Skip to main content

Advertisement

Log in

Uptake and adherence to an online intervention for cancer-related distress: older age is not a barrier to adherence but may be a barrier to uptake

  • Original Article
  • Published:
Supportive Care in Cancer Aims and scope Submit manuscript

Abstract

Purpose

While online interventions are increasingly explored as an alternative to therapist-based interventions for cancer-related distress, limitations to efficacy potentially include low uptake and adherence. Few predictors of uptake or adherence to online interventions have been consistently identified, particularly in individuals with cancer. This study examined rates and predictors of uptake and adherence to Finding My Way, a RCT of an online intervention versus an information-only online control for cancer-related distress.

Methods

Participants were adults with cancer treated with curative intent. Adherence was assessed by login frequency, duration and activity level; analyses examined demographic, medical and psychological predictors of uptake and adherence.

Results

The study enrolled 191 adults (aged 26–94 years) undergoing active treatment for cancer of any type. Uptake was highest for females and for individuals with ovarian (80%) and breast cancer (49.8%), and lowest for those with melanoma (26.5%). Adherence was predicted by older age and control-group allocation. Baseline distress levels did not predict adherence. High adherers to the full intervention had better emotion regulation and quality of life than low adherers.

Conclusions

Uptake of online intervention varies according to age, gender and cancer type. While uptake was higher amongst younger individuals, once enrolled, older individuals were more likely to adhere to online interventions for cancer-related distress.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Zabora J et al (2001) The prevalence of psychological distress by cancer site. Psycho-Oncology 10:19–28

    Article  CAS  PubMed  Google Scholar 

  2. Brebach, R., Sharpe, L., Costa, D., Rhoes, P., & Butow, P. 2016 Psychological intervention targeting distress for cancer patients: a meta-analytic study investigating uptake and adherence. Psycho-Oncology

  3. Cancer Australia and Cancer Council Australia (2010) Review of national cancer control activity in Australia. Cancer Australia, Canberra

    Google Scholar 

  4. Carlson LE et al (2004) High levels of untreated distress and fatigue in cancer patients. Br J Cancer 90:2297–2304

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Beatty L et al (2015) Finding My Way: protocol of a randomised controlled trial evaluating an internet self-help program for cancer-related distress. BMC Cancer 15(1):328–337

    Article  PubMed  PubMed Central  Google Scholar 

  6. Beatty L, Koczwara B, Wade TD (2016) Evaluating the efficacy of a self-guided web-based CBT intervention for reducing cancer-distress: a pilot randomised controlled trial. Support Care Cancer 24(3):1043–1051

    Article  PubMed  Google Scholar 

  7. Carpenter KM et al (2014) An online stress management workbook for breast cancer. J Behav Med 37:458–468

    Article  PubMed  Google Scholar 

  8. van den Berg SW, Gielissen MFM, Custers JAE, van der Graaf WTA, Ottevanger PB, Prins JB (2015) BREATH: web-based self-management for psychological adjustment after primary breast cancer—results of a multicenter randomized controlled trial. J Clin Oncol 33(25):2763–2771

    Article  PubMed  Google Scholar 

  9. Willems, R.A., et al. 2016, Short-term effectiveness of a web-based tailored intervention for cancer survivors on quality of life, anxiety, depression, and fatigue: randomized controlled trial. Psycho Oncology: p. n/a-n/a

  10. Barak A, Klein B, Proudfoot J (2009) Defining internet-supported therapeutic interventions. Ann Behav Med 38(1):4–17

    Article  PubMed  Google Scholar 

  11. Barak A et al (2008) A comprehensive review and a meta-analysis of the effectiveness of Internet-based psychotherapeutic interventions. J Technol Hum Serv 26(2–4):109–160

    Article  Google Scholar 

  12. Gellatly J et al (2007) What makes self-help interventions effective in the management of depressive symptoms? Meta-analysis and meta-regression. Psychol Med 37(9):1217–1228

    Article  PubMed  Google Scholar 

  13. Beatty L, Lambert S (2013) A systematic review of internet-based self-help therapeutic interventions to improve distress and disease-control among adults with chronic health conditions. Clin Psychol Rev 33:609–622

