Effect of Electronic Reminders, Financial Incentives, and Social Support on Outcomes After Myocardial Infarction: The HeartStrong Randomized Clinical Trial

Effectiveness of eHealth Interventions in Improving Medication Adherence Among Patients With Cardiovascular Disease: Systematic Review and Meta-Analysis

BACKGROUND

Nonadherence to medication among patients with cardiovascular diseases undermines the desired therapeutic outcomes. eHealth interventions emerge as promising strategies to effectively tackle this issue.

OBJECTIVE

The aim of this study was to conduct a network meta-analysis (NMA) to compare and rank the efficacy of various eHealth interventions in improving medication adherence among patients with cardiovascular diseases (CVDs).

METHODS

A systematic search strategy was conducted in PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure Library (CNKI), China Science and Technology Journal Database (Weipu), and WanFang databases to search for randomized controlled trials (RCTs) published from their inception on January 15, 2024. We carried out a frequentist NMA to compare the efficacy of various eHealth interventions. The quality of the literature was assessed using the risk of bias tool from the Cochrane Handbook (version 2.0), and extracted data were analyzed using Stata16.0 (StataCorp LLC) and RevMan5.4 software (Cochrane Collaboration). The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach.

RESULTS

A total of 21 RCTs involving 3904 patients were enrolled. The NMA revealed that combined interventions (standardized mean difference [SMD] 0.89, 95% CI 0.22-1.57), telephone support (SMD 0.68, 95% CI 0.02-1.33), telemonitoring interventions (SMD 0.70, 95% CI 0.02-1.39), and mobile phone app interventions (SMD 0.65, 95% CI 0.01-1.30) were statistically superior to usual care. However, SMS compared to usual care showed no statistical difference. Notably, the combined intervention, with a surface under the cumulative ranking curve of 79.3%, appeared to be the most effective option for patients with CVDs. Regarding systolic blood pressure and diastolic blood pressure outcomes, the combined intervention also had the highest probability of being the best intervention.

CONCLUSIONS

The research indicates that the combined intervention (SMS text messaging and telephone support) has the greatest likelihood of being the most effective eHealth intervention to improve medication adherence in patients with CVDs, followed by telemonitoring, telephone support, and app interventions. The results of these network meta-analyses can provide crucial evidence-based support for health care providers to enhance patients' medication adherence. Given the differences in the design and implementation of eHealth interventions, further large-scale, well-designed multicenter trials are needed.

TRIAL REGISTRATION

INPLASY 2023120063; https://inplasy.com/inplasy-2023-12-0063/.

Leveraging Habits to Improve Adherence to Gout Medications: A Qualitative Study

OBJECTIVE

This study investigates patients' medication-taking routines and the feasibility of harnessing habit formation through context cues and rewards to improve medication adherence.

METHODS

Semistructured qualitative interviews with patients with gout from an urban health care system were conducted to explore typical medication-taking behavior, experiences using electronic pill bottles, barriers to adherence, existing context cues, and potential cues and rewards for habit-forming behavior. Medication-taking patterns were recorded for six weeks using electronic pill bottles before interviews to inform discussion. Transcribed interviews were analyzed to generate themes using codes developed by the study team, with representative quotations selected as illustrations.

RESULTS

We conducted interviews with 15 individuals (mean age 60.6 [SD 20.3] years, three women [20%], and nine White patients [60%]). Pill bottle-recorded adherence to urate-lowering therapy (ULT) was high (mean 0.91 [SD 0.10]), and one patient was experiencing an active gout flare. Five key themes emerged: (1) reasons for nonadherence, (2) internal and external motivations for adherence, (3) structured routines around taking medications, (4) rewards for good medication adherence, and (5) the role of pill cap technology in medication-taking.

CONCLUSION

The importance of a predictable, structured routine in which participants could incorporate their medication-taking behavior emerged as a key factor that promoted consistent adherence. Further, identifying context cues and reminders seemed to promote incorporation of medication-taking into routines. Therefore, habit-based interventions that use context cues to establish routines around medication-taking may be a feasible strategy to improve adherence in patients with chronic conditions such as gout.

A behavioral economics approach to enhancing HIV preexposure and postexposure prophylaxis implementation

PURPOSE OF REVIEW

The 'PrEP cliff' phenomenon poses a critical challenge in global HIV PrEP implementation, marked by significant dropouts across the entire PrEP care continuum. This article reviews new strategies to address 'PrEP cliff'.

RECENT FINDINGS

Canadian clinicians have developed a service delivery model that offers presumptive PEP to patients in need and transits eligible PEP users to PrEP. Early findings are promising. This service model not only establishes a safety net for those who were not protected by PrEP, but it also leverages the immediate salience and perceived benefits of PEP as a natural nudge towards PrEP use. Aligning with Behavioral Economics, specifically the Salience Theory, this strategy holds potential in tackling PrEP implementation challenges.

SUMMARY

A natural pathway between PEP and PrEP has been widely observed. The Canadian service model exemplifies an innovative strategy that leverages this organic pathway and enhances the utility of both PEP and PrEP services. We offer theoretical insights into the reasons behind these PEP-PrEP transitions and evolve the Canadian model into a cohesive framework for implementation.

Self-management behavior strategy based on behavioral economics in patients with hypertension: a scoping review

Hypertensive patients often do not make the most favorable choices and behaviors for managing disease. Behavioral economics strategies offer new ideas for guiding patients toward health behavior. The scoping review aimed to summarize behavioral economics strategies designed to improve hypertension self-management behaviors. A literature search was conducted in September 2022 using the following electronic databases: Embase, Medline, CINAHL, PsycINFO, Web of Science, Cochrane Library, CNKI, Wan Fang Database for Chinese Periodicals, and CBM-SinoMed. We screened the literature for experimental studies written in Chinese or English reporting on BE strategies designed to improve self-management behavior in hypertension. We searched 17 820 records and included 18 articles in the final scoping review. We performed qualitative synthesis by the categories of choice architecture. The most common BE strategies were those targeting decision information and decision assistance, such as changing the presentation of information, making information visible, and providing reminders for actions. Most strategies targeted BP, diet, medication adherence, and physical activity behavior. Ten out of 18 studies reported statistically significant improvement in self-management behavior. Further research on BE strategies should focus on addressing the challenges, including changing the decision structure, encompassing a more comprehensive range of target behaviors, and examining the long-term effects of BE strategies.

Using mobile health to expedite access to specialty care for youth presenting to the emergency department with concussion at highest risk of developing persisting symptoms: a protocol paper for a non-randomised hybrid implementation-effectiveness trial

INTRODUCTION

Paediatric concussion is a common injury. Approximately 30% of youth with concussion will experience persisting postconcussion symptoms (PPCS) extending at least 1 month following injury. Recently, studies have shown the benefit of early, active, targeted therapeutic strategies. However, these are primarily prescribed from the specialty setting. Early access to concussion specialty care has been shown to improve recovery times for those at risk for persisting symptoms, but there are disparities in which youth are able to access such care. Mobile health (mHealth) technology has the potential to improve access to concussion specialists. This trial will evaluate the feasibility of a mHealth remote patient monitoring (RPM)-based care handoff model to facilitate access to specialty care, and the effectiveness of the handoff model in reducing the incidence of PPCS.

METHODS AND ANALYSIS

This study is a non-randomised type I, hybrid implementation-effectiveness trial. Youth with concussion ages 13-18 will be enrolled from the emergency department of a large paediatric healthcare network. Patients deemed a moderate-to-high risk for PPCS using the predicting and preventing postconcussive problems in paediatrics (5P) stratification tool will be registered for a web-based chat platform that uses RPM to collect information on symptoms and activity. Those patients with escalating or plateauing symptoms will be contacted for a specialty visit using data collected from RPM to guide management. The primary effectiveness outcome will be the incidence of PPCS, defined as at least three concussion-related symptoms above baseline at 28 days following injury. Secondary effectiveness outcomes will include the number of days until return to preinjury symptom score, clearance for full activity and return to school without accommodations. The primary implementation outcome will be fidelity, defined as the per cent of patients meeting specialty care referral criteria who are ultimately seen in concussion specialty care. Secondary implementation outcomes will include patient-defined and clinician-defined appropriateness and acceptability.

ETHICS AND DISSEMINATION

This study was approved by the Institutional Review Board of the Children's Hospital of Philadelphia (IRB 22-019755). Study findings will be published in peer-reviewed journals and disseminated at national and international meetings.

TRIAL REGISTRATION NUMBER

NCT05741411.

Remote Blood Pressure Monitoring With Social Support for Patients With Hypertension: A Randomized Clinical Trial

Importance

Hypertension management has traditionally been based on office visits. Integrating remote monitoring into routine clinical practices and leveraging social support might improve blood pressure (BP) control.

Objective

To evaluate the effectiveness of a bidirectional text monitoring program focused on BP control and medication adherence with and without social support in adults with hypertension.

Design, Setting, and Participants

This randomized clinical trial included adults aged 18 to 75 treated at an academic family medicine practice in Philadelphia in 2018 and 2019. Patients had been seen at least twice in the prior 24 months and had at least 2 elevated BP measurements (>150/90 mm Hg or >140/90 mm Hg for patients aged 18-59 years or with diabetes or chronic kidney disease) during visits. All participants had a cell phone with text messaging, offered at least 1 support partner, and were taking maintenance medications to treat hypertension. Patients were randomized 2:2:1 to remote monitoring of BP and medication adherence (RM), remote monitoring of BP and medication adherence with feedback provided to a social support partner (SS), or usual care (UC). Data were analyzed on an intention-to-treat basis between October 14, 2019, and May 30, 2020, and were revisited from May 23 through June 2, 2023.

