The effect of visual interventions on illness beliefs and medication adherence for chronic conditions: A scoping review of the literature and mapping to behaviour change techniques (BCTs)

2021 ◽  
Author(s):  
S.L. Brown ◽  
D. McRae ◽  
E. Sheils ◽  
B.J. McDonnell ◽  
I. Khan ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Behaviour Change ◽  
Scoping Review ◽  
Chronic Conditions ◽  
Behaviour Change Techniques ◽  
Illness Beliefs ◽  
Review Of The Literature

scholarly journals Barriers, facilitators, and interventions for medication adherence across chronic conditions with the highest non-adherence rates: a scoping review with recommendations for intervention development

2020 ◽  
Author(s):  
Pinelopi Konstantinou ◽  
Angelos P Kassianos ◽  
Giοrgos Georgiou ◽  
Andreas Panayides ◽  
Alexia Papageorgiou ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Behavioral Health ◽  
Scoping Review ◽  
Low Income ◽  
Chronic Conditions ◽  
Health Interventions ◽  
Barriers And Facilitators ◽  
World Health ◽  
Medication Cost ◽  
Multicomponent Interventions

Abstract Medication non-adherence (MNA) constitutes a complex health problem contributing to increased economic burden and poor health outcomes. The Medication Adherence Model (MAM) supports that numerous processes are involved in medication adherence (MA). Based on the MAM and guidelines of the World Health Organization (WHO), this scoping review aimed to identify the barriers and facilitators associated with MA, and the behavioral health interventions and techniques among chronic conditions presenting with high non-adherence rates (asthma, cancer, diabetes, epilepsy, HIV/AIDS, and hypertension). PubMed, PsycINFO, and Scopus databases were screened, and 243 studies were included. A mixed methods approach was used to collate the evidence and interpret findings. The most commonly reported barriers to MA across conditions were younger age, low education, low income, high medication cost, side effects, patient beliefs/perceptions, comorbidities, and poor patient–provider communication. Additionally, digitally delivered interventions including components such as medication and condition education, motivational interviewing (MI), and reinforcement and motivational messages led to improvements in MA. This review highlights the importance of administrating multicomponent interventions digitally and personalized to the patients’ individual needs and characteristics, responding to the adherence barriers faced. This is the first review examining and synthesizing evidence on barriers and facilitators to MA and behavioral health interventions used for improving MA across chronic conditions with the highest non-adherence rates and providing recommendations to researchers and clinicians. Stakeholders are called to explore methods overcoming barriers identified and developing effective multicomponent interventions that can reduce the high rates of MNA.

scholarly journals Implementing the use of objective medication adherence data in routine clinical practice via the digital CFHealthHub platform: situation analysis and strategy development using the theoretical domains framework

2021 ◽  
Author(s):  
Carla Girling ◽  
Anna Packham ◽  
Louisa Robinson ◽  
Madelynne A Arden ◽  
Daniel Hind ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Medication Adherence ◽  
Behaviour Change ◽  
Implementation Strategy ◽  
Clinical Care ◽  
Theoretical Domains Framework ◽  
Behaviour Change Techniques ◽  
Implementation Phase ◽  
Adherence Data ◽  
Healthcare Innovation

Abstract Background Preventative inhaled treatments preserve lung function and reduce exacerbations in Cystic Fibrosis (CF). Self-reported adherence to these treatments is over-estimated. An online platform (CFHealthHub) has been developed with patients and clinicians to display real-time objective adherence data from dose-counting nebulisers, so that clinical teams can offer informed treatment support. Methods In this paper, we identify pre-implementation barriers to healthcare practitioners performing two key behaviours: accessing objective adherence data through the website CFHealthHub and discussing medication adherence with patients. We aimed to understand barriers during the pre-implementation phase, so that appropriate strategy could be developed for the scale up of implementing objective adherence data in 19 CF centres. Thirteen semi-structured interviews were conducted with healthcare practitioners working in three UK CF centres. Qualitative data were coded using the Theoretical Domains Framework (TDF), which describes 14 validated domains to implementation behaviour change. Results Analysis indicated that an implementation strategy should address all 14 domains of the TDF to successfully support implementation. Participants did not report routines or habits for using objective adherence data in clinical care. Examples of salient barriers included skills, beliefs in consequences, and social influence and professional roles. The results also affirmed a requirement to address organisational barriers. Relevant behaviour change techniques were selected to develop implementation strategy modules using the behaviour change wheel approach to intervention development. ConclusionsThis paper demonstrates the value of applying the TDF at pre-implementation, to understand context and to support the development of a situationally relevant implementation strategy. Contribution to the literature· Research indicates that the implementation of healthcare innovations may be more likely to succeed when context and theory are taken into consideration. · In this study, healthcare professionals identified barriers to two behaviours that were key to the implementation of a national Cystic Fibrosis (CF) healthcare innovation. By coding barriers to the Theoretical Domains Framework (TDF), a contextually relevant implementation strategy was developed, with a focus on clinician behaviour change. · The study highlights the challenges CF teams face when implementing new remote monitoring of medication adherence, and provides an important opportunity to apply the TDF in the pre-implementation phase of a healthcare innovation.

