Mobile technology for medication adherence in people with mood disorders: A systematic review

The Minimum Feature Set for Designing Mobile Apps to Support Bipolar Disorder-Affected Patients: Proposal of Essential Functions and Requirements

Research conducted on mobile apps providing mental health services has concluded that patients with mental disorders tend to use such apps to maintain mental health balance technology may help manage and monitor issues like bipolar disorder (BP). This study was conducted in four steps to identify the features of designing a mobile application for BP-affected patients including (1) a literature search, (2) analyzing existing mobile apps to examine their efficiency, (3) interviewing patients affected with BP to discover their needs, and 4) exploring the points of view of experts using a dynamic narrative survey. Literature search and mobile app analysis resulted in 45 features, which were later reduced to 30 after the experts were surveyed about the project. The features included the following: mood monitoring, sleep schedule, energy level evaluation, irritability, speech level, communication, sexual activity, self-confidence level, suicidal thoughts, guilt, concentration level, aggressiveness, anxiety, appetite, smoking or drug abuse, blood pressure, the patient's weight and the side effects of medication, reminders, mood data scales, diagrams or charts of the collected data, referring the collected data to a psychologist, educational information, sending feedbacks to patients using the application, and standard tests for mood assessment. The first phase of analysis should consider an expert and patient view survey, mood and medication tracking, as well as communication with other people in the same situation are the most features to be considered. The present study has identified the necessity of apps intended to manage and monitor bipolar patients to maximize efficiency and minimize relapse and side effects.

Effectiveness of interventions to improve medication adherence in adults with depressive disorders: a meta-analysis

BACKGROUND

Non-adherence to medication is a major obstacle in the treatment of depressive disorders. We systematically reviewed the literature to evaluate the effectiveness of interventions aimed at improving adherence to medication among adults with depressive disorders with emphasis on initiation and implementation phase.

METHODS

We searched Medline, EMBASE, The Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, Social Science Citation Index and Science Citation Index for randomized or non-randomized controlled trials up to January 2022. Risk of bias was assessed using the criteria of the Cochrane Collaboration. Meta-analyses, cumulative and meta-regression analyses for adherence were conducted.

RESULTS

Forty-six trials (n = 24,324) were included. Pooled estimate indicates an increase in the probability of adherence to antidepressants at 6 months with the different types of interventions (OR 1.33; 95% CI: 1.09 to 1.62). The improvement in adherence is obtained from 3 months (OR 1.62, 95% CI: 1.25 to 2.10) but it is attenuated at 12 months (OR 1.25, 95% CI: 1.02 to 1.53). Selected articles show methodological differences, mainly the diversity of both the severity of the depressive disorder and intervention procedures. In the samples of these studies, patients with depression and anxiety seem to benefit most from intervention (OR 2.77, 95% CI: 1.74 to 4.42) and collaborative care is the most effective intervention to improve adherence (OR 1.88, 95% CI: 1.40 to 2.54).

CONCLUSIONS

Our findings indicate that interventions aimed at improving adherence to medication among adults with depressive disorders are effective up to six months. However, the evidence on the effectiveness of long-term adherence is insufficient and supports the need for further research efforts.

TRIAL REGISTRATION

International Prospective Register for Systematic Reviews (PROSPERO) number: CRD42017065723 .

Web-Based and mHealth Interventions for Intimate Partner Violence Victimization Prevention: A Systematic Review

Mobile health (mHealth) technologies are increasingly used across health programming including intimate partner violence (IPV) prevention to optimize screening, educational outreach, and linkages to care via telehealth. We systematically evaluated current web-based and mHealth interventions, which include web- or mobile-based delivery methods for primary, secondary, and tertiary IPV victimization prevention. We searched MEDLINE/PubMed, Embase, CINAHL, PsycINFO, Open Grey, and Google Scholar for empirical studies published 1998-2019. Studies were included if they considered empirical data, participants in adult romantic relationships, IPV as a primary or secondary outcome, and an mHealth component. The Mixed Methods Appraisal Tool was used to record critical ratings of quality among studies selected for inclusion. We assessed variation in targeted populations, types of IPV addressed, and mHealth approaches used. Of 133 studies identified for full-text review, 31 were included. Computer-based screening with or without integrated education was the most common mHealth approach (n = 8, 26%), followed by safety decision aids (n = 7, 23%). Feasibility and acceptability were found to be generally high where assessed (23% of studies, n = 7). There was limited evidence around whether mHealth interventions better addressed population needs compared to conventional interventions. mHealth tools for IPV prevention are especially acceptable in health-care settings, on mobile phone platforms, or when connecting victims to health care. Despite enthusiasm in pilot projects, evidence for efficacy compared to conventional IPV prevention approaches is limited. A major strength of mHealth IPV prevention programming is the ability to tailor interventions to individual victim needs without extensive human resource expenditure by providers.

Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review

Background

Accumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking.

Objective

The aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic.

Methods

A rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic.

Results

Overall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited.

Conclusions

There is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.

Investigator Experiences Using Mobile Technologies in Clinical Research: Qualitative Descriptive Study

Background

The successful adoption of mobile technology for use in clinical trials relies on positive reception from key stakeholders, including clinical investigators; however, little information is known about the perspectives of investigators using mobile technologies in clinical trials.

Objective

The aim of this study was to seek investigators’ insights on the advantages and challenges of mobile clinical trials (MCTs); site-level budgetary, training, and other support needs necessary to adequately prepare for and implement MCTs; and the advantages and disadvantages for trial participants using mobile technologies in clinical trials.

Methods

Using a qualitative descriptive study design, we conducted in-depth interviews with investigators involved in the conduct of MCTs. Data were analyzed using applied thematic analysis.

Results

We interviewed 12 investigators who represented a wide variety of clinical specialties and reported using a wide range of mobile technologies. Investigators most commonly cited 3 advantages of MCTs over traditional clinical trials: more streamlined study operations, remote data capture, and improvement in the quality of studies and data collected. Investigators also reported that MCTs can be designed around the convenience of trial participants, and individuals may be more willing to participate in MCTs because they can take part from their homes. In addition, investigators recognized that MCTs can also involve additional burden for participants and described that operational challenges, technology adoption barriers, uncertainties about data quality, and time burden made MCTs more challenging than traditional clinical trials. Investigators stressed that additional training and dedicated staff effort may be needed to select a particular technology for use in a trial, helping trial participants learn and use the technology, and for staff troubleshooting the technology. Investigators also expressed that sharing data collected in real time with investigators and trial participants is an important aspect of MCTs that warrants consideration and potentially additional training and education.

Conclusions

Investigator perspectives can inform the use of mobile technologies in future clinical trials by proactively identifying and addressing potential challenges.

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.

The emergence of digital mental health in low-income and middle-income countries: A review of recent advances and implications for the treatment and prevention of mental disorders

In low-income and middle-income countries (LMICs), emerging digital mental health interventions should be accompanied by regular and comprehensive assessment of available scientific evidence. This review aims to support efforts to monitor progress in digital mental health research, ensuring new evidence can guide researchers, clinicians, policymakers and program managers positioned to adopt and implement these digitally-enabled treatments. In accordance with PRISMA guidelines, an electronic database search from 2016 to 2020 yielded 37 digital intervention studies for detection, diagnosis, prevention, treatment, and/or management of a broad range of mental disorders in 13 LMICs. This date range was selected to update previous reviews. Most studies involved online interventions and many reported feasibility and acceptability, reflected by participant satisfaction or program adherence. About half the studies (N = 23) reported clinical benefits based on changes in mental health. For depression and mood disorders, some digital interventions showed improvements in depressive symptoms, quality of life, treatment adherence, and recovery. However, sample sizes were small and studies focused primarily on adults. Further limiting generalizability was the lack of consistency in clinical assessment and measurement tools between studies. No studies reported worsening symptoms, negative acceptability or dissatisfaction with digital interventions, suggesting possible publication bias. While digital interventions show promise, it remains difficult to conclude that digital interventions are effective from these studies, as it is prudent to exercise caution before drawing conclusions about clinical effectiveness. This review reflects continued growth in digital mental health research in LMICs and further highlights the need for rigorous evaluation of effectiveness and cost-effectiveness.

Interventions to improve medication adherence in mental health: the update of a systematic review of cost-effectiveness

OBJECTIVE

Medication non-adherence in mental health problems has social and economic costs. The objective of the study was to review the cost-effectiveness of interventions to enhance medication adherence in patients with mental health problems.

METHODS

The update of a previous systematic review was performed. Databases were searched in June 2019: MEDLINE, PSYCINFO, EMBASE, CINAHL, CRD, WOS. Cost-effectiveness studies comparing an intervention to improve the medication adherence with other interventions/usual care in adults with mental health problems were included. Data were extracted, methodological quality of the studies was assessed and a narrative synthesis was performed.

RESULTS

Nine studies were included in the review. The interventions that showed medication adherence increase were: a financial incentive when depot injection was taken by patients with psychotic disorders, a value-based benefit design policy including copayment and counselling in a company setting, and a medication treatment decision supported by a pharmacogenetic test. The other studies (coaching by pharmacists; a psychological and educational intervention at health care centres) did not find differences between groups. No study found cost differences between alternatives.

