Cited by 29Health Literacy and Information AccessibilityMobile Health and mHealth ApplicationsMedication Adherence and Compliance

Understanding adherence to web-based interventions

Open access
Kelders, Saskia M.·2012

Abstract

to investigate two major informational issues relevant to societal and technological trends: 1) information behavior of Dutch citizens: information seeking/searching behavior, background variables, motivational variables, deployment of image and sound, consumer health vocabulary (e-) health literacy, the emerging on-demand health consumer; 2) information tools and services for citizens: support systems for a general public (idem for high risk and underserved populations; health disparities), evaluation methods, tailored health communication, search engines, integrating good examples, reaching the user (…)"The investigation of the first aim resulted in the thesis 'iHealth -Supporting Health by Technology', which was successfully defended by dr.Hans Ossebaard in June 2012.The second line of research is the topic of this thesis.In 2007, the aim of this part of the project was specified as: "to develop a virtual coach to support healthier behavior of populations at risk for chronic diseases.The system should be tailored to the needs of its users, to enable a "smooth flow of consumer-friendly information" and to encourage disease-management.Besides, the system should be consistent with high quality standards for electronic communication."Specific focus points that were identified in the research plan were, for example: justin-time preventive care; development of a virtual coach; an interactive system to support patient-system communication; and an adaptive system.The project started from a very broad point of view.Through advanced insights on the impact and uptake of eHealth technologies as seen, for example, in the work of Nijland presented in her thesis 'Grounding eHealth' and the study presented in Chapter 2 of this thesis, the focus has gradually become more specific towards the issue of non-adherence.Non-adherence (i.e.participants not following an intervention protocol) and, related, the gap in eHealth research on how to support patient-system interaction were seen in many eHealth interventions.More insight in, and ways to cope with these issues were considered a prerequisite to reach the aim of this part of the gettingBetter.nlproject and therefore became the focus of this thesis.Through the shifting and specification of the research goals, the intended target area of the research project (chronic disease) has been broadened to include lifestyle and mental Preface | 11 health.Nonetheless, many of the original goals are being addressed in the current thesis.For example, the web-based intervention "Living to the full", which is the case for Chapter 4-6, is a preventive intervention for people with mild to moderate depressive symptoms and is intended to provide 'just-in-time' care.Furthermore, the interactive system to support patient-system communication can be seen in the dialogue support category of the Persuasive System Design-model which has been found to be a main predictor of adherence in Chapter 3.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3990/1.9789036534178

Cites

307 of 307 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Persuasive elements (such as text messages, tunneling and social support) are incorporated in the design of the intervention in order to improve adherence to the intervention.

    “Also, persuasive elements (such as text messages, tunneling and social support) are incorporated in the design of intervention in order to improve adherence to the intervention [24].”

    From A web-based self-help intervention for partners of cancer patients based on Acceptance and Commitment Therapy: a protocol of a randomized controlled trial. (2015) · cites this paper as [24]

    The Principal results passage reports that greater dialogue support was associated with better adherence, and the Persuasive technology passage says reminders increase adherence. But the Principal results report only a trend for social support and no predictive value for primary task support, the category that includes tunneling. The source therefore supports designing with persuasive elements to improve adherence, but not an adherence benefit for every example listed. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Part of this paper’s reference list could not be split into single entries.

