Treatment non-adherence in teenage and young adult patients with cancer

Adhering to treatment can be a significant issue for many patients diagnosed with chronic health conditions and this has been reported to be greater during the adolescent years. However, little is known about treatment adherence in teenage and young adult (TYA) patients with cancer. To increase awareness of the adherence challenges faced by these patients, we have reviewed the published work. The available evidence suggests that a substantial proportion of TYA patients with cancer do have difficulties, with reports that up to 63% of patients do not adhere to their treatment regimens. However, with inconsistent findings across studies, the true extent of non-adherence for these young patients is still unclear. Furthermore, it is apparent that there are many components of the cancer treatment regimen that have yet to be assessed in relation to patient adherence. Factors that have been shown to affect treatment adherence in TYA patients include patient emotional functioning (depression and self-esteem), patient health beliefs (perceived illness severity and vulnerability), and family environment (parental support and parent–child concordance). Strategies that foster greater patient adherence are also identified. These strategies are multifactorial, targeting not only the patient, but the health professional, family, and treatment regimen. This review highlights the lack of interventional studies addressing treatment adherence in TYA patients with cancer, with only one such intervention being identified: a video game intervention focusing on behavioural issues related to cancer treatment and care. Methodological issues in measuring adherence are addressed and suggestions for improving the design of future adherence studies highlighted, of which there is a great need.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.