Feasibility of an eHealth service to support collaborative depression care: results of a pilot study

Remote measurement based care (RMBC) interventions for mental health-Protocol of a systematic review and meta-analysis

BACKGROUND

Poor management of mental illnesses is associated with lower treatment adherence, chronification, avoidable re-hospitalisations, and high costs. Remote measurement based care (RMBC) interventions have gained increasing relevance due to its potential in providing a comprehensive and patient-centric approach to mental health management.

OBJECTIVES

The systematic review and meta-analysis aims to provide a comprehensive overview and analysis of existing evidence on the use of RMBC for patients with mental illness and to examine the effectiveness of RMBC interventions in alleviating disorder-specific symptoms, reducing relapse and improving recovery-oriented outcomes, global functioning, and quality of life.

METHODS AND ANALYSIS

Our multidisciplinary research team will develop a comprehensive search strategy, adapted to each electronic database (PubMed, Medline, Embase, and PsychINFO) to be examined systematically. Studies with patients formally diagnosed by the International Classification of Diseases or the Diagnostic and Statistical Manual of Mental Disorders which include assessment of self-reported psychiatric symptoms will be included. Publications will be reviewed by teams of independent researchers. Quality of studies will be assessed using the Cochrane Collaboration's tool for assessing risk of bias. Outcomes cover symptom-focused or disease-specific outcomes, relapse, recovery-focused outcomes, global functioning, quality of life and acceptability of the intervention. Further data that will be extracted includes study characteristics, target population, intervention, and tracking characteristics. Data will be synthesised qualitatively, summarising findings of the systematic review. Randomised controlled trials (RCTs) will be considered for meta-analysis if data is found comparable in terms of mental illness, study design and outcomes. Cumulative evidence will be evaluated according to the Grading of Recommendations Assessment, Development and Evaluation framework.

TRIAL REGISTRATION

Trial registration number: PROSPERO CRD42022356176.

Eliciting Depression Patients' Preferences for Medication Management: A Protocol for Discrete Choice Experiment

Introduction

Depression threatens people's lives and imposes huge economic burden. Antidepressant therapy is the first-line treatment for depression, and patient adherence to medication is the key to successful treatment. Depression patients have poor medication adherence, which leads to failure of depression management and significantly poorer clinical outcomes. Incorporating patient preferences into clinical decisions can improve uptake rates, optimize treatment adherence. A discrete choice experiment (DCE) can elicit and quantify individual preferences. Previous DCE studies were conducted in developed countries and ignored the influences of factors other than the medication. This paper outlines an ongoing DCE that aims to (1) explore medication-management-related characteristics that may affect depression patients' adherence to antidepressant, (2) elicit how depression patients consider the trade-offs among different medication managements.

Methods

The six attributes and their levels were developed through a literature review, semi-structured interviews and experts and focus group discussions. A fractional factorial design in the software Ngene 1.2 version was used to generate 36 choice sets, and they were divided into 3 blocks. A mixed logit model will be used to explore the patients' preferences, willingness to pay and uptake rate of depression patients for medication management attributes.

Results

The final questionnaire consists of three parts. The first is the introduction, which introduces the purpose of the study and the requirements of completing the questionnaire. This was followed by a general information questionnaire, which included sociodemographic characteristics. The last part is DCE tasks, which include 13 DCE choice sets, and each choice set include two alternative and one "opt-out" option. The pilot-test results showed the questionnaire was easy to understand and could be used in formal surveys.

Conclusion

Our study shows how the development process of the study can be conducted and reported systematically and rigorously according to the theoretical foundation and design principles in DCE.

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 .

Digital and Mobile Health Technology in Collaborative Behavioral Health Care: Scoping Review

BACKGROUND

The collaborative care model (CoCM) is a well-established system of behavioral health care in primary care settings. There is potential for digital and mobile technology to augment the CoCM to improve access, scalability, efficiency, and clinical outcomes.

OBJECTIVE

This study aims to conduct a scoping review to synthesize the evidence available on digital and mobile health technology in collaborative care settings.

METHODS

This review included cohort and experimental studies of digital and mobile technologies used to augment the CoCM. Studies examining primary care without collaborative care were excluded. A literature search was conducted using 4 electronic databases (MEDLINE, Embase, Web of Science, and Google Scholar). The search results were screened in 2 stages (title and abstract screening, followed by full-text review) by 2 reviewers.

RESULTS

A total of 3982 nonduplicate reports were identified, of which 20 (0.5%) were included in the analysis. Most studies used a combination of novel technologies. The range of digital and mobile health technologies used included mobile apps, websites, web-based platforms, telephone-based interactive voice recordings, and mobile sensor data. None of the identified studies used social media or wearable devices. Studies that measured patient and provider satisfaction reported positive results, although some types of interventions increased provider workload, and engagement was variable. In studies where clinical outcomes were measured (7/20, 35%), there were no differences between groups, or the differences were modest.

CONCLUSIONS

The use of digital and mobile health technologies in CoCM is still limited. This study found that technology was most successful when it was integrated into the existing workflow without relying on patient or provider initiative. However, the effect of digital and mobile health on clinical outcomes in CoCM remains unclear and requires additional clinical trials.

Characteristics of Mobile Health Platforms for Depression and Anxiety: Content Analysis Through a Systematic Review of the Literature and Systematic Search of Two App Stores

Background

Mobile health (mHealth) platforms show promise in the management of mental health conditions such as anxiety and depression. This has resulted in an abundance of mHealth platforms available for research or commercial use.

Objective

The objective of this review is to characterize the current state of mHealth platforms designed for anxiety or depression that are available for research, commercial use, or both.

Methods

A systematic review was conducted using a two-pronged approach: searching relevant literature with prespecified search terms to identify platforms in published research and simultaneously searching 2 major app stores—Google Play Store and Apple App Store—to identify commercially available platforms. Key characteristics of the mHealth platforms were synthesized, such as platform name, targeted condition, targeted group, purpose, technology type, intervention type, commercial availability, and regulatory information.