Interventions

The RM and SS groups received an automatic home BP monitor, 3 weekly texts requesting BP measurements, 1 weekly text inquiring about medication adherence, and a weekly text with feedback. In the SS arm, support partners received a weekly progress report. The UC group received UC through their primary care practice. Clinicians caring for the patients in the intervention groups received nudges via electronic health records to adjust medications when 3 of 10 reported BP measurements were elevated. Patients were followed up for 4 months.

Main Outcomes and Measures

The primary outcome was systolic BP at 4 months measured during the final follow-up visit. Secondary outcomes included achievement of normotension and diastolic BP.

Results

In all, 246 patients (mean [SD] age, 50.9 [11.4] years; 175 females [71.1%]; 223 Black individuals [90.7%] and 13 White individuals [5.3%]) were included in the intention-to-treat analysis: 100 patients in the RM arm, 97 in the SS arm, and 49 in the UC arm. Compared with the UC arm, there was no significant difference in systolic or diastolic BP at the 4-month follow-up visit in the RM arm (systolic BP adjusted mean difference, -5.25 [95% CI, -10.65 to 0.15] mm Hg; diastolic BP adjusted mean difference, -1.94 [95% CI, -5.14 to 1.27] mm Hg) or the SS arm (systolic BP adjusted mean difference, -0.91 [95% CI, -6.37 to 4.55] mm Hg; diastolic BP adjusted mean difference, -0.63 [95% CI, -3.77 to 2.51] mm Hg). Of the 206 patients with a final BP measurement at 4 months, BP was controlled in 49% (41 of 84) of patients in the RM arm, 31% (27 of 87) of patients in the SS arm, and 40% (14 of 35) of patients in the UC arm; these rates did not differ significantly between the intervention arms and the UC group.

Conclusions and Relevance

In this randomized clinical trial, neither remote BP monitoring nor remote BP monitoring with social support improved BP control compared with UC in adults with hypertension. Additional efforts are needed to examine whether interventions directed at helping patients remember to take their BP medications can lead to improved BP control.

Trial Registration

ClinicalTrials.gov Identifier: NCT03416283.

Effectiveness of cardiac rehabilitation programs on medication adherence in patients with cardiovascular disease: A systematic review and meta-analysis

Background

Education to improve medication adherence is one of the core components of cardiac rehabilitation (CR) programs. However, the evidence on the effectiveness of CR programs on medication adherence is conflicting. Therefore, we aimed to summarize the effectiveness of CR programs versus standard care on medication adherence in patients with cardiovascular disease.

Methods

A systematic review and meta-analysis was conducted. Seven databases and clinical trial registries were searched for published and unpublished articles from database inception to 09 Feb 2022. Only randomised controlled trials and quasi-experimental studies were included. Two independent reviewers conducted the screening, extraction, and appraisal. The JBI methodology for effectiveness reviews and PRISMA 2020 guidelines were followed. A statistical meta-analysis of included studies was pooled using RevMan version 5.4.1.

Results

In total 33 studies were included with 16,677 participants. CR programs increased medication adherence by 14 % (RR = 1.14; 95 % CI: 1.07 to 1.22; p = 0.0002) with low degree of evidence certainty. CR also lowered the risk of dying by 17 % (RR = 0.83; 95 % CI: 0.69 to 1.00; p = 0.05); primary care and emergency department visit by mean difference of 0.19 (SMD = -0.19; 95 % CI: -0.30 to -0.08; p = 0.0008); and improved quality of life by 0.93 (SMD = 0.93; 95 % CI: 0.38 to 1.49; p = 0.0010). But no significant difference was observed in lipid profiles, except with total cholesterol (SMD = -0.26; 95 % CI: -0.44 to -0.07; p = 0.006) and blood pressure levels.

Conclusions

CR improves medication adherence with a low degree of evidence certainty and non-significant changes in lipid and blood pressure levels. This result requires further investigation.

The impact of using reinforcement learning to personalize communication on medication adherence: findings from the REINFORCE trial

Text messaging can promote healthy behaviors, like adherence to medication, yet its effectiveness remains modest, in part because message content is rarely personalized. Reinforcement learning has been used in consumer technology to personalize content but with limited application in healthcare. We tested a reinforcement learning program that identifies individual responsiveness ("adherence") to text message content and personalizes messaging accordingly. We randomized 60 individuals with diabetes and glycated hemoglobin A1c [HbA1c] ≥ 7.5% to reinforcement learning intervention or control (no messages). Both arms received electronic pill bottles to measure adherence. The intervention improved absolute adjusted adherence by 13.6% (95%CI: 1.7%-27.1%) versus control and was more effective in patients with HbA1c 7.5- < 9.0% (36.6%, 95%CI: 25.1%-48.2%, interaction p < 0.001). We also explored whether individual patient characteristics were associated with differential response to tested behavioral factors and unique clusters of responsiveness. Reinforcement learning may be a promising approach to improve adherence and personalize communication at scale.

Optimising the implementation of digital-supported interventions for the secondary prevention of heart disease: a systematic review using the RE-AIM planning and evaluation framework

BACKGROUND

mHealth technologies are now widely utilised to support the delivery of secondary prevention programs in heart disease. Interventions with mHealth included have shown a similar efficacy and safety to conventional programs with improvements in access and adherence. However, questions remain regarding the successful wider implementation of digital-supported programs. By applying the Reach-Effectiveness-Adoption-Implementation-Maintenance (RE-AIM) framework to a systematic review and meta-analysis, this review aims to evaluate the extent to which these programs report on RE-AIM dimensions and associated indicators.

METHODS

This review extends our previous systematic review and meta-analysis that investigated the effectiveness of digital-supported programs for patients with coronary artery disease. Citation searches were performed on the 27 studies of the systematic review to identify linked publications that reported data for RE-AIM dimensions. All included studies and, where relevant, any additional publications, were coded using an adapted RE-AIM extraction tool. Discrepant codes were discussed amongst reviewers to gain consensus. Data were analysed to assess reporting on indicators related to each of the RE-AIM dimensions, and average overall reporting rates for each dimension were calculated.

RESULTS

Searches found an additional nine publications. Across 36 publications that were linked to the 27 studies, 24 (89%) of the studies were interventions solely delivered at home. The average reporting rates for RE-AIM dimensions were highest for effectiveness (75%) and reach (67%), followed by adoption (54%), implementation (36%) and maintenance (11%). Eleven (46%) studies did not describe relevant characteristics of their participants or of staff involved in the intervention; most studies did not describe unanticipated consequences of the intervention; the ongoing cost of intervention implementation and maintenance; information on intervention fidelity; long-term follow-up outcomes, or program adaptation in other settings.

CONCLUSIONS

Through the application of the RE-AIM framework to a systematic review we found most studies failed to report on key indicators. Failing to report these indicators inhibits the ability to address the enablers and barriers required to achieve optimal intervention implementation in wider settings and populations. Future studies should consider alternative hybrid trial designs to enable reporting of implementation indicators to improve the translation of research evidence into routine practice, with special consideration given to the long-term sustainability of program effects as well as corresponding ongoing costs.

REGISTRATION

PROSPERO-CRD42022343030.

Social network interventions to support cardiac rehabilitation and secondary prevention in the management of people with heart disease

BACKGROUND

Globally, cardiovascular diseases (CVD, that is, coronary heart (CHD) and circulatory diseases combined) contribute to 31% of all deaths, more than any other cause. In line with guidance in the UK and globally, cardiac rehabilitation programmes are widely offered to people with heart disease, and include psychosocial, educational, health behaviour change, and risk management components. Social support and social network interventions have potential to improve outcomes of these programmes, but whether and how these interventions work is poorly understood.  OBJECTIVES: To assess the effectiveness of social network and social support interventions to support cardiac rehabilitation and secondary prevention in the management of people with heart disease. The comparator was usual care with no element of social support (i.e. secondary prevention alone or with cardiac rehabilitation).  SEARCH METHODS: We undertook a systematic search of the following databases on 9 August 2022: CENTRAL, MEDLINE, Embase, and the Web of Science. We also searched ClinicalTrials.gov and the WHO ICTRP. We reviewed the reference lists of relevant systematic reviews and included primary studies, and we contacted experts to identify additional studies.  SELECTION CRITERIA: We included randomised controlled trials (RCTs) of social network or social support interventions for people with heart disease. We included studies regardless of their duration of follow-up, and included those reported as full text, published as abstract only, and unpublished data.

DATA COLLECTION AND ANALYSIS

Using Covidence, two review authors independently screened all identified titles. We retrieved full-text study reports and publications marked 'included', and two review authors independently screened these, and conducted data extraction. Two authors independently assessed risk of bias, and assessed the certainty of the evidence using GRADE. Primary outcomes were all-cause mortality, cardiovascular-related mortality, all-cause hospital admission, cardiovascular-related hospital admission, and health-related quality of life (HRQoL) measured at > 12 months follow-up.  MAIN RESULTS: We included 54 RCTs (126 publications) reporting data for a total of 11,445 people with heart disease. The median follow-up was seven months and median sample size was 96 participants. Of included study participants, 6414 (56%) were male, and the mean age ranged from 48.6 to 76.3 years. Studies included heart failure (41%), mixed cardiac disease (31%), post-myocardial infarction (13%), post-revascularisation (7%), CHD (7%), and cardiac X syndrome (1%) patients. The median intervention duration was 12 weeks. We identified notable diversity in social network and social support interventions, across what was delivered, how, and by whom.  We assessed risk of bias (RoB) in primary outcomes at > 12 months follow-up as either 'low' (2/15 studies), 'some concerns' (11/15), or 'high' (2/15). 'Some concerns' or 'high' RoB resulted from insufficient detail on blinding of outcome assessors, data missingness, and absence of pre-agreed statistical analysis plans. In particular, HRQoL outcomes were at high RoB. Using the GRADE method, we assessed the certainty of evidence as low or very low across outcomes. Social network or social support interventions had no clear effect on all-cause mortality (risk ratio (RR) 0.75, 95% confidence interval (CI) 0.49 to 1.13, I2 = 40%) or cardiovascular-related mortality (RR 0.85, 95% CI 0.66 to 1.10, I2 = 0%) at > 12 months follow-up. The evidence suggests that social network or social support interventions for heart disease may result in little to no difference in all-cause hospital admission (RR 1.03, 95% CI 0.86 to 1.22, I2 = 0%), or cardiovascular-related hospital admission (RR 0.92, 95% CI 0.77 to 1.10, I2 = 16%), with a low level of certainty. The evidence was very uncertain regarding the impact of social network interventions on HRQoL at > 12 months follow-up (SF-36 physical component score: mean difference (MD) 31.53, 95% CI -28.65 to 91.71, I2 = 100%, 2 trials/comparisons, 166 participants; mental component score MD 30.62, 95% CI -33.88 to 95.13, I2 = 100%, 2 trials/comparisons, 166 participants).  Regarding secondary outcomes, there may be a decrease in both systolic and diastolic blood pressure with social network or social support interventions. There was no evidence of impact found on psychological well-being, smoking, cholesterol, myocardial infarction, revascularisation, return to work/education, social isolation or connectedness, patient satisfaction, or adverse events.  Results of meta-regression did not suggest that the intervention effect was related to risk of bias, intervention type, duration, setting, and delivery mode, population type, study location, participant age, or percentage of male participants.  AUTHORS' CONCLUSIONS: We found no strong evidence for the effectiveness of such interventions, although modest effects were identified in relation to blood pressure. While the data presented in this review are indicative of potential for positive effects, the review also highlights the lack of sufficient evidence to conclusively support such interventions for people with heart disease. Further high-quality, well-reported RCTs are required to fully explore the potential of social support interventions in this context. Future reporting of social network and social support interventions for people with heart disease needs to be significantly clearer, and more effectively theorised, in order to ascertain causal pathways and effect on outcomes.

Measurement Tools and Utility of Hair Analysis for Screening Adherence to Antihypertensive Medication

Poor adherence to the prescribed antihypertensive therapy is an understated public health problem and is one of the main causes of the high prevalence of uncontrolled hypertension in sub-Saharan Africa. Medication adherence is vital for the effectiveness of antihypertensive treatment and is key to ameliorating the clinical outcomes in hypertensive patients. However, it has often been ignored because the current methods used to assess medication adherence are not reliable, limiting their utilization in clinical practice. Therefore, the identification of the most accurate and clinically feasible method for measuring medication adherence is critical for tailoring effective strategies to improve medication adherence and consequently achieve blood pressure goals. This review not only explores various available methods for estimating medication adherence but also proposes therapeutic drug monitoring in hair for the measurement of medication adherence to the antihypertensive medication period.

Efficacy of a lay community health worker (promotoras de salud) program to improve adherence to emollients in Spanish-speaking Latin American pediatric patients in the United States with atopic dermatitis: A randomized, controlled, evaluator-blinded study

BACKGROUND

Latin American patients in the United States experience significant health disparities. Community health workers (promotoras de salud) reduce disparities by providing culturally appropriate education. While educational interventions have been studied in atopic dermatitis (AD), a chronic dermatologic condition affecting children, none have evaluated the use of promotoras in Spanish-speaking pediatric patients in the United States.

OBJECTIVE

To create and evaluate a promotora-led education program for Spanish-speaking caregivers of Latin American, pediatric patients with AD through a randomized, controlled, evaluator-blinded study.

METHODS

Children with moderate/severe AD (n = 48) were recruited from the pediatric dermatology clinic at Children's Health℠ in Dallas, TX and randomized to receive clinic education (n = 26) or clinic education plus promotora home visits (n = 22). The primary outcome was overall adherence to topical emollients over the 12-week study, quantified by MEMSCap™ devices; several secondary endpoints were evaluated.

RESULTS

Intention-to-treat analysis revealed a trend toward increased overall adherence to emollients over the 12-week study period in promotora (median [interquartile range, IQR]: 43% [26%-61%]) versus non-promotora (median [IQR]: 20% [11%-49%]) (p = .09) groups. SCORAD, AD knowledge, and Spanish-language Parental Quality of Life Questionnaire for AD (Sp-PIQoL-AD) improved in both groups, although there was no statistically significant difference between groups. There was a trend toward increased AD knowledge at Week 4 (p = .06) in the promotora group.

CONCLUSIONS

A promotora-led educational intervention is a promising approach in increasing caregiver medication adherence in pediatric, Latin American patients with AD in the United States. Further research using creative and culturally appropriate strategies to increase medication adherence is necessary to reduce health disparities in other racial and ethnic minority populations in the United States.

Medication delivery factors and adjuvant endocrine therapy adherence in breast cancer

PURPOSE

Over 50% of breast cancer patients prescribed a 5-year course of daily oral adjuvant endocrine therapy (ET) are nonadherent. We investigated the role of costs and cancer medication delivery mode and other medication delivery factors on adherence.

METHODS

We conducted a retrospective cohort study of commercially insured and Medicare advantage patients with newly diagnosed breast cancer in 2007-2015 who initiated ET. We examined the association between 12-month ET adherence (proportion of days covered by fills ≥ 0.80) and ET copayments, 90-day prescription refill use, mail order pharmacy use, number of pharmacies, and synchronization of medications. We used regression models to estimate nonadherence risk ratios adjusted for demographics (age, income, race, urbanicity), comorbidities, total medications, primary cancer treatments, and generic AI availability. Sensitivity analyses were conducted using alternative specifications for independent variables.

RESULTS

Mail order users had higher adherence in both commercial and Medicare-insured cohorts. Commercially insured patients who used mail order were more likely to be adherent if they had low copayments (< $5) and 90-day prescription refills. For commercially insured patients who used local pharmacies, use of one pharmacy and better synchronized refills were also associated with adherence. Among Medicare patients who used mail order pharmacies, only low copayments were associated with adherence, while among Medicare patients using local pharmacies both low copayments and 90-day prescriptions were associated with ET adherence.

CONCLUSION

Out-of-pocket costs, medication delivery mode, and other pharmacy-related medication delivery factors are associated with adherence to breast cancer ET. Future work should investigate whether interventions aimed at streamlining medication delivery could improve adherence for breast cancer patients.

Study design of BETTER-BP: Behavioral economics trial to enhance regulation of blood pressure

Background

Nonadherence to antihypertensive medications remains a persistent problem that leads to preventable morbidity and mortality. Behavioral economic strategies represent a novel way to improve antihypertensive medication adherence, but remain largely untested especially in vulnerable populations which stand to benefit the most. The Behavioral Economics Trial To Enhance Regulation of Blood Pressure (BETTER-BP) was designed in this context, to test whether a digitally-enabled incentive lottery improves antihypertensive adherence and reduces systolic blood pressure (SBP).

Design

BETTER-BP is a pragmatic randomized trial conducted within 3 safety-net clinics in New York City: Bellevue Hospital Center, Gouveneur Hospital Center, and NYU Family Health Centers - Park Slope. The trial will randomize 435 patients with poorly controlled hypertension and poor adherence (<80% days adherent) in a 2:1 ratio (intervention:control) to receive either an incentive lottery versus passive monitoring. The incentive lottery is delivered via short messaging service (SMS) text messages that are delivered based on (1) antihypertensive adherence tracked via a wireless electronic monitoring device, paired with (2) a probability of lottery winning with variable incentives and a regret component for nonadherence. The study intervention lasts for 6 months, and ambulatory systolic blood pressure (SBP) will be measured at both 6 and 12 months to evaluate immediate and durable lottery effects.

Conclusions

BETTER-BP will generate knowledge about whether an incentive lottery is effective in vulnerable populations to improve antihypertensive medication adherence. If successful, this could lead to the implementation of this novel strategy on a larger scale to improve outcomes.

Medication Nonuse and Hospital Utilization: Medicaid Participants With Type 2 Diabetes in New York City

INTRODUCTION

This study assesses the proportion of New York City Medicaid participants diagnosed with type 2 diabetes who did not have any claims for diabetes medication for an entire year and the association between nonuse of diabetes medication and subsequent hospitalizations.

METHODS

The 2014‒2016 New York State Medicaid claims data were used for this cohort study. Two types of hospitalizations were examined: all-cause hospitalizations and preventable diabetes hospitalizations. A potential association between medication nonuse and the number of hospitalizations in the following year was assessed using the negative binomial regression model, adjusting for individual- and neighborhood-level factors. The study was conducted in 2019‒2020.

RESULTS

Among the 117,183 individuals included in this study, 27.5% did not use any diabetes medication for an entire year. Compared with individuals using oral hypoglycemic medication only, the crude rate of all-cause hospitalizations among individuals who used no medication was approximately twice as high (37,111 vs 19,209 per 100,000 population), and the crude rate of preventable diabetes hospitalizations was almost 3 times as high (1,488 vs 537 per 100,000 population). Adjusting for individual- and neighborhood-level characteristics, medication nonuse was still associated with higher levels of all-cause hospitalizations (incidence rate ratio=1.26; 95% CI=1.21, 1.31) and preventable diabetes hospitalizations (incidence rate ratio=1.66; 95% CI=1.39, 1.99).

CONCLUSIONS

Medication use and adherence are important for managing diabetes. However, almost 30% of New York City Medicaid participants with type 2 diabetes had no claims for diabetes medication for an entire year. Significantly higher hospitalization rates among this group warrant attention from providers and policy makers.

The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: To adopt what we call the "i-frame," rather than the "s-frame." The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contribute to public policy is by employing their skills to develop and implement value-creating system-level change.

Considerations for Conducting Bring Your Own “Device” (BYOD) Clinical Studies

Background

Digital health technologies are attracting attention as novel tools for data collection in clinical research. They present alternative methods compared to in-clinic data collection, which often yields snapshots of the participants' physiology, behavior, and function that may be prone to biases and artifacts, e.g., white coat hypertension, and not representative of the data in free-living conditions. Modern digital health technologies equipped with multi-modal sensors combine different data streams to derive comprehensive endpoints that are important to study participants and are clinically meaningful. Used for data collection in clinical trials, they can be deployed as provisioned products where technology is given at study start or in a bring your own “device” (BYOD) manner where participants use their technologies to generate study data.

Summary

The BYOD option has the potential to be more user-friendly, allowing participants to use technologies that they are familiar with, ensuring better participant compliance, and potentially reducing the bias that comes with introducing new technologies. However, this approach presents different technical, operational, regulatory, and ethical challenges to study teams. For example, BYOD data can be more heterogeneous, and recruiting historically underrepresented populations with limited access to technology and the internet can be challenging. Despite the rapid increase in digital health technologies for clinical and healthcare research, BYOD use in clinical trials is limited, and regulatory guidance is still evolving.

Key Messages

We offer considerations for academic researchers, drug developers, and patient advocacy organizations on the design and deployment of BYOD models in clinical research. These considerations address: (1) early identification and engagement with internal and external stakeholders; (2) study design including informed consent and recruitment strategies; (3) outcome, endpoint, and technology selection; (4) data management including compliance and data monitoring; (5) statistical considerations to meet regulatory requirements. We believe that this article acts as a primer, providing insights into study design and operational requirements to ensure the successful implementation of BYOD clinical studies.

Feasibility of a pharmacist-led symptom monitoring and management intervention to improve breast cancer endocrine therapy adherence

BACKGROUND

Adjuvant endocrine therapy (AET) for breast cancer reduces mortality, but one-third to one-half of patients discontinue it early or are nonadherent.

OBJECTIVE

We developed a pilot single-site study of patients with evidence of early nonadherence to AET to assess the feasibility of a novel, clinical pharmacist-led intervention targeting symptom and medication management.

METHODS

Patients with prescription fill records showing nonadherence were enrolled in a single-arm feasibility study. Automated reminders were sent by e-mail or text with a link to symptom monitoring assessments weekly for 1 month and monthly until 6 months. Clinical oncology pharmacists used guideline-based symptom management and other medication management tools to support adherence and ameliorate symptoms reported on the assessments. Patient-reported outcome assessments included physical, mental, and social health domains and self-efficacy to manage symptoms and medications. Feasibility outcomes included completion of symptom reports and pharmacist recommendations.

RESULTS

Of 19 participants who were nonadherent who enrolled and completed initial assessments, 18 completed all final study procedures, with 14 completing all assessments and no patient missing more than 3 assessments. All 18 participants reported at least one of 3 symptom types, and the majority reported attempting pharmacist recommendations. Patient-reported measures of physical, mental, and social health and self-efficacy improved, and 44% of the patients became adherent.

CONCLUSION

An intervention using pharmacists in an oncology practice to systematically monitor and manage symptoms shows promise to reduce symptoms, enhance support and self-efficacy, and improve adherence to AET.

Unblinded and Blinded N-of-1 Trials Versus Usual Care: A Randomized Controlled Trial to Increase Statin Uptake in Primary Care

BACKGROUND

The aim was to assess whether an intervention incorporating a practicable open-label n-of-1 trial would lead to greater uptake of statin than usual care and comparable uptake to a closed-label gold-standard n-of-1 trial.

METHODS

We enrolled patients who had stopped or declined statins into a 3-arm trial (usual care, unblinded, and blinded n-of-1 intervention arms). Physicians advised participants randomized to usual care to take statin therapy to prevent cardiovascular disease. In both intervention arms, physicians delivered a theoretically informed informed intervention endorsing the value of experimenting with medication in n-of-1 trials to assess whether it caused side-effects. In these trials, participants alternated between 4 weeks of medication and no medication (unblinded arm) or randomly sorted active and placebo (blinded arm) and recorded symptoms and symptom attributions for 6 months. Thereafter, physicians discussed participants' symptom reports during active/inactive treatment periods and asked participants to resume statins if appropriate.

RESULTS

Seventy-three were randomized to the intervention arms and 20 to the control group. Fifty-six of 73 (77%) attempted the n-of-1 experiment; 28/36 (78%) in the unblinded arm; and 28/37 (76%) in the blinded arm. Forty-three of 56 (77%) completed the 6-month experiment and received feedback from the physician; 20/28 (71%) in the unblinded arm and 23/28 (82%) in the blinded arm. Thirty-three of 76 (45%) people restarted statins in the n-of-1 arms compared with 4/20 (20%) in the control arm, difference 24% (95% CI, 5%-43%; P=0.041). There was no evidence this differed between blinded and unblinded arms, difference 2% (95% CI, -20% to 24%; P=0.86). Adverse events occurred at a similar rate on and off statin.

CONCLUSIONS

In patients refusing or intolerant of statin, supporting experimentation with n-of-1 trials increases medication uptake compared with usual care. Alternating on-off medication in unblinded n-of-1 experiments appears as effective as a blinded experiment.

REGISTRATION

URL: https://doi.org/10.1186/ISRCTN11142694; Unique identifier: ISRCTN11142694.

Are clinical trials randomising households to lifestyle interventions to delay cognitive decline feasible? A pilot study to determine the beliefs, preferences, and deterrents for households impacted by dementia based on semi-structured interviews

Introduction

While lifestyle risk factors are implicated in the development and progression of cognitive impairment, interventional trials of individual participants have yielded unconvincing evidence. We sought to explore the development of lifestyle interventions targeting the household-unit.

Methods

Semi-structured interviews were carried out among eight households affected by cognitive impairment (i.e. member of the household had cognitive impairment). Interviews took place online using a secure, web-based video platform recommended for patient clinician interaction. Interview content was analysed, and important themes identified.

Results

Eighteen participants were interviewed within households, of which eight (one per household) had cognitive impairment and others were spouses or first-degree relatives living in the same home. Several themes emerged; 1) household members without cognitive impairment were more likely to report poor sleep habits, and sleep was perceived to be the hardest behaviour to change; 2) diet generated most interest as a potential lifestyle intervention target as most participants believed there is a strong link with nutrition and cognition; 3) physical activity is challenging to adapt due to lack of motivation and focus when individuals are cognitively impaired. Barriers to study participation, including risk of harm, complexity of intervention and deviation from routine emerged during discussions.

Conclusions

This study identified beliefs and preferences of households towards lifestyle intervention trials. Findings from this study may be used to inform future clinical trial protocols and future qualitative studies should explore acceptability and feasibility of digital intervention applications.

The Impact of Delayed Symptomatic Treatment Implementation in the Intensive Care Unit

We estimated the harm related to medication delivery delays across 12,474 medication administration instances in an intensive care unit using retrospective data in a large urban academic medical center between 2012 and 2015. We leveraged an instrumental variables (IV) approach that addresses unobserved confounds in this setting. We focused on nurse shift changes as disruptors of timely medication (vasodilators, antipyretics, and bronchodilators) delivery to estimate the impact of delay. The average delay around a nurse shift change was 60.8 min (p < 0.001) for antipyretics, 39.5 min (p < 0.001) for bronchodilators, and 57.1 min (p < 0.001) for vasodilators. This delay can increase the odds of developing a fever by 32.94%, tachypnea by 79.5%, and hypertension by 134%, respectively. Compared to estimates generated by a naïve regression approach, our IV estimates tend to be higher, suggesting the existence of a bias from providers prioritizing more critical patients.

Reevaluating medication adherence in the era of digital health

INTRODUCTION

Medication adherence is a worldwide issue impacting more than half the population. The cost associated with nonadherence is tremendous and has spurred the growth of novel technologies to address this growing problem.

AREAS COVERED

This perspective covers the different digital health medication adherence tools that have come to market in the past decade and their clinical impact. These digital interventions and their applicability to medication adherence across different stakeholders are then evaluated.

