Impact of Loneliness and Social Support on Acute Health Service Use and Symptom Exacerbation Among Adults with Asthma and COPD.

Loneliness and low social support are associated with negative health outcomes among adults with asthma or COPD. Although social support is correlated with loneliness, low social support is neither necessary nor sufficient for the experience of loneliness. This study compares the relative association of loneliness and social support on symptom exacerbation (i.e., acute deteriorations in respiratory health) and acute health service utilization (i.e., hospitalizations, emergency department visits) among 206 adults with asthma and 308 adults with COPD. Separate logistic regression models were used to simultaneously examine the association of loneliness and social support with each outcome. Among adults with asthma, loneliness was associated with greater odds of hospitalization (AOR = 2.81, 95%CI [1.13, 7.02]), while low social support was not (AOR = 1.44, 95%CI [0.78, 2.65]). However, neither loneliness nor social support were associated with any other acute health service use or symptom exacerbation among adults with asthma. Among adults with COPD, loneliness, and greater social support were associated with increased odds of symptom exacerbation (AOR = 1.67, 95%CI [1.03, 2.69]; AOR = 1.36, 95%CI 1.02, 1.83]) and hospitalization (AOR = 3.46, 95%CI [1.65, 7.24]; AOR = 1.92, 95%CI [1.15, 3.22]), but only social support was significantly associated with ED visits (AOR = 1.72, 95%CI 1.12, 2.66]). These findings support prior research demonstrating that loneliness and social support are related but separate determinants of patients' physical symptoms and service utilization.

Behavioral Engagement and Activation Model Study (BEAMS): A latent class analysis of adopters and non-adopters of digital health technologies among people with Type 2 diabetes.

Many people with Type 2 diabetes (T2D) who could benefit from digital health technologies (DHTs) are either not using DHTs or do use them, but not for long enough to reach their behavioral or metabolic goals. We aimed to identify subgroups within DHT adopters and non-adopters and describe their unique profiles to better understand the type of tailored support needed to promote effective and sustained DHT use across a diverse T2D population. We conducted latent class analysis of a sample of adults with T2D who responded to an internet survey between December 2021 and March 2022. We describe the clinical and psychological characteristics of DHT adopters and non-adopters, and their attitudes toward DHTs. A total of 633 individuals were characterized as either DHT "Adopters" (n = 376 reporting any use of DHT) or "Non-Adopters" (n = 257 reporting never using any DHT). Within Adopters, three subgroups were identified: 21% (79/376) were "Self-managing Adopters," who reported high health activation and self-efficacy for diabetes management, 42% (158/376) were "Activated Adopters with dropout risk," and 37% (139/376) were "Non-Activated Adopters with dropout risk." The latter two subgroups reported barriers to using DHTs and lower rates of intended future use. Within Non-Adopters, two subgroups were identified: 31% (79/257) were "Activated Non-Adopters," and 69% (178/257) were "Non-Adopters with barriers," and were similarly distinguished by health activation and barriers to using DHTs. Beyond demographic characteristics, psychological, and clinical factors may help identify different subgroups of Adopters and Non-Adopters.

In this study, we characterized subgroups of adopters and non-adopters of digital health technologies (DHTs) for managing Type 2 diabetes, such as apps to track nutrition, continuous glucose monitors, and activity monitors like Fitbit. Self-efficacy for diabetes management, health activation, and perceived barriers to use DHT emerged as characteristics that distinguished subgroups. Notably, subgroups of adopters differed in their interest to use these technologies in the next 3 months; groups with low levels of self-efficacy and health activation were least interested in using them and thus at risk of discontinuing use. The ability to identify these subgroups can inform strategies tailored to each subgroup that motivate adoption of DHTs and promote long-term engagement.

A Randomized Controlled Trial to Improve Unmet Social Needs and Clinical Outcomes Among Adults with Diabetes.