    Article  PubMed  Google Scholar 

  14. Waller R, Gilbody S (2009) Barriers to the uptake of computerized cognitive behavioural therapy: a systematic review of the quantitative and qualitative evidence. Psychol Med 39(5):705–712

    Article  CAS  PubMed  Google Scholar 

  15. Geraghty AWA, Wood AM, Hyland ME (2010) Attrition from self-directed interventions: investigating the relationship between psychological predictors, intervention content and dropout from a body dissatisfaction intervention. Soc Sci Med 71(1):30–37

    Article  PubMed  Google Scholar 

  16. Christensen H et al (2004) A comparison of changes in anxiety and depression symptoms of spontaneous users and trial participants of a cognitive behavior therapy website. Journal of Medical Internet Research 6(4):e46

    Article  PubMed  PubMed Central  Google Scholar 

  17. Farvolden P et al (2005) Usage and longitudinal effectiveness of a Web-based self-help cognitive behavioral therapy program for panic disorder. Journal of Medical Internet Research 7(1):e7

    Article  PubMed  PubMed Central  Google Scholar 

  18. Christensen H et al (2006) Free range users and one hit wonders: community users of an Internet-based cognitive behaviour therapy program. Aust N Z J Psychiatry 40:59–62

    Article  PubMed  Google Scholar 

  19. Christensen H, Griffiths K, Farrer L (2009) Adherence in internet interventions for anxiety and depression: systematic review. Journal of Medical Internet Research 11(2):e13

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ghaderi A (2006) Attrition and outcome in self-help treatment for bulimia nervosa and binge eating disorder: a constructive replication. Eat Behav 7(4):300–308

    Article  PubMed  Google Scholar 

  21. Beatty, L., & Binnion, Claire 2016, A systematic review of predictors of, and reasons for, adherence to online psychological interventions. International Journal of Behavioral Medicine

  22. van den Berg S et al (2013) Usage of a generic web-based self-management intervention for breast cancer survivors: substudy analysis of the BREATH trial. Journal of Medical Internet Research 15(8):e170

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kanera IM et al (2016) Use and appreciation of a tailored self-management ehealth intervention for early cancer survivors: process evaluation of a randomized controlled trial. Journal of Medical Internet Research 18(8):e229

    Article  PubMed  PubMed Central  Google Scholar 

  24. Wade TD, Nehmy T, Koczwara B (2005) Predicting worries about health after breast cancer surgery. Psycho-Oncology 14(6):503–509

    Article  PubMed  Google Scholar 

  25. Berrigan D et al (2003) Patterns of health behavior in U.S. adults. Prev Med 36(5):615–623

    Article  PubMed  Google Scholar 

  26. Donkin L et al (2011) A systematic review of the impact of adherence on the effectiveness of e-therapies. Journal of Medical Internet Research 13(3):e52

    Article  PubMed  PubMed Central  Google Scholar 

  27. Batterham PJ et al (2008) Predictors of adherence among community users of a cognitive behavior therapy website. Patient Preference and Adherence 2:97–105

    PubMed  PubMed Central  Google Scholar 

  28. Proudfoot NJ et al (2010) The ins and outs of an online bipolar education program: a study of program attrition. Journal of Medical Internet Research 12(5):e57

    Article  PubMed  PubMed Central  Google Scholar 

  29. Mor V, Allen S, Malin M (1994) The psychosocial impact of cancer on older versus younger patients and their families. Cancer 74:2118–2127

    Article  CAS  PubMed  Google Scholar 

  30. Cuijpers P, van Straten A, Andersson G (2008) Internet-administered cognitive behavior therapy for health problems: a systematic review. J Behav Med 31(2):169–177

    Article  PubMed  Google Scholar 

  31. Desrosiers A et al (2013) Mindfulness and emotion regulation in depression and anxiety: common and distinct mechanisms of action. Depression and Anxiety 13(7):654–661

    Article  Google Scholar 

  32. Ehring T, Watkins E (2008) Repetitive negative thinking as a transdiagnostic process. International Journal of Cognitive Therapy 1(3):192–205

    Article  Google Scholar 

  33. National Institute for Health and Care Excellence (2009) Depression in adults with a chronic physical health problem: recognition and management. National Institute for Health Care and Excellence, Manchester, UK

