Internet-Delivered Disease Management for Recurrent Depression: A Multicenter Randomized Controlled Trial

Self-help interventions for the prevention of relapse in mood disorder: a systematic review and meta-analysis

INTRODUCTION

Self-help interventions may offer a scalable adjunct to traditional care, but their effectiveness in relapse prevention is not well-established. Objectives: This review aimed to assess their effectiveness in preventing relapses among individuals with mood disorders.

METHODS

We systematically reviewed the pertinent trial literature in Web of Science, EMBASE, PubMed, PsycINFO, and Cochrane databases until May 2024. Randomized controlled trials that examined the self-help interventions among individuals diagnosed with major depressive disorder (MDD) or bipolar disorder (BD) were included. The random-effects model computed the pooled risk ratios of relapse, with subgroup analyses and meta-regression analyses to explore heterogeneity sources.

RESULTS

Fifteen papers and 16 comparisons of randomized trials involving 2735 patients with mood disorders were eligible for this meta-analysis. Adjunct self-help interventions had a small but significant effect on reducing the relapse rates of major depressive disorder (pooled risk ratio: 0.78, 95% confidence interval (CI): 0.66-0.92, P = 0.0032, NNT = 11), and were marginally better in bipolar disorder (pooled risk ratio: 0.62, 95% CI: 0.40-0.97, P = .0344, NNT = 12), as compared to treatment as usual (TAU). No subgroup difference was found based on intervention components, settings, delivery method, or guidance levels. The average dropout rate for self-help interventions (18.9%) did not significantly differ from TAU dropout rates. The examination of treatment adherence was highly variable, precluding definitive conclusions.

CONCLUSIONS

Self-help interventions demonstrate a modest preventative effect on relapse in mood disorders, despite low to very low certainty. Future research is essential to identify which elements of self-help interventions are most effective.

A systematic review and meta analysis on digital mental health interventions in inpatient settings

E-mental health (EMH) interventions gain increasing importance in the treatment of mental health disorders. Their outpatient efficacy is well-established. However, research on EMH in inpatient settings remains sparse and lacks a meta-analytic synthesis. This paper presents a meta-analysis on the efficacy of EMH in inpatient settings. Searching multiple databases (PubMed, ScienceGov, PsycInfo, CENTRAL, references), 26 randomized controlled trial (RCT) EMH inpatient studies (n = 6112) with low or medium assessed risk of bias were included. A small significant total effect of EMH treatment was found (g = 0.3). The effect was significant both for blended interventions (g = 0.42) and post-treatment EMH-based aftercare (g = 0.29). EMH treatment yielded significant effects across different patient groups and types of therapy, and the effects remained stable post-treatment. The results show the efficacy of EMH treatment in inpatient settings. The meta-analysis is limited by the small number of included studies.

Alleviating the burden of depression: a simulation study on the impact of mental health services

AIMS

Depressive disorders are ranked as the single leading cause of disability worldwide. Despite immense efforts, there is no evidence of a global reduction in the disease burden in recent decades. The aim of the study was to determine the public health impact of the current service system (status quo), to quantify its effects on the depression-related disease burden and to identify the most promising strategies for improving healthcare for depression on the population level.

METHODS

A Markov model was developed to quantify the impact of current services for depression (including prevention, treatment and aftercare interventions) on the total disease burden and to investigate the potential of alternative scenarios (e.g., improved reach or improved treatment effectiveness). Parameter settings were derived from epidemiological information and treatment data from the literature. Based on the model parameters, 10,000,000 individual lives were simulated for each of the models, based on monthly transition rates between dichotomous health states (healthy vs. diseased). Outcome (depression-related disease burden) was operationalized as the proportion of months spent in depression.

RESULTS

The current healthcare system alleviates about 9.5% (95% confidence interval [CI]: 9.2%-9.7%) of the total disease burden related to depression. Chronic cases cause the majority (83.2%) of depression-related burden. From a public health perspective, improving the reach of services holds the largest potential: Maximum dissemination of prevention (26.9%; CI: 26.7%-27.1%) and treatment (26.5%; CI: 26.3%-26.7%) would result in significant improvements on the population level.

CONCLUSIONS

The results confirm an urgent need for action in healthcare for depression. Extending the reach of services is not only more promising but also probably more achievable than increasing their effectiveness. Currently, the system fails to address the prevention and treatment of chronic cases. The large proportion of the disease burden associated with chronic courses highlights the need for improved treatment policies and clinical strategies for this group (e.g., disease management and adaptive or personalized interventions). The model complements the existing literature by providing a new perspective on the depression-related disease burden and the complex interactions between healthcare services and the lifetime course.