BACKGROUND: Adults with type 1 or type 2 diabetes often face financial challenges and other unmet social needs to effective diabetes self-management. OBJECTIVE: Whether a digital intervention focused on addressing socioeconomic determinants of health improves diabetes clinical outcomes more than usual care. DESIGN: Randomized trial from 2019 to 2023. PARTICIPANTS: A total of 600 adults with diabetes, HbA1c ≥ 7.5%, and self-reported unmet social needs or financial burden from a health system and randomized to the intervention or standard care. INTERVENTION: CareAvenue is an automated, e-health intervention with eight videos that address unmet social needs contributing to poor outcomes. MEASURES: Primary outcome was HbA1c, measured at baseline, and 6 and 12 months after randomization. Secondary outcomes included systolic blood pressure and reported met social needs, cost-related non-adherence (CRN), and financial burden. We examined main effects and variation in effects across predefined subgroups. RESULTS: Seventy-eight percent of CareAvenue participants completed one or more modules of the website. At 12-month follow-up, there were no significant differences in HbA1c changes between CareAvenue and control group (p = 0.24). There were also no significant between-group differences in systolic blood pressure (p = 0.29), met social needs (p = 0.25), CRN (p = 0.18), and perceived financial burden (p = 0.31). In subgroup analyses, participants with household incomes 100-400% FPL (1.93 (SE = 0.76), p < 0.01), 201-400% FPL (1.30 (SE = 0.62), p < 0.04), and > 400% FPL (1.27 (SE = 0.64), p < 0.05) had significantly less A1c decreases compared to the control group. CONCLUSIONS: On average, CareAvenue participants did not achieve better A1c lowering, met needs, CRN, or perceived financial burden compared to control participants. CareAvenue participants with higher incomes achieved significantly less A1c reductions than control. Further research is needed on social needs interventions that consider tailored approaches to population subgroups. CLINICAL TRIALS REGISTRY: ClinicalTrials.gov ID NCT03950973, May 2019.

Mapping the Cardiometabolic Patient Experience and Self-Care Behaviors to Inform Design, Implementation, and Persistent Use of Digital Health Care Solutions: Mixed Methods Study.

BACKGROUND: Cardiometabolic conditions including acute coronary syndrome (ACS) and type 2 diabetes (T2D) require comprehensive care and patient engagement in self-care behaviors, and the drivers of those behaviors at the individual and health system level are still poorly understood. OBJECTIVE: We aim to gain insights into self-care behaviors of individuals with cardiometabolic conditions. METHODS: A convenience sample of 98 adult patients with ACS and T2D was recruited in the United States, Germany, and Taiwan to participate in a mixed methods study using ethnographic methods. All participants completed 7-day web-based diaries tracking their level of engagement, and 48 completed 90-minute web-based semistructured interviews between February 4, 2021, and March 27, 2021, focusing on themes including moments of engagement. Qualitative analysis identified factors influencing self-care practices and a Patient Mind States Model prototype. RESULTS: Patient reports indicate that many patients feel social pressure to adhere to treatment. Patients' experience can be understood within 5 categories defined in terms of their degree of engagement and adherence ("ignoring," "struggling," "juggling," "controlling," and "reframing"). CONCLUSIONS: For people living with ACS and T2D, the self-care journey is defined by patterns of patient experiences, which can identify areas that tailored digital health care interventions may play a meaningful role.

Profiles of Web-based Portal Users with Inflammatory Bowel Disease.

BACKGROUND: Web-based portals can enhance communication between patients and providers to support IBD self-management and improve care. We aimed to identify portal use patterns of patients with inflammatory bowel disease (IBD) to inform future web portal-based interventions and portal design. METHODS: Patients with IBD receiving care at the University of Michigan between 2012 and 2021 were identified. Meta-data from electronic logs of each patient's most recent year of portal use were abstracted. Portal engagement was characterized in terms of intensity (ie, frequency of use); comprehensiveness (ie, number of portal functions used); and duration (ie, quarters per year of portal use). We used k-means clustering, a machine-learning technique, to identify groupings of portal users defined in terms of engagement features. RESULTS: We found 5605 patients with IBD who had accessed their portal account at least once. The average age was 41.2 years (SD 16.7), 3035 (54.2%) were female, and 2214 (39.5%) received immune-targeted therapies. We identified 3 patterns of portal engagement: (1) low intensity users (29.5%); (2) moderate intensity, comprehensive, and sustained users (63.3%); and (3) high intensity, comprehensive, sustained users (7.2%). Patients with more intense, comprehensive, and sustained use of the portal were older, female, with more comorbidities, and were more likely to receive immune-targeted therapies. CONCLUSION: Understanding distinct patterns of portal use can inform portal-based interventions and portal design. Patient portals may be particularly helpful in delivering assistance to those with comorbidities and those receiving immune-targeted therapies-many of whom demonstrate more intense, comprehensive, and sustained portal use.

Inflammatory bowel disease patients have varying patterns of web-based portal engagement that can be characterized into distinct groupings. Portals-based interventions may be particularly helpful for those with comorbidities or receiving immune-targeted therapies­many of whom demonstrate more intense, comprehensive, and sustained use.

An mHealth Text Messaging Program Providing Symptom Detection Training and Psychoeducation to Improve Hypoglycemia Self-Management: Intervention Development Study.