Results

The literature and app store searches yielded 169 and 179 mHealth platforms, respectively. Most platforms developed for research purposes were designed for depression (116/169, 68.6%), whereas the app store search reported a higher number of platforms developed for anxiety (Android: 58/179, 32.4%; iOS: 27/179, 15.1%). The most common purpose of platforms in both searches was treatment (literature search: 122/169, 72.2%; app store search: 129/179, 72.1%). With regard to the types of intervention, cognitive behavioral therapy and referral to care or counseling emerged as the most popular options offered by the platforms identified in the literature and app store searches, respectively. Most platforms from both searches did not have a specific target age group. In addition, most platforms found in app stores lacked clinical and real-world evidence, and a small number of platforms found in the published research were available commercially.

Conclusions

A considerable number of mHealth platforms designed for anxiety or depression are available for research, commercial use, or both. The characteristics of these mHealth platforms greatly vary. Future efforts should focus on assessing the quality—utility, safety, and effectiveness—of the existing platforms and providing developers, from both commercial and research sectors, a reporting guideline for their platform description and a regulatory framework to facilitate the development, validation, and deployment of effective mHealth platforms.

Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Background

Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions.

Objective

This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs.

Methods

A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included.

Results

A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health.

Conclusions

Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.

Transforming Population-Based Depression Care: a Quality Improvement Initiative Using Remote, Centralized Care Management

INTRODUCTION

With the growing prevalence of value-based contracts, health systems are incentivized to consider population approaches to service delivery, particularly for chronic conditions like depression. To this end, UW Medicine implemented the Depression-Population Approach to Health (PATH) program in primary care (PC) as part of a system-wide Center for Medicare and Medicaid Innovation (CMMI) quality improvement (QI) initiative.

AIM

To examine the feasibility of a pilot PATH program and its impact on clinical and process-of-care outcomes.

SETTING

A large, diverse, geographically disparate academic health system in Western Washington State including 28 PC clinics across five networks.

PROGRAM DESCRIPTION

The PATH program was a population-level, centralized, measurement-based care intervention that utilized a clinician to provide remote monitoring of treatment progress via chart review and facilitate patient engagement when appropriate. The primary goals of the program were to improve care engagement and increase follow-up PHQ-9 assessments for patients with depression and elevated initial PHQ-9 scores.

PROGRAM EVALUATION

We employed a prospective, observational study design, including commercially insured adult patients with new depression diagnoses and elevated initial PHQ-9 scores. The pilot intervention group, consisting of accountable care network (ACN) self-enrollees (N = 262), was compared with a similar commercially insured cohort (N = 2527) using difference-in-differences analyses adjusted for patient comorbidities, initial PHQ-9 score, and time trends. The PATH program was associated with three times the odds of PHQ-9 follow-up (OR 3.28, 95% CI 1.79-5.99), twice the odds of a follow-up PC clinic visit (OR 1.74, 95% CI 0.99-3.08), and twice the odds of treatment response, defined as reduction in PHQ-9 score by ≥ 50% (OR 2.02, 95% CI 0.97-4.21).

DISCUSSION

Our results demonstrate that a centralized, remote care management initiative is both feasible and effective for large academic health systems aiming to improve depression outcome ascertainment, treatment engagement, and clinical care.

Encouraging Patient Engagement Behaviors from the Perspective of Functional Quality

Despite extensive research on how patient engagement behaviors (PEBs) are facilitated though explicit technical interventions in medical services, research on the encouragement of PEBs from the perspective of the service process is lacking. This study explores how functional quality dimensions (responsiveness, empathy, surroundings, and access) affect PEBs (compliance and loyalty) through a two-channel psychological mechanism (trust and satisfaction). This study tests the proposed model using survey data from two public hospitals in southeastern China and employs the partial least square (PLS) technique of structural equation modeling (SEM) to analyze the data. The results show that service providers’ responsiveness, empathy, and access affect patient compliance and loyalty through patient satisfaction; however, the effect of surroundings is not significant. The responsiveness and empathy of service staff affect PEBs through patient trust. Considering the high-contact professional nature of medical services, we call for more efforts toward improving service processes rather than simply relying on technical interventions. Specifically, hospitals and contact employees should devote time and effort to functional quality management in three dimensions, namely responsiveness, empathy, and access, to secure patient trust and satisfaction.

Strategies for engaging patients and families in collaborative care programs for depression and anxiety disorders: A systematic review

BACKGROUND

Patients and families are often referred to as important partners in collaborative mental health care (CMHC). However, how to meaningfully engage them as partners remains unclear. We aimed to identify strategies for engaging patients and families in CMHC programs for depression and anxiety disorders.

METHODS

We updated a Cochrane review of CMHC programs for depression and anxiety disorders. Searches were conducted in Cochrane CCDAN and CINAHL, complemented by additional database searches, trial registry searches, and cluster searches for 'sibling' articles. Coding and data extraction of engagement strategies was an iterative process guided by a conceptual framework. We used narrative synthesis and descriptive statistics to report on findings.

FINDINGS

We found 148 unique CMCH programs, described in 578 articles. Most programs (96%) featured at least one strategy for engaging patients or families. Programs adopted 15 different strategies overall, with a median of two strategies per program (range 0-9 strategies). The most common strategies were patient education (87% of programs) and self-management supports (47% of programs). Personalized care planning, shared decision making, and family or peer supports were identified in fewer than one third of programs.

LIMITATIONS

Our search strategy was designed to capture programs evaluated in clinical trials and so other innovative programs not studied in trials were likely missed.

CONCLUSION

Most CMHC programs for depression and anxiety disorders adopted a limited number of strategies to engage patients and families in their care. However, this review identifies numerous strategies that can be used to strengthen the patient- and family-centeredness of collaborative care.

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.

Evidence-Based Evaluation of eHealth Interventions: Systematic Literature Review

Background

Until now, the use of technology in health care was driven mostly by the assumptions about the benefits of electronic health (eHealth) rather than its evidence. It is noticeable that the magnitude of evidence of effectiveness and efficiency of eHealth is not proportionate to the number of interventions that are regularly conducted. Reliable evidence generated through comprehensive evaluation of eHealth interventions may accelerate the growth of eHealth for long-term successful implementation and help to experience eHealth benefits in an enhanced way.

