A qualitative exploration of barriers and facilitatorsto adherence to an online self-help intervention for cancer-related distress.

OBJECTIVE: This study qualitatively explored barriers and facilitators of adherence to an online psychological intervention for cancer-related distress. METHODS: Semi-structured interviews were conducted with 13 adults with cancer, randomised to receive either a 6-week intervention (n = 8) or attention control (n = 5) as part of a larger RCT. Transcripts were coded for themes and subthemes, and recruitment ceased when saturation of themes occurred. RESULTS: Adherence overall was high: six participants completed all six modules, three completed five modules, two completed four modules, one completed one module, and one did not access the program. The total numbers of barriers (n = 19) and facilitators (n = 17) identified were equivalent and were categorised into five overarching themes: illness factors, psychological factors, personal factors, intervention factors and computer factors. However, the prevalence with which themes were discussed differed: illness factors (specifically cancer treatment side effects) were the main reported barrier to adherence; intervention factors (email reminders, program satisfaction, ease of use, program content) were the most common facilitators. CONCLUSION: While some factors were cited as both facilitating and barring adherence, and therefore reflective of personal preferences and circumstances, a number of recommendations were derived regarding (i) the best timing for online interventions and (ii) the need for multi-platform programs.

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.

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.

A Systematic Review of Predictors of, and Reasons for, Adherence to Online Psychological Interventions.

PURPOSE: A key issue regarding the provision of psychological therapy in a self-guided online format is low rates of adherence. The aim of this systematic review was to assess both quantitative and qualitative data on the predictors of adherence, as well as participant reported reasons for adhering or not adhering to online psychological interventions. METHODS: Database searches of PsycINFO, Medline, and CINAHL identified 1721 potentially relevant articles published between 1 January 2000 and 25 November 2015. A further 34 potentially relevant articles were retrieved from reference lists. Articles that reported predictors of, or reasons for, adherence to an online psychological intervention were included. RESULTS: A total of 36 studies met the inclusion criteria. Predictors assessed included demographic, psychological, characteristics of presenting problem, and intervention/computer-related predictors. Evidence suggested that female gender, higher treatment expectancy, sufficient time, and personalized intervention content each predicted higher adherence. Age, baseline symptom severity, and control group allocation had mixed findings. The majority of assessed variables however, did not predict adherence. CONCLUSIONS: Few clear predictors of adherence emerged overall, and most results were either mixed or too preliminary to draw conclusions. More research of predictors associated with adherence to online interventions is warranted.