EXPERT OPINION

Digital health will play a significant role in creating new pathways to care in the 2020s. However, the current design of medication adherence tools has not demonstrated a clinical impact that will be relevant for the digital health space without a change in redesign factoring in relevant stakeholders' incentives to address adherence issues. A focus on only adherence has not yielded the economic or clinical benefit as expected, which is likely due to a lack of focus on broader drug-related problems (DRPs) that are causative factors beyond adherence alone. As such, adherence tools will see disparate uptake, likely due to condition-specific interventions rather than adherence issues as a whole, and future endeavors will need to address the larger DRP considerations to actualize clinical outcomes.

REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial

INTRODUCTION

Achieving optimal diabetes control requires several daily self-management behaviours, especially adherence to medication. Evidence supports the use of text messages to support adherence, but there remains much opportunity to improve their effectiveness. One key limitation is that message content has been generic. By contrast, reinforcement learning is a machine learning method that can be used to identify individuals' patterns of responsiveness by observing their response to cues and then optimising them accordingly. Despite its demonstrated benefits outside of healthcare, its application to tailoring communication for patients has received limited attention. The objective of this trial is to test the impact of a reinforcement learning-based text messaging programme on adherence to medication for patients with type 2 diabetes.

METHODS AND ANALYSIS

In the REinforcement learning to Improve Non-adherence For diabetes treatments by Optimising Response and Customising Engagement (REINFORCE) trial, we are randomising 60 patients with suboptimal diabetes control treated with oral diabetes medications to receive a reinforcement learning intervention or control. Subjects in both arms will receive electronic pill bottles to use, and those in the intervention arm will receive up to daily text messages. The messages will be individually adapted using a reinforcement learning prediction algorithm based on daily adherence measurements from the pill bottles. The trial's primary outcome is average adherence to medication over the 6-month follow-up period. Secondary outcomes include diabetes control, measured by glycated haemoglobin A1c, and self-reported adherence. In sum, the REINFORCE trial will evaluate the effect of personalising the framing of text messages for patients to support medication adherence and provide insight into how this could be adapted at scale to improve other self-management interventions.

ETHICS AND DISSEMINATION

This study was approved by the Mass General Brigham Institutional Review Board (IRB) (USA). Findings will be disseminated through peer-reviewed journals, clinicaltrials.gov reporting and conferences.

TRIAL REGISTRATION NUMBER

Clinicaltrials.gov (NCT04473326).

Randomised controlled trial targeting habit formation to improve medication adherence to daily oral medications in patients with gout

INTRODUCTION

Medication adherence for patients with chronic conditions such as gout, a debilitating form of arthritis that requires daily medication to prevent flares, is a costly problem. Existing interventions to improve medication adherence have only been moderately effective. Habit formation theory is a promising strategy to improve adherence. The cue-reward-repetition principle posits that habits are formed by repeatedly completing an activity after the same cue and having the action rewarded every time. Over time, cues become increasingly important whereas rewards become less salient because the action becomes automatic. Leveraging the cue-reward-repetition principle could improve adherence to daily gout medications.

METHODS AND ANALYSIS

This three-arm parallel randomised controlled trial tests an adaptive intervention that leverages the repetition cue-reward principle. The trial will began recruitment in August 2021 in Boston, Massachusetts, USA. Eligible patients are adults with gout who have been prescribed a daily oral medication for gout and whose most recent uric acid is above 6 mg/dL. Participants will be randomised to one of three arms and given electronic pill bottles. In the two intervention arms, participants will select a daily activity to link to their medication-taking (cue) and a charity to which money will be donated every time they take their medication (reward). Participants in Arm 1 will receive reminder texts about their cue and their charity reward amount will be US$0.50 per day of medication taken. Arm 2 will be adaptive; participants will receive a US$0.25 per adherent-day and no reminder texts. If their adherence is <75% 6 weeks postrandomisation, their reward will increase to US$0.50 per adherent-day and they will receive reminder texts. The primary outcome is adherence to gout medications over 18 weeks.

ETHICS AND DISSEMINATION

This trial has ethical approval in the USA. Results will be published in a publicly accessible peer-reviewed journal.

TRIAL REGISTRATION NUMBER

NCT04776161.

Methylphenidate augmentation of escitalopram to enhance adherence to antidepressant treatment: a pilot randomized controlled trial

BACKGROUND

Adherence to treatment, i.e. the extent to which a patient's therapeutic engagement coincides with the prescribed treatment, is among the most important problems in mental health care. The current study investigated the influence of pairing an acute positive reinforcing dopaminergic/noradrenergic effect (methylphenidate, MPH) with a standard antidepressant on the rates of adherence to medication treatment. The primary objective of this study was to determine whether MPH + escitalopram resulted in higher rates of medication adherence relative to placebo + escitalopram.

METHODS

Twenty participants with moderate to severe depression were 1-1 randomized to either (1) 5 mg MPH + 10 mg escitalopram or (2) placebo + 10 mg escitalopram with the possibility for a dose increase at 4 weeks. A Bayesian analysis was conducted to evaluate the outcomes.

RESULTS

First, neither percent Pill count nor Medication Electronic Monitoring System adherence showed that MPH was superior to placebo. In fact, placebo showed slightly higher adherence rates on the primary (7.82% better than MPH) and secondary (7.07% better than MPH) outcomes. There was a less than 25% chance of MPH augmentation showing at least as good or better adherence than placebo. Second, both groups showed a significant effect of treatment on the QIDS-SR with a median effect of an 8.6-point score reduction. Third, neither subjective measures of adherence attitudes nor socio-demographic covariates had a significant influence on the primary or secondary outcome variables.

CONCLUSIONS

These data do not support the use of MPH to increase adherence to antidepressant medication in individuals with moderate to severe depression. CLINICALTRIALS.

GOV IDENTIFIER

NCT03388164 , registered on 01/02/2018.

European Network to Advance Best Practices and Technology on Medication Adherence: Mission Statement

Medication non-adherence is associated with almost 200,000 deaths annually and €80-125 billion in the European Union. Novel technological advances (smart pill bottles, digital inhalers and spacers, electronic pill blisters, e-injection pens, e-Health applications, big data) could help managing non-adherence. Healthcare professionals seem however inadequately informed about non-adherence, availability of technological solutions in daily practice is limited, and collaborative efforts to push forward their implementation are scarce. The European Network to Advance Best practices and technoLogy on medication adherencE (ENABLE, COST Action 19132) aims to 1) raise awareness of adherence enhancing solutions, 2) foster knowledge on medication adherence, 3) accelerate clinical application of novel technologies and 4) work collaboratively towards economically viable policy, and implementation of adherence enhancing technology across healthcare systems.

Medication Adherence and Blood Pressure Control: A Scientific Statement From the American Heart Association

The widespread treatment of hypertension and resultant improvement in blood pressure have been major contributors to the dramatic age-specific decline in heart disease and stroke. Despite this progress, a persistent gap remains between stated public health targets and achieved blood pressure control rates. Many factors may be important contributors to the gap between population hypertension control goals and currently observed control levels. Among them is the extent to which patients adhere to prescribed treatment. The goal of this scientific statement is to summarize the current state of knowledge of the contribution of medication nonadherence to the national prevalence of poor blood pressure control, methods for measuring medication adherence and their associated challenges, risk factors for antihypertensive medication nonadherence, and strategies for improving adherence to antihypertensive medications at both the individual and health system levels.

The Role of Behavioral Economics in Improving Cardiovascular Health Behaviors and Outcomes

PURPOSE OF REVIEW

Behavioral economics represents a promising set of principles to inform the design of health-promoting interventions. Techniques from the field have the potential to increase quality of cardiovascular care given suboptimal rates of guideline-directed care delivery and patient adherence to optimal health behaviors across the spectrum of cardiovascular care delivery.

RECENT FINDINGS

Cardiovascular health-promoting interventions have demonstrated success in using a wide array of principles from behavioral economics, including loss framing, social norms, and gamification. Such approaches are becoming increasingly sophisticated and focused on clinical cardiovascular outcomes in addition to health behaviors as a primary endpoint. Many approaches can be used to improve patient decisions remotely, which is particularly useful given the shift to virtual care in the context of the COVID-19 pandemic. Numerous applications for behavioral economics exist in the cardiovascular care delivery space, though more work is needed before we will have a full understanding of ways to best leverage such applications in each clinical context.

Effect of Financial Incentives for Process, Outcomes, or Both on Cholesterol Level Change: A Randomized Clinical Trial

Importance

Financial incentives may improve health behaviors. It is unknown whether incentives are more effective if they target a key process (eg, medication adherence), an outcome (eg, low-density lipoprotein cholesterol [LDL-C] levels), or both.

Objective

To determine whether financial incentives awarded daily for process (adherence to statins), awarded quarterly for outcomes (personalized LDL-C level targets), or awarded for process plus outcomes induce reductions in LDL-C levels compared with control.

Design, Setting, and Participants

A randomized clinical trial was conducted from February 12, 2015, to October 3, 2018; data analysis was performed from October 4, 2018, to May 27, 2021, at the University of Pennsylvania Health System, Philadelphia. Participants included 764 adults with an active statin prescription, elevated risk of atherosclerotic cardiovascular disease, suboptimal LDL-C level, and evidence of imperfect adherence to statin medication.

Interventions

Interventions lasted 12 months. All participants received a smart pill bottle to measure adherence and underwent LDL-C measurement every 3 months. In the process group, daily financial incentives were awarded for statin adherence. In the outcomes group, participants received incentives for achieving or sustaining at least a quarterly 10-mg/dL LDL-C level reduction. The process plus outcomes group participants were eligible for incentives split between statin adherence and quarterly LDL-C level targets.

Main Outcomes and Measures

Change in LDL-C level from baseline to 12 months, determined using intention-to-treat analysis.

Results

Of the 764 participants, 390 were women (51.2%); mean (SD) age was 62.4 (10.0) years, 310 (40.6%) had diabetes, 298 (39.0%) had hypertension, and mean (SD) baseline LDL-C level was 138.8 (37.6) mg/dL. Mean LDL-C level reductions from baseline to 12 months were -36.9 mg/dL (95% CI, -42.0 to -31.9 mg/dL) among control participants, -40.0 mg/dL (95% CI, -44.7 to -35.4 mg/dL) among process participants, -41.6 mg/dL (95% CI, -46.3 to -37.0 mg/dL) among outcomes participants, and -42.8 mg/dL (95% CI, -47.4 to -38.1 mg/dL) among process plus outcomes participants. In exploratory analysis among participants with diabetes and hypertension, no spillover effects of incentives were detected compared with the control group on hemoglobin A1c level and blood pressure over 12 months.

Conclusions and Relevance

In this randomized clinical trial, process-, outcomes-, or process plus outcomes-based financial incentives did not improve LDL-C levels vs control.

Trial Registration

ClinicalTrials.gov Identifier: NCT02246959.

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

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.

Mobile health in preventive cardiology: current status and future perspective

PURPOSE OF REVIEW

Despite cutting edge acute interventions and growing preventive strategies supported by robust clinical trials, cardiovascular disease (CVD) has stubbornly persisted as a leading cause of death in the United States and globally. The American Heart Association recognizes mobile health technologies (mHealth) as an emerging strategy in the mitigation of CVD risk factors, with significant potential for improving population health. The purpose of this review is to highlight and summarize the latest available literature on mHealth applications and provide perspective on future directions and barriers to implementation.

RECENT FINDINGS

While available randomized controlled trials and systematic reviews tend to support efficacy of mHealth, published literature includes heterogenous approaches to similar problems with inconsistent results. Some of the strongest recent evidence has been focused on the use of wearables in arrhythmia detection. Systematic reviews of mHealth approaches demonstrate benefit when applied to risk factor modification in diabetes, cigarette smoking cessation, and physical activity/weight loss, while also showing promise in multi risk factor modification via cardiac rehabilitation.

SUMMARY

Evidence supports efficacy of mHealth in a variety of applications for CVD prevention and management, but continued work is needed for further validation and scaling. Future directions will focus on platform optimization, data and sensor consolidation, and clinical workflow integration. Barriers include application heterogeneity, lack of reimbursement structures, and inequitable access to technology. Policies to promote access to technology will be critical to evidence-based mHealth technologies reaching diverse populations and advancing health equity.

Developing and Implementing a Mobile Health Heart Failure Self-Care Program to Reduce Readmissions: A Patient-Centered Outcomes Research Randomized Controlled Trial (Preprint)

Background

Patients admitted with decompensated heart failure (HF) are at risk for hospital readmission and poor quality of life during the discharge period. Lifestyle behavior modifications that promote the self-management of chronic cardiac diseases have been associated with an improved quality of life. However, whether a mobile health (mHealth) program can assist patients in the self-management of HF during the acute posthospital discharge period is unknown.

Objective

We aimed to develop an mHealth program designed to enhance patients’ self-management of HF by increasing knowledge, self-efficacy, and symptom detection. We hypothesized that patients hospitalized with HF would be willing to use a feasibly deployed mHealth program after their hospital discharge.

Methods

We employed a patient-centered outcomes research methodology to design a stakeholder-informed mHealth program. Adult patients with HF admitted to a large academic hospital were enrolled and randomized to receive the mHealth intervention versus usual care. Our feasibility outcomes included ease of program deployment, use of the clinical escalation process, duration of participant recruitment, and participant attrition. Surveys assessing the demographics and clinical characteristics of HF were measured at baseline and at 30 and 90 days after discharge.

Results

The study period was between July 1, 2019, and April 7, 2020. The mean cohort (N=31) age was 60.4 (range 22-85) years. Over half of the participants were men (n=18, 58%) and 77% (n=24) were White. There were no significant differences in baseline measures. We determined that an educational mHealth program tailored for patients with HF is feasibly deployed and acceptable by patients. Though not significant, we found notable trends including a higher mean quality of life at 30 days posthospitalization among program users and a longer duration before rehospitalization, which are suggestive of better HF prognosis.

Conclusions

Our mHealth tool should be further assessed in a larger comparative effectiveness trial. Our pilot intervention offers promise as an innovative means to help HF patients lead healthy, independent lives. These preliminary data suggest that patient-centered mHealth tools can enable high-risk patients to play a role in the management of their HF after discharge.

Trial Registration

ClinicalTrials.gov NCT03982017; https://clinicaltrials.gov/ct2/show/NCT03982017

Comparison of measures of medication adherence from pharmacy dispensing and insurer claims data

OBJECTIVE

Medication nonadherence is linked to worsened clinical outcomes and increased costs. Existing system-level adherence interventions rely on insurer claims for patient identification and outcome measurement, yet suffer from incomplete capture and lags in data acquisition. Data from pharmacies regarding prescription filling, captured in retail dispensing, may be more efficient.

DATA SOURCES

Pharmacy fill and insurer claims data.

STUDY DESIGN

We compared adherence measured using pharmacy fill data to adherence using insurer claims data, expressed as proportion of days covered (PDC) over 12 months. Agreement was evaluated using correlation/validation metrics. We also explored the relationship between adherence in both sources and disease control using prediction modeling.

DATA EXTRACTION METHODS

Large pragmatic trial of cardiometabolic disease in an integrated delivery network.

PRINCIPAL FINDINGS

Among 1113 patients, adherence was higher in pharmacy fill (mean = 50.0%) versus claims data (mean = 47.4%), although they had moderately high correlation (R = 0.57, 95% CI: 0.53-0.61) with most patients (86.9%) being similarly classified as adherent or nonadherent. Sensitivity and specificity of pharmacy fill versus claims data were high (0.89, 95% CI: 0.86-0.91 and 0.80, 95% CI: 0.75-0.85). Pharmacy fill-based PDC predicted better disease control slightly more than claims-based PDC, although the difference was nonsignificant.

CONCLUSIONS

Pharmacy fill data may be an alternative to insurer claims for adherence measurement.

Medication adherence in cardiovascular medicine

Cardiovascular disease is the leading cause of death globally. While pharmacological advancements have improved the morbidity and mortality associated with cardiovascular disease, non-adherence to prescribed treatment remains a significant barrier to improved patient outcomes. A variety of strategies to improve medication adherence have been tested in clinical trials, and include the following categories: improving patient education, implementing medication reminders, testing cognitive behavioral interventions, reducing medication costs, utilizing healthcare team members, and streamlining medication dosing regimens. In this review, we describe specific trials within each of these categories and highlight the impact of each on medication adherence. We also examine ongoing trials and future lines of inquiry for improving medication adherence in patients with cardiovascular diseases.

Electronic pill bottles to monitor and promote medication adherence for people with multiple sclerosis: A randomized, virtual clinical trial

OBJECTIVE

We perform a randomized trial to test the impact of electronic pill bottles with audiovisual reminders on oral disease modifying therapy (DMT) adherence in people with MS (PwMS).

METHODS

Adults with multiple sclerosis (MS) taking an oral DMT were randomized 1:1 for 90 days to remote smartphone app- and pill bottle-based (a) adherence monitoring, or (b) adherence monitoring with audiovisual medication reminders. Optimal adherence was defined as the proportion of doses taken ±3 h of the scheduled time. Numbers of missed pills and pills taken early, on time, late, and extra were recorded. A multivariable regression model tested possible associations between optimal adherence and age, MS duration, cognitive functioning, and number of daily prescription pills.

RESULTS

85 participants (66 female; mean age 44.9 years) took dimethyl/diroximel fumarate (n = 49), fingolimod (n = 26), or teriflunomide (n = 10). Optimal adherence was on average higher in the monitoring with reminders arm (71.4%) than the monitoring only arm (61.6%; p = 0.033). In a multivariable model, optimal adherence was less likely in younger participants (p < 0.001) and those taking more daily prescription pills (p < 0.001). In the monitoring only arm, 4.0% of doses were taken early, 61.6% on time, 5.6% late, 4.4% in excess, and 24.4% were missed. In the reminders arm, these proportions were 3.4%, 71.4%, 3.7%, 8.7%, and 12.8%, respectively.

CONCLUSION

We map real-world oral DMT adherence patterns using mHealth technology. PwMS who received medication reminders had higher optimal adherence. Nonadherence was more nuanced than simply missing pills. Developing strategies to improve adherence remains important in longitudinal MS care.

Sleep disturbance in patients with cancer: a feasibility study of multimodal therapy

BACKGROUND

Our aim was to determine feasibility and effect sizes of bright light therapy (BLT), melatonin (MLT), methylphenidate (MP) and eight combinations (BLT+MLT+MP, BLT+MLT, BLT+MP, BLT alone, MLT+MP, MLT alone, MP alone, placebo for BLT, MLT and MP) defined as multimodal therapy (MMT), to improve sleep quality (SQ) (Pittsburgh Sleep Quality Index (PSQI)) from baseline to day 15. We also examined the effects of MMT on insomnia, fatigue, depression, quality of life and actigraphy.

METHODS

Patients with advanced cancer with poor SQ (PSQI ≥5) were eligible. Using a double-blind randomised factorial study design, patients were randomised into 1 of the 8 arms for 2 weeks. Feasibility and effect sizes were assessed.

RESULTS

81% (54/67) of randomised patients completed the study. There were no differences in the demographics and SQ between groups. The adherence rates for BLT, MLT and MP were 93%, 100% and 100%, respectively. BLT+MLT+placebo of MP; BLT+placebo of MLT+placebo of MP; BLT+MLT+MP showed an effect size (Cohen's d) for change in PSQI scores of 0.64, 0.57 and 0.63, respectively. PSQI change using linear regression showed BLT (n=29) has effect size of 0.46, p=0.017; MLT (n=26), 0.24, p=0.20; MP (n=26), 0.06, p=0.46. No significant differences were observed in scores for insomnia, fatigue, depression, quality of life and actigraphy. There were no differences in adverse events by groups(p=0.80).

CONCLUSIONS

The use of MMT to treat SQ disturbance was feasible. BLT+MLT showed the most promising effect size in improvement in SQ, and additional larger studies are needed.

TRIAL REGISTRATION NUMBER

NCT01628029.

Effect of the ExactCare medication care management model on adherence, health care utilization, and costs

BACKGROUND: Multimorbidity and polypharmacy are common in the United States and are associated with greater risk of disease-related complications and higher health care costs. ExactCare has implemented a high-touch approach that includes home visits, comprehensive ongoing medication reviews, patient education, medication reconciliation, medication compliance packaging, and electronic reminders and trackers. OBJECTIVE: To test whether the ExactCare program improves medication adherence and reduces health care utilization and costs. METHODS: Using a national database from a large U.S. insurer, we identified Medicare Advantage plan members in 8 states from 2007 to 2018 who had both medical and prescription drug coverage. The index year for an ExactCare patient was identified using the date of the first prescription filled by ExactCare, with the previous year being the baseline. All patients without a prescription from an ExactCare pharmacy were considered potential comparison patients. To propensity match ExactCare and comparison patients, the probability of ExactCare participation was modeled using a logistic regression based on demographics, state, year, urban status, Medicaid eligibility, low-income subsidies, comorbidities, and baseline utilization and costs. Multivariate regression analysis was conducted to generate a difference-in-differences estimate of program effect for the matched pairs as well as patient-level fixed effects, while adjusting for additional time-varying characteristics. Adherence outcomes included the proportion of days covered for oral diabetic medications, antihypertensives, and hydroxymethylglutaryl-coenzyme A reductase inhibitors (statins). Utilization outcomes included emergency department (ED) visits, hospitalizations, and skilled nursing facility (SNF) admissions, hospitalization days, and SNF days. Cost outcomes included total cost of care, prescription drug cost, hospital inpatient cost, and SNF cost. RESULTS: ExactCare patients (N = 701) were propensity-matched to comparison patients (N = 1,395) using the nearest 1:2 match approach, with an average follow-up period of 6.6 and 5.4 years for ExactCare and comparison patients, respectively. One year of ExactCare participation was associated with statistically significant increases in adherence to statins (8.4 percentage points; P < 0.001) and antihypertensive drugs (4.9 percentage points; P < 0.001), but the increase in adherence for diabetes drugs was not statistically significant. ExactCare participation was associated with statistically significant decreases in SNF admission rates (-67 SNF stays per 1,000 member-years; P = 0.011), inpatient days (-857 days per 1,000 member-years; P = 0.022), and SNF days (-1,801 days per 1,000 member-years; P = 0.002), but not with the rates of ED visits or hospital admissions. Each year of ExactCare participation was associated with increases in prescription drug costs ($30 per-member per month [PMPM]; P = 0.006) and decreases in total costs (-$196 PMPM; P = 0.023) and medical costs (-$226 PMPM; P = 0.008), largely attributable to decreases in hospital inpatient costs (-$119 PMPM; P = 0.001) and SNF costs (-$30 PMPM; P = 0.007). CONCLUSIONS: ExactCare's medication care management model was associated with improved medication adherence and an approximately $2,400 per member per year reduction in total cost of care, representing a 5% reduction in average costs. DISCLOSURES: This study was funded by ExactCare Pharmacy under a contract with RAND that grants the study authors sole responsibility for data management, study design, data analysis, manuscript drafting, and the decision to publish. The sponsor had no role in the study design and manuscript drafting. All data analysis was conducted by the study authors. A draft manuscript was reviewed by the sponsor, but the study authors made final decisions regarding the content and study conclusions. Shetty, Chen, and Liu are employed by RAND. Rose has nothing to disclose.

Patient preferences for medication adherence financial incentive structures: A discrete choice experiment

BACKGROUND

Medication adherence for chronic conditions continues to be a challenge for patients. Patient incentives for medication adherence may help. Financial incentives delivered at the point of care may act as cues for medication-taking behavior.

OBJECTIVES

The purpose of this study was to investigate patient preferences for specific structures of financial medication adherence incentives that could feasibly be delivered at the point of care.

METHODS

A discrete choice experiment (DCE) was performed using a national online survey. Study participants were adults who self-reported taking at least one prescription medication for one or more chronic conditions. Following an orthogonal design generated in SAS, the DCE included 32 paired-choice tasks. Data were analyzed using mixed logit models and stratified on participants' income level.

RESULTS

In the full cohort (n = 933), form of financial reward (such as gift-card or cash) was 1.02 times as important to participants as the probability of incentive receipt, 1.58 times as important as monetary value, and 1.93 times as important as timing of receipt. Participants were willing to give up $31.04 of an incentive's monetary value (95% CI = $27.11-$34.98) to receive the incentive 5 months sooner (1-month vs. 6-month time-lag); $60.79 (95% CI = $53.19-$68.39) for probability of receipt to increase from a 1 out of 100 chance to a 1 out of 20 chance; and $10.52 (95% CI = $6.46-$14.58) to receive an incentive in the form of a Visa® gift-card instead of grocery store voucher. These patterns of trade-offs between attributes were generally consistent among participants with lower and higher income.

CONCLUSIONS

Regardless of socioeconomic status, patient preferences for financial medication adherence incentives delivered at the point of care may be most heavily influenced by incentive form and probability of receipt. This has implications for designing medication adherence programs in terms of incentive sustainability, patient engagement, plan star ratings, and patient outcomes.

The role of a clinician amid the rise of mobile health technology

Mobile health (mHealth) interventions have demonstrated promise in improving outcomes by motivating patients to adopt and maintain healthy lifestyle changes as well as improve adherence to guideline-directed medical therapy. Early results combining behavioral economic strategies with mHealth delivery have demonstrated mixed results. In reviewing these studies, we propose that the success of a mHealth intervention links more strongly with how well it connects patients back to routine clinical care, rather than its behavior modification technique in isolation. This underscores the critical role of clinician-patient partnerships in the design and delivery of such interventions, while also raising important questions regarding long-term sustainability and scalability. Further exploration of our hypothesis may increase opportunities for multidisciplinary clinical teams to connect with and engage patients using mHealth technologies in unprecedented ways.

Mobile Health Intervention in the Maternal Care Pathway: Protocol for the Impact Evaluation of hAPPyMamma

Background

Mobile health (mHealth) has great potential to both improve the quality and efficiency of care and increase health literacy and empowerment of patient users. There are several studies related to the introduction of mHealth tools for supporting pregnancy and the postnatal period, with promising but not yet rigorously evaluated impacts. This article presents the protocol for evaluating an mHealth intervention (hAPPyMamma) applied in the maternal and child care pathway of a high-income country (in a pilot area of Tuscany Region, Italy).

Objective

The protocol describes hAPPyMamma and the methods for evaluating its impact, including the points of view of women and practitioners. The research hypothesis is that the use of hAPPyMamma will facilitate a more appropriate use of available services, a better care experience for women, and an improvement in the maternal competencies of the women using the app compared to the control group. The protocol also includes analysis of the organizational impact of the introduction of hAPPyMamma in the maternal pathway.

Methods

A pre-post quasiexperimental design with a control group is used to undertake difference-in-differences analysis for assessing the impact of the mHealth intervention from the mothers’ points of view. The outcome measures are improvement of maternal health literacy and empowerment as well as experience in the maternal care pathway of the control and intervention groups of sampled mothers. The organizational impact is evaluated through a quantitative and qualitative survey addressing professionals and managers of the maternal care pathway involved in the intervention.

Results

Following study recruitment, 177 women were enrolled in the control group and 150 in the intervention group, with a participation rate of 97%-98%. The response rate was higher in the control group than in the intervention group (96% vs 67%), though the intervention group had less respondent loss at the postintervention survey (10% compared to 33% of the control group). Data collection from the women was completed in April 2018, while that from professionals and managers is underway.

Conclusions

The study helps consolidate evidence of the utility of mHealth interventions for maternal and child care in developed countries. This paper presents a protocol for analyzing the potential role of hAPPyMamma as an effective mHealth tool for improving the maternal care pathway at individual and organizational levels and consequently helps to understand whether and how to scale up this intervention, with local, national, and international scopes of application.

International Registered Report Identifier (IRRID)

DERR1-10.2196/19073

Interventions to Improve Adherence to Cardiovascular Medication: What About Gender Differences? A Systematic Literature Review

BACKGROUND

Compared to men, women have lower treatment rates for cardiovascular disease (CVD), are at higher risk for medication non-adherence and have different reasons for being non-adherent. The aim of this study was to synthesize and evaluate gender-specific adherence-promoting interventions for cardiovascular medication and gender-specific effects of gender-neutral interventions.

METHODS

A systematic literature search was performed in PubMed, Embase, PsycINFO, CINAHL and Cochrane Library from January 2007 to October 2019. Intervention studies (with control group) aimed at improving cardiovascular medication adherence with minimally 14 weeks follow-up were included. Two reviewers independently screened titles and abstracts. Full text was obtained for selected abstracts and screened for final inclusion. Data extraction included gender-specific targeting or analysis.

RESULTS

The search identified 6502 citations. After screening title and abstract, full text was obtained from 127 potentially eligible articles. Ultimately, 11 articles were included that analyzed gender differences in gender-neutral interventions. Two reported a gender-specific intervention effect. Using an electronic reminder device, one study increased statin adherence in women. The other found a larger increase in adherence to CVD medication following telephone counseling for men than women. Nine studies did not identify a gender-specific effect.

CONCLUSION

Despite differences in levels of and reasons for non-adherence, most studies addressing adherence did not analyze potential differences in effect by gender. Moreover, none of the identified studies used gender-specific adherence promoting interventions. Increasing awareness about gender differences in adherence might lead to better tailoring of interventions to gender-specific needs and better results in improving adherence.

Effect of Patient Financial Incentives on Statin Adherence and Lipid Control: A Randomized Clinical Trial

IMPORTANCE

Financial incentives can improve medication adherence and cardiovascular disease risk, but the optimal design to promote sustained adherence after incentives are discontinued is unknown.

OBJECTIVE

To determine whether 6-month interventions involving different financial incentives to encourage statin adherence reduce low-density lipoprotein cholesterol (LDL-C) levels from baseline to 12 months.

DESIGN, SETTING, AND PARTICIPANTS

This 4-group, randomized clinical trial was conducted from August 2013 to July 2018 among several large US insurer or employer populations and the University of Pennsylvania Health System. The study population included adults with elevated risk of cardiovascular disease, suboptimal LDL-C control, and evidence of imperfect adherence to statin medication. Data analysis was performed from July 2017 to June 2019.

INTERVENTIONS

The interventions lasted 6 months during which all participants received daily medication reminders and an electronic pill bottle. Statin adherence was measured by opening the bottle. For participants randomized to the 3 intervention groups, adherence was rewarded with financial incentives. The sweepstakes group involved incentives for daily adherence. In the deadline sweepstakes group, incentives were reduced if participants were adherent only after a reminder. The sweepstakes plus deposit contract group split incentives between daily adherence and a monthly deposit reduced for each day of nonadherence.

MAIN OUTCOMES AND MEASURES

The primary outcome was change in LDL-C level from baseline to 12 months.

RESULTS

Among 805 participants randomized (199 in the simple daily sweepstakes group, 204 in the deadline sweepstakes group, 201 in the sweepstakes plus deposit contract group, and 201 in the control group), the mean (SD) age was 58.5 (10.3) years; 519 participants (64.5%) were women, 514 (63.9%) had diabetes, and 273 (33.9%) had cardiovascular disease. The mean (SD) baseline LDL-C level was 143.2 (42.5) mg/dL. Measured adherence at 6 months (defined as the proportion of 180 days with electronic pill bottle opening) in the control group (0.69; 95% CI, 0.66-0.72) was lower than that in the simple sweepstakes group (0.84; 95% CI, 0.81-0.87), the deadline sweepstakes group (0.86; 95% CI, 0.83-0.89), and the sweepstakes plus deposit contract group (0.87; 95% CI, 0.84-0.90) (P < .001 for each incentive group vs control). LDL-C levels were measured for 636 participants at 12 months. Mean LDL-C level reductions from baseline to 12 months were 33.6 mg/dL (95% CI, 28.4-38.8 mg/dL) in the control group, 32.4 mg/dL (95% CI, 27.3-37.6 mg/dL) in the sweepstakes group, 33.2 mg/dL (95% CI, 28.1-38.3 mg/dL) in the deadline sweepstakes group, and 36.5 mg/dL (95% CI, 31.3-41.7 mg/dL) in the sweepstakes plus deposit contract group (adjusted P > .99 for each incentive group vs control).

CONCLUSIONS AND RELEVANCE

Compared with the control group, different financial incentives improved measured statin adherence but not LDL-C levels. This result points to the importance of directly measuring health outcomes, rather than simply adherence, in trials aimed at improving health behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01798784.

Behavioral Economic Insights to Improve Medication Adherence in Adults with Chronic Conditions: A Scoping Review

BACKGROUND AND OBJECTIVE

Medication adherence is poor in patients with chronic conditions. Behavioral economic interventions may reduce biases that are associated with poor adherence. The objective of this review is to map the available evidence on behavioral economic interventions to improve medication adherence in adults with chronic conditions in high-income settings.

METHODS

We conducted a scoping review and reported the study using the Joanna Briggs Institute Reviewers' Manual and the PRISMA Extension for Scoping Review checklist. We searched PubMed, EMBASE, SCOPUS, PsycINFO, EconLit, and CINAHL from database inception to 29 August, 2018 for peer-reviewed studies and included a search of the gray literature. Data on study characteristics, study design, and study outcomes were extracted by one reviewer. Twenty-five percent of the studies were verified by a second reviewer.

RESULTS

Thirty-four studies, targeting diabetes mellitus, human immunodeficiency virus, and cardiovascular and renal diseases met our inclusion criteria. All but two studies were from the USA. The majority of interventions used financial incentives, often in conjunction with other behavioral economic concepts. Non-financial interventions included framing, social influences, reinforcement, and feedback. The effectiveness of interventions was mixed.

CONCLUSIONS

Behavioral economic informed interventions show promise in terms of improving medication adherence. However, there is no single simple intervention. This review highlighted the importance of targeting non-adherent patients, understanding their reasons for non-adherence, providing reminders and feedback to patients and physicians, and measuring clinical outcomes in addition to medication adherence. Further research in settings that differ from the US health system is needed.

Improving Patients' Medication Adherence and Outcomes in Nonhospital Settings Through eHealth: Systematic Review of Randomized Controlled Trials

Background

Electronic health (eHealth) refers to the use of information and communication technologies for health. It plays an increasingly important role in patients’ medication management.

Objective

To assess evidence on (1) whether eHealth for patients’ medication management can improve drug adherence and health outcomes in nonhospital settings and (2) which eHealth functions are commonly used and are effective in improving drug adherence.

Methods

We searched for randomized controlled trials (RCTs) on PubMed, MEDLINE, CINAHL, EMBASE, EmCare, ProQuest, Scopus, Web of Science, ScienceDirect, and IEEE Xplore, in addition to other published sources between 2000 and 2018. We evaluated the studies against the primary outcome measure of medication adherence and multiple secondary health care outcome measures relating to adverse events, quality of life, patient satisfaction, and health expenditure. The quality of the studies included was assessed using the Cochrane Collaboration’s Risk of Bias (RoB) tool.

Results

Our initial search yielded 9909 records, and 24 studies met the selection criteria. Of these, 13 indicated improvement in medication adherence at the significance level of P<.1 and 2 indicated an improved quality of life at the significance level of P<.01. The top 3 functions that were employed included mechanisms to communicate with caregivers, monitoring health features, and reminders and alerts. eHealth functions of providing information and education, and dispensing treatment and administration support tended to favor improved medication adherence outcomes (Fisher exact test, P=.02). There were differences in the characteristics of the study population, intervention design, functionality provided, reporting adherence, and outcome measures among the included studies. RoB assessment items, including blinding of outcome assessment and method for allocation concealment, were not explicitly reported in a large number of studies.

Conclusions

All the studies included were designed for patient home-based care application and provided a mechanism to communicate with caregivers. A targeted study population such as older patients should be considered to maximize the public health impact on the self-management of diseases.

Trial Registration

International Prospective Register of Systematic Reviews (PROSPERO) CRD42018096627; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=96627

Social Support and Antibody Responses to Vaccination: A Meta-Analysis

BACKGROUND

Social support and social integration have been linked to lower rates of morbidity and mortality. However, the biological mechanisms responsible for such links need greater attention. Vaccine paradigms provide an integrative window into immune system involvement in the protective influence of social support/integration.

PURPOSE

The main aim of this article was to conduct a meta-analytic review of the association between social support/social integration and antibody responses to vaccines. Exploratory analyses also examined effect sizes and confidence intervals as a function of several factors to inform future research.

METHOD

A literature search was conducted using the ancestry approach and with PsycInfo, Medline, and the Psychology and Behavioral Science Collection by crossing the exact keywords of social support or social integration with vaccine or antibodies. The review identified nine studies with a total of 672 participants.

RESULTS

The omnibus meta-analysis showed that social support/social integration was related to higher antibody levels following vaccination, but the average effect size was small and the lower bound of the confidence interval included zero (Zr = 0.06 [-.04, .15]). These results did not appear to differ much as a function of the operationalization of social relationships, participant age, or follow-up period, although effect sizes appeared larger for studies using a primary antigen.

CONCLUSIONS

These data provide some evidence that social support may be linked to antibody responses to vaccines. However, effect sizes are mostly small and zero overall effect cannot be ruled out. Future studies would benefit from larger sample sizes and greater consideration of methodological issues associated with secondary immune responses to antigen.