BACKGROUND: Hypoglycemia remains a challenge for roughly 25% of people with type 1 diabetes (T1D) despite using advanced technologies such as continuous glucose monitors (CGMs) or automated insulin delivery systems. Factors impacting hypoglycemia self-management behaviors (including reduced ability to detect hypoglycemia symptoms and unhelpful hypoglycemia beliefs) can lead to hypoglycemia development in people with T1D who use advanced diabetes technology. OBJECTIVE: This study aims to develop a scalable, personalized mobile health (mHealth) behavioral intervention program to improve hypoglycemia self-management and ultimately reduce hypoglycemia in people with T1D who use advanced diabetes technology. METHODS: We (a multidisciplinary team, including clinical and health psychologists, diabetes care and education specialists, endocrinologists, mHealth interventionists and computer engineers, qualitative researchers, and patient partners) jointly developed an mHealth text messaging hypoglycemia behavioral intervention program based on user-centered design principles. The following five iterative steps were taken: (1) conceptualization of hypoglycemia self-management processes and relevant interventions; (2) identification of text message themes and message content development; (3) message revision; (4) patient partner assessments for message readability, language acceptability, and trustworthiness; and (5) message finalization and integration with a CGM data-connected mHealth SMS text message delivery platform. An mHealth web-based SMS text message delivery platform that communicates with a CGM glucose information-sharing platform was also developed. RESULTS: The mHealth SMS text messaging hypoglycemia behavioral intervention program HypoPals, directed by patients' own CGM data, delivers personalized intervention messages to (1) improve hypoglycemia symptom detection and (2) elicit self-reflection, provide fact-based education, and suggest practical health behaviors to address unhelpful hypoglycemia beliefs and promote hypoglycemia self-management. The program is designed to message patients up to 4 times per day over a 10-week period. CONCLUSIONS: A rigorous conceptual framework, a multidisciplinary team (including patient partners), and behavior change techniques were incorporated to create a scalable, personalized mHealth SMS text messaging behavioral intervention. This program was systematically developed to improve hypoglycemia self-management in advanced diabetes technology users with T1D. A clinical trial is needed to evaluate the program's efficacy for future clinical implementation.

Improving depression management with support from close others: A thematic analysis of individuals with depression and their partners in care.

OBJECTIVES: With support from others, individuals with depression can build skills and implement lifestyle changes that help them manage their illness. The objective of the current study was to understand how the CarePartners for Depression Program, a randomized clinical trial aimed at enhancing the role of caregivers in the management of depression, improved communication and shared understandings of depression among individuals with depression and their close others. METHODS: We conducted in-depth, semi-structured interviews with individuals with depression and their caregivers who participated in the CarePartners program. Interviews were qualitatively coded using a thematic analytic framework. RESULTS: We conducted individual interviews with 39 participants in the CarePartners program, including 18 individuals with depression, 14 out-of-home care partners, and 7 informal caregivers. Three central themes were derived from analyses: (a) The quality of interpersonal relationships influenced the management of depression; (2) having clearly defined roles for CarePartners improved communication between CarePartners and individuals with depression; and (3) shared understanding of depression improved management of depression. DISCUSSION: Our findings established the conditions under which the management of depression was influenced in a dyadic intervention. Dyadic interventions may make it easier for individuals to support patients with depression by fostering communication and collaboration.

A Pilot Randomized Trial of a Purposeful and Stimulating Volunteer Opportunity: Program Satisfaction and Potential Impacts on Perceived Cognitive Change in a Neurologically Mixed Sample of Older Adults.

BACKGROUND: Purposeful social interactions are important for healthy aging. We conducted a pilot trial of SPEAK! (Seniors Promoting English Acquisition and Knowledge), an intervention providing older volunteers with a safe, accessible opportunity to converse via webcam with English-language learners. METHODS: A neurologically mixed sample of older adults was randomized to 8 weekly, webcam conversations with English-language learners or a waitlist control. Outcomes included the Cognitive Change Index (CCI) and surveys of program satisfaction. Here, we report on session completion, intervention satisfaction, and follow-up CCI scores. Exploratory analyses of CCI intervention effects controlled for baseline CCI scores and the interaction between group and baseline CCI. RESULTS: Participants (N=38) were on average 70.8 years of age, 28/38 were White, and 16/38 demonstrated possible cognitive impairment on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Pairs completed 115/136 sessions (85%) and all volunteers said they would recommend the program. Controlling for the interaction between baseline CCI and randomization group, SPEAK! volunteers had better follow-up CCI scores than controls (P=0.018). Improvements in CCI were greater among participants with fewer baseline memory problems. CONCLUSIONS: SPEAK! was feasible and appreciated by older adults with and without cognitive impairment. Larger studies should confirm benefits for memory and other determinants of quality of life.

An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures.