scholarly journals The Challenges of Engaging Users with Diabetes Apps: A Randomized Controlled Trial of two Commercially Available Diabetes Apps (Preprint)

2020 ◽  
Author(s):  
Alita Maharaj ◽  
David Lim ◽  
Rinki Murphy ◽  
Anna Serlachius
Keyword(s):  
Outcome Measures ◽  
Behaviour Change ◽  
Self Care ◽  
Secondary Outcome ◽  
Behaviour Change Techniques ◽  
User Engagement ◽  
Illness Beliefs ◽  
Glucose Testing ◽  
Management Interventions ◽  
Clinical Support

BACKGROUND Diabetes apps represent a promising addition to face-to-face self-management interventions, which can be time and resource intensive. However, few randomised controlled trials have evaluated the efficacy of diabetes apps, in particular as a stand-alone intervention without additional clinical support. OBJECTIVE We used a parallel group randomised trial design to investigate user engagement of two commercially available apps (free versions of Glucose Buddy and mySugr) over two weeks. We hypothesised higher user engagement would be associated with improved self-care behaviours and illness beliefs in adults with type 2 diabetes (T2D). METHODS Adults with T2D attending outpatient diabetes clinics in Auckland were recruited and randomised (1:1 without blinding) to use either the Glucose Buddy or mySugr diabetes apps. User engagement and self-care behaviours (primary outcome measures) and illness beliefs (secondary outcome) were measured two weeks after baseline. Spearman’s correlations, Mann-Whitney U tests and Wilcoxon-signed ranks tests were used to explore associations between the outcome measures, as well as to investigate changes between and within groups. Six participants were interviewed to further explore acceptability and usability. RESULTS Fifty-eight participants (29/group) completed the two-week follow-up, out of which only 38 reported using the apps (Glucose Buddy = 20; mySugr = 18). Both groups reported low engagement (days used Mdn=4 for Glucose Buddy and Mdn=6.5 for mySugr, P=.06; minutes used Mdn=10 for both groups). No changes were observed in self-care or illness beliefs in either group. Out of the self-care behaviours, only blood glucose testing was significantly associated with minutes of app use (P=.02). The interviews suggested that although both apps were deemed acceptable, they were generally viewed as time-consuming and complex to use. CONCLUSIONS Low engagement with both Glucose Buddy and mySugr reflect the challenges associated with engaging users with diabetes apps. The results highlight the need for more clinical support as well as involvement from end users and behaviour change specialists in order to incorporate evidence-based behaviour change techniques to motivate and provide value to users. CLINICALTRIAL Registered with Australia New Zealand Clinical Trials Registry on March 23rd 2018 (ACTRN12618000424202).

A Scoping Review of Methods Used to Assess Medication Adherence in Patients with Chronic Conditions

2021 ◽  
Author(s):  
Pinelopi Konstantinou ◽  
Orestis Kasinopoulos ◽  
Christiana Karashiali ◽  
Geοrgios Georgiou ◽  
Andreas Panayides ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Quality Indicators ◽  
Scoping Review ◽  
Chronic Conditions ◽  
Electronic Monitoring ◽  
Intervention Development ◽  
Assessment Methods ◽  
Self Report ◽  
Evidence Based ◽  
Gold Standard Method

Abstract Background Medication nonadherence of patients with chronic conditions is a complex phenomenon contributing to increased economic burden and decreased quality of life. Intervention development relies on accurately assessing adherence but no “gold standard” method currently exists. Purpose The present scoping review aimed to: (a) review and describe current methods of assessing medication adherence (MA) in patients with chronic conditions with the highest nonadherence rates (asthma, cancer, diabetes, epilepsy, HIV/AIDS, hypertension), (b) outline and compare the evidence on the quality indicators between assessment methods (e.g., sensitivity), and (c) provide evidence-based recommendations. Methods PubMed, PsycINFO and Scopus databases were screened, resulting in 62,592 studies of which 71 met criteria and were included. Results Twenty-seven self-report and 10 nonself-report measures were identified. The Medication Adherence Report Scale (MARS-5) was found to be the most accurate self-report, whereas electronic monitoring devices such as Medication Event Monitoring System (MEMS) corresponded to the most accurate nonself-report. Higher MA rates were reported when assessed using self-reports compared to nonself-reports, except from pill counts. Conclusions Professionals are advised to use a combination of self-report (like MARS-5) and nonself-report measures (like MEMS) as these were found to be the most accurate and reliable measures. This is the first review examining self and nonself-report methods for MA, across chronic conditions with the highest nonadherence rates and provides evidence-based recommendations. It highlights that MA assessment methods are understudied in certain conditions, like epilepsy. Before selecting a MA measure, professionals are advised to inspect its quality indicators. Feasibility of measures should be explored in future studies as there is presently a lack of evidence.

scholarly journals Systematic Review of RCTs Assessing the Effectiveness of mHealth Interventions to Improve Statin Medication Adherence: Using the Behaviour-Change Technique Taxonomy to Identify the Techniques that Improve Adherence

Healthcare ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1282
Author(s):  
Zoe Bond ◽  
Tanya Scanlon ◽  
Gaby Judah
Keyword(s):  
Medication Adherence ◽  
Behaviour Change ◽  
Standard Of Care ◽  
Behaviour Change Techniques ◽  
Delivery Method ◽  
Improve Medication Adherence ◽  
Behaviour Change Technique ◽  
Effective Interventions ◽  
Statin Adherence ◽  
Credible Source

Statin non-adherence is a common problem in the management of cardiovascular disease (CVD), increasing patient morbidity and mortality. Mobile health (mHealth) interventions may be a scalable way to improve medication adherence. The objectives of this review were to assess the literature testing mHealth interventions for statin adherence and to identify the Behaviour-Change Techniques (BCTs) employed by effective and ineffective interventions. A systematic search was conducted of randomised controlled trials (RCTs) measuring the effectiveness of mHealth interventions to improve statin adherence against standard of care in those who had been prescribed statins for the primary or secondary prevention of CVD, published in English (1 January 2000–17 July 2020). For included studies, relevant data were extracted, the BCTs used in the trial arms were coded, and a quality assessment made using the Risk of Bias 2 (RoB2) questionnaire. The search identified 17 relevant studies. Twelve studies demonstrated a significant improvement in adherence in the mHealth intervention trial arm, and five reported no impact on adherence. Automated phone messages were the mHealth delivery method most frequently used in effective interventions. Studies including more BCTs were more effective. The BCTs most frequently associated with effective interventions were “Goal setting (behaviour)”, “Instruction on how to perform a behaviour”, and “Credible source”. Other effective techniques were “Information about health consequences”, “Feedback on behaviour”, and “Social support (unspecified)”. This review found moderate, positive evidence of the effect of mHealth interventions on statin adherence. There are four primary recommendations for practitioners using mHealth interventions to improve statin adherence: use multifaceted interventions using multiple BCTs, consider automated messages as a digital delivery method from a credible source, provide instructions on taking statins, and set adherence goals with patients. Further research should assess the optimal frequency of intervention delivery and investigate the generalisability of these interventions across settings and demographics.

Using Insights from Behavioural Science and Design Thinking to Develop mHealth Interventions: a Systematic Scoping Review (Preprint)

2022 ◽  
Author(s):  
Paula Voorheis ◽  
Albert Zhao ◽  
Kerry Kuluski ◽  
Quynh Pham ◽  
Ted Scott ◽  
...  
Keyword(s):  
Behaviour Change ◽  
Design Process ◽  
Scoping Review ◽  
Design Thinking ◽  
Design Science ◽  
Data Extraction ◽  
Descriptive Analysis ◽  
Future Research ◽  
Behaviour Change Techniques ◽  
Behavioural Science

BACKGROUND Mobile health (mHealth) interventions are increasingly being designed to facilitate health-related behaviour change. Integrating insights from behavioural science and design science can help support the development of more effective mHealth interventions. Behavioural Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process. OBJECTIVE The aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what approaches do mHealth design teams use to integrate BD and DT during the mHealth design process? (3) what are key implementation considerations, design challenges, and future directions for integrating BD and DT during mHealth design? METHODS We identified relevant studies from MEDLINE, PSYCINFO, EMBASE, CINAHL and JMIR using search terms related to mHealth, behavioural design, and design thinking. Included articles had to clearly describe their mHealth design process and how behaviour change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened articles for inclusion and completed the data extraction. A descriptive analysis was conducted. RESULTS A total of 75 articles met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which we refer to as “Behavioural Design Thinking”. Five steps were followed in the “Behavioural Design Thinking” approach: (1) empathise with users and their behaviour change needs, (2) define user and behaviour change requirements, (3) ideate user-centred features and behaviour change content, (4) prototype a user-centred solution that supports behaviour change, (5) test the solution against users’ needs and for its behaviour change potential. Key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behaviour change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems. Guidance is needed on how to conduct the design process itself, how to meaningfully engage key stakeholders, and how to operationalize behaviour change techniques in a user-friendly and context-specific way. CONCLUSIONS Best practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT could be integrated during mHealth design, future research is needed to identify the most effective design approaches. CLINICALTRIAL n/a

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