Protocol of a mixed-methods evaluation of Perfect Fit:A personalized mHealth intervention with a virtual coach to promote smoking cessation and physical activity in adults

Objective: Adopting healthy behavior is vital for preventing chronic diseases. Mobile health (mHealth) interventions utilizing virtual coaches (i.e., artificial intelligence conversational agents) can offer scalable and cost-effective solutions. Additionally, targeting multiple unhealthy behaviors, like low physical activity and smoking, simultaneously seems beneficial. We developed Perfect Fit, an mHealth intervention with a virtual coach providing personalized feedback to simultaneously promote smoking cessation and physical activity. Through innovative methods (e.g., sensor technology) and iterative development involving end-users, we strive to overcome challenges encountered by mHealth interventions, such as shortage of evidence-based interventions and insufficient personalization. This paper outlines the content of Perfect Fit and the protocol for evaluating its feasibility, acceptability, and preliminary effectiveness, the role of participant characteristics, and the study's feasibility. Methods: A single-arm, mixed-method, real-world evaluation study will be conducted in the Netherlands. We aim to recruit 100 adult daily smokers intending to quit within 6 weeks. The personalized intervention will last approximately 16 weeks. Primary outcomes include Perfect Fit's feasibility and acceptability. Secondary outcomes are preliminary effectiveness and study feasibility, and we will measure participant characteristics. Quantitative data will be collected through questionnaires administered at baseline, post-intervention and 2, 6, and 12 months post-intervention. Qualitative data will be gathered via semi-structured interviews post-intervention. Data analysis will involve descriptive analyses, generalized linear mixed models (quantitative) and the Framework Approach (qualitative), integrating quantitative and qualitative data during interpretation. Conclusions: This study will provide novel insight into the potential of interventions like Perfect Fit, as a multiple health behavior change strategy. Findings will inform further intervention development and help identify methods to foster feasibility and acceptability. Successful mHealth interventions with virtual coaches will prevent chronic diseases and promote public health.</p

Targeting Key Risk Factors for Cardiovascular Disease in At-Risk Individuals: Developing a Digital, Personalized, and Real-Time Intervention to Facilitate Smoking Cessation and Physical Activity

Health care is under pressure due to an aging population with an increasing prevalence of chronic diseases, including cardiovascular disease. Smoking and physical inactivity are 2 key preventable risk factors for cardiovascular disease. Yet, as with most health behaviors, they are difficult to change. In the interdisciplinary Perfect Fit project, scientists from different fields join forces to develop an evidence-based virtual coach (VC) that supports smokers in quitting smoking and increasing their physical activity. In this Viewpoint paper, intervention content, design, and implementation, as well as lessons learned, are presented to support other research groups working on similar projects. A total of 6 different approaches were used and combined to support the development of the Perfect Fit VC. The approaches used are (1) literature reviews, (2) empirical studies, (3) collaboration with end users, (4) content and technical development sprints, (5) interdisciplinary collaboration, and (6) iterative proof-of-concept implementation. The Perfect Fit intervention integrates evidence-based behavior change techniques with new techniques focused on identity change, big data science, sensor technology, and personalized real-time coaching. Intervention content of the virtual coaching matches the individual needs of the end users. Lessons learned include ways to optimally implement and tailor interactions with the VC (eg, clearly explain why the user is asked for input and tailor the timing and frequency of the intervention components). Concerning the development process, lessons learned include strategies for effective interdisciplinary collaboration and technical development (eg, finding a good balance between end users’ wishes and legal possibilities). The Perfect Fit development process was collaborative, iterative, and challenging at times. Our experiences and lessons learned can inspire and benefit others. Advanced, evidence-based digital interventions, such as Perfect Fit, can contribute to a healthy society while alleviating health care burden

A mixed-methods evaluation of a virtual coach for smoking cessation and physical activity in adults