Flagged first, then by citations

Research works printed but not linked: 154

  1. Eysenbach G. What is e-health? J Med Internet Res 2001 Apr-Jun;3(2):E20.
  2. Nijland N. Grounding eHealth: towards a holistic framework for sustainable eHealth technologies (Doctoral Dissertation): University of Twente; 2011.
  3. Fogg BJ. Persuasive technology: using computers to change what we think and do. Boston: Morgan Kaufmann Publishers; 2003.
  4. Schubart JR, Stuckey HL, Ganeshamoorthy A, Sciamanna CN. Chronic health conditions and internet behavioral interventions: a review of factors to enhance user engagement. Comput Inform Nurs 2011 Feb;29(2 Suppl):TC9-20.
  5. Balmford J, Borland R, Benda P. Patterns of use of an automated interactive personalized coaching program for smoking cessation. J Med Internet Res 2008;10(5):e54.
  6. Kroeze W, Werkman A, Brug J. A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Ann Behav Med 2006 Jun;31(3):205-223.
  7. An JY, Hayman LL, Park YS, Dusaj TK, Ayres CG. Web-based weight management programs for children and adolescents: a systematic review of randomized controlled trial studies. ANS Adv Nurs Sci 2009;32(3):222-240.
  8. Douwes M, Hildebrandt VH. Vragen naar de mate van lichamelijke activiteit. Geneeskd Sport 2000;33(1):9-16.
  9. Balmford J, Borland R, Benda P. Patterns of use of an automated interactive personalized coaching program for smoking cessation. J Med Internet Res 2008;10(5):e54.
  10. Nijland N, van Gemert-Pijnen JE, Boer H, Steehouder MF, Seydel ER. Increasing the use of e-consultation in primary care: results of an online survey among non-users of e- consultation. Int J Med Inform 2009 Oct;78(10):688-703.
  11. Neve MJ, Collins CE, Morgan PJ. Dropout, nonusage attrition, and pretreatment predictors of nonusage attrition in a commercial Web-based weight loss program. J Med Internet Res 2010;12(4):e69.
  12. Binks M, van Mierlo T. Utilization patterns and user characteristics of an ad libitum Internet weight loss program. J Med Internet Res 2010;12(1):e9.
  13. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res 2010;12(1):e4.
  14. Fogg BJ. Persuasive Technology: Using Computers to Change What We Think and Do. San Francisco, CA: Morgan Kaufmann Publishers; 2003. References
  15. Barak A, Klein B, Proudfoot JG. Defining internet-supported therapeutic interventions. Ann Behav Med 2009 Aug;38(1):4-17.
  16. Barak A, Hen L, Boniel-Nissim M, Shapira Na. A Comprehensive Review and a Meta- Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions. J Technol Hum Serv 2008;26(2/4):109-160.
  17. Cuijpers P, van Straten A, Andersson G. Internet-administered cognitive behavior therapy for health problems: a systematic review. J Behav Med 2008 Apr;31(2):169-177.
  18. Spek V, Cuijpers P, Nyklicek I, Riper H, Keyzer J, Pop V. Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis. Psychol Med 2007 Mar;37(3):319-328.
  19. Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The effectiveness of Web-based vs. non-Web-based interventions: a meta-analysis of behavioral change outcomes. J Med Internet Res 2004 Nov 10;6(4):e40.
  20. Vandelanotte C, Spathonis KM, Eakin EG, Owen N. Website-delivered physical activity interventions a review of the literature. Am J Prev Med 2007 Jul;33(1):54-64.
  21. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res 2010;12(1):e4.
  22. Norman GJ, Zabinski MF, Adams MA, Rosenberg DE, Yaroch AL, Atienza AA. A review of eHealth interventions for physical activity and dietary behavior change. Am J Prev Med 2007 Oct;33(4):336-345.
  23. Neve M, Morgan PJ, Jones PR, Collins CE. Effectiveness of web-based interventions in achieving weight loss and weight loss maintenance in overweight and obese adults: a systematic review with meta-analysis. Obes Rev 2010 Apr;11(4):306-321.
  24. Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med 2011;8(1):e1000387.
  25. van Gemert-Pijnen JE, Nijland N, van Limburg M, Ossebaard HC, Kelders SM, Eysenbach G, Seydel ER. A holistic framework to improve the uptake and impact of eHealth technologies. J Med Internet Res 2011;13(4):e111.
  26. Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. J Med Internet Res 2009;11(2):e13.
  27. Cugelman B, Thelwall M, Dawes P. Online interventions for social marketing health behavior change campaigns: a meta-analysis of psychological architectures and adherence factors. J Med Internet Res 2011;13(1):e17.
  28. Eysenbach G. The law of attrition. J Med Internet Res 2005;7(1):e11.
  29. Neil AL, Batterham P, Christensen H, Bennett K, Griffiths KM. Predictors of adherence by adolescents to a cognitive behavior therapy website in school and community- based settings. J Med Internet Res 2009;11(1):e6.
  30. Wangberg SC, Bergmo TS, Johnsen JA. Adherence in Internet-based interventions. Patient Prefer Adherence 2008;2:57-65.
  31. Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. J Med Internet Res 2011;13(3):e52.
  32. Manwaring JL, Bryson SW, Goldschmidt AB, Winzelberg AJ, Luce KH, Cunning D, Wilfley DE, Taylor CB. Do adherence variables predict outcome in an online program for the prevention of eating disorders? J Consult Clin Psychol 2008 Apr;76(2):341-346.
  33. Aronson JK. Compliance, concordance, adherence. Br J Clin Pharmacol 2007 Apr;63(4):383-384.
  34. Neve MJ, Collins CE, Morgan PJ. Dropout, nonusage attrition, and pretreatment predictors of nonusage attrition in a commercial Web-based weight loss program. J Med Internet Res 2010;12(4):e69.
  35. Fogg BJ. Persuasive technology: using computers to change what we think and do. Amsterdam; Boston: Morgan Kaufmann Publishers; 2003.
  36. Purpura S, Schwanda V, Williams K, Stubler W, Sengers P. Fit4life: the design of a persuasive technology promoting healthy behavior and ideal weight. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems; 2011 May 7-12; Vancouver, BC, Canada.
  37. Brouwer W, Kroeze W, Crutzen R, de Nooijer J, de Vries NK, Brug J, Oenema A. Which intervention characteristics are related to more exposure to internet-delivered healthy lifestyle promotion interventions? A systematic review. J Med Internet Res 2011;13(1):e2.
  38. Schubart JR, Stuckey HL, Ganeshamoorthy A, Sciamanna CN. Chronic health conditions and internet behavioral interventions: a review of factors to enhance user engagement. Comput Inform Nurs 2011 Feb;29(2 Suppl):TC9-20.
  39. Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: Key Issues, Process Model, and System Features. Commun Assoc Inf Syst 2009;24(1):28.
  40. Noar SM, Benac CN, Harris MS. Does tailoring matter? Meta-analytic review of tailored print health Behavior change interventions. Psychol Bull 2007 Jul;133(4):673-693.
  41. Fry JP, Neff RA. Periodic Prompts and Reminders in Health Promotion and Health Behavior Interventions: Systematic Review. J Med Internet Res 2009 Apr-Jun;11(2).
  42. Deterding S, Dixon D, Khaled R. Gamification: Toward a Definition. Proceedings of the ACM CHI Gamification Workshop; 2011 May 7-12; Vancouver, BC, Canada.
  43. Glasgow RE, Christiansen SM, Kurz D, King DK, Woolley T, Faber AJ, Estabrooks PA, Strycker L, Toobert D, Dickman J. Engagement in a Diabetes Self-management Website: Usage Patterns and Generalizability of Program Use. J Med Internet Res 2011 Jan-Mar;13(1):70-83.
  44. van Bastelaar KMP, Pouwer F, Cuijpers P, Riper H, Snoek FJ. Web-Based Depression Treatment for Type 1 and Type 2 Diabetic Patients A randomized, controlled trial. Diabetes Care 2011 Feb;34(2):320-325.
  45. Postel MG, de Haan HA, ter Huurne ED, Becker ES, de Jong CA. Effectiveness of a web- based intervention for problem drinkers and reasons for dropout: randomized controlled trial. Journal of Medical Internet Research 2010;12(4):e68.
  46. Griffiths F, Lindenmeyer A, Powell J, Lowe P, Thorogood M. Why are health care interventions delivered over the Internet? A systematic review of the published literature. Journal of Medical Internet Research 2006;8(2).
  47. Eysenbach G. What is e-health? Journal of Medical Internet Research 2001 Apr- Jun;3(2):E20.
  48. Barak A, Hen L, Boniel-Nissim M, Shapira Na. A Comprehensive Review and a Meta- Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions. Journal of Technology in Human Services 2008;26(2/4):109-160.
  49. Van Gemert-Pijnen JE, Nijland N, Van Limburg MAH, Ossebaard HC, Kelders SM, Eysenbach G, Seydel ER. A holistic framework to improve the uptake and impact of eHealth technologies. Journal of medical Internet research 2011;13(4).
  50. Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med 2011;8(1):e1000387.
  51. Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. Journal of medical Internet research 2009;11(2):e13.
  52. Eysenbach G. The law of attrition. Journal of medical Internet research 2005;7(1):e11.
  53. Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. Journal of medical Internet research 2011;13(3):e52.
  54. Kelders SM, Van Gemert-Pijnen JE, Werkman A, Nijland N, Seydel ER. Effectiveness of a Web-based intervention aimed at healthy dietary and physical activity behavior: a randomized controlled trial about users and usage. Journal of medical Internet research 2011;13(2):e32.
  55. Nijland N. Grounding eHealth: towards a holistic framework for sustainable eHealth technologies (Doctoral Dissertation). 2011; Retrieved from http://www.utwente.nl/gw/pgt/proefschriften/nijlandproefschrift.doc/.
  56. van Limburg M, van Gemert-Pijnen JEWC, Nijland N, Ossebaard HC, Hendrix RMG, Seydel ER. Why Business Modeling is Crucial in the Development of eHealth Technologies. Journal of Medical Internet Research 2011 Oct-Dec;13(4).
  57. Pagliari C. Design and evaluation in eHealth: challenges and implications for an interdisciplinary field. Journal of medical Internet research 2007;9(2):e15.
  58. Fogg BJ. Persuasive technology: using computers to change what we think and do. Boston: Morgan Kaufmann Publishers; 2003.
  59. Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems 2009;24(1):28.
  60. Gould JD, Lewis C. Designing for Usability -Key Principles and What Designers Think. Communications of the ACM 1985;28(3):300-311.
  61. Kujala S. User involvement: a review of the benefits and challenges. Behaviour & Information Technology 2003;22(1):1.
  62. Osterwalder A, Pigneur Y. Business model generation: a handbook for visionaries, game changers, and challengers. Hoboken, NJ: John Wiley & Sons; 2010.
  63. Mohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. Journal of medical Internet research 2011;13(1):e30.
  64. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. Journal of medical Internet research 2010;12(1):e4.
  65. Fry JP, Neff RA. Periodic Prompts and Reminders in Health Promotion and Health Behavior Interventions: Systematic Review. Journal of medical Internet research 2009 Apr-Jun;11(2).
  66. Andrews G, Issakidis C, Sanderson K, Corry J, Lapsley H. Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment of ten mental disorders. Br J Psychiatry 2004 Jun;184:526-533.
  67. Cuijpers P, van Straten A, Smit F, Mihalopoulos C, Beekman A. Preventing the onset of depressive disorders: a meta-analytic review of psychological interventions. A J Psychiatry 2008 Oct;165(10):1272-1280.
  68. Hollon SD, Munoz RF, Barlow DH, Beardslee WR, Bell CC, Bernal G, Clarke GN, Franciosi LP, Kazdin AE, Kohn L, Linehan MM, Markowitz JC, Miklowitz DJ, Persons JB, Niederehe G, Sommers D. Psychosocial intervention development for the prevention and treatment of depression: Promoting innovation and increasing access. Biol Psychiat 2002 Sep 15;52(6):610-630.
  69. Andrews G, Cuijpers P, Craske MG, McEvoy P, Titov N. Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: a meta-analysis. PLoS One 2010;5(10):e13196.
  70. Barak A, Hen L, Boniel-Nissim M, Shapira Na. A Comprehensive Review and a Meta- Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions. J Technol Hum Serv 2008;26(2/4):109-160.
  71. Beekman AT, Smit F, Stek ML, Reynolds CF, 3rd, Cuijpers PC. Preventing depression in high-risk groups. Curr Opin Psychiatry 2010 Jan;23(1):8-11.
  72. Cuijpers P, van Straten A, Warmerdam L, van Rooy MJ. Recruiting participants for interventions to prevent the onset of depressive disorders: possible ways to increase participation rates. BMC Health Services Research 2010;10:181.
  73. Van Voorhees BW, Mahoney N, Mazo R, Barrera AZ, Siemer CP, Gladstone TR, Munoz RF. Internet-based depression prevention over the life course: a call for behavioral vaccines. The Psychiatric clinics of North America 2011 Mar;34(1):167-183.
  74. Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cognitive behaviour therapy 2009 Dec;38(4):196-205.
  75. Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med 2011;8(1):e1000387.
  76. Van Gemert-Pijnen JE, Nijland N, Van Limburg MAH, Ossebaard HC, Kelders SM, Eysenbach G, Seydel ER. A holistic framework to improve the uptake and impact of eHealth technologies. Journal of Medical Internet Research 2011;13(4).
  77. Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. Journal of medical Internet research 2009;11(2):e13.
  78. Eysenbach G. The law of attrition. Journal of medical Internet research 2005;7(1):e11.
  79. Manwaring JL, Bryson SW, Goldschmidt AB, Winzelberg AJ, Luce KH, Cunning D, Wilfley DE, Taylor CB. Do adherence variables predict outcome in an online program for the prevention of eating disorders? J Consult Clin Psychol 2008 Apr;76(2):341-346.
  80. Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. Journal of medical Internet research 2011;13(3):e52.
  81. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. Journal of medical Internet research 2010;12(1):e4.
  82. Brouwer W, Kroeze W, Crutzen R, de Nooijer J, de Vries NK, Brug J, Oenema A. Which intervention characteristics are related to more exposure to internet-delivered healthy lifestyle promotion interventions? A systematic review. Journal of medical Internet research 2011;13(1):e2.
  83. Kelders SM, Van Gemert-Pijnen JE, Werkman A, Nijland N, Seydel ER. Effectiveness of a Web-based intervention aimed at healthy dietary and physical activity behavior: a randomized controlled trial about users and usage. Journal of medical Internet research 2011;13(2):e32.
  84. Hayes SC, Strosahl K, Wilson KG. Acceptance and Commitment Therapy: An experiential approach to behavior change. New York: Guilford Press; 1999.
  85. Kabat-Zinn J. Full catastrophe living : using the wisdom of your body and mind to face stress, pain, and illness. New York: Delacorte Press; 1990.
  86. Bohlmeijer ET, Fledderus M, Rokx TA, Pieterse ME. Efficacy of an early intervention based on acceptance and commitment therapy for adults with depressive symptomatology: Evaluation in a randomized controlled trial. Behav Res Ther 2011 Jan;49(1):62-67.
  87. Fledderus M, Bohlmeijer ET, Smit F, Westerhof GJ. Mental health promotion as a new goal in public mental health care: a randomized controlled trial of an intervention enhancing psychological flexibility. Am J Public Health 2010 Dec;100(12):2372.
  88. Titov N, Andrews G, Choi I, Schwencke G, Johnston L. Randomized controlled trial of web-based treatment of social phobia without clinician guidance. Aust N Z J Psychiatry 2009;43(10):913-919.
  89. Kelders SM, Kok RN, Ossebaard HC, Van Gemert-Pijnen JEWC. Persuasive system design does matter: a systematic review of adherence to web-based interventions. J Med Internet Res; in press.
  90. Fogg BJ. Persuasive technology: using computers to change what we think and do. Boston: Morgan Kaufmann Publishers; 2003.
  91. Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems 2009;24(1):28.
  92. Fry JP, Neff RA. Periodic Prompts and Reminders in Health Promotion and Health Behavior Interventions: Systematic Review. Journal of medical Internet research 2009 Apr-Jun;11(2).
  93. Tsang MW, Mok M, Kam G, Jung M, Tang A, Chan U, Chu CM, Li I, Chan J. Improvement in diabetes control with a monitoring system based on a hand-held, touch-screen electronic diary. J Telemed Telecare 2001;7(1):47-50.
  94. Andrews G, Issakidis C, Sanderson K, Corry J, Lapsley H. Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment of ten mental disorders. Br J Psychiatry 2004 Jun;184:526-533.
  95. Cuijpers P, van Straten A, Smit F, Mihalopoulos C, Beekman A. Preventing the onset of depressive disorders: a meta-analytic review of psychological interventions. Am J Psychiatry 2008 Oct;165(10):1272-1280.
  96. Hollon SD, Munoz RF, Barlow DH, Beardslee WR, Bell CC, Bernal G, Clarke GN, Franciosi LP, Kazdin AE, Kohn L, Linehan MM, Markowitz JC, Miklowitz DJ, Persons JB, Niederehe G, Sommers D. Psychosocial intervention development for the prevention and treatment of depression: Promoting innovation and increasing access. Biol Psychiat 2002 Sep 15;52(6):610-630.
  97. Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cognitive behaviour therapy 2009 Dec;38(4):196-205.
  98. Andrews G, Cuijpers P, Craske MG, McEvoy P, Titov N. Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: a meta-analysis. PLoS One 2010;5(10):e13196.
  99. Barak A, Hen L, Boniel-Nissim M, Shapira Na. A Comprehensive Review and a Meta- Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions. J Technol Hum Serv 2008;26(2/4):109-160.
  100. Beekman AT, Smit F, Stek ML, Reynolds CF, 3rd, Cuijpers PC. Preventing depression in high-risk groups. Current opinion in psychiatry 2010 Jan;23(1):8-11.
  101. Cuijpers P, van Straten A, Warmerdam L, van Rooy MJ. Recruiting participants for interventions to prevent the onset of depressive disorders: possible ways to increase participation rates. BMC Health Services Research 2010;10:181.
  102. Van Voorhees BW, Mahoney N, Mazo R, Barrera AZ, Siemer CP, Gladstone TR, Munoz RF. Internet-based depression prevention over the life course: a call for behavioral vaccines. The Psychiatric clinics of North America 2011 Mar;34(1):167-183.
  103. Barak A, Klein B, Proudfoot JG. Defining internet-supported therapeutic interventions. Ann Behav Med 2009 Aug;38(1):4-17.
  104. Van Gemert-Pijnen JE, Nijland N, Van Limburg MAH, Ossebaard HC, Kelders SM, Eysenbach G, Seydel ER. A holistic framework to improve the uptake and impact of eHealth technologies. Journal of Medical Internet Research 2011;13(4).
  105. Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med 2011;8(1):e1000387.
  106. Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. Journal of medical Internet research 2009;11(2):e13.
  107. Eysenbach G. The law of attrition. Journal of medical Internet research 2005;7(1):e11.
  108. Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. Journal of medical Internet research 2011;13(3):e52.
  109. Manwaring JL, Bryson SW, Goldschmidt AB, Winzelberg AJ, Luce KH, Cunning D, Wilfley DE, Taylor CB. Do adherence variables predict outcome in an online program for the prevention of eating disorders? J Consult Clin Psychol 2008 Apr;76(2):341-346.
  110. Kelders SM, Van Gemert-Pijnen JE, Werkman A, Nijland N, Seydel ER. Effectiveness of a Web-based intervention aimed at healthy dietary and physical activity behavior: a randomized controlled trial about users and usage. Journal of medical Internet research 2011;13(2):e32.
  111. Brouwer W, Kroeze W, Crutzen R, de Nooijer J, de Vries NK, Brug J, Oenema A. Which intervention characteristics are related to more exposure to internet-delivered healthy lifestyle promotion interventions? A systematic review. Journal of medical Internet research 2011;13(1):e2.
  112. Schubart JR, Stuckey HL, Ganeshamoorthy A, Sciamanna CN. Chronic health conditions and internet behavioral interventions: a review of factors to enhance user engagement. Comput Inform Nurs 2011 Feb;29(2 Suppl):TC9-20.
  113. Balmford J, Borland R, Benda P. Patterns of use of an automated interactive personalized coaching program for smoking cessation. Journal of Medical Internet Research 2008;10(5):e54.
  114. Binks M, van Mierlo T. Utilization patterns and user characteristics of an ad libitum Internet weight loss program. Journal of Medical Internet Research 2010;12(1):e9.
  115. Christensen H, Griffiths KM, Korten A. Web-based cognitive behavior therapy: analysis of site usage and changes in depression and anxiety scores. Journal of Medical Internet Research 2002 Jan-Mar;4(1):e3.
  116. Couper MP, Alexander GL, Zhang NH, Little RJA, Maddy N, Nowak MA, McClure JB, Calvi JJ, Rolnick SJ, Stopponi MA, Johnson CC. Engagement and Retention: Measuring Breadth and Depth of Participant Use of an Online Intervention. Journal of Medical Internet Research 2010 Oct-Dec;12(4):41-55.
  117. Davies C, Corry K, Van Itallie A, Vandelanotte C, Caperchione C, Mummery WK. Prospective associations between intervention components and website engagement in a publicly available physical activity website: the case of 10,000 Steps Australia. Journal of Medical Internet Research 2012;14(1):e4.
  118. Linke S, Murray E, Butler C, Wallace P. Internet-based interactive health intervention for the promotion of sensible drinking: patterns of use and potential impact on members of the general public. Journal of Medical Internet Research 2007;9(2):e10.
  119. Zbikowski SM, Hapgood J, Smucker Barnwell S, McAfee T. Phone and web-based tobacco cessation treatment: real-world utilization patterns and outcomes for 11,000 tobacco users. Journal of Medical Internet Research 2008;10(5):e41.
  120. Glasgow RE, Christiansen SM, Kurz D, King DK, Woolley T, Faber AJ, Estabrooks PA, Strycker L, Toobert D, Dickman J. Engagement in a diabetes self-management website: usage patterns and generalizability of program use. Journal of Medical Internet Research 2011;13(1):e9.
  121. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Applied psychological measurement 1977;1(3):385-401.
  122. Hayes SC, Strosahl K, Wilson KG. Acceptance and Commitment Therapy: An experiential approach to behavior change. New York: Guilford Press; 1999.
  123. Kabat-Zinn J. Full catastrophe living : using the wisdom of your body and mind to face stress, pain, and illness. New York: Delacorte Press; 1990.
  124. Bohlmeijer ET, Fledderus M, Rokx TA, Pieterse ME. Efficacy of an early intervention based on acceptance and commitment therapy for adults with depressive symptomatology: Evaluation in a randomized controlled trial. Behav Res Ther 2011 Jan;49(1):62-67.
  125. Fledderus M, Bohlmeijer ET, Smit F, Westerhof GJ. Mental health promotion as a new goal in public mental health care: a randomized controlled trial of an intervention enhancing psychological flexibility. Am J Public Health 2010 Dec;100(12):2372.
  126. Haringsma R, Engels GI, Beekman ATF, Spinhoven P. The criterion validity of the Center for Epidemiological Studies Depression Scale (CES-D) in a sample of self- referred elders with depressive symptomatology. Int J Geriatr Psych 2004 Jun;19(6):558-563.
  127. Spinhoven P, Ormel J, Sloekers PPA, Kempen GIJM, Speckens AEM, VanHemert AM. A validation study of the Hospital Anxiety and Depression Scale (HADS) in different groups of Dutch subjects. Psychol Med 1997 Mar;27(2):363-370.
  128. Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiat Scand 1983;67(6):361-370.
  129. DeLone WH, McLean ER. The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems 2003;19(4):9.
  130. Nijland N, van Gemert-Pijnen JEWC, Kelders SM, Brandenburg BJ, Seydel ER. Factors Influencing the Use of a Web-Based Application for Supporting the Self-Care of Patients with Type 2 Diabetes: A Longitudinal Study. Journal of Medical Internet Research 2011 Jul-Sep;13(3).
  131. Hirsh JB, Kang SK, Bodenhausen GV. Personalized persuasion: tailoring persuasive appeals to recipients' personality traits. Psychological science 2012 Jun 1;23(6):578-581.
  132. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Applied psychological measurement 1977;1(3):385-401.
  133. Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiat Scand 1983;67(6):361-370.
  134. Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. J Med Internet Res 2009;11(2):e13.
  135. Eysenbach G. The law of attrition. J Med Internet Res 2005;7(1):e11.
  136. Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems 2009;24(1):28.
  137. Farvolden P, Denisoff E, Selby P, Bagby RM, Rudy L. Usage and longitudinal effectiveness of a Web-based self-help cognitive behavioral therapy program for panic disorder. J Med Internet Res 2005;7(1):e7.
  138. Balmford J, Borland R, Benda P. Patterns of use of an automated interactive personalized coaching program for smoking cessation. J Med Internet Res 2008;10(5):e54.
  139. Binks M, van Mierlo T. Utilization patterns and user characteristics of an ad libitum Internet weight loss program. J Med Internet Res 2010;12(1):e9.
  140. Christensen H, Griffiths KM, Korten A. Web-based cognitive behavior therapy: analysis of site usage and changes in depression and anxiety scores. J Med Internet Res 2002 Jan-Mar;4(1):e3.
  141. Couper MP, Alexander GL, Zhang NH, Little RJA, Maddy N, Nowak MA, McClure JB, Calvi JJ, Rolnick SJ, Stopponi MA, Johnson CC. Engagement and Retention: Measuring Breadth and Depth of Participant Use of an Online Intervention. J Med Internet Res 2010 Oct-Dec;12(4):41-55.
  142. Davies C, Corry K, Van Itallie A, Vandelanotte C, Caperchione C, Mummery WK. Prospective associations between intervention components and website engagement in a publicly available physical activity website: the case of 10,000 Steps Australia. J Med Internet Res 2012;14(1):e4.
  143. Glasgow RE. eHealth evaluation and dissemination research. Am J Prev Med 2007 May;32(5):S119-S126.
  144. Linke S, Murray E, Butler C, Wallace P. Internet-based interactive health intervention for the promotion of sensible drinking: patterns of use and potential impact on members of the general public. J Med Internet Res 2007;9(2):e10.
  145. Zbikowski SM, Hapgood J, Smucker Barnwell S, McAfee T. Phone and web-based tobacco cessation treatment: real-world utilization patterns and outcomes for 11,000 tobacco users. J Med Internet Res 2008;10(5):e41.
  146. Glasgow RE, Christiansen SM, Kurz D, King DK, Woolley T, Faber AJ, Estabrooks PA, Strycker L, Toobert D, Dickman J. Engagement in a diabetes self-management website: usage patterns and generalizability of program use. J Med Internet Res 2011;13(1):e9.
  147. Krukowski RA, Harvey-Berino J, Ashikaga T, Thomas CS, Micco N. Internet-Based Weight Control: The Relationship Between Web Features and Weight Loss. Telemed J E-Health 2008 Oct;14(8):775-782.
  148. Van Gemert-Pijnen JE, Riper H. Workshop Blended Care. Symposium Supporting Health by Technology IV 2012.
  149. Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. J Med Internet Res 2011;13(3):e52.
  150. Collins LM, Murphy SA, Nair VN, Strecher VJ. A strategy for optimizing and evaluating behavioral interventions. Ann Behav Med 2005 Aug;30(1):65-73.
  151. Oinas-Kukkonen H. Behavior Change Support Systems: A Research Model and Agenda. Lect Notes Comput Sc 2010;6137:4-14.
  152. Fogg BJ. Persuasive technology: using computers to change what we think and do. Boston: Morgan Kaufmann Publishers; 2003.
  153. Rothert K, Strecher VJ, Doyle LA, Caplan WM, Joyce JS, Jimison HB, Karm LM, Mims AD, Roth MA. Web-based weight management programs in an integrated health care setting: a randomized, controlled trial. Obesity (Silver Spring) 2006 Feb;14(2):266-272.
  154. Nijland N. Grounding eHealth: towards a holistic framework for sustainable eHealth technologies (Doctoral Dissertation): University of Twente; 2011.

Cited by

Sorted by citations

Authors
Kelders, S. M.
Corresponding author
Kelders, Saskia M.
Published
2012-07-30
OpenAlex
W2117698425
Cited by
29
References
307
Citations by year
2023: 1 · 2022: 1 · 2021: 2 · 2020: 2 · 2018: 2 · 2017: 3 · 2016: 4 · 2015: 6 · 2014: 3 · 2013: 5
Type
dissertation
Language
en
Open access
Licence
other-oa
Locations
University of Twente Research Information (submittedVersion, other-oa)
Funders
  • University of Twente
  • Rijksinstituut voor Volksgezondheid en Milieu
Topics
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
Keywords
online intervention, intervention adherence, virtual coach, chronic disease prevention, adaptive systems, health literacy, e-health, tailored health communication, health disparities, underserved populations, information seeking, digital health literacy

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review