BACKGROUND: Some patients prescribed opioid analgesic (OA) medications for pain experience serious side effects, including dependence, sedation, and overdose. As most patients are at low risk for OA-related harms, risk reduction interventions requiring multiple counseling sessions are impractical on a large scale. OBJECTIVE: This study evaluates whether an intervention based on reinforcement learning (RL), a field of artificial intelligence, learned through experience to personalize interactions with patients with pain discharged from the emergency department (ED) and decreased self-reported OA misuse behaviors while conserving counselors' time. METHODS: We used data representing 2439 weekly interactions between a digital health intervention ("Prescription Opioid Wellness and Engagement Research in the ED" [PowerED]) and 228 patients with pain discharged from 2 EDs who reported recent opioid misuse. During each patient's 12 weeks of intervention, PowerED used RL to select from 3 treatment options: a brief motivational message delivered via an interactive voice response (IVR) call, a longer motivational IVR call, or a live call from a counselor. The algorithm selected session types for each patient each week, with the goal of minimizing OA risk, defined in terms of a dynamic score reflecting patient reports during IVR monitoring calls. When a live counseling call was predicted to have a similar impact on future risk as an IVR message, the algorithm favored IVR to conserve counselor time. We used logit models to estimate changes in the relative frequency of each session type as PowerED gained experience. Poisson regression was used to examine the changes in self-reported OA risk scores over calendar time, controlling for the ordinal session number (1st to 12th). RESULTS: Participants on average were 40 (SD 12.7) years of age; 66.7% (152/228) were women and 51.3% (117/228) were unemployed. Most participants (175/228, 76.8%) reported chronic pain, and 46.2% (104/225) had moderate to severe depressive symptoms. As PowerED gained experience through interactions over a period of 142 weeks, it delivered fewer live counseling sessions than brief IVR sessions (P=.006) and extended IVR sessions (P<.001). Live counseling sessions were selected 33.5% of the time in the first 5 weeks of interactions (95% CI 27.4%-39.7%) but only for 16.4% of sessions (95% CI 12.7%-20%) after 125 weeks. Controlling for each patient's changes during the course of treatment, this adaptation of treatment-type allocation led to progressively greater improvements in self-reported OA risk scores (P<.001) over calendar time, as measured by the number of weeks since enrollment began. Improvement in risk behaviors over time was especially pronounced among patients with the highest risk at baseline (P=.02). CONCLUSIONS: The RL-supported program learned which treatment modalities worked best to improve self-reported OA risk behaviors while conserving counselors' time. RL-supported interventions represent a scalable solution for patients with pain receiving OA prescriptions. TRIAL REGISTRATION: Clinicaltrials.gov NCT02990377; https://classic.clinicaltrials.gov/ct2/show/NCT02990377.

Adapting a Telephone-Based, Dyadic Self-management Program to Be Delivered Over the Web: Methodology and Usability Testing.

BACKGROUND: The COVID-19 pandemic has amplified the need for web-based behavioral interventions to support individuals who are diagnosed with chronic conditions and their informal caregivers. However, most interventions focus on patient outcomes. Dyadic technology-enabled interventions that simultaneously improve outcomes for patients and caregivers are needed. OBJECTIVE: This study aimed to describe the methodology used to adapt a telephone-based, facilitated, and dyadic self-management program called Self-care Using Collaborative Coping Enhancement in Diseases (SUCCEED) into a self-guided, web-based version (web-SUCCEED) and to conduct usability testing for web-SUCCEED. METHODS: We developed web-SUCCEED in 6 steps: ideation-determine the intervention content areas; prototyping-develop the wireframes, illustrating the look and feel of the website; prototype refinement via feedback from focus groups; finalizing the module content; programming web-SUCCEED; and usability testing. A diverse team of stakeholders including content experts, web designers, patients, and caregivers provided input at various stages of development. Costs, including full-time equivalent employee, were summarized. RESULTS: At the ideation stage, we determined the content of web-SUCCEED based on feedback from the program's original pilot study. At the prototyping stage, the principal investigator and web designers iteratively developed prototypes that included inclusive design elements (eg, large font size). Feedback about these prototypes was elicited through 2 focus groups of veterans with chronic conditions (n=13). Rapid thematic analysis identified two themes: (1) web-based interventions can be useful for many but should include ways to connect with other users and (2) prototypes were sufficient to elicit feedback about the esthetics, but a live website allowing for continual feedback and updating would be better. Focus group feedback was incorporated into building a functional website. In parallel, the content experts worked in small groups to adapt SUCCEED's content, so that it could be delivered in a didactic, self-guided format. Usability testing was completed by veterans (8/16, 50%) and caregivers (8/16, 50%). Veterans and caregivers gave web-SUCCEED high usability scores, noting that it was easy to understand, easy to use, and not overly burdensome. Notable negative feedback included "slightly agreeing" that the site was confusing and awkward. All veterans (8/8, 100%) agreed that they would choose this type of program in the future to access an intervention that aims to improve their health. Developing and maintaining the software and hosting together cost approximately US $100,000, excluding salary and fringe benefits for project personnel (steps 1-3: US $25,000; steps 4-6: US $75,000). CONCLUSIONS: Adapting an existing, facilitated self-management support program for delivery via the web is feasible, and such programs can remotely deliver content. Input from a multidisciplinary team of experts and stakeholders can ensure the program's success. Those interested in adapting programs should have a realistic estimate of the budget and staffing requirements.