Mobile health (mHealth) interventions with virtual coaches (i.e. AI conversational agents) offer scalable and cost-effective solutions for health behavior change. We developed Perfect Fit, an mHealth intervention with a virtual coach providing personalized feedback to promote smoking cessation and physical activity simultaneously. Through innovative techniques (e.g. sensor technology) and iterative development involving end-users, we aim to overcome challenges faced by mHealth interventions, like insufficient personalization. This study examines Perfect Fit’s feasibility and acceptability.A single-arm, mixed-method, real-world evaluation study was conducted with 100 adult smokers in the Netherlands. The intervention lasted approximately 16 weeks. Data were collected at baseline and post-intervention. Quantitative data included usage data and self-report questionnaires on feasibility, acceptability and participant characteristics (e.g. eHealth literacy). Qualitative data included semi-structured post-intervention interviews with a subsample of 12 participants. Descriptive analyses (quantitative) and the Framework Approach (qualitative) were used for data analysis, and quantitative and qualitative data were integrated during interpretation.Participants adapted the use of Perfect Fit to their preferences. Many participants were satisfied with the content but missed variations in conversations with the virtual coach. The coach offered anonymity, positively experienced by some (e.g. non-judgemental), but negatively by others (e.g. lower accountability). Many participants liked the combination of smoking cessation and physical activity enhancement.Findings show the potential of interventions like Perfect Fit as a multiple health behavior change strategy in promoting public health and preventing chronic disease. Findings can inform intervention development and identify methods to foster feasibility and acceptability.• mHealth interventions with virtual coaches, like Perfect Fit, could promote public health.• Targeting multiple behaviors, like low physical activity and smoking, simultaneously seems beneficial

Extracellular Vesicles: Evolving Factors in Stem Cell Biology

Stem cells are proposed to continuously secrete trophic factors that potentially serve as mediators of autocrine and paracrine activities, associated with reprogramming of the tumor microenvironment, tissue regeneration, and repair. Hitherto, significant efforts have been made to understand the level of underlying paracrine activities influenced by stem cell secreted trophic factors, as little is known about these interactions. Recent findings, however, elucidate this role by reporting the effects of stem cell derived extracellular vesicles (EVs) that mimic the phenotypes of the cells from which they originate. Exchange of genetic information utilizing persistent bidirectional communication mediated by stem cell-EVs could regulate stemness, self-renewal, and differentiation in stem cells and their subpopulations. This review therefore discusses stem cell-EVs as evolving communication factors in stem cell biology, focusing on how they regulate cell fates by inducing persistent and prolonged genetic reprogramming of resident cells in a paracrine fashion. In addition, we address the role of stem cell-secreted vesicles in shaping the tumor microenvironment and immunomodulation and in their ability to stimulate endogenous repair processes during tissue damage. Collectively, these functions ensure an enormous potential for future therapies

Extracellular Vesicles: Evolving Factors in Stem Cell Biology

Stem cells are proposed to continuously secrete trophic factors that potentially serve as mediators of autocrine and paracrine activities, associated with reprogramming of the tumor microenvironment, tissue regeneration, and repair. Hitherto, significant efforts have been made to understand the level of underlying paracrine activities influenced by stem cell secreted trophic factors, as little is known about these interactions. Recent findings, however, elucidate this role by reporting the effects of stem cell derived extracellular vesicles (EVs) that mimic the phenotypes of the cells from which they originate. Exchange of genetic information utilizing persistent bidirectional communication mediated by stem cell-EVs could regulate stemness, self-renewal, and differentiation in stem cells and their subpopulations. This review therefore discusses stem cell-EVs as evolving communication factors in stem cell biology, focusing on how they regulate cell fates by inducing persistent and prolonged genetic reprogramming of resident cells in a paracrine fashion. In addition, we address the role of stem cell-secreted vesicles in shaping the tumor microenvironment and immunomodulation and in their ability to stimulate endogenous repair processes during tissue damage. Collectively, these functions ensure an enormous potential for future therapies

Autoimmune Disease Classification by Inverse Association with SNP Alleles

With multiple genome-wide association studies (GWAS) performed across autoimmune diseases, there is a great opportunity to study the homogeneity of genetic architectures across autoimmune disease. Previous approaches have been limited in the scope of their analysis and have failed to properly incorporate the direction of allele-specific disease associations for SNPs. In this work, we refine the notion of a genetic variation profile for a given disease to capture strength of association with multiple SNPs in an allele-specific fashion. We apply this method to compare genetic variation profiles of six autoimmune diseases: multiple sclerosis (MS), ankylosing spondylitis (AS), autoimmune thyroid disease (ATD), rheumatoid arthritis (RA), Crohn's disease (CD), and type 1 diabetes (T1D), as well as five non-autoimmune diseases. We quantify pair-wise relationships between these diseases and find two broad clusters of autoimmune disease where SNPs that make an individual susceptible to one class of autoimmune disease also protect from diseases in the other autoimmune class. We find that RA and AS form one such class, and MS and ATD another. We identify specific SNPs and genes with opposite risk profiles for these two classes. We furthermore explore individual SNPs that play an important role in defining similarities and differences between disease pairs. We present a novel, systematic, cross-platform approach to identify allele-specific relationships between disease pairs based on genetic variation as well as the individual SNPs which drive the relationships. While recognizing similarities between diseases might lead to identifying novel treatment options, detecting differences between diseases previously thought to be similar may point to key novel disease-specific genes and pathways

Effect of SGLT2 inhibitors on stroke and atrial fibrillation in diabetic kidney disease: Results from the CREDENCE trial and meta-analysis

BACKGROUND AND PURPOSE: Chronic kidney disease with reduced estimated glomerular filtration rate or elevated albuminuria increases risk for ischemic and hemorrhagic stroke. This study assessed the effects of sodium glucose cotransporter 2 inhibitors (SGLT2i) on stroke and atrial fibrillation/flutter (AF/AFL) from CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) and a meta-Analysis of large cardiovascular outcome trials (CVOTs) of SGLT2i in type 2 diabetes mellitus. METHODS: CREDENCE randomized 4401 participants with type 2 diabetes mellitus and chronic kidney disease to canagliflozin or placebo. Post hoc, we estimated effects on fatal or nonfatal stroke, stroke subtypes, and intermediate markers of stroke risk including AF/AFL. Stroke and AF/AFL data from 3 other completed large CVOTs and CREDENCE were pooled using random-effects meta-Analysis. RESULTS: In CREDENCE, 142 participants experienced a stroke during follow-up (10.9/1000 patient-years with canagliflozin, 14.2/1000 patient-years with placebo; hazard ratio [HR], 0.77 [95% CI, 0.55-1.08]). Effects by stroke subtypes were: ischemic (HR, 0.88 [95% CI, 0.61-1.28]; n=111), hemorrhagic (HR, 0.50 [95% CI, 0.19-1.32]; n=18), and undetermined (HR, 0.54 [95% CI, 0.20-1.46]; n=17). There was no clear effect on AF/AFL (HR, 0.76 [95% CI, 0.53-1.10]; n=115). The overall effects in the 4 CVOTs combined were: Total stroke (HRpooled, 0.96 [95% CI, 0.82-1.12]), ischemic stroke (HRpooled, 1.01 [95% CI, 0.89-1.14]), hemorrhagic stroke (HRpooled, 0.50 [95% CI, 0.30-0.83]), undetermined stroke (HRpooled, 0.86 [95% CI, 0.49-1.51]), and AF/AFL (HRpooled, 0.81 [95% CI, 0.71-0.93]). There was evidence that SGLT2i effects on total stroke varied by baseline estimated glomerular filtration rate (P=0.01), with protection in the lowest estimated glomerular filtration rate (45 mL/min/1.73 m2]) subgroup (HRpooled, 0.50 [95% CI, 0.31-0.79]). CONCLUSIONS: Although we found no clear effect of SGLT2i on total stroke in CREDENCE or across trials combined, there was some evidence of benefit in preventing hemorrhagic stroke and AF/AFL, as well as total stroke for those with lowest estimated glomerular filtration rate. Future research should focus on confirming these data and exploring potential mechanisms

Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to 300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m 2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Canagliflozin and Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus and Chronic Kidney Disease in Primary and Secondary Cardiovascular Prevention Groups

Background: Canagliflozin reduces the risk of kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease, but effects on specific cardiovascular outcomes are uncertain, as are effects in people without previous cardiovascular disease (primary prevention). Methods: In CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation), 4401 participants with type 2 diabetes mellitus and chronic kidney disease were randomly assigned to canagliflozin or placebo on a background of optimized standard of care. Results: Primary prevention participants (n=2181, 49.6%) were younger (61 versus 65 years), were more often female (37% versus 31%), and had shorter duration of diabetes mellitus (15 years versus 16 years) compared with secondary prevention participants (n=2220, 50.4%). Canagliflozin reduced the risk of major cardiovascular events overall (hazard ratio [HR], 0.80 [95% CI, 0.67-0.95]; P=0.01), with consistent reductions in both the primary (HR, 0.68 [95% CI, 0.49-0.94]) and secondary (HR, 0.85 [95% CI, 0.69-1.06]) prevention groups (P for interaction=0.25). Effects were also similar for the components of the composite including cardiovascular death (HR, 0.78 [95% CI, 0.61-1.00]), nonfatal myocardial infarction (HR, 0.81 [95% CI, 0.59-1.10]), and nonfatal stroke (HR, 0.80 [95% CI, 0.56-1.15]). The risk of the primary composite renal outcome and the composite of cardiovascular death or hospitalization for heart failure were also consistently reduced in both the primary and secondary prevention groups (P for interaction &gt;0.5 for each outcome). Conclusions: Canagliflozin significantly reduced major cardiovascular events and kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease, including in participants who did not have previous cardiovascular disease