CONCLUSIONS

Interventions to improve medication adherence in adults with mental health problems could be cost-effective, especially those based on financial incentives, although more research is needed. KEYPOINTS There are several types of interventions designed to enhance medication adherence in patients with mental health problems. Few of them have demonstrated cost-effectiveness. Two studies found that a financial incentive per depot injection in patients with psychotic disorders improved the medication adherence. Two other studies found improvement in adherence due to two specific interventions: a value-based benefit design policy in a company setting and a pharmacogenetic test supporting the medication treatment decision. No study found differences in costs between the intervention and the comparator. More research is needed to implement cost-effective interventions.

Medication adherence in patients with mental illness and recent homelessness: contributing factors and perceptions on mobile technology use

OBJECTIVES

The primary objective was to determine medication-taking behaviours and factors influencing adherence in patients with mental illness and recent homelessness. Secondary objectives were to explore patients' perceptions on mobile technology use to support adherence.

METHODS

A constructivist approach and qualitative description method was used. The sample population consisted of patients with recent homelessness and mental illness affiliated with a community-based outreach programme in Canada. Participants were purposefully selected; semi-structured interviews were conducted to elicit information on medication-taking strategies and mobile technology to support adherence. A standardized questionnaire collected demographic and medical information; the Medication Adherence Rating Scale (MARS) was used to evaluate self-reported adherence. Questionnaire data were analysed using summary descriptive statistics. Interview data were subject to qualitative content analysis.

KEY FINDINGS

Fifteen participants with a mean age of 44 years were included. The mean MARS score ± standard deviation was 7.3 ± 1.5. Themes arising from the data included patient factors (i.e. insight, attitudes towards medications, coping strategies) and external factors (i.e. therapeutic alliance, family support that impacted adherence) and technology use and health. Eight participants (53%) had access to a mobile phone. There was a moderate interest in the use of mobile technology to support adherence, with cost and technology literacy identified as barriers.

CONCLUSION

External supports and individual medication management strategies were important in supporting medication adherence in this patient group. Perceived need for mobile technology, in addition to existing supports for adherence, was not high. Challenges accessing and maintaining consistent mobile technology and individual preferences should be considered when developing mobile technology-based interventions.

Characteristics of Future Models of Integrated Outpatient Care

Replacement of fee-for-service with capitation arrangements, forces physicians and institutions to minimize health care costs, while maintaining high-quality care. In this report we described how patients and their families (or caregivers) can work with members of the medical care team to achieve these twin goals of maintaining-and perhaps improving-high-quality care and minimizing costs. We described how increased self-management enables patients and their families/caregivers to provide electronic patient-reported outcomes (i.e., symptoms, events) (ePROs), as frequently as the patient or the medical care team consider appropriate. These capabilities also allow ongoing assessments of physiological measurements/phenomena (mHealth). Remote surveillance of these communications allows longer intervals between (fewer) patient visits to the medical-care team, when this is appropriate, or earlier interventions, when it is appropriate. Systems are now available that alert medical care providers to situations when interventions might be needed.

Technological Interventions for Medication Adherence in Adult Mental Health and Substance Use Disorders: A Systematic Review

BACKGROUND

Medication adherence is critical to the effectiveness of psychopharmacologic therapy. Psychiatric disorders present special adherence considerations, notably an altered capacity for decision making and the increased street value of controlled substances. A wide range of interventions designed to improve adherence in mental health and substance use disorders have been studied; recently, many have incorporated information technology (eg, mobile phone apps, electronic pill dispensers, and telehealth). Many intervention components have been studied across different disorders. Furthermore, many interventions incorporate multiple components, making it difficult to evaluate the effect of individual components in isolation.

OBJECTIVE

The aim of this study was to conduct a systematic scoping review to develop a literature-driven, transdiagnostic taxonomic framework of technology-based medication adherence intervention and measurement components used in mental health and substance use disorders.

METHODS

This review was conducted based on a published protocol (PROSPERO: CRD42018067902) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review guidelines. We searched 7 electronic databases: MEDLINE, EMBASE, PsycINFO, the Cochrane Central Register of Controlled Trials, Web of Science, Engineering Village, and ClinicalTrials.gov from January 2000 to September 2018. Overall, 2 reviewers independently conducted title and abstract screens, full-text screens, and data extraction. We included all studies that evaluate populations or individuals with a mental health or substance use disorder and contain at least 1 technology-delivered component (eg, website, mobile phone app, biosensor, or algorithm) designed to improve medication adherence or the measurement thereof. Given the wide variety of studied interventions, populations, and outcomes, we did not conduct a risk of bias assessment or quantitative meta-analysis. We developed a taxonomic framework for intervention classification and applied it to multicomponent interventions across mental health disorders.