Objective

This study aimed to understand how the evidence of effectiveness and efficiency of eHealth can be generated through evaluation. Hence, we aim to discern (1) how evaluation is conducted in distinct eHealth intervention phases, (2) the aspects of effectiveness and efficiency that are typically evaluated during eHealth interventions, and (3) how eHealth interventions are evaluated in practice.

Methods

A systematic literature review was conducted to explore the evaluation methods for eHealth interventions. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were followed. We searched Google Scholar and Scopus for the published papers that addressed the evaluation of eHealth or described an eHealth intervention study. A qualitative analysis of the selected papers was conducted in several steps.

Results

We intended to see how the process of evaluation unfolds in distinct phases of an eHealth intervention. We revealed that in practice and in several conceptual papers, evaluation is performed at the end of the intervention. There are some studies that discuss the importance of conducting evaluation throughout the intervention; however, in practice, we found no case study that followed this. For our second research question, we discovered aspects of efficiency and effectiveness that are proposed to be assessed during interventions. The aspects that were recurrent in the conceptual papers include clinical, human and social, organizational, technological, cost, ethical and legal, and transferability. However, the case studies reviewed only evaluate the clinical and human and social aspects. At the end of the paper, we discussed a novel approach to look into the evaluation. Our intention was to stir up a discussion around this approach with the hope that it might be able to gather evidence in a comprehensive and credible way.

Conclusions

The importance of evidence in eHealth has not been discussed as rigorously as have the diverse evaluation approaches and evaluation frameworks. Further research directed toward evidence-based evaluation can not only improve the quality of intervention studies but also facilitate successful long-term implementation of eHealth in general. We conclude that the development of more robust and comprehensive evaluation of eHealth studies or an improved validation of evaluation methods could ease the transferability of results among similar studies. Thus, the resources can be used for supplementary research in eHealth.

Measuring Psychiatric Symptoms Remotely: a Systematic Review of Remote Measurement-Based Care

PURPOSE OF REVIEW

This article systematically reviews studies examining remote measurement-based care (RMBC), defined as using technology to measure patients' psychiatric symptoms outside the context of a clinical encounter.

RECENT FINDINGS

Thirty-six studies were identified that measured patients' psychiatric symptoms remotely and provided feedback to treatment providers. The majority were single group designs. There was evidence supporting the short-term feasibility and acceptability of RMBC, although long-term sustainability was less clear. Thirteen randomized controlled trials were identified. RMBC was typically implemented as part of a multicomponent intervention (e.g., internet-based cognitive behavioral therapy with feedback to provider). Three studies experimentally isolated the clinical effects of RMBC, with two reporting no statistically significant differences between the RMBC and control conditions and one reporting greater symptom improvement associated with RMBC. RMBC appears feasible and acceptable and may be a promising intervention for improving mental health care, but additional experimental studies are needed.

Digital technologies for social inclusion of individuals with disabilities

Information technology can be an important facilitator of social inclusion for people with disabilities into society. However, the goals specified in this area by organizations such as the European Commission have not yet been achieved in their totality. The aim of this paper is to explore which types of information communication technology-based applications and/or digital services have been suggested to facilitate the social integration of people who suffer from different types of disabilities. We performed a literature review that included studies published during a period of 6 years (2010–2016). The results show that, in the data we have had access to, no concrete patterns can be identified regarding the type of technology or technological trends that can be used to support the social integration of individuals with disabilities. This literature review is of relevance to the identification of further research areas and to the identification of issues which have to be considered in the context of the development and implementation of technological innovations that are aimed at promoting or facilitating social inclusion of individuals with disabilities.

Patient Health Engagement (PHE) model in enhanced recovery after surgery (ERAS): monitoring patients' engagement and psychological resilience in minimally invasive thoracic surgery

In the last decade, the humanization of medicine has contributed to an important shift in medical paradigms (from a doctor-centered to a patient-centered approach to care). This paradigm shift promoted a greater acknowledgement of patient engagement as a crucial asset for healthcare due to its benefits on both clinical outcomes and healthcare sustainability. Particularly, patient engagement should be considered a vital parameter for the healthcare system as well as it is a marker of the patients' ability to be resilient to the illness experience and thus to be an effective manager of his/her own health after the diagnosis. For this reason, measuring and promoting patient engagement both in chronic and acute care is today a priority for healthcare systems all over the world. In this contribution, the authors propose the Patient Health Engagement (PHE) model and the PHE scale as scientific and reliable tools to orient clinical actions and organizational strategies based on the patient engagement score. Particularly, this work discusses the implication of the adoption of these scientific tools in the enhanced recovery after surgery (ERAS) experience and their potentialities for healthcare professionals working in thoracic surgery settings.

eHealth in integrated care programs for people with multimorbidity in Europe: Insights from the ICARE4EU project

INTRODUCTION

Care for people with multimorbidity requires an integrated approach in order to adequately meet their complex needs. In this respect eHealth could be of help. This paper aims to describe the implementation, as well as benefits and barriers of eHealth applications in integrated care programs targeting people with multimorbidity in European countries, including insights on older people 65+.

METHODS

Within the framework of the ICARE4EU project, in 2014, expert organizations in 24 European countries identified 101 integrated care programs based on selected inclusion criteria. Managers of these programs completed a related on-line questionnaire addressing various aspects including the use of eHealth. In this paper we analyze data from this questionnaire, in addition to qualitative information from six programs which were selected as 'high potential' for their innovative approach and studied in depth through site visits.

RESULTS

Out of 101 programs, 85 adopted eHealth applications, of which 42 focused explicitly on older people. In most cases Electronic Health Records (EHRs), registration databases with patients' data and tools for communication between care providers were implemented. Percentages were slightly higher for programs addressing older people. eHealth improves care integration and management processes. Inadequate funding mechanisms, interoperability and technical support represent major barriers.

CONCLUSION

Findings seems to suggest that eHealth could support integrated care for (older) people with multimorbidity.

Telepsychiatry as an Economically Better Model for Reaching the Unreached: A Retrospective Report from South India

AIM

In a resource-poor country such as India, telepsychiatry could be an economical method to expand health-care services. This study was planned to compare the costing and feasibility of three different service delivery models. The end user was a state-funded long-stay Rehabilitation Center (RC) for the homeless.