    Google Scholar 

  34. Browne GB et al (1990) Individual correlates of health service utilisation and the cost of poor adjustment to chronic illness. Med Care 28(1):43–58

    Article  CAS  PubMed  Google Scholar 

  35. Mausbach BT, Schwab RB, Irwin SA (2015) Depression as a predictor of adherence to adjuvant endocrine therapy (AET) in women with breast cancer: a systematic review and meta-analysis. Breast Cancer Res Treat 152(2):239–246

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Beatty L, Koczwara B, Wade T (2011) ‘Cancer Coping Online’: a pilot trial of a self-guided CBT internet intervention for cancer-related distress. Electronic Journal of Applied Psychology 7(2):17–25

    Google Scholar 

  37. Lancee J et al (2013) Motivational support provided via email improves the effectiveness of internet-delivered self-help treatment for insomnia: a randomized trial. Behaviour Research & Therapy 51(12):797–805

    Article  Google Scholar 

  38. Strecher, V.J., et al. 2008, The role of engagement in a tailored web-based smoking cessation program: randomized controlled trial. Journal of Medical Internet Research. 10(5)

  39. Australian Bureau of Statistics, 1991 1989–1990 National health survey users’ guide, Canberra: ABS. Cat No. 4363.0

  40. Foa EB et al (1993) Reliability and validity of a brief instrument for assessing post-traumatic stress disorder. J Trauma Stress 6(4):459–473

    Article  Google Scholar 

  41. Lovibond SH, Lovibond PH (1995) Manual for the Depression Anxiety Stress Scales (DASS). University of New South Wales, Sydney

    Google Scholar 

  42. Klee M, Groenvold M, Machin D (1997) Quality of life of Danish women: population-based norms for the EORTC QLQ-C30. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care & Rehabilitation 6(1):27–34

    Article  CAS  Google Scholar 

  43. Watson M et al (1994) The Mini-MAC: further development of the Mental Adjustment to Cancer scale. J Psychosoc Oncol 12(3):33–46

    Article  Google Scholar 

  44. Sherbourne CD, Stewart AL (1991) The MOS social support survey. Soc Sci Med 32(6):705–714

    Article  CAS  PubMed  Google Scholar 

  45. Miller SM (1987) Monitoring and blunting: validation of a questionnaire to assess styles of information seeking under threat. J Pers Soc Psychol 52:345–353

    Article  CAS  PubMed  Google Scholar 

  46. Gratz K, Roemer L (2004) Multidimensional assessment of emotion regulation and dysregulation: development, factor structure, and inital validation of the difficulties in emotion regulation scale. J Psychopathol Behav Assess 26(1):41–54

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the men and women who participated in this clinical trial, during a difficult stage of their lives.

The authors would like to acknowledge all Finding My Way Investigators and Recruiters for their assistance and support on this project.

This research was supported by a number of hospital sites and organisations. This includes recruitment support by Register4 through its members’ participation in research and/or provision of samples and information; and from Breast Cancer Network Australia’s (BCNA) Review & Survey Group, a national, online group of Australian women living with breast cancer who are interested in receiving invitations to participate in research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Emma Kemp.

Ethics declarations

Conflict of interest

This study was conducted as part of a larger clinical trial, for which L.B. is the recipient of a grant funded by the National Health and Medical Research Council (grant number 1042942). All other authors declare no conflict of interest.

Ethical approval

All procedures in studies involving human participants were conducted in accordance with the ethical standards of the Southern Adelaide Clinical Human Research Ethics Committee, the Royal Brisbane and Women’s Hospital Human Research Ethics Committee, and the ACT Health Human Research Ethics Committee, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Funding

This work was conducted as part of a larger clinical trial, supported by the National Health and Medical Research Council (grant number 1042942).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Beatty, L., Kemp, E., Binnion, C. et al. Uptake and adherence to an online intervention for cancer-related distress: older age is not a barrier to adherence but may be a barrier to uptake. Support Care Cancer 25, 1905–1914 (2017). https://doi.org/10.1007/s00520-017-3591-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00520-017-3591-1

Keywords

Navigation