Self-Efficacy and the Impact of Inflammatory Bowel Disease on Patients' Daily Lives.

INTRODUCTION: Self-efficacy, i.e., the confidence in one's capacity to perform a behavior, is crucial to the development of inflammatory bowel disease (IBD) self-management skills. We aimed to measure IBD self-efficacy and the relationship between self-efficacy and the patient-reported impact of IBD on daily life. METHODS: We surveyed patients with IBD from a single academic center using the IBD Self-Efficacy Scale (IBD-SES) and patient-reported outcome (PRO) measures. The IBD-SES assesses 4 IBD domains: patients' confidence in managing stress and emotions, symptoms and disease, medical care, and remission. IBD PROs evaluate daily life impact, coping strategies, emotional impact, and systemic symptoms. We examined the association between IBD-SES domains with the lowest scores and IBD daily life impact. RESULTS: A total of 160 patients completed the survey. Domain scores on the IBD-SES were lowest for managing stress and emotions (mean 6.76, SD 1.86) and symptoms and disease (mean 6.71, SD 2.12) on a 1-10 scale. Controlling for age, sex, IBD type, disease activity, moderate-to-severe disease, depression and anxiety, a higher confidence in managing stress and emotions (ß -0.12, 95% confidence interval -0.20 to -0.05, P = 0.001), and managing symptoms and disease (ß -0.28, 95% confidence interval -0.35 to -0.20, P < 0.001) were each associated with lower IBD daily life impact. DISCUSSION: Patients with IBD report low confidence in managing stress and emotion and managing symptoms and disease. Higher self-efficacy in these domains was associated with lower IBD daily life impact. Self-management tools that promote self-efficacy in managing these domains have the potential to reduce IBD's daily life impact.

Using Daily Ratings to Examine Treatment Dose and Response in Cognitive Behavioral Therapy for Chronic Pain: A Secondary Analysis of the Co-Operative Pain Education and Self-Management Clinical Trial.

BACKGROUND: Cognitive behavioral therapy for chronic pain (CBT-CP) has a strong evidence base, but little is known about when treatment benefits are achieved. The present study is a secondary analysis of individuals with chronic back pain recruited for a noninferiority trial comparing interactive voice response (IVR) CBT-CP with in-person CBT-CP. METHODS: On the basis of data from daily IVR surveys, a clinically meaningful change was defined as a 30% reduction in pain intensity (n = 108) or a 45% increase in daily steps (n = 104) compared with the baseline week. We identified individuals who achieved a meaningful change at any point during treatment, and then we compared those who maintained a meaningful change in their final treatment week (i.e., responders) with those who did not or who achieved a meaningful change but lapsed (i.e., nonresponders). RESULTS: During treatment, 46% of participants achieved a clinically meaningful decrease in pain intensity, and 66% achieved a clinically significant increase in number of steps per day. A total of 54% of patients were classified as responders in terms of decreases in pain intensity, and 70% were responders in terms of increases in step count. Survival analyses found that 50% of responders first achieved a clinically meaningful change by week 4 for pain intensity and week 2 for daily steps. Dropout and demographic variables were unrelated to responder status, and there was low agreement between the two measures of treatment response. CONCLUSIONS: Collectively, results suggest that most responders improve within 4 weeks. Evaluating treatment response is highly specific to the outcome measure, with little correlation across outcomes.

Providing a Purposeful and Stimulating Volunteer Opportunity for Older Adults With Mild Cognitive Impairment: A Pilot Study.

Social interactions have cognitive and emotional benefits for older adults with mild cognitive impairment (MCI). The prevalence of loneliness and isolation in this population has been repeatedly noted, but interventions remain limited. We designed a program to connect older adults with MCI with an engaging volunteering opportunity, through videoconferencing conversations with another adult practicing English (English language learner). Ten MCI-English language learner pairs had conversation sessions over 6 weeks. We tracked session engagement, monitored conversations, and interviewed participants at follow-up. Pairs completed 78% of scheduled sessions; only 7% were missed because the MCI participant canceled or failed to appear. Qualitative interviews suggested that participants felt comfortable and engaged. No negative experiences were observed or reported. This program is feasible and potentially desirable for older adults with MCI. This model is interesting given the concern about in-person volunteering risks, and the millions of people motivated to improve English fluency.