METHODOLOGY

Model A comprised patients going to a tertiary care center for clinical care, Model B was community outreach service, and Model C comprised telepsychiatry services. The costing included expenses incurred by the health system to complete a single consultation for a patient on an outpatient basis. It specifically excluded the cost borne by the care-receiver. No patients were interviewed for the study.

RESULTS

The RC had 736 inmates, of which 341 had mental illness of very long duration. On comparing the costing, Model A costed 6047.5 INR (100$), Model B costed 577.1 INR (9.1$), and Model C costed 137.2 INR (2.2$). Model C was found fifty times more economical when compared to Model A and four times more economical when compared to Model B.

CONCLUSION

Telepsychiatry services connecting tertiary center and a primary health-care center have potential to be an economical model of service delivery compared to other traditional ones. This resource needs to be tapped in a better fashion to reach the unreached.

Systematic review of patients' participation in and experiences of technology-based monitoring of mental health symptoms in the community

OBJECTIVES

To review systematically the literature on patients' experiences of, and participation in, technology-based monitoring of mental health symptoms. This practice was defined as patients monitoring their mental health symptoms, emotions or behaviours outside of routine clinical appointments by submitting symptom data using technology, with feedback arising from the data (for example, supportive messages or symptom summaries, being sent to the patient, clinician or carer).

DESIGN

Systematic review following PRISMA guidelines of studies evaluating technology-based symptom monitoring. Tools from narrative synthesis were used to analyse quantitative findings on participation rates and qualitative findings on patient views.

DATA SOURCES

PubMed, EMBASE, PsycINFO, BNI, CINAHL, Cochrane Registers and Web of Science electronic databases were searched using a combination of 'psychiatry', 'symptom monitoring' and 'technology' descriptors. A secondary hand search was performed in grey literature and references.

RESULTS

57 papers representing 42 studies met the inclusion criteria for the review. Technology-based symptom monitoring was used for a range of mental health conditions, either independently of a specific therapeutic intervention or as an integrated component of therapeutic interventions. The majority of studies reported moderate-to-strong rates of participation, though a third reported lower rates. Qualitative feedback suggests that acceptability of monitoring is related to perceived validity, ease of practice, convenient technology, appropriate frequency and helpfulness of feedback, as well as the impact of monitoring on participants' ability to manage health and personal relationships.

CONCLUSIONS

Such symptom monitoring practices appear to be well accepted and may be a feasible complement to clinical practice. However, there is limited availability of data and heterogeneity of studies. Future research should examine robustly patients' role in the development and evaluation of technology-based symptom monitoring in order to maximise its clinical utility.

Do Web-based Mental Health Literacy Interventions Improve the Mental Health Literacy of Adult Consumers? Results From a Systematic Review

BACKGROUND

Low levels of mental health literacy (MHL) have been identified as an important contributor to the mental health treatment gap. Interventions to improve MHL have used traditional media (eg, community talks, print media) and new platforms (eg, the Internet). Evaluations of interventions using conventional media show improvements in MHL improve community recognition of mental illness as well as knowledge, attitude, and intended behaviors toward people having mental illness. However, the potential of new media, such as the Internet, to enhance MHL has yet to be systematically evaluated.

OBJECTIVE

Study aims were twofold: (1) To systematically appraise the efficacy of Web-based interventions in improving MHL. (2) To establish if increases in MHL translated into improvement in individual health seeking and health outcomes as well as reductions in stigma toward people with mental illness.

METHODS

We conducted a systematic search and appraisal of all original research published between 2000 and 2015 that evaluated Web-based interventions to improve MHL. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were used to report findings.

RESULTS

Fourteen studies were included: 10 randomized controlled trials and 4 quasi-experimental studies. Seven studies were conducted in Australia. A variety of Web-based interventions were identified ranging from linear, static websites to highly interactive interventions such as social media games. Some Web-based interventions were specifically designed for people living with mental illness whereas others were applicable to the general population. Interventions were more likely to be successful if they included "active ingredients" such as a structured program, were tailored to specific populations, delivered evidenced-based content, and promoted interactivity and experiential learning.

CONCLUSIONS

Web-based interventions targeting MHL are more likely to be successful if they include active ingredients. Improvements in MHL see concomitant improvements in health outcomes, especially for individuals with mild to moderate depression. The most promising interventions suited to this cohort appear to be MoodGYM and BluePages, 2 interventions from Australia. However, the relationship between MHL and formal and informal help seeking is less clear; self-stigma appears to be an important mediator with results showing that despite improvements in MHL and community attitudes to mental illness, individuals with mental illness still seek help at relatively low rates. Overall, the Internet is a viable method to improve MHL. Future studies could explore how new technology interfaces (eg, mobile phones vs computers) can help improve MHL, mental health outcomes, and reduce stigma.

Mixing Online and Face-to-Face Therapy: How to Benefit From Blended Care in Mental Health Care

Blended care, a combination of online and face-to-face therapy, is increasingly being applied in mental health care to obtain optimal benefit from the advantages these two treatment modalities have. Promising results have been reported, but a variety in descriptions and ways of operationalizing blended care exists. Currently, what type of "blend" works for whom, and why, is unclear. Furthermore, a rationale for setting up blended care is often lacking. In this viewpoint paper, we describe postulates for blended care and provide an instrument (Fit for Blended Care) that aims to assist therapists and patients whether and how to set up blended care treatment. A review of the literature, two focus groups (n=5 and n=5), interviews with therapists (n=14), and interviews with clients (n=2) were conducted to develop postulates of eHealth and blended care and an instrument to assist therapists and clients in setting up optimal blended care. Important postulates for blended care are the notion that both treatment modalities should complement each other and that set up of blended treatment should be based on shared decision making between patient and therapist. The "Fit for Blended Care" instrument is presented which addresses the following relevant themes: possible barriers to receiving blended treatment such as the risk of crisis, issues in communication (at a distance), as well as possible facilitators such as social support. More research into the reasons why and for whom blended care works is needed. To benefit from blended care, face-to-face and online care should be combined in such way that the potentials of both treatment modalities are used optimally, depending on patient abilities, needs, and preferences. To facilitate the process of setting up a personalized blended treatment, the Fit for Blended Care instrument can be used. By applying this approach in research and practice, more insight into the working mechanisms and optimal (personal) "blends" of online and face-to-face therapy becomes within reach.

The Impact of Information Technology on Patient Engagement and Health Behavior Change: A Systematic Review of the Literature

Background

Advancements in information technology (IT) and its increasingly ubiquitous nature expand the ability to engage patients in the health care process and motivate health behavior change.

Objective

Our aim was to systematically review the (1) impact of IT platforms used to promote patients’ engagement and to effect change in health behaviors and health outcomes, (2) behavior theories or models applied as bases for developing these interventions and their impact on health outcomes, (3) different ways of measuring health outcomes, (4) usability, feasibility, and acceptability of these technologies among patients, and (5) challenges and research directions for implementing IT platforms to meaningfully impact patient engagement and health outcomes.

Methods

PubMed, Web of Science, PsycINFO, and Google Scholar were searched for studies published from 2000 to December 2014. Two reviewers assessed the quality of the included papers, and potentially relevant studies were retrieved and assessed for eligibility based on predetermined inclusion criteria.

Results

A total of 170 articles met the inclusion criteria and were reviewed in detail. Overall, 88.8% (151/170) of studies showed positive impact on patient behavior and 82.9% (141/170) reported high levels of improvement in patient engagement. Only 47.1% (80/170) referenced specific behavior theories and only 33.5% (57/170) assessed the usability of IT platforms. The majority of studies used indirect ways to measure health outcomes (65.9%, 112/170).

Conclusions

In general, the review has shown that IT platforms can enhance patient engagement and improve health outcomes. Few studies addressed usability of these interventions, and the reason for not using specific behavior theories remains unclear. Further research is needed to clarify these important questions. In addition, an assessment of these types of interventions should be conducted based on a common framework using a large variety of measurements; these measurements should include those related to motivation for health behavior change, long-standing adherence, expenditure, satisfaction, and health outcomes.

eHealth for Patient Engagement: A Systematic Review

eHealth interventions are recognized to have a tremendous potential to promote patient engagement. To date, the majority of studies examine the efficacy of eHealth in enhancing clinical outcomes without focusing on patient engagement in its specificity. This paper aimed at reviewing findings from the literature about the use of eHealth in engaging patients in their own care process. We undertook a comprehensive literature search within the peer-reviewed international literature. Eleven studies met the inclusion criteria. eHealth interventions reviewed were mainly devoted to foster only partial dimensions of patient engagement (i.e., alternatively cognitive, emotional or behavioral domains related to healthcare management), thus failing to consider the complexity of such an experience. This also led to a great heterogeneity of technologies, assessed variables and achieved outcomes. This systematic review underlines the need for a more holistic view of patient needs to actually engage them in eHealth interventions and obtaining positive outcomes. In this sense, patient engagement constitute a new frontiers for healthcare models where eHealth could maximize its potentialities.

Smartphone-Supported versus Full Behavioural Activation for Depression: A Randomised Controlled Trial

BACKGROUND

There is need for more cost and time effective treatments for depression. This is the first randomised controlled trial in which a blended treatment--including four face-to-face sessions and a smartphone application--was compared against a full behavioural treatment. Hence, the aim of the current paper was to examine whether a blended smartphone treatment was non-inferior to a full behavioural activation treatment for depression.

METHODS

This was a randomised controlled non-inferiority trial (NCT01819025) comparing a blended treatment (n=46) against a full ten-session treatment (n=47) for people suffering from major depression. Primary outcome measure was the BDI-II, that was administered at pre- and post-treatment, as well as six months after the treatment.

RESULTS

Results showed significant improvements in both groups across time on the primary outcome measure (within-group Cohen's d=1.35; CI [-0.82, 3.52] to d=1.47; CI [-0.41, 3.35]; between group d=-0.13 CI [-2.37, 2.09] and d=-0.10 CI [-2.53, 2.33]). At the same time, the blended treatment reduced the therapist time with an average of 47%.

CONCLUSIONS

We could not establish whether the blended treatment was non-inferior to a full BA treatment. Nevertheless, this study points to that the blended treatment approach could possibly treat nearly twice as many patients suffering from depression by using a smartphone application as add-on. More studies are needed before we can suggest that the blended treatment method is a promising cost-effective alternative to regular face-to-face treatment for depression.

TRIAL REGISTRATION

Cognitive Behavioral Therapy Treatment of Depression With Smartphone Support NCT01819025.

Results of a pilot test of a self-administered smartphone-based treatment system for alcohol use disorders: usability and early outcomes

BACKGROUND

This paper provides results from a pilot study focused on assessing early-stage effectiveness and usability of a smartphone-based intervention system that provides a stand-alone, self-administered intervention option, the Location-Based Monitoring and Intervention for Alcohol Use Disorders (LBMI-A). The LBMI-A provided numerous features for intervening with ongoing drinking, craving, connection with supportive others, managing life problems, high-risk location alerting, and activity scheduling.

METHODS

Twenty-eight participants, ranging in age from 22 to 45, who met criteria for an alcohol use disorder used an LBMI-A-enabled smartphone for 6 weeks.

RESULTS

Participants indicated the LBMI-A intervention modules were helpful in highlighting alcohol use patterns. Tools related to managing alcohol craving, monitoring consumption, and identifying triggers to drink were rated by participants as particularly helpful. Participants also demonstrated significant reductions in hazardous alcohol use while using the system (56% of days spent hazardously drinking at baseline vs. 25% while using the LBMI-A) and drinks per day diminished by 52%.

CONCLUSIONS

Implications for system improvement as well as suggestions for designing ecological momentary assessment and intervention systems for substance use disorders are discussed.

The eHealth Enhanced Chronic Care Model: a theory derivation approach

BACKGROUND

Chronic illnesses are significant to individuals and costly to society. When systematically implemented, the well-established and tested Chronic Care Model (CCM) is shown to improve health outcomes for people with chronic conditions. Since the development of the original CCM, tremendous information management, communication, and technology advancements have been established. An opportunity exists to improve the time-honored CCM with clinically efficacious eHealth tools.

OBJECTIVE

The first goal of this paper was to review research on eHealth tools that support self-management of chronic disease using the CCM. The second goal was to present a revised model, the eHealth Enhanced Chronic Care Model (eCCM), to show how eHealth tools can be used to increase efficiency of how patients manage their own chronic illnesses.

METHODS

Using Theory Derivation processes, we identified a "parent theory", the Chronic Care Model, and conducted a thorough review of the literature using CINAHL, Medline, OVID, EMBASE PsychINFO, Science Direct, as well as government reports, industry reports, legislation using search terms "CCM or Chronic Care Model" AND "eHealth" or the specific identified components of eHealth. Additionally, "Chronic Illness Self-management support" AND "Technology" AND several identified eHealth tools were also used as search terms. We then used a review of the literature and specific components of the CCM to create the eCCM.

RESULTS

We identified 260 papers at the intersection of technology, chronic disease self-management support, the CCM, and eHealth and organized a high-quality subset (n=95) using the components of CCM, self-management support, delivery system design, clinical decision support, and clinical information systems. In general, results showed that eHealth tools make important contributions to chronic care and the CCM but that the model requires modification in several key areas. Specifically, (1) eHealth education is critical for self-care, (2) eHealth support needs to be placed within the context of community and enhanced with the benefits of the eCommunity or virtual communities, and (3) a complete feedback loop is needed to assure productive technology-based interactions between the patient and provider.

CONCLUSIONS

The revised model, eCCM, offers insight into the role of eHealth tools in self-management support for people with chronic conditions. Additional research and testing of the eCCM are the logical next steps.

Community pharmacy patient perceptions of a pharmacy-initiated mobile technology app to improve adherence

OBJECTIVES

To determine patient perceptions of using a demonstration application (app) of mobile technology to improve medication adherence and to identify desired features to assist in the management of medications.

METHODS

A qualitative study using key informant interviews was conducted in a community pharmacy chain for patients aged 50 and older, on statin therapy and owning a smart device.

KEY FINDINGS

Three main themes emerged from 24 interviews at four pharmacy locations, which included benefits, barriers and desired features of the app. Benefits such as accessibility, privacy, pros of appearance and beneficiaries were more likely to lead to usage of the app. Barriers that might prevent usage of the app were related to concerns of appearance, the burden it might cause for others, cost, privacy, motivation and reliability. Specific features patients desired were categorized under appearance, customization, communication, functionality, input and the app platform.

CONCLUSIONS

Patients provided opinions about using a mobile app to improve medication adherence and assist with managing medications. Patients envisioned the app within their lifestyle and expressed important considerations, identifying benefits to using this technology and voicing relevant concerns. App developers can use patient perceptions to guide development of a mobile app addressing patient medication-related needs.

Blending online therapy into regular face-to-face therapy for depression: content, ratio and preconditions according to patients and therapists using a Delphi study

BACKGROUND

Blending online modules into face-to-face therapy offers perspectives to enhance patient self-management and to increase the (cost-)effectiveness of therapy, while still providing the support patients need. The aim of this study was to outline optimal usage of blended care for depression, according to patients and therapists.

METHODS

A Delphi method was used to find consensus on suitable blended protocols (content, sequence and ratio). Phase 1 was an explorative phase, conducted in two rounds of online questionnaires, in which patients' and therapists' preferences and opinions about online psychotherapy were surveyed. In phase 2, data from phase 1 was used in face-to-face interviews with therapists to investigate how blended therapy protocols could be set up and what essential preconditions would be.

RESULTS

Twelve therapists and nine patients completed the surveys. Blended therapy was positively perceived among all respondents, especially to enhance the self-management of patients. According to most respondents, practical therapy components (assignments, diaries and psycho-education) may be provided via online modules, while process-related components (introduction, evaluation and discussing thoughts and feelings), should be supported face-to-face. The preferred blend of online and face-to-face sessions differs between therapists and patients; most therapists prefer 75% face-to-face sessions, most patients 50 to 60%. The interviews showed that tailoring treatment to individual patients is essential in secondary mental health care, due to the complexity of their problems. The amount and ratio of online modules needs to be adjusted according to the patient's problems, skills and characteristics. Therapists themselves should also develop skills to integrate online and face-to-face sessions.

CONCLUSIONS

Blending online and face-to-face sessions in an integrated depression therapy is viewed as a positive innovation by patients and therapists. Following a standard blended protocol, however, would be difficult in secondary mental health care. A database of online modules could provide flexibility to tailor treatment to individual patients, which asks motivation and skills of both patients and therapists. Further research is necessary to determine the (cost-)effectiveness of blended care, but this study provides starting points and preconditions to blend online and face-to-face sessions and create a treatment combining the best of both worlds.

Examining perceptions of a smartphone-based intervention system for alcohol use disorders

BACKGROUND

This study presents results from qualitative interviews conducted with participants in a study on the effectiveness of the Location-Based Monitoring and Intervention System for Alcohol Use Disorders (LBMI-A), a smartphone-based, stand-alone intervention application (app) for adults with alcohol use disorders.

MATERIALS AND METHODS

Participants were provided an LBMI-A-enabled smartphone to use during a 6-week pilot study. The LBMI-A was composed of psychoeducational modules, assessment and feedback of alcohol use patterns, geographic high-risk location monitoring and alerts, and in vivo assessment and intervention for alcohol cravings and help with managing psychological distress. Semistructured interviews were conducted with all participants following 6 weeks of interacting with the LBMI-A app (n=26). Interviews explored user perceptions of the ease and utility of LBMI-A features, module helpfulness, barriers to use, and recommendations for improvements to the program. Researchers applied a systematic qualitative coding process to transcripts that included both a priori themes identified as important by the research team and new themes that emerged during the coding process.

RESULTS AND CONCLUSIONS

Narrative analysis found the emergence of five main themes identified by LBMI-A users as the most helpful functions of the phone: (1) Awareness, (2) Accountability, (3) Skill Transference, (4) Tracking Progress, and (5) Prompts. These themes are explored, and implications of these findings for future smartphone-based interventions are discussed.

Routine real-time cost-effectiveness monitoring of a web-based depression intervention: a risk-sharing proposal

Background

A new health care technology must be cost-effective in order to be adopted. If evidence regarding cost-effectiveness is uncertain, then the decision maker faces two choices: (1) adopt the technology and run the risk that it is less effective in actual practice, or (2) reject the technology and risk that potential health is forgone. A new depression eHealth service was found to be cost-effective in a previously published study. The results, however, were unreliable because it was based on a pilot clinical trial. A conservative decision maker would normally require stronger evidence for the intervention to be implemented.

Objective

Our objective was to evaluate how to facilitate service implementation by shifting the burden of risk due to uncertainty to the service provider and ensure that the intervention remains cost-effective during routine use.

Methods

We propose a risk-sharing scheme, where the service cost depends on the actual effectiveness of the service in real-life setting. Routine efficacy data can be used as the input to the cost-effectiveness model, which employs a mapping function to translate a depression specific score into quality-adjusted life-years. The latter is the denominator in the cost-effectiveness ratio calculation, required by the health care decision maker. The output of the model is a “value graph”, showing intervention value as a function of its observed (future) efficacy, using the €30,000 per quality-adjusted life-year (QALY) threshold.

Results

We found that the eHealth service should improve the patient’s outcome by at least 11.9 points on the Beck Depression Inventory scale in order for the cost-effectiveness ratio to remain below the €30,000/QALY threshold. The value of a single point improvement was found to be between €200 and €700, depending on depression severity at treatment start. Value of the eHealth service, based on the current efficacy estimates, is €1900, which is significantly above its estimated cost (€200).

Conclusions

The eHealth depression service is particularly suited to routine monitoring, since data can be gathered through the Internet within the service communication channels. This enables real-time cost-effectiveness evaluation and allows a value-based price to be established. We propose a novel pricing scheme where the price is set to a point in the interval between cost and value, which provides an economic surplus to both the payer and the provider. Such a business model will assure that a portion of the surplus is retained by the payer and not completely appropriated by the private provider. If the eHealth service were to turn out less effective than originally anticipated, then the price would be lowered in order to achieve the cost-effectiveness threshold and this risk of financial loss would be borne by the provider.

The impact of web-based approaches on psychosocial health in chronic physical and mental health conditions

Chronic conditions such as cancer, cardiovascular disease and mental illness are increasingly prevalent and associated with considerable psychosocial burden. There is a need to consider population health approaches to reducing this burden. Web-based interventions offer an alternative to traditional face-to-face interventions with several potential advantages. This systematic review explores the effectiveness, reach and adoption of web-based approaches for improving psychosocial outcomes in patients with common chronic conditions. A systematic review of published work examining web-based psychosocial interventions for patients with chronic conditions from 2001 to 2011. Seventy-four publications were identified. Thirty-six studies met the criteria for robust research design. A consistent significant effect in favour of the web-based intervention was identified in 20 studies, particularly those using cognitive behavioural therapy for depression. No positive effect was found in 11 studies, and mixed effects were found in 5 studies. The role of sociodemographic characteristics in relation to outcomes or issues of reach and adoption was explored in very few studies. Although it is possible to achieve positive effects on psychosocial outcomes using web-based approaches, effects are not consistent across conditions. Robust comparisons of the reach, adoption and cost-effectiveness of web-based support compared with other options such as face-to-face and print-based approaches are needed.

Seeking health advice on the Internet in patients with health problems: a cross-sectional population study in Slovenia

AIM

To determine the one-month prevalence of the seeking of web-based health information in the general adult population and to identify the symptoms associated with more frequent searching for information online.

METHODS

This was an observational cross-sectional study in a representative sample of 1,002 randomly selected Slovenian inhabitants. We used the method of computer-assisted telephone interviews. The questionnaire consisted of demographic questions, questions about the prevalence and duration of pre-selected symptoms in the past month, questions on the presence of chronic disease and a question about using the Internet for seeking health advice in the past month.

RESULTS

Among 774 respondents who reported having had symptoms in the past month, 25.8% of them reported seeking health information on the Internet. The factors found to be independently associated with the seeking of health information on the Internet were a younger age, a higher education level and the presence of constipation, irritability, fatigue, memory impairment and excessive sweating in the past month.

CONCLUSIONS

The study showed that the Internet was a common source of health information in the general adult population, particularly used for symptoms which are common but not well defined and not associated with a particular disease.

Cost-effectiveness of a novel e-health depression service

OBJECTIVES

A recent trial assessed feasibility of an e-health service (" Improvehealth.eu ") to support depression care and reported positive outcomes. Our objective was to examine cost-effectiveness of the Improvehealth.eu service. A baseline model was used to evaluate cost and effects of the intervention. Given the high uncertainty in the input space, a series of alternative scenarios were evaluated to challenge the result. The aim was to find if conservative or even pessimistic estimates and assumptions could result in a change of the cost-effectiveness from the baseline model.

MATERIALS AND METHODS

A probabilistic depression model combined with bootstrapping was built and populated with data from the literature and from the pilot efficacy trial of the e-health service. The core of the model was a stochastic mapping function that translated depression-specific outcomes to quality-adjusted life years. Correlated sampling was used to obtain unbiased and consistent piecewise linear transformation of Beck Depression Inventory scores to utilities. The results are shown as cost-effectiveness acceptability curves with value of information data. An extreme scenario analysis was then performed to deal with parameter, structural, and modeling uncertainty.

RESULTS

Cost-effectiveness of the e-health service was favorable because of low cost and high efficacy of the intervention. Apart from the most pessimistic one, none of the 13 alternative scenarios changed the preferred alternative.

CONCLUSIONS

Improvehealth.eu is cost-effective relative to usual care, given the available efficacy data. Results of the health economic evaluation were robust to alternative assumptions, despite considerable uncertainty in input data.

The impact of technology on medication adherence

Medication nonadherence is a large contributor to inadequate therapeutic outcomes, especially among patients with mental illness and carries a high cost. Intervention strategies to increase adherence have incorporated technological advances, including electronic symptom monitoring and communication systems for patients and providers. This article presents a review of several studies demonstrating how technology may affect medication adherence.

Telepsychiatry: Promise, potential, and challenges

Despite the high prevalence and potentially disabling consequences of mental disorders, specialized mental health services are extremely deficient, leading to the so-called 'Mental Health Gap'. Moreover, the services are concentrated in the urban areas, further worsening the rural-urban and tertiary primary care divide. Strengthening of and expanding the existing human resources and infrastructure, and integrating mental health into primary care appear to be the two major solutions. However, both the strategies are riddled with logistic difficulties and have a long gestation period. In such a scenario, telepsychiatry or e-mental health, defined as the use of information and communication technology to provide or support psychiatric services across distances, appears to be a promising answer. Due to its enormous potential, a review of the existing literature becomes imperative. An extensive search of literature was carried out and has been presented to delineate the modes of communication, acceptability and satisfaction, reliability, outcomes, cost-effectiveness, and legal and ethical challenges related to telepsychiatry. Telepsychiatry has been applied for direct patient care (diagnosis and management), consultation, and training, education, and research purposes. Both real-time, live interaction (synchronous) and store-forward (asynchronous) types of technologies have been used for these purposes. A growing amount of literature shows that training, supervision, and consultation by specialists to primary care physicians through telepsychiatry has several advantages. In this background, we have further focused on the models of telepsychiatry best suited for India, considering that mental health care can be integrated into primary care and taken to the doorstep of patients in the community.

Collaborative care for depression and anxiety problems

BACKGROUND

Common mental health problems, such as depression and anxiety, are estimated to affect up to 15% of the UK population at any one time, and health care systems worldwide need to implement interventions to reduce the impact and burden of these conditions. Collaborative care is a complex intervention based on chronic disease management models that may be effective in the management of these common mental health problems.

OBJECTIVES

To assess the effectiveness of collaborative care for patients with depression or anxiety.

SEARCH METHODS

We searched the following databases to February 2012: The Cochrane Collaboration Depression, Anxiety and Neurosis Group (CCDAN) trials registers (CCDANCTR-References and CCDANCTR-Studies) which include relevant randomised controlled trials (RCTs) from MEDLINE (1950 to present), EMBASE (1974 to present), PsycINFO (1967 to present) and the Cochrane Central Register of Controlled Trials (CENTRAL, all years); the World Health Organization (WHO) trials portal (ICTRP); ClinicalTrials.gov; and CINAHL (to November 2010 only). We screened the reference lists of reports of all included studies and published systematic reviews for reports of additional studies.

SELECTION CRITERIA

Randomised controlled trials (RCTs) of collaborative care for participants of all ages with depression or anxiety.

DATA COLLECTION AND ANALYSIS

Two independent researchers extracted data using a standardised data extraction sheet. Two independent researchers made 'Risk of bias' assessments using criteria from The Cochrane Collaboration. We combined continuous measures of outcome using standardised mean differences (SMDs) with 95% confidence intervals (CIs). We combined dichotomous measures using risk ratios (RRs) with 95% CIs. Sensitivity analyses tested the robustness of the results.

MAIN RESULTS

We included seventy-nine RCTs (including 90 relevant comparisons) involving 24,308 participants in the review. Studies varied in terms of risk of bias.The results of primary analyses demonstrated significantly greater improvement in depression outcomes for adults with depression treated with the collaborative care model in the short-term (SMD -0.34, 95% CI -0.41 to -0.27; RR 1.32, 95% CI 1.22 to 1.43), medium-term (SMD -0.28, 95% CI -0.41 to -0.15; RR 1.31, 95% CI 1.17 to 1.48), and long-term (SMD -0.35, 95% CI -0.46 to -0.24; RR 1.29, 95% CI 1.18 to 1.41). However, these significant benefits were not demonstrated into the very long-term (RR 1.12, 95% CI 0.98 to 1.27).The results also demonstrated significantly greater improvement in anxiety outcomes for adults with anxiety treated with the collaborative care model in the short-term (SMD -0.30, 95% CI -0.44 to -0.17; RR 1.50, 95% CI 1.21 to 1.87), medium-term (SMD -0.33, 95% CI -0.47 to -0.19; RR 1.41, 95% CI 1.18 to 1.69), and long-term (SMD -0.20, 95% CI -0.34 to -0.06; RR 1.26, 95% CI 1.11 to 1.42). No comparisons examined the effects of the intervention on anxiety outcomes in the very long-term.There was evidence of benefit in secondary outcomes including medication use, mental health quality of life, and patient satisfaction, although there was less evidence of benefit in physical quality of life.

AUTHORS' CONCLUSIONS

Collaborative care is associated with significant improvement in depression and anxiety outcomes compared with usual care, and represents a useful addition to clinical pathways for adult patients with depression and anxiety.

Factors associated with antidepressant medication adherence and adherence-enhancement programmes: a systematic literature review

Medication adherence is critical to the efficacy of available treatment for depression in primary care settings. This review identifies factors associated with adherence and what is known about the effectiveness of adherence-enhancement programmes. A comprehensive systematic review of English language publications from January 2002 to October 2011 was conducted using the following databases: PUBMED/MEDLINE, PsycINFO and the Cochrane database. Twenty-one studies met the inclusion criteria for adherence-enhancement evaluations. Eleven of the studies evaluated demonstrated significantly positive effects on adherence; the remaining 10 reported mixed or no effects. Similar to previous literature reviews, factors shown to be associated with adherence were multifactorial and in this analysis were grouped as patient, condition and comorbidities, therapy or treatment, patient-provider relationship and healthcare system level. Adherence improved most notably in studies that included sustainable system and patient-targeted changes. Evaluating adherence-enhancement interventions is key to promoting successful approaches; however, a number of gaps exist between intervention and implementation: (1) the cost in resources and time to implement and sustain these programmes is unknown, (2) specific details about which subgroups of patients are best helped with such programmes is not clear, and (3) what specific processes or content are critical to programme success is still to be identified. There are sufficient data supporting the substantial need for planning and implementing adherence interventions despite reported mixed results. Primary care providers are often positioned to impact patients' adherence; however, practice constraints can limit their implementation.

Theme issue on e-mental health: a growing field in internet research

This theme issue on e-mental health presents 16 articles from leading researchers working on systems and theories related to supporting and improving mental health conditions and mental health care using information and communication technologies. In this editorial, we present the background of this theme issue, and highlight the content of this issue.