Development of decision rules for an adaptive aftercare intervention based on individual symptom courses for agoraphobia patients

As other mental illnesses, agoraphobia is associated with a significant risk for relapse after the end of treatment. Personalized and adaptive approaches appear promising to improve maintenance treatment and aftercare as they acknowledge patients' varying individual needs with respect to intensity of care over time. Currently, there is a deficit of knowledge about the detailed symptom course after discharge from acute treatment, which is a prerequisite for the empirical development of rules to decide if and when aftercare should be intensified. Therefore, this study aimed firstly at the investigation of the naturalistic symptom course of agoraphobia after discharge from initial treatment and secondly at the development and evaluation of a data-driven algorithm for a digital adaptive aftercare intervention. A total of 56 agoraphobia patients were recruited in 3 hospitals. Following discharge, participants completed a weekly online monitoring assessment for three months. While symptom severity remained stable at the group level, individual courses were highly heterogeneous. Approximately two-thirds of the patients (70%) reported considerable symptoms at some time, indicating a need for medium or high-intense therapeutic support. Simulating the application of the algorithm to the data set resulted in an early (86% before week six) and relatively even allocation of patients to three groups (need for no, medium, and high-intense support respectively). Overall, findings confirm the need for adaptive aftercare strategies in agoraphobia. Digital, adaptive approaches may provide immediate support to patients who experience symptom deterioration and thus promise to contribute to an optimized allocation of therapeutic resources and overall improvement of care.

Patient Experience of Digitalized Follow-up of Antidepressant Treatment in Psychiatric Outpatient Care: Qualitative Analysis

BACKGROUND

Nonadherence to pharmaceutical antidepressant treatment is common among patients with depression. Digitalized follow-up (ie, self-monitoring systems through mobile apps) has been suggested as an effective adjunct to conventional antidepressant treatment to increase medical adherence, improve symptoms of depression, and reduce health care resource use.

OBJECTIVE

The aim of this study was to determine patients' experience of digitalized follow-up using a mobile app as an adjunct to treatment concurrent with a new prescription, a change of antidepressant, or a dose increase.

METHODS

This was a qualitative, descriptive study. Patients at 2 psychiatric outpatient clinics were recruited at the time of changing antidepressant medication. After using a mobile app (either a commercial app or a public app) for 4-6 weeks with daily registrations of active data, such as medical intake and questions concerning general mental health status, individual semistructured interviews were conducted. Recorded data were transcribed and then analyzed using content analysis.

RESULTS

In total, 13 patients completed the study. The mean age was 35 (range 20-67) years, 8 (61.5%) were female, and all reported high digital literacy. Overall, the emerging themes indicated that the patients found the digital app to be a valuable adjunct to antidepressant treatment but with potential for improvement. Both user adherence and medical adherence were positively affected by a daily reminder and the app's ease of use. User adherence was negatively affected by the severity of depression. The positive experience of visually presented data as graphs was a key finding, which was beneficial for self-awareness, the patient-physician relationship, and user adherence. Finally, the patients had mixed reactions to the app's content and requested tailored content.

CONCLUSIONS

The patients identified several factors addressing both medical adherence and user adherence to a digital app when using it for digitalized follow-up concurrent with the critical time related to changes in antidepressant medication. The findings highlight the need for rigorous evidence-based empirical studies to generate sustainable research results.

Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review

BACKGROUND

New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness.

OBJECTIVE

This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy.

METHODS

We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study.

RESULTS

This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability.

CONCLUSIONS

Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.

A mobile-based aftercare intervention to increase self-esteem in inpatients diagnosed with depression: A randomized controlled trial

OBJECTIVE

In this randomized controlled trial, we investigated the effectiveness, side effects and user satisfaction of the self-help smartphone app "MCT & More" among inpatients with a diagnosis of depression after their discharge from a psychiatric hospital over a period of 4 weeks.

METHODS

A total of 159 inpatients were recruited in four German psychiatric hospitals three days before hospital discharge (intervention group: n = 79; treatment as usual: n = 80). Based on the vulnerability model (low self-esteem contributes to depression), self-esteem represented the primary outcome, quality of life and depressive symptoms the secondary outcomes.

RESULTS

Intention-to-treat analyzes showed no statistical significance for the primary and secondary outcome parameters, except for the subscale self-competence in favor of the intervention group (with a small effect size of d = 0.35), in the context of an exploratory approach (post hoc). The more positive the attitude toward mobile-based interventions and the more positive the treatment expectations, the more frequently the app was used (r = .35, p = .008; r = .34, p = .009).

CONCLUSION

Further symptom reduction could not be obtained. However, the results suggest that an effect on improvement in self-competence could be achieved by low-threshold aftercare programs. Future studies should include long-term assessments to examine the impact of mobile-based aftercare on relapse.Trial registration: DRKS00022559.