Assessment of Outcome-Based Measures of Depression Care Quality in Veterans Health Administration Facilities.

To inform the potential use of patient-reported depression symptom outcomes as measures of care quality, this study collected and analyzed longitudinal Patient Health Questionnaire (PHQ9) scores among 1,638 patients who screened positive for major depression according to a PHQ9 ≥ 10 across 29 Department of Veterans Affairs facilities. The study found baseline PHQ9, prior mental health visits, physical functioning, and treatment expectancy were consistently associated with subsequent PHQ9 outcomes. No facilities outperformed any others on PHQ9 scores at the 6-month primary endpoint, and the corresponding intra-class coefficient was ≤ .01 for the entire sample (n = 1,214) and 0.03 for the subgroup of patients with new depression episodes (n = 629). Measures of antidepressant receipt, psychotherapy, or treatment intensification were not associated with 6-month PHQ9 scores. PHQ9 outcomes are therefore unlikely to be useful as quality indicators for VA healthcare facilities due to low inter-facility variation, and new care process measures are needed to inform care for patients with chronic depression prevalent in this sample.

Effectiveness of a Health Coaching Intervention for Patient-Family Dyads to Improve Outcomes Among Adults With Diabetes: A Randomized Clinical Trial.

Importance: More than 75% of US adults with diabetes do not meet treatment goals. More effective support from family and friends ("supporters") may improve diabetes management and outcomes. Objective: To determine if the Caring Others Increasing Engagement in Patient Aligned Care Teams (CO-IMPACT) intervention improves patient activation, diabetes management, and outcomes compared with standard care. Design, Setting, and Participants: This randomized clinical trial was conducted from November 2016 to August 2019 among participants recruited from 2 Veterans Health Administration primary care sites. All patient participants were adults aged 30 to 70 years with diabetes who had hemoglobin A1c (HbA1c) levels greater than 8% of total hemoglobin (to convert to proportion of total hemoglobin, multiply by 0.01) or systolic blood pressure (SBP) higher than 150 mm Hg; each participating patient had an adult supporter. Of 1119 recruited, 239 patient-supporter dyads were enrolled between November 2016 and May 2018, randomized 1:1 to receive the CO-IMPACT intervention or standard care, and followed up for 12 to 15 months. Investigators and analysts were blinded to group assignment. Interventions: Patient-supporter dyads received a health coaching session focused on dyadic information sharing and positive support techniques, then 12 months of biweekly automated monitoring telephone calls to prompt dyadic actions to meet diabetes goals, coaching calls to help dyads prepare for primary care visits, and after-visit summaries. Standard-care dyads received general diabetes education materials only. Main Outcomes and Measures: Intent-to-treat analyses were conducted according to baseline dyad assignment. Primary prespecified outcomes were 12-month changes in Patient Activation Measure-13 (PAM-13) and UK Prospective Diabetes Study (UKPDS) 5-year diabetes-specific cardiac event risk scores. Secondary outcomes included 12-month changes in HbA1c levels, SBP, diabetes self-management behaviors, diabetes distress, diabetes management self-efficacy, and satisfaction with health system support for the involvement of family supporters. Changes in outcome measures between baseline and 12 months were analyzed using linear regression models. Results: A total of 239 dyads enrolled; among patient participants, the mean (SD) age was 60 (8.9) years, and 231 (96.7%) were male. The mean (SD) baseline HbA1c level was 8.5% (1.6%) and SBP was 140.2 mm Hg (18.4 mm Hg). A total of 168 patients (70.3%) lived with their enrolled supporter; 229 patients (95.8%) had complete 12-month outcome data. In intention-to-treat analyses vs standard care, CO-IMPACT patients had greater 12-month improvements in PAM-13 scores (intervention effect, 2.60 points; 95% CI, 0.02-5.18 points; P = .048) but nonsignificant differences in UKPDS 5-year cardiac risk (intervention effect, 1.01 points; 95% CI, -0.74 to 2.77 points; P = .26). Patients in the CO-IMPACT arm also had greater 12-month improvements in healthy eating (intervention effect, 0.71 d/wk; 95% CI, 0.20-1.22 d/wk; P = .007), diabetes self-efficacy (intervention effect, 0.40 points; 95% CI, 0.09-0.71 points; P = .01), and satisfaction with health system support for the family supporter participants' involvement (intervention effect, 0.28 points; 95% CI, 0.07-0.49 points; P = .009); however, the 2 arms had similar improvements in HbA1c levels and in other measures. Conclusions and Relevance: In this randomized clinical trial, the CO-IMPACT intervention successfully engaged patient-supporter dyads and led to improved patient activation and self-efficacy. Physiological outcomes improved similarly in both arms. More intensive direct coaching of supporters, or targeting patients with less preexisting support or fewer diabetes management resources, may have greater impact. Trial Registration: ClinicalTrials.gov Identifier: NCT02328326.