RESULTS

The initial search identified 21,749 results; after screening, 127 included studies remained (Cohen kappa: 0.8, 95% CI 0.72-0.87). Major intervention component categories include reminders, support messages, social support engagement, care team contact capabilities, data feedback, psychoeducation, adherence-based psychotherapy, remote care delivery, secure medication storage, and contingency management. Adherence measurement components include self-reports, remote direct visualization, fully automated computer vision algorithms, biosensors, smart pill bottles, ingestible sensors, pill counts, and utilization measures. Intervention modalities include short messaging service, mobile phone apps, websites, and interactive voice response. We provide graphical representations of intervention component categories and an element-wise breakdown of multicomponent interventions.

CONCLUSIONS

Many technology-based medication adherence and monitoring interventions have been studied across psychiatric disease contexts. Interventions that are useful in one psychiatric disorder may be useful in other disorders, and further research is necessary to elucidate the specific effects of individual intervention components. Our framework is directly developed from the substance use disorder and mental health treatment literature and allows for transdiagnostic comparisons and an organized conceptual mapping of interventions.

Recent developments in the use of smartphone interventions for mental health

PURPOSE OF REVIEW

The purpose of this update is to provide an overview of the breadth of research studies published from April 2017 to April 2018 on mobile-based interventions for mental health, with a special emphasis on smartphone-based interventions.

RECENT FINDINGS

Several studies during the review period have described the process of applying user-centred design in the development of mental health apps and novel approaches to enhance user-engagement. Studies on consumer perspectives indicate largely positive findings about open-ness to utilize mental health apps. There is a scarcity of similar studies on health providers. Efficacy studies have provided evidence for apps for a variety of psychiatric disorders. There are fewer studies on preventive and promotive interventions. Although a plethora of mental health apps is available for public, most have not undergone scientific evaluation. Many well researched apps are not accessible to public. The potential of smartphone technology in enhancing healthcare service delivery in low-resource settings has also been examined in a few studies.

SUMMARY

Evidence for acceptability, feasibility and efficacy of mobile-based mental health interventions for facilitating recovery is on the rise. More research is needed on implementation and integration of these interventions in diverse real-world clinical and community contexts.

Patient-Centered eHealth Interventions for Children, Adolescents, and Adults With Sickle Cell Disease: Systematic Review

Background

Sickle cell disease is an inherited blood disorder that affects over 100,000 Americans. Sickle cell disease–related complications lead to significant morbidity and early death. Evidence supporting the feasibility, acceptability, and efficacy of self-management electronic health (eHealth) interventions in chronic diseases is growing; however, the evidence is unclear in sickle cell disease.

Objective

We systematically evaluated the most recent evidence in the literature to (1) review the different types of technological tools used for self-management of sickle cell disease, (2) discover and describe what self-management activities these tools were used for, and (3) assess the efficacy of these technologies in self-management.

Methods

We reviewed literature published between 1995 and 2016 with no language limits. We searched MEDLINE, EMBASE, CINAHL, PsycINFO, and other sources. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Two independent reviewers screened titles and abstracts, assessed full-text articles, and extracted data from articles that met inclusion criteria. Eligible studies were original research articles that included texting, mobile phone–based apps, or other eHealth interventions designed to improve self-management in pediatric and adult patients with sickle cell disease.

Results

Of 1680 citations, 16 articles met all predefined criteria with a total of 747 study participants. Interventions were text messaging (4/16, 25%), native mobile apps (3/16, 19%), Web-based apps (5/16, 31%), mobile directly observed therapy (2/16, 13%), internet-delivered cognitive behavioral therapy (2/16, 13%), electronic pill bottle (1/16, 6%), or interactive gamification (2/16, 13%). Interventions targeted monitoring or improvement of medication adherence (5/16, 31%); self-management, pain reporting, and symptom reporting (7/16, 44%); stress, coping, sleep, and daily activities reporting (4/16, 25%); cognitive training for memory (1/16, 6%); sickle cell disease and reproductive health knowledge (5/16, 31%); cognitive behavioral therapy (2/16, 13%); and guided relaxation interventions (1/16, 6%). Most studies (11/16, 69%) included older children or adolescents (mean or median age 10-17 years; 11/16, 69%) and 5 included young adults (≥18 years old) (5/16, 31%). Sample size ranged from 11 to 236, with a median of 21 per study: <20 in 6 (38%), ≥20 to <50 in 6 (38%), and >50 participants in 4 studies (25%). Most reported improvement in self-management–related outcomes (15/16, 94%), as well as high satisfaction and acceptability of different study interventions (10/16, 63%).

Conclusions

Our systematic review identified eHealth interventions measuring a variety of outcomes, which showed improvement in multiple components of self-management of sickle cell disease. Despite the promising feasibility and acceptability of eHealth interventions in improving self-management of sickle cell disease, the evidence overall is modest. Future eHealth intervention studies are needed to evaluate their efficacy, effectiveness, and cost effectiveness in promoting self-management in patients with sickle cell disease using rigorous methods and theoretical frameworks with clearly defined clinical outcomes.