Novel digital methods for gathering intensive time series data in mental health research: scoping review of a rapidly evolving field

Recent technological advances enable the collection of intensive longitudinal data. This scoping review aimed to provide an overview of methods for collecting intensive time series data in mental health research as well as basic principles, current applications, target constructs, and statistical methods for this type of data.In January 2021, the database MEDLINE was searched. Original articles were identified that (1) used active or passive data collection methods to gather intensive longitudinal data in daily life, (2) had a minimum sample size of N ⩾ 100 participants, and (3) included individuals with subclinical or clinical mental health problems.In total, 3799 original articles were identified, of which 174 met inclusion criteria. The most widely used methods were diary techniques (e.g. Experience Sampling Methodology), various types of sensors (e.g. accelerometer), and app usage data. Target constructs included affect, various symptom domains, cognitive processes, sleep, dysfunctional behaviour, physical activity, and social media use. There was strong evidence on feasibility of, and high compliance with, active and passive data collection methods in diverse clinical settings and groups. Study designs, sampling schedules, and measures varied considerably across studies, limiting the generalisability of findings.Gathering intensive longitudinal data has significant potential to advance mental health research. However, more methodological research is required to establish and meet critical quality standards in this rapidly evolving field. Advanced approaches such as digital phenotyping, ecological momentary interventions, and machine-learning methods will be required to efficiently use intensive longitudinal data and deliver personalised digital interventions and services for improving public mental health.

Predicting Mental Health Status in Remote and Rural Farming Communities: Computational Analysis of Text-Based Counseling

Background

Australians living in rural and remote areas are at elevated risk of mental health problems and must overcome barriers to help seeking, such as poor access, stigma, and entrenched stoicism. e-Mental health services circumvent such barriers using technology, and text-based services are particularly well suited to clients concerned with privacy and self-presentation. They allow the client to reflect on the therapy session after it has ended as the chat log is stored on their device. The text also offers researchers an opportunity to analyze language use patterns and explore how these relate to mental health status.

Objective

In this project, we investigated whether computational linguistic techniques can be applied to text-based communications with the goal of identifying a client’s mental health status.

Methods

Client-therapist text messages were analyzed using the Linguistic Inquiry and Word Count tool. We examined whether the resulting word counts related to the participants’ presenting problems or their self-ratings of mental health at the completion of counseling.

Results

The results confirmed that word use patterns could be used to differentiate whether a client had one of the top 3 presenting problems (depression, anxiety, or stress) and, prospectively, to predict their self-rated mental health after counseling had been completed.

Conclusions

These findings suggest that language use patterns are useful for both researchers and clinicians trying to identify individuals at risk of mental health problems, with potential applications in screening and targeted intervention.

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.

Feasibility of an Intervention Delivered via Mobile Phone and Internet to Improve the Continuity of Care in Schizophrenia: A Randomized Controlled Pilot Study

Schizophrenia is a severe mental illness associated with a heavy symptom burden and high relapse rates. Digital interventions are increasingly suggested as means to facilitate continuity of care, relapse prevention, and long-term disease management for schizophrenia spectrum disorders. In order to investigate the feasibility of a mobile and internet-based aftercare program, a 2-arm randomized controlled pilot study was conducted. The program could be used by patients for six months after inpatient treatment and included psychoeducation, an individual crisis plan, optional counseling via internet chat or phone and a supportive monitoring module. Due to the slow pace of enrollment, recruitment was stopped before the planned sample size was achieved. Reasons for the high exclusion rate during recruitment were analyzed as well as attitudes, satisfaction, and utilization of the program by study participants. The data of 25 randomized patients suggest overall positive attitudes towards the program, high user satisfaction and good adherence to the monitoring module. Overall, the results indicate that the digital program might be suitable to provide support following discharge from intensive care. In addition, the study provides insights into specific barriers to recruitment which may inform future research in the field of digital interventions for severe mental illness.

