The Use of SMS Text Messaging to Improve the Hospital-to-Community Transition in Patients With Acute Coronary Syndrome (Txt2Prevent): Results From a Pilot Randomized Controlled Trial

Emily S Ross, Brodie M Sakakibara, Martha H Mackay, David G T Whitehurst, Joel Singer, Mustafa Toma, Kitty K Corbett, Harriette G C Van Spall, Kimberly Rutherford, Bobby Gheorghiu, Jillianne Code, Scott A Lear, Emily S Ross, Brodie M Sakakibara, Martha H Mackay, David G T Whitehurst, Joel Singer, Mustafa Toma, Kitty K Corbett, Harriette G C Van Spall, Kimberly Rutherford, Bobby Gheorghiu, Jillianne Code, Scott A Lear

Abstract

Background: Acute coronary syndrome (ACS) is a leading cause of hospital admission in North America. Many patients with ACS experience challenges after discharge that impact their clinical outcomes and psychosocial well-being. SMS text messaging has the potential to provide support to patients during this postdischarge period.

Objective: This study pilot tested a 60-day SMS text messaging intervention (Txt2Prevent) for patients with ACS. The primary objective was to compare self-management domains between usual care and usual care plus Txt2Prevent. The secondary objectives were to compare medication adherence, health-related quality of life, self-efficacy, and health care resource use between groups. The third objective was to assess the feasibility of the study protocol and the acceptability of the intervention.

Methods: This was a randomized controlled trial with blinding of outcome assessors. We recruited 76 patients with ACS from St. Paul's Hospital in Vancouver, Canada, and randomized them to 1 of 2 groups within 7 days of discharge. The Txt2Prevent program included automated 1-way SMS text messages about follow-up care, self-management, and healthy living. Data were collected during the index admission and at 60 days after randomization. The primary outcome was measured with the Health Education Impact Questionnaire (heiQ). Other outcomes included the EQ-5D-5L, EQ-5D-5L Visual Analog Scale, a modified Sullivan Cardiac Self-Efficacy Scale, and Morisky Medication Adherence Scale scores, and self-reported health care resource use. Analyses of covariance were used to test the effect of group assignment on follow-up scores (controlling for baseline) and were considered exploratory in nature. Feasibility was assessed with descriptive characteristics of the study protocol. Acceptability was assessed with 2 survey questions and semistructured interviews.

Results: There were no statistically significant differences between the groups for the heiQ domains (adjusted mean difference [Txt2Prevent minus usual care] for each domain-Health-directed activity: -0.13, 95% CI -0.39 to 0.13, P=.31; Positive and active engagement in life: 0.03, 95% CI -0.19 to 0.25, P=.76; Emotional distress: 0.04, 95% CI -0.22 to 0.29, P=.77; Self-monitoring and insight: -0.14, 95% CI -0.33 to 0.05, P=.15; Constructive attitudes and approaches: -0.10, 95% CI -0.36 to 0.17, P=.47; Skill technique and acquisition: 0.05, 95% CI -0.18 to 0.27, P=.69; Social integration and support: -0.12, 95% CI -0.34 to 0.10, P=.27; and Health services navigation: -0.05, 95% CI -0.29 to 0.19, P=.69). For the secondary outcomes, there were no statistically significant differences in adjusted analyses except in 1 self-efficacy domain (Total plus), where the Txt2Prevent group had lower scores (mean difference -0.36, 95% CI -0.66 to -0.50, P=.03). The study protocol was feasible, but recruitment took longer than expected. Over 90% (29/31 [94%]) of participants reported they were satisfied with the program.

Conclusions: The Txt2Prevent study was feasible to implement; however, although exploratory, there were no differences between the 2 groups in adjusted analyses except for 1 self-efficacy domain. As the intervention appeared acceptable, there is potential in using SMS text messages in this context. The design of the intervention may need to be reconsidered to have more impact on outcome measures.

Trial registration: ClinicalTrials.gov NCT02336919; https://ichgcp.net/clinical-trials-registry/NCT02336919.

International registered report identifier (irrid): RR2-10.2196/resprot.6968.

Keywords: SMS text messaging; acute coronary syndrome; cardiovascular disease; mHealth.

Conflict of interest statement

Conflicts of Interest: None declared.

©Emily S Ross, Brodie M Sakakibara, Martha H Mackay, David G T Whitehurst, Joel Singer, Mustafa Toma, Kitty K Corbett, Harriette G C Van Spall, Kimberly Rutherford, Bobby Gheorghiu, Jillianne Code, Scott A Lear. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 14.05.2021.

Figures

Figure 1
Figure 1
CONSORT flow diagram.

References

    1. Canadian Institute for Health Information A Snapshot of Health Care in Canada as Demonstrated by Top 10 Lists, 2011. 2012. [2021-04-08]. .
    1. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, Das SR, de FS, Després J, Fullerton HJ, Howard VJ, Huffman MD, Isasi CR, Jiménez MC, Judd SE, Kissela BM, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Magid DJ, McGuire DK, Mohler ER, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Rosamond W, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Woo D, Yeh RW, Turner MB, American HASC, Stroke SS. Heart Disease and Stroke Statistics-2016 Update: A Report From the American Heart Association. Circulation. 2016 Jan 26;133(4):e38–360. doi: 10.1161/CIR.0000000000000350.
    1. Dharmarajan K, Hsieh AF, Lin Z, Bueno H, Ross JS, Horwitz LI, Barreto-Filho JA, Kim N, Bernheim SM, Suter LG, Drye EE, Krumholz HM. Diagnoses and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia. JAMA. 2013 Jan 23;309(4):355–63. doi: 10.1001/jama.2012.216476.
    1. Southern DA, Ngo J, Martin B, Galbraith PD, Knudtson ML, Ghali WA, James MT, Wilton SB. Characterizing types of readmission after acute coronary syndrome hospitalization: implications for quality reporting. J Am Heart Assoc. 2014 Sep 18;3(5):e001046. doi: 10.1161/JAHA.114.001046.
    1. Chow CK, Jolly S, Rao-Melacini P, Fox KAA, Anand SS, Yusuf S. Association of diet, exercise, and smoking modification with risk of early cardiovascular events after acute coronary syndromes. Circulation. 2010 Feb 16;121(6):750–8. doi: 10.1161/CIRCULATIONAHA.109.891523.
    1. Canadian Institute for Health Information Physician Follow-up after Hospital Discharge: Progress in Meeting Best Practices. 2015. [2021-04-09]. .
    1. Tung Y, Chang G, Chang H, Yu T. Relationship between Early Physician Follow-Up and 30-Day Readmission after Acute Myocardial Infarction and Heart Failure. PLoS One. 2017;12(1):e0170061. doi: 10.1371/journal.pone.0170061.
    1. Faridi KF, Peterson ED, McCoy LA, Thomas L, Enriquez J, Wang TY. Timing of First Postdischarge Follow-up and Medication Adherence After Acute Myocardial Infarction. JAMA Cardiol. 2016 May 01;1(2):147–55. doi: 10.1001/jamacardio.2016.0001.
    1. Daugherty SL, Ho PM, Spertus JA, Jones PG, Bach RG, Krumholz HM, Peterson ED, Rumsfeld JS, Masoudi FA. Association of early follow-up after acute myocardial infarction with higher rates of medication use. Arch Intern Med. 2008 Mar 10;168(5):485–91; discussion 492. doi: 10.1001/archinte.168.5.485.
    1. Hickson RP, Robinson JG, Annis IE, Killeya-Jones LA, Korhonen MJ, Cole AL, Fang G. Changes in Statin Adherence Following an Acute Myocardial Infarction Among Older Adults: Patient Predictors and the Association With Follow-Up With Primary Care Providers and/or Cardiologists. J Am Heart Assoc. 2017 Oct 19;6(10):e007106. doi: 10.1161/JAHA.117.007106.
    1. Jackevicius CA, Li P, Tu JV. Prevalence, predictors, and outcomes of primary nonadherence after acute myocardial infarction. Circulation. 2008 Feb 26;117(8):1028–36. doi: 10.1161/CIRCULATIONAHA.107.706820.
    1. Hanssen TA, Nordrehaug JE, Hanestad BR. A qualitative study of the information needs of acute myocardial infarction patients, and their preferences for follow-up contact after discharge. Eur J Cardiovasc Nurs. 2005 Mar;4(1):37–44. doi: 10.1016/j.ejcnurse.2004.11.001.
    1. Roebuck A, Furze G, Thompson DR. Health-related quality of life after myocardial infarction: an interview study. J Adv Nurs. 2001 Jun;34(6):787–94. doi: 10.1046/j.1365-2648.2001.01809.x.
    1. Feng L, Li L, Liu W, Yang J, Wang Q, Shi L, Luo M. Prevalence of depression in myocardial infarction: A PRISMA-compliant meta-analysis. Medicine (Baltimore) 2019 Feb;98(8):e14596. doi: 10.1097/MD.0000000000014596. doi: 10.1097/MD.0000000000014596.
    1. Ziebland S, Locock L, Fitzpatrick R. Appendix 4, Myocardial infarction patients? perspectives of care: a secondary analysis of qualitative interviews. Informing the Development of NICE (National Institute for Health and Care Excellence) Quality Standards through Secondary Analysis of Qualitative Narrative Interviews on Patients' Experiences. 2014. [2021-04-09].
    1. Ko DT, Newman AM, Alter DA, Austin PC, Chiu M, Cox JL, Goodman SG, Tu JV, Canadian CORT. Secular trends in acute coronary syndrome hospitalization from 1994 to 2005. Can J Cardiol. 2010 Mar;26(3):129–34.
    1. Spencer FA, Lessard D, Gore JM, Yarzebski J, Goldberg RJ. Declining length of hospital stay for acute myocardial infarction and postdischarge outcomes: a community-wide perspective. Arch Intern Med. 2004 Apr 12;164(7):733–40. doi: 10.1001/archinte.164.7.733.
    1. Jørstad HT, Minneboo M, Helmes HJM, Fagel ND, Scholte Op Reimer WJ, Tijssen JGP, Peters RJG. Effects of a nurse-coordinated prevention programme on health-related quality of life and depression in patients with an acute coronary syndrome: results from the RESPONSE randomised controlled trial. BMC Cardiovasc Disord. 2016 Jul 08;16(1):144. doi: 10.1186/s12872-016-0321-4.
    1. Sinclair AJ, Conroy SP, Davies M, Bayer AJ. Post-discharge home-based support for older cardiac patients: a randomised controlled trial. Age Ageing. 2005 Jul;34(4):338–43. doi: 10.1093/ageing/afi116.
    1. Pew Research Center Demographics of Mobile Device Ownership and Adoption in the United States. 2021. [2021-05-10].
    1. Pew Research Center Cell Phone Activities. 2015. [2021-04-09].
    1. Unal E, Giakoumidakis K, Khan E, Patelarou E. Mobile phone text messaging for improving secondary prevention in cardiovascular diseases: A systematic review. Heart Lung. 2018;47(4):351–359. doi: 10.1016/j.hrtlng.2018.05.009.
    1. Maddison R, Pfaeffli L, Whittaker R, Stewart R, Kerr A, Jiang Y, Kira G, Leung W, Dalleck L, Carter K, Rawstorn J. A mobile phone intervention increases physical activity in people with cardiovascular disease: Results from the HEART randomized controlled trial. Eur J Prev Cardiol. 2015 Jun;22(6):701–9. doi: 10.1177/2047487314535076.
    1. Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML, Jan S, Graves N, de KL, Barry T, Bompoint S, Stepien S, Whittaker R, Rodgers A, Thiagalingam A. Effect of Lifestyle-Focused Text Messaging on Risk Factor Modification in Patients With Coronary Heart Disease: A Randomized Clinical Trial. JAMA. 2015;314(12):1255–63. doi: 10.1001/jama.2015.10945.
    1. Shariful Islam SM, Farmer AJ, Bobrow K, Maddison R, Whittaker R, Pfaeffli Dale LA, Lechner A, Lear S, Eapen Z, Niessen LW, Santo K, Stepien S, Redfern J, Rodgers A, Chow CK. Mobile phone text-messaging interventions aimed to prevent cardiovascular diseases (Text2PreventCVD): systematic review and individual patient data meta-analysis. Open Heart. 2019;6(2):e001017. doi: 10.1136/openhrt-2019-001017.
    1. Ross ES, Sakakibara BM, Mackay MH, Whitehurst DG, Singer J, Toma M, Corbett KK, Van Spall HG, Rutherford K, Gheorghiu B, Code J, Lear SA. The Use of Text Messaging to Improve the Hospital-to-Community Transition in Acute Coronary Syndrome Patients (Txt2Prevent): Intervention Development and Pilot Randomized Controlled Trial Protocol. JMIR Res Protoc. 2017 May 23;6(5):e91. doi: 10.2196/resprot.6968.
    1. Eysenbach G, CONSORT- E. CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J Med Internet Res. 2011;13(4):e126. doi: 10.2196/jmir.1923.
    1. Dharmarajan K, Hsieh AF, Kulkarni VT, Lin Z, Ross JS, Horwitz LI, Kim N, Suter LG, Lin H, Normand ST, Krumholz HM. Trajectories of risk after hospitalization for heart failure, acute myocardial infarction, or pneumonia: retrospective cohort study. BMJ. 2015 Feb 05;350:h411.
    1. Grace SL, Tan Y, Marcus L, Dafoe W, Simpson C, Suskin N, Chessex C. Perceptions of cardiac rehabilitation patients, specialists and rehabilitation programs regarding cardiac rehabilitation wait times. BMC Health Serv Res. 2012 Aug 16;12:259. doi: 10.1186/1472-6963-12-259.
    1. Smedegaard L, Numé A, Charlot M, Kragholm K, Gislason G, Hansen PR. Return to Work and Risk of Subsequent Detachment From Employment After Myocardial Infarction: Insights From Danish Nationwide Registries. J Am Heart Assoc. 2017 Oct 04;6(10):e006486. doi: 10.1161/JAHA.117.006486.
    1. Jackson D, Daly J, Davidson P, Elliott D, Cameron-Traub E, Wade V, Chin C, Salamonson Y. Women recovering from first-time myocardial infarction (MI): a feminist qualitative study. J Adv Nurs. 2000 Dec;32(6):1403–11. doi: 10.1046/j.1365-2648.2000.01622.x.
    1. Osborne RH, Elsworth GR, Whitfield K. The Health Education Impact Questionnaire (heiQ): an outcomes and evaluation measure for patient education and self-management interventions for people with chronic conditions. Patient Educ Couns. 2007 May;66(2):192–201. doi: 10.1016/j.pec.2006.12.002.
    1. Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, Bonsel G, Badia X. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L) Qual Life Res. 2011 Dec;20(10):1727–36. doi: 10.1007/s11136-011-9903-x.
    1. Xie F, Pullenayegum E, Gaebel K, Bansback N, Bryan S, Ohinmaa A, Poissant L, Johnson JA, Canadian EVSG. A Time Trade-off-derived Value Set of the EQ-5D-5L for Canada. Med Care. 2016 Jan;54(1):98–105. doi: 10.1097/MLR.0000000000000447.
    1. EuroQol Research Foundation EQ-5D-5L user guide. 2019. [2021-04-09]. .
    1. Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, Swinburn P, Busschbach J. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2013 Sep;22(7):1717–27. doi: 10.1007/s11136-012-0322-4.
    1. Schweikert B, Hahmann H, Leidl R. Validation of the EuroQol questionnaire in cardiac rehabilitation. Heart. 2006 Jan;92(1):62–7. doi: 10.1136/hrt.2004.052787.
    1. Sullivan MD, LaCroix AZ, Russo J, Katon WJ. Self-efficacy and self-reported functional status in coronary heart disease: a six-month prospective study. Psychosom Med. 1998;60(4):473–8.
    1. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich) 2008 May;10(5):348–54.
    1. Krousel-Wood M, Islam T, Webber LS, Re RN, Morisky DE, Muntner P. New medication adherence scale versus pharmacy fill rates in seniors with hypertension. Am J Manag Care. 2009 Jan;15(1):59–66.
    1. Morisky DE, DiMatteo MR. Improving the measurement of self-reported medication nonadherence: response to authors. J Clin Epidemiol. 2011 Mar;64(3):255–7; discussion 258. doi: 10.1016/j.jclinepi.2010.09.002.
    1. Amsterdam EA, Wenger NK, Brindis RG, Casey DE, Ganiats TG, Holmes DR, Jaffe AS, Jneid H, Kelly RF, Kontos MC, Levine GN, Liebson PR, Mukherjee D, Peterson ED, Sabatine MS, Smalling RW, Zieman SJ, ACC/AHA Task Force Members 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014 Dec 23;130(25):e344–426. doi: 10.1161/CIR.0000000000000134.
    1. Lauck S, Johnson JL, Ratner PA. Self-care behaviour and factors associated with patient outcomes following same-day discharge percutaneous coronary intervention. Eur J Cardiovasc Nurs. 2009 Sep;8(3):190–9. doi: 10.1016/j.ejcnurse.2008.12.002.
    1. Morris SB. Estimating Effect Sizes From Pretest-Posttest-Control Group Designs. Organizational Research Methods. 2007 Jul 23;11(2):364–386. doi: 10.1177/1094428106291059.
    1. McNutt L, Wu C, Xue X, Hafner JP. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol. 2003 May 15;157(10):940–3.
    1. Statistics Canada Census Dictionary: Census Year, 2011. 2015. [2021-04-09]. .
    1. Torbjørnsen A, Jenum AK, Småstuen MC, Arsand E, Holmen H, Wahl AK, Ribu L. A Low-Intensity Mobile Health Intervention With and Without Health Counseling for Persons With Type 2 Diabetes, Part 1: Baseline and Short-Term Results From a Randomized Controlled Trial in the Norwegian Part of RENEWING HEALTH. JMIR Mhealth Uhealth. 2014;2(4):e52. doi: 10.2196/mhealth.3535.
    1. Sakakibara BM, Ross E, Arthur G, Brown-Ganzert L, Petrin S, Sedlak T, Lear SA. Using Mobile-Health to Connect Women with Cardiovascular Disease and Improve Self-Management. Telemed J E Health. 2017 Mar;23(3):233–239. doi: 10.1089/tmj.2016.0133.
    1. Ammerlaan J, van Os-Medendorp H, de Boer-Nijhof N, Scholtus L, Kruize AA, van Pelt P, Prakken B, Bijlsma H. Short term effectiveness and experiences of a peer guided web-based self-management intervention for young adults with juvenile idiopathic arthritis. Pediatr Rheumatol Online J. 2017 Oct 13;15(1):75. doi: 10.1186/s12969-017-0201-1.
    1. Weymann N, Dirmaier J, von Wolff A, Kriston L, Härter M. Effectiveness of a Web-based tailored interactive health communication application for patients with type 2 diabetes or chronic low back pain: randomized controlled trial. J Med Internet Res. 2015;17(3):e53. doi: 10.2196/jmir.3904.
    1. Boroumand S, Moeini M. The effect of a text message and telephone follow-up program on cardiac self-efficacy of patients with coronary artery disease: A randomized controlled trial. Iran J Nurs Midwifery Res. 2016;21(2):171–6. doi: 10.4103/1735-9066.178243.
    1. Adler AJ, Martin N, Mariani J, Tajer CD, Owolabi OO, Free C, Serrano NC, Casas JP, Perel P. Mobile phone text messaging to improve medication adherence in secondary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2017 Apr 29;4:CD011851. doi: 10.1002/14651858.CD011851.pub2.
    1. Zheng X, Spatz ES, Bai X, Huo X, Ding Q, Horak P, Wu X, Guan W, Chow CK, Yan X, Sun Y, Wang X, Zhang H, Liu J, Li J, Li X, Spertus JA, Masoudi FA, Krumholz HM. Effect of Text Messaging on Risk Factor Management in Patients With Coronary Heart Disease: The CHAT Randomized Clinical Trial. Circ Cardiovasc Qual Outcomes. 2019 Apr;12(4):e005616. doi: 10.1161/CIRCOUTCOMES.119.005616.
    1. Anand SS, Samaan Z, Middleton C, Irvine J, Desai D, Schulze KM, Sothiratnam S, Hussain F, Shah BR, Pare G, Beyene J, Lear SA, South Asian Heart Risk Assessment Investigators A Digital Health Intervention to Lower Cardiovascular Risk: A Randomized Clinical Trial. JAMA Cardiol. 2016 Aug 01;1(5):601–6. doi: 10.1001/jamacardio.2016.1035.
    1. Amsterdam EA, Wenger NK, Brindis RG, Casey DE, Ganiats TG, Holmes DR, Jaffe AS, Jneid H, Kelly RF, Kontos MC, Levine GN, Liebson PR, Mukherjee D, Peterson ED, Sabatine MS, Smalling RW, Zieman SJ. 2014 AHA/ACC Guideline for the Management of Patients with Non-ST-Elevation Acute Coronary Syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014 Dec 23;64(24):e139–e228. doi: 10.1016/j.jacc.2014.09.017.
    1. Park LG, Howie-Esquivel J, Dracup K. A quantitative systematic review of the efficacy of mobile phone interventions to improve medication adherence. J Adv Nurs. 2014 Sep;70(9):1932–53. doi: 10.1111/jan.12400.
    1. Head KJ, Noar SM, Iannarino NT, Grant HN. Efficacy of text messaging-based interventions for health promotion: a meta-analysis. Soc Sci Med. 2013 Nov;97:41–8. doi: 10.1016/j.socscimed.2013.08.003.
    1. Sahin C, Courtney KL, Naylor PJ, E Rhodes R. Tailored mobile text messaging interventions targeting type 2 diabetes self-management: A systematic review and a meta-analysis. Digit Health. 2019;5:2055207619845279. doi: 10.1177/2055207619845279.
    1. Thakkar J, Kurup R, Laba T, Santo K, Thiagalingam A, Rodgers A, Woodward M, Redfern J, Chow CK. Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-analysis. JAMA Intern Med. 2016 Mar;176(3):340–9. doi: 10.1001/jamainternmed.2015.7667.
    1. Redfern J, Thiagalingam A, Jan S, Whittaker R, Hackett ML, Mooney J, De KL, Hillis GS, Chow CK. Development of a set of mobile phone text messages designed for prevention of recurrent cardiovascular events. Eur J Prev Cardiol. 2014 Apr;21(4):492–9. doi: 10.1177/2047487312449416.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013 Aug;46(1):81–95. doi: 10.1007/s12160-013-9486-6.
    1. Winter SJ, Sheats JL, King AC. The Use of Behavior Change Techniques and Theory in Technologies for Cardiovascular Disease Prevention and Treatment in Adults: A Comprehensive Review. Prog Cardiovasc Dis. 2016;58(6):605–12. doi: 10.1016/j.pcad.2016.02.005.
    1. Park LG, Howie-Esquivel J, Chung ML, Dracup K. A text messaging intervention to promote medication adherence for patients with coronary heart disease: a randomized controlled trial. Patient Educ Couns. 2014 Feb;94(2):261–8. doi: 10.1016/j.pec.2013.10.027.
    1. Kandola DK, Banner D, Araki Y, Bates J, Hadi H, Lear SA. The Participant Recruitment Outcomes (PRO) study: Exploring contemporary perspectives of telehealth trial non-participation through insights from patients, clinicians, study investigators, and study staff. Contemp Clin Trials Commun. 2018 Sep;11:75–82. doi: 10.1016/j.conctc.2018.05.005.
    1. Quilici J, Fugon L, Beguin S, Morange PE, Bonnet J, Alessi M, Carrieri P, Cuisset T. Effect of motivational mobile phone short message service on aspirin adherence after coronary stenting for acute coronary syndrome. Int J Cardiol. 2013 Sep 20;168(1):568–9. doi: 10.1016/j.ijcard.2013.01.252.
    1. Khonsari S, Subramanian P, Chinna K, Latif LA, Ling LW, Gholami O. Effect of a reminder system using an automated short message service on medication adherence following acute coronary syndrome. Eur J Cardiovasc Nurs. 2015 Apr;14(2):170–9. doi: 10.1177/1474515114521910.
    1. Guo P, Harris R. The effectiveness and experience of self-management following acute coronary syndrome: A review of the literature. Int J Nurs Stud. 2016 Sep;61:29–51. doi: 10.1016/j.ijnurstu.2016.05.008.
    1. Wheeler JRC, Janz NK, Dodge JA. Can a disease self-management program reduce health care costs? The case of older women with heart disease. Med Care. 2003 Jun;41(6):706–15. doi: 10.1097/01.MLR.0000065128.72148.D7.
    1. Panagioti M, Richardson G, Small N, Murray E, Rogers A, Kennedy A, Newman S, Bower P. Self-management support interventions to reduce health care utilisation without compromising outcomes: a systematic review and meta-analysis. BMC Health Serv Res. 2014;14:356. doi: 10.1186/1472-6963-14-356.
    1. Wyrwich KW, Bullinger M, Aaronson N, Hays RD, Patrick DL, Symonds T, Clinical Significance Consensus Meeting Group Estimating clinically significant differences in quality of life outcomes. Qual Life Res. 2005 Mar;14(2):285–95. doi: 10.1007/s11136-004-0705-2.

Source: PubMed

3
Sottoscrivi