Influence of Digital Intervention Messaging on Influenza Vaccination Rates Among Adults With Cardiovascular Disease in the United States: Decentralized Randomized Controlled Trial.

BACKGROUND: Seasonal influenza affects 5% to 15% of Americans annually, resulting in preventable deaths and substantial economic impact. Influenza infection is particularly dangerous for people with cardiovascular disease, who therefore represent a priority group for vaccination campaigns. OBJECTIVE: We aimed to assess the effects of digital intervention messaging on self-reported rates of seasonal influenza vaccination. METHODS: This was a randomized, controlled, single-blind, and decentralized trial conducted at individual locations throughout the United States over the 2020-2021 influenza season. Adults with self-reported cardiovascular disease who were members of the Achievement mobile platform were randomized to receive or not receive a series of 6 patient-centered digital intervention messages promoting influenza vaccination. The primary end point was the between-group difference in self-reported vaccination rates at 6 months after randomization. Secondary outcomes included the levels of engagement with the messages and the relationship between vaccination rates and engagement with the messages. Subgroup analyses examined variation in intervention effects by race. Controlling for randomization group, we examined the impact of other predictors of vaccination status, including cardiovascular condition type, vaccine drivers or barriers, and vaccine knowledge. RESULTS: Of the 49,138 randomized participants, responses on the primary end point were available for 11,237 (22.87%; 5575 in the intervention group and 5662 in the control group) participants. The vaccination rate was significantly higher in the intervention group (3418/5575, 61.31%) than the control group (3355/5662, 59.25%; relative risk 1.03, 95% CI 1.004-1.066; P=.03). Participants who were older, more educated, and White or Asian were more likely to report being vaccinated. The intervention was effective among White participants (P=.004) but not among people of color (P=.42). The vaccination rate was 13 percentage points higher among participants who completed all 6 intervention messages versus none, and at least 2 completed messages appeared to be needed for effectiveness. Participants who reported a diagnosis of COVID-19 were more likely to be vaccinated for influenza regardless of treatment assignment. CONCLUSIONS: This personalized, evidence-based digital intervention was effective in increasing vaccination rates in this population of high-risk people with cardiovascular disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT04584645; https://clinicaltrials.gov/ct2/show/NCT04584645.

Measurement and Validation of the Comprehensive Score for Financial Toxicity (COST) in a Population With Diabetes.

OBJECTIVE: The Comprehensive Score for Financial Toxicity-Functional Assessment of Chronic Illness Therapy (COST-FACIT) is a validated instrument measuring financial distress among people with cancer. The reliability and construct validity of the 11-item COST-FACIT were examined in adults with diabetes and high A1C. RESEARCH DESIGN AND METHODS: We examined the factor structure (exploratory factor analysis), internal consistency reliability (Cronbach α), floor/ceiling effects, known-groups validity, and predictive validity among a sample of 600 adults with diabetes and high A1C. RESULTS: COST-FACIT demonstrated a two-factor structure with high internal consistency: general financial situation (7-items, α = 0.86) and impact of illness on financial situation (4-items, α = 0.73). The measure demonstrated a ceiling effect for 2% of participants and floor effects for 7%. Worse financial toxicity scores were observed among adults who were women, were below the poverty line, had government-sponsored health insurance, were middle-aged, were not in the workforce, and had less educational attainment (P < 0.01). Worse financial toxicity was observed for those engaging in cost coping behaviors, such as taking less or skipping medicines, delaying care, borrowing money, "maxing out" the limit on credit cards, and not paying bills (P < 0.01). In regression models for the full measure and its two factors, worse financial toxicity was correlated with higher A1C (P < 0.01), higher levels of diabetes distress (P < 0.01), more chronic conditions (P < 0.01), and more depressive symptoms (P < 0.01). CONCLUSIONS: Findings support both the reliability and validity of the COST-FACIT tool among adults with diabetes and high A1C levels. More research is needed to support the use of the COST-FACIT tool as a clinically relevant patient-centered instrument for diabetes care.

Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: A Randomized Comparative Effectiveness Trial.

Importance: Cognitive behavioral therapy for chronic pain (CBT-CP) is a safe and effective alternative to opioid analgesics. Because CBT-CP requires multiple sessions and therapists are scarce, many patients have limited access or fail to complete treatment. Objectives: To determine if a CBT-CP program that personalizes patient treatment using reinforcement learning, a field of artificial intelligence (AI), and interactive voice response (IVR) calls is noninferior to standard telephone CBT-CP and saves therapist time. Design, Setting, and Participants: This was a randomized noninferiority, comparative effectiveness trial including 278 patients with chronic back pain from the Department of Veterans Affairs health system (recruitment and data collection from July 11, 2017-April 9, 2020). More patients were randomized to the AI-CBT-CP group than to the control (1.4:1) to maximize the system's ability to learn from patient interactions. Interventions: All patients received 10 weeks of CBT-CP. For the AI-CBT-CP group, patient feedback via daily IVR calls was used by the AI engine to make weekly recommendations for either a 45-minute or 15-minute therapist-delivered telephone session or an individualized IVR-delivered therapist message. Patients in the comparison group were offered 10 therapist-delivered telephone CBT-CP sessions (45 minutes/session). Main Outcomes and Measures: The primary outcome was the Roland Morris Disability Questionnaire (RMDQ; range 0-24), measured at 3 months (primary end point) and 6 months. Secondary outcomes included pain intensity and pain interference. Consensus guidelines were used to identify clinically meaningful improvements for responder analyses (eg, a 30% improvement in RMDQ scores and pain intensity). Data analyses were performed from April 2021 to May 2022. Results: The study population included 278 patients (mean [SD] age, 63.9 [12.2] years; 248 [89.2%] men; 225 [81.8%] White individuals). The 3-month mean RMDQ score difference between AI-CBT-CP and standard CBT-CP was -0.72 points (95% CI, -2.06 to 0.62) and the 6-month difference was -1.24 (95% CI, -2.48 to 0); noninferiority criterion were met at both the 3- and 6-month end points (P < .001 for both). A greater proportion of patients receiving AI-CBT-CP had clinically meaningful improvements at 6 months as indicated by RMDQ (37% vs 19%; P = .01) and pain intensity scores (29% vs 17%; P = .03). There were no significant differences in secondary outcomes. Pain therapy using AI-CBT-CP required less than half of the therapist time as standard CBT-CP. Conclusions and Relevance: The findings of this randomized comparative effectiveness trial indicated that AI-CBT-CP was noninferior to therapist-delivered telephone CBT-CP and required substantially less therapist time. Interventions like AI-CBT-CP could allow many more patients to be served effectively by CBT-CP programs using the same number of therapists. Trial Registration: ClinicalTrials.gov Identifier: NCT02464449.

Development of the SPUR tool: a profiling instrument for patient treatment behavior.

BACKGROUND: Long-term treatment adherence is a worldwide concern, with nonadherence resulting from a complex interplay of behaviors and health beliefs. Determining an individual's risk of nonadherence and identifying the drivers of that risk are crucial for the development of successful interventions for improving adherence. Here, we describe the development of a new tool assessing a comprehensive set of characteristics predictive of patients' treatment adherence based on the Social, Psychological, Usage and Rational (SPUR) adherence framework. Concepts from existing self-reporting tools of adherence-related behaviors were identified following a targeted MEDLINE literature review and a subset of these concepts were then selected for inclusion in the new tool. SPUR tool items, simultaneously generated in US English and in French, were tested iteratively through two rounds of cognitive interviews with US and French patients taking long-term treatments for chronic diseases. The pilot SPUR tool, resulting from the qualitative analysis of patients' responses, was then adapted to other cultural settings (China and the UK) and subjected to further rounds of cognitive testing. RESULTS: The literature review identified 27 relevant instruments, from which 49 concepts were included in the SPUR tool (Social: 6, Psychological: 13, Usage: 11, Rational: 19). Feedback from US and French patients suffering from diabetes, multiple sclerosis, or breast cancer (n = 14 for the first round; n = 16 for the second round) indicated that the SPUR tool was well accepted and consistently understood. Minor modifications were implemented, resulting in the retention of 45 items (Social: 5, Psychological: 14, Usage: 10, Rational: 16). Results from the cognitive interviews conducted in China (15 patients per round suffering from diabetes, breast cancer or chronic obstructive pulmonary disease) and the UK (15 patients suffering from diabetes) confirmed the validity of the tool content, with no notable differences being identified across countries or chronic conditions. CONCLUSION: Our qualitative analyses indicated that the pilot SPUR tool is a promising model that may help clinicians and health systems to predict patient treatment behavior. Further steps using quantitative methods are needed to confirm its predictive validity and other psychometric properties.