Clinical and Cost-Effectiveness of PSYCHOnlineTHERAPY: Study Protocol of a Multicenter Blended Outpatient Psychotherapy Cluster Randomized Controlled Trial for Patients With Depressive and Anxiety Disorders

Introduction: Internet- and mobile-based interventions (IMIs) and their integration into routine psychotherapy (i.e., blended therapy) can offer a means of complementing psychotherapy in a flexible and resource optimized way. Objective: The present study will evaluate the non-inferiority, cost-effectiveness, and safety of two versions of integrated blended psychotherapy for depression and anxiety compared to standard cognitive behavioral therapy (CBT). Methods: A three-armed multicenter cluster-randomized controlled non-inferiority trial will be conducted comparing two implementations of blended psychotherapy (PSYCHOnlineTHERAPYfix/flex) compared to CBT. Seventy-five outpatient psychotherapists with a CBT-license will be randomized in a 1:1:1 ratio. Each of them is asked to include 12 patients on average with depressive or anxiety disorders resulting in a total sample size of N = 900. All patients receive up to a maximum of 16 psychotherapy sessions, either as routine CBT or alternating with Online self-help sessions (fix: 8/8; flex: 0-16). Assessments will be conducted at patient study inclusion (pre-treatment) and 6, 12, 18, and 24 weeks and 12 months post-inclusion. The primary outcome is depression and anxiety severity at 18 weeks post-inclusion (post-treatment) using the Patient Health Questionnaire Anxiety and Depression Scale. Secondary outcomes are depression and anxiety remission, treatment response, health-related quality of life, patient satisfaction, working alliance, psychotherapy adherence, and patient safety. Additionally, several potential moderators and mediators including patient characteristics and attitudes toward the interventions will be examined, complemented by ecological day-to-day digital behavior variables via passive smartphone sensing as part of an integrated smart-sensing sub-study. Data-analysis will be performed on an intention-to-treat basis with additional per-protocol analyses. In addition, cost-effectiveness and cost-utility analyses will be conducted from a societal and a public health care perspective. Additionally, qualitative interviews on acceptance, feasibility, and optimization potential will be conducted and analyzed. Discussion: PSYCHOnlineTHERAPY will provide evidence on blended psychotherapy in one of the largest ever conducted psychotherapy trials. If shown to be non-inferior and cost-effective, PSYCHOnlineTHERAPY has the potential to innovate psychotherapy in the near future by extending the ways of conducting psychotherapy. The rigorous health care services approach will facilitate a timely implementation of blended psychotherapy into standard care. Trial Registration: The trial is registered in the German Clinical Trials Register (DRKS00023973; date of registration: December 28th 2020).

Suitability of Text-Based Communications for the Delivery of Psychological Therapeutic Services to Rural and Remote Communities: Scoping Review

BACKGROUND

People living in rural and remote areas have poorer access to mental health services than those living in cities. They are also less likely to seek help because of self-stigma and entrenched stoic beliefs about help seeking as a sign of weakness. E-mental health services can span great distances to reach those in need and offer a degree of privacy and anonymity exceeding that of traditional face-to-face counseling and open up possibilities for identifying at-risk individuals for targeted intervention.

OBJECTIVE

This scoping review maps the research that has explored text-based e-mental health counseling services and studies that have used language use patterns to predict mental health status. In doing so, one of the aims was to determine whether text-based counseling services have the potential to circumvent the barriers faced by clients in rural and remote communities using technology and whether text-based communications, in particular, can be used to identify individuals at risk of psychological distress or self-harm.

METHODS

We conducted a comprehensive electronic literature search of PsycINFO, PubMed, ERIC, and Web of Science databases for articles published in English through November 2020.

RESULTS

Of the 9134 articles screened, 70 met the eligibility criteria and were included in the review. There is preliminary evidence to suggest that text-based, real-time communication with a qualified therapist is an effective form of e-mental health service delivery, particularly for individuals concerned with stigma and confidentiality. There is also converging evidence that text-based communications that have been analyzed using computational linguistic techniques can be used to accurately predict progress during treatment and identify individuals at risk of serious mental health conditions and suicide.

CONCLUSIONS

This review reveals a clear need for intensified research into the extent to which text-based counseling (and predictive models using modern computational linguistics tools) may help deliver mental health treatments to underserved groups such as regional communities, identify at-risk individuals for targeted intervention, and predict progress during treatment. Such approaches have implications for policy development to improve intervention accessibility in at-risk and underserved populations.

Two-Year Follow-Up after Treatment with the Cognitive Behavioral Analysis System of Psychotherapy versus Supportive Psychotherapy for Early-Onset Chronic Depression

BACKGROUND

Evidence on the long-term efficacy of psychotherapeutic approaches for chronic depression is scarce.

OBJECTIVE

To evaluate the effects of the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) compared to Supportive Psychotherapy (SP) 1 year and 2 years after treatment termination.

METHODS

In this study, we present 1- and 2-year follow-up assessments of a prospective, multicenter, evaluator-blinded, randomized clinical trial of outpatients with early-onset chronic major depression (n = 268). The initial treatment included 32 sessions of CBASP or SP over 48 weeks. The primary outcome was the rate of "well weeks" (Longitudinal Interval Follow-Up Evaluation; no/minimal symptoms) after 1 year and 2 years. The secondary outcomes were, among others, clinician- and self-rated depressive symptoms, response/remission rates, and quality of life.

RESULTS

Of the 268 randomized patients, 207 (77%) participated in the follow-up. In the intention-to-treat analysis, there was no statistically significant difference between CBASP and SP patients in experiencing well weeks (CBASP: mean [SD] of 48.6 [36.9] weeks; SP: 39.0 [34.8]; rate ratio 1.26, 95% CI 0.99-1.59, p = 0.057, d = 0.18) and in remission rates (CBASP: 1 year 40%, 2 years 40.2%; SP: 1 year 28.9%, 2 years 33%) in the 2 years after treatment. Statistically significant effects were found in favor of CBASP 1 year after treatment termination regarding the rate of well weeks, self-rated depressive symptoms, and depression-related quality of life.

CONCLUSIONS

CBASP lost its superiority over SP at some point between the first and the second year. This suggests the necessity of maintenance treatment for early-onset chronically depressed patients remitted with CBASP during the acute therapy phase, as well as the sequential integration of other treatment strategies, including medication for those who did not reach remission.

Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis

Digitally delivered interventions for depression vary in many aspects, including their therapeutic orientation, depth of content, interactivity, individual tailoring, inclusion of multimedia, cost, and effectiveness. However, their effectiveness is rarely examined in intervention-specific meta-analyses. An earlier meta-analysis of eight randomized controlled trials (RCT) demonstrated the effectiveness of a tailored, integrative digital intervention (deprexis), which is delivered via the Internet. This updated meta-analysis of twelve deprexis-specific RCT with a total of N = 2901 participants confirmed the effectiveness of deprexis for depression reduction at post-intervention (g = 0.51, 95% CI: 0.40-0.62, I2 = 26%). Results were analogous when study quality, screening and randomization procedure were taken into account. Clinician guidance, developer-involvement, setting (community vs. clinical), and initial symptom severity did not have statistically significant effects on the effect size, and there was no evidence of publication bias. Thus, these findings demonstrate that deprexis can facilitate clinically relevant reduction of depressive symptoms over 8-12 weeks across a broad range of initial symptom severity, and that the intervention can be combined with other forms of depression treatment. There is now a need to study the intervention's implementation in routine care settings as well as its long-term effectiveness and cost-effectiveness in diverse cultural and linguistic settings.

Internet- and mobile-based aftercare and relapse prevention in mental disorders: A systematic review and recommendations for future research

BACKGROUND

Mental disorders are characterized by a high likelihood of recurrence. Thus, aftercare and follow-up interventions aim to maintain treatment gains and to prevent relapse. Internet- and mobile-based interventions (IMIs) may represent promising instruments in tertiary prevention. This systematic review summarizes and evaluates the research on the efficacy of IMIs as aftercare or follow-up interventions for adults with mental health issues.

METHODS

A systematic database search (PsycInfo, MEDLINE, CENTRAL) was conducted and studies selected according to predefined eligibility criteria (RCTs, adult population, clinical symptoms/disorder, assessed with validated instruments, clinical-psychological intervention rationale, aftercare/follow-up intervention, web-/mobile-based, minimum follow-up measurement of three months, inclusion of a control group). Inspected outcomes were symptom severity, recurrence- and rehospitalization rates, functioning, quality of life and adherence to primary treatment.Systematic review registration: PROSPERO CRD42017055289.

RESULTS

Sixteen RCTs met the inclusion criteria, covering trials on depression (n = 5), eating disorders (n = 4) and transdiagnostic interventions (n = 7). The majority of the interventions were based on Cognitive Behavioral Therapy (CBT) principles and were web-based (n = 11). Methodological quality of included studies was suboptimal. Limitations included attrition bias and non-specification of routine care co-interventions. IMIs yielded small to medium post-treatment effects for symptom severity (d = -0.08 - d = -0.45) in comparison to control groups. Best evidence base was found for symptom severity of depression and anxiety. Study results regarding recurrence and rehospitalization were inconsistent.

DISCUSSION

There is some evidence, that IMIs are feasible instruments for maintaining treatment gains for some mental disorders. However, further high quality, large-scale trials are needed to expand research fields, improve adherence to and uptake of IMIs and facilitate implementation of effective interventions into routine care.

Evaluation of a text-message-based maintenance intervention for Major Depressive Disorder after inpatient cognitive behavioral therapy

INTRODUCTION

High relapse rates in Major Depressive Disorder (MDD) indicate the need for interventions enhancing the sustainability of treatment outcomes. Primary aim of the present study was to evaluate the effectiveness of a text-message-based maintenance intervention for depression (TMMI-D). Additionally, we aimed to clarify whether the use of individualized messages would lead to better outcome than the use of standardized messages which focused upon adaptive ways of regulating undesired emotions.

METHODS

In this RCT, 226 individuals who had completed inpatient treatment for MDD were randomly allocated to a condition in which participants received TMMI-D with standardized messages targeting emotion regulation, or to a condition with individualized messages, or to a waitlist control condition. Primary outcome was depressive symptom severity assessed with the BDI-II.

RESULTS

Multilevel analyses suggest that participants receiving TIMMI-D with standardized messages reported a significantly smaller increase of depressive symptoms during the post-treatment and follow-up interval than did patients in the waitlist control condition. Contrastingly, there was no such effect for patients who had used TIMMI-D with individualized messages.

LIMITATIONS

Limitations include proportions of missing data, thus, generalizing the findings of the present study might be an overestimation.

CONCLUSION

Text-message-based interventions may help increase the sustainability of outcome after treatment for MDD. The unexpected superiority of the standardized over the individualized version is in line with research that points to the efficacy of interventions fostering adaptive emotion regulation as a means to treat depression (and other mental disorders).

Novel technology as platform for interventions for caregivers and individuals with severe mental health illnesses: A systematic review

BACKGROUND

Severe mental illnesses (SMIs) have been found to be associated with both increases in morbidity-mortality, need for treatment care in patients themselves, and burden for relatives as caregivers. A growing number of web-based and mobile software applications have appeared that aim to address various barriers with respect to access to care. Our objective was to review and summarize recent advancements in such interventions for caregivers of individuals with a SMI.

METHODS

We conducted a systematic search for papers evaluating interactive mobile or web-based software (using no or only minimal support from a professional) specifically aimed at supporting informal caregivers. We also searched for those supporting patients with SMI so as to not to miss any which might include relatives.

RESULTS

Out of a total of 1673 initial hits, we identified 11 articles reporting on 9 different mobile or web-based software programs. The main result is that none of those studies focused on caregivers, and the ones we identified using mobile or web-based applications were just for patients and not their relatives.

LIMITATIONS

Differentiating between online and offline available software might not always have been totally reliable, and we might have therefore missed some studies.

CONCLUSIONS

In summary, the studies provided evidence that remotely accessible interventions for patients with SMI are feasible and acceptable to patients. No such empirically evaluated program was available for informal caregivers such as relatives. Keeping in mind the influential role of those informal caregivers in the process of treatment and self-management, this is highly relevant for public health. Supporting informal caregivers can improve well-being of both caregivers and patients.

Internetbasierte Therapie in der Versorgung von Patienten mit depressiven Störungen: Ein Überblick

Zusammenfassung. Internet- und mobilbasierten Interventionen wird großes Potenzial in der Behandlung von Menschen mit depressiver Symptomatik zugeschrieben. Diese Einschätzung hat sich in den letzten Jahren vor dem Hintergrund mehrerer Programmentwicklungen und einer Vielzahl von Studien zur Wirksamkeitsprüfung der zumeist auf der kognitiven Verhaltenstherapie basierten Angebote etabliert. Ziel der vorliegenden Übersichtsarbeit ist es, zu prüfen, inwieweit sich aus der empirischen Befundlage wissenschaftlich fundierte Empfehlungen für die Versorgungsbereiche Prävention, Primärversorgung, ambulante Psychotherapie, fachärztliche Versorgung sowie die stationäre Behandlung ableiten lassen. Hierfür werden die Ergebnisse ausgewählter Studien, die in den genannten Versorgungsbereichen angesiedelt sind und die Erhebung der Diagnose depressive Störung auf ein Expertenurteil stützen, kritisch bewertet. In der Schlussfolgerung ermöglicht die gegenwärtige Studienlage keine eindeutige Empfehlung zum Einsatz von internetbasierten Behandlungsprogrammen in den genannten Versorgungsbereichen.

Discharge management strategies and post-discharge care interventions for depression - Systematic review and meta-analysis

BACKGROUND

Patients with depression require treatment continuity when discharged from inpatient care. Interventions aimed at optimizing transition into outpatient care may be effective in preventing symptom deterioration and readmission. We aimed to evaluate the effectiveness of care transition interventions for patients with depression after psychiatric hospitalization.

METHODS

Systematic review and random-effects meta-analysis of controlled trials. Primary outcomes were readmissions and symptoms of depression. The control condition was treatment as usual.

RESULTS

We included 16 publications reporting the results of 13 different studies. Studies were heterogeneous concerning patient selection and interventional approach. Effects on readmissions and depression symptoms were non-significant in meta-analysis of 8 studies/710 patients and 7 studies/592 patients, respectively. Overall risk ratio for readmission during follow-up was 0.65 (95% CI [0.42;1.01], p=0.06), standardized mean difference for depression symptoms was -0.09 (95% CI [-0.37;0.19], p=0.53). Subgroup analyses indicated no preference for a specific interventional strategy. Data point to considerable risk for selection and publication bias.

LIMITATIONS

Included studies are heterogeneous; subgroups are often small and may not attain the power to detect effects. Reasonable classification of interventions into groups of comparable approaches was a challenge and may be arbitrary in some cases.

CONCLUSIONS

This systematic review and meta-analysis could not identify any convincingly effective interventional transition approach for patients with depression after psychiatric hospitalization. Current evidence regarding discharge management for depression is limited, heterogeneous and potentially prone to bias. Interventions might be more appropriate for patients with other diagnoses than depression. Further high-quality randomized studies are required.

Effectiveness of telephone-based aftercare case management for adult patients with unipolar depression compared to usual care: A randomized controlled trial

BACKGROUND

Patients with depression often have limited access to outpatient psychotherapy following inpatient treatment. The objective of the study was to evaluate the long-term effectiveness of a telephone-based aftercare case management (ACM) intervention for patients with depression.

METHODS

We performed a prospective randomized controlled trial in four psychotherapeutic inpatient care units with N = 199 patients with major depression or dysthymia (F32.x, F33.x, F34.1, according to the ICD-10). The ACM consisted of six phone contacts at two-week intervals performed by trained and certified psychotherapists. The control group received usual care (UC). The primary outcome was depressive symptom severity (BDI-II) at 9-month follow-up, and secondary outcomes were health-related quality of life (SF-8, EQ-5D), self-efficacy (SWE), and the proportion of patients initiating outpatient psychotherapy. Mixed model analyses were conducted to compare improvements between treatment groups.

RESULTS

Regarding the primary outcome of symptom severity, the groups did not significantly differ after 3 months (p = .132; ES = -0.23) or at the 9-month follow-up (p = .284; ES = -0.20). No significant differences in health-related quality of life or self-efficacy were found between groups. Patients receiving ACM were more likely to be in outpatient psychotherapy after 3 months (OR: 3.00[1.12-8.07]; p = .029) and 9 months (OR: 4.78 [1.55-14.74]; p = .006) than those receiving UC.

CONCLUSIONS

Although telephone-based ACM did not significantly improve symptom severity, it seems to be a valuable approach for overcoming treatment barriers to the clinical pathways of patients with depression regarding their access to outpatient psychotherapy.

Supportive Mental Health Self-Monitoring among Smartphone Users with Psychological Distress: Protocol for a Fully Mobile Randomized Controlled Trial

Mobile health (mHealth) could be widely used in the population to improve access to psychological treatment. In this paper, we describe the development of a mHealth intervention on the basis of supportive self-monitoring and describe the protocol for a randomized controlled trial to evaluate its effectiveness among smartphone users with psychological distress. Based on power analysis, a representative quota sample of N = 186 smartphone users will be recruited, with an over-sampling of persons with moderate to high distress. Over a 4-week period, the intervention will be compared to a self-monitoring without intervention group and a passive control group. Telephone interviews will be conducted at baseline, post-intervention (4 weeks), and 12-week follow-up to assess study outcomes. The primary outcome will be improvement of mental health. Secondary outcomes will include well-being, intentions toward help-seeking and help-seeking behavior, user activation, attitudes toward mental-health services, perceived stigmatization, smartphone app quality, user satisfaction, engagement, and adherence with the intervention. Additionally, data from the user's daily life as collected during self-monitoring will be used to investigate risk and protective factors of mental health in real-world settings. Therefore, this study will allow us to demonstrate the effectiveness of a smartphone application as a widely accessible and low-cost intervention to improve mental health on a population level. It also allows to identify new assessment approaches in the field of psychiatric epidemiology.

Blending Face-to-Face and Internet-Based Interventions for the Treatment of Mental Disorders in Adults: Systematic Review

Background

Many studies have provided evidence for the effectiveness of Internet-based stand-alone interventions for mental disorders. A newer form of intervention combines the strengths of face-to-face (f2f) and Internet approaches (blended interventions).

Objective

The aim of this review was to provide an overview of (1) the different formats of blended treatments for adults, (2) the stage of treatment in which these are applied, (3) their objective in combining face-to-face and Internet-based approaches, and (4) their effectiveness.

Methods

Studies on blended concepts were identified through systematic searches in the MEDLINE, PsycINFO, Cochrane, and PubMed databases. Keywords included terms indicating face-to-face interventions (“inpatient,” “outpatient,” “face-to-face,” or “residential treatment”), which were combined with terms indicating Internet treatment (“internet,” “online,” or “web”) and terms indicating mental disorders (“mental health,” “depression,” “anxiety,” or “substance abuse”). We focused on three of the most common mental disorders (depression, anxiety, and substance abuse).

Results

We identified 64 publications describing 44 studies, 27 of which were randomized controlled trials (RCTs). Results suggest that, compared with stand-alone face-to-face therapy, blended therapy may save clinician time, lead to lower dropout rates and greater abstinence rates of patients with substance abuse, or help maintain initially achieved changes within psychotherapy in the long-term effects of inpatient therapy. However, there is a lack of comparative outcome studies investigating the superiority of the outcomes of blended treatments in comparison with classic face-to-face or Internet-based treatments, as well as of studies identifying the optimal ratio of face-to-face and Internet sessions.

Conclusions

Several studies have shown that, for common mental health disorders, blended interventions are feasible and can be more effective compared with no treatment controls. However, more RCTs on effectiveness and cost-effectiveness of blended treatments, especially compared with nonblended treatments are necessary.

Effectiveness of online and mobile telephone applications ('apps') for the self-management of suicidal ideation and self-harm: a systematic review and meta-analysis

BACKGROUND

Online and mobile telephone applications ('apps') have the potential to improve the scalability of effective interventions for suicidal ideation and self-harm. The aim of this review was therefore to investigate the effectiveness of digital interventions for the self-management of suicidal ideation or self-harm.

METHODS

Seven databases (Applied Science & Technology; CENTRAL; CRESP; Embase; Global Health; PsycARTICLES; PsycINFO; Medline) were searched to 31 March, 2017. Studies that examined the effectiveness of digital interventions for suicidal ideation and/or self-harm, or which reported outcome data for suicidal ideation and/or self-harm, within a randomised controlled trial (RCT), pseudo-RCT, or observational pre-test/post-test design were included in the review.

RESULTS

Fourteen non-overlapping studies were included, reporting data from a total of 3,356 participants. Overall, digital interventions were associated with reductions for suicidal ideation scores at post-intervention. There was no evidence of a treatment effect for self-harm or attempted suicide.

CONCLUSIONS

Most studies were biased in relation to at least one aspect of study design, and particularly the domains of participant, clinical personnel, and outcome assessor blinding. Performance and detection bias therefore cannot be ruled out. Digital interventions for suicidal ideation and self-harm may be more effective than waitlist control. It is unclear whether these reductions would be clinically meaningful at present. Further evidence, particularly with regards to the potential mechanisms of action of these interventions, as well as safety, is required before these interventions could recommended.

Application of Synchronous Text-Based Dialogue Systems in Mental Health Interventions: Systematic Review

Background

Synchronous written conversations (or “chats”) are becoming increasingly popular as Web-based mental health interventions. Therefore, it is of utmost importance to evaluate and summarize the quality of these interventions.

Objective

The aim of this study was to review the current evidence for the feasibility and effectiveness of online one-on-one mental health interventions that use text-based synchronous chat.

Methods

A systematic search was conducted of the databases relevant to this area of research (Medical Literature Analysis and Retrieval System Online [MEDLINE], PsycINFO, Central, Scopus, EMBASE, Web of Science, IEEE, and ACM). There were no specific selection criteria relating to the participant group. Studies were included if they reported interventions with individual text-based synchronous conversations (ie, chat or text messaging) and a psychological outcome measure.

Results

A total of 24 articles were included in this review. Interventions included a wide range of mental health targets (eg, anxiety, distress, depression, eating disorders, and addiction) and intervention design. Overall, compared with the waitlist (WL) condition, studies showed significant and sustained improvements in mental health outcomes following synchronous text-based intervention, and post treatment improvement equivalent but not superior to treatment as usual (TAU) (eg, face-to-face and telephone counseling).

Conclusions

Feasibility studies indicate substantial innovation in this area of mental health intervention with studies utilizing trained volunteers and chatbot technologies to deliver interventions. While studies of efficacy show positive post-intervention gains, further research is needed to determine whether time requirements for this mode of intervention are feasible in clinical practice.

[Internet-based interventions in the treatment of mental disorders : Overview, quality criteria, perspectives]

BACKGROUND

Mental disorders are frequently not or only insufficiently treated. Internet-based interventions offer the potential of closing the existing gaps in the treatment of mental disorders; however, it is very difficult for patients and providers to choose from the numerous interventions available.

OBJECTIVE

The aim of this study was to develop a set of quality criteria that can help patients and care providers to identify recommendable internet-based interventions.

METHODS

A selective literature search was carried out and the existing evidence on internet-based interventions in the treatment of mental disorders was collated. A panel of experts then developed quality criteria based on existing models for the systematic assessment of telemedicine applications.

RESULTