apr 19;5(4):e50. doi: 10.2196/mhealth.6837.

Marcano Belisario JS, Huckvale K, Greenfield G, Car J, Gunn LH. Smartphone and tablet self management apps for asthma. Cochrane Database Syst Rev. 2013 Nov 27;2013(11):CD010013. doi: 10.1002/14651858.CD010013.pub2.

Gächter S, Orzen H, Renner E and Starmer C. Are experimental economists prone to framing effects? A natural field experiment. . Journal of Economic Behavior & Organization. 2009;70.

Meredith SE, Jarvis BP, Raiff BR, Rojewski AM, Kurti A, Cassidy RN, Erb P, Sy JR, Dallery J. The ABCs of incentive-based treatment in health care: a behavior analytic framework to inform research and practice. Psychol Res Behav Manag. 2014 Mar 19;7:103-14. doi: 10.2147/PRBM.S59792. eCollection 2014.

Lynagh MC, Sanson-Fisher RW, Bonevski B. What's good for the goose is good for the gander. Guiding principles for the use of financial incentives in health behaviour change. Int J Behav Med. 2013 Mar;20(1):114-20. doi: 10.1007/s12529-011-9202-5.

Bénabou R and Tirole J. Intrinsic and extrinsic motivation. Review of Economic Studies. 2003;30:489-520.

Sen AP, Sewell TB, Riley EB, Stearman B, Bellamy SL, Hu MF, Tao Y, Zhu J, Park JD, Loewenstein G, Asch DA, Volpp KG. Financial incentives for home-based health monitoring: a randomized controlled trial. J Gen Intern Med. 2014 May;29(5):770-7. doi: 10.1007/s11606-014-2778-0. Epub 2014 Feb 13.

Halpern SD, French B, Small DS, Saulsgiver K, Harhay MO, Audrain-McGovern J, Loewenstein G, Brennan TA, Asch DA, Volpp KG. Randomized trial of four financial-incentive programs for smoking cessation. N Engl J Med. 2015 May 28;372(22):2108-17. doi: 10.1056/NEJMoa1414293. Epub 2015 May 13.

Patel MS, Asch DA, Rosin R, Small DS, Bellamy SL, Heuer J, Sproat S, Hyson C, Haff N, Lee SM, Wesby L, Hoffer K, Shuttleworth D, Taylor DH, Hilbert V, Zhu J, Yang L, Wang X, Volpp KG. Framing Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults: A Randomized, Controlled Trial. Ann Intern Med. 2016 Mar 15;164(6):385-94. doi: 10.7326/M15-1635. Epub 2016 Feb 16.

Mulvaney S, Lee JM. Motivating Health Behaviors in Adolescents Through Behavioral Economics. JAMA Pediatr. 2017 Dec 1;171(12):1145-1146. doi: 10.1001/jamapediatrics.2017.3464. No abstract available.

Blakemore SJ, Robbins TW. Decision-making in the adolescent brain. Nat Neurosci. 2012 Sep;15(9):1184-91. doi: 10.1038/nn.3177. Epub 2012 Aug 28.

van Driel ML, Morledge MD, Ulep R, Shaffer JP, Davies P, Deichmann R. Interventions to improve adherence to lipid-lowering medication. Cochrane Database Syst Rev. 2016 Dec 21;12(12):CD004371. doi: 10.1002/14651858.CD004371.pub4.

Pew Research Internet Project: cell phone and smartphone ownership demographics. 2014. http://www.pewinternet.org/data-trend/mobile/cell-phone-and-smartphone-ownership-demographics. Accessed January 22, 2018.

Burke LE, Ma J, Azar KM, Bennett GG, Peterson ED, Zheng Y, Riley W, Stephens J, Shah SH, Suffoletto B, Turan TN, Spring B, Steinberger J, Quinn CC; American Heart Association Publications Committee of the Council on Epidemiology and Prevention, Behavior Change Committee of the Council on Cardiometabolic Health, Council on Cardiovascular and Stroke Nursing, Council on Functional Genomics and Translational Biology, Council on Quality of Care and Outcomes Research, and Stroke Council. Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention: A Scientific Statement From the American Heart Association. Circulation. 2015 Sep 22;132(12):1157-213. doi: 10.1161/CIR.0000000000000232. Epub 2015 Aug 13. No abstract available. Erratum In: Circulation. 2015 Nov 10;132(19):e233.

Sardi L, Idri A, Fernandez-Aleman JL. A systematic review of gamification in e-Health. J Biomed Inform. 2017 Jul;71:31-48. doi: 10.1016/j.jbi.2017.05.011. Epub 2017 May 20.

Lau RR, Quadrel MJ, Hartman KA. Development and change of young adults' preventive health beliefs and behavior: influence from parents and peers. J Health Soc Behav. 1990 Sep;31(3):240-59.

Telama R, Yang X, Laakso L, Viikari J. Physical activity in childhood and adolescence as predictor of physical activity in young adulthood. Am J Prev Med. 1997 Jul-Aug;13(4):317-23.

Molfenter TD, Bhattacharya A, Gustafson DH. The roles of past behavior and health beliefs in predicting medication adherence to a statin regimen. Patient Prefer Adherence. 2012;6:643-51. doi: 10.2147/PPA.S34711. Epub 2012 Sep 6.

Riekert K. Promoting Adherence And Increasing Life Span. Johns Hopkins Advanced Studies in Medicine. 2009;9.

https://www.ssoar.info/ssoar/bitstream/handle/document/28311/ssoar-jebo-2009-3-gachter_et_al-are_experimental_economists_prone_to.pdf?sequence=1

The MMAS-8 Scale, content, name, and trademarks are protected by US copyright and trademark laws. Permission for use of the scale and its coding is required. A license agreement is available from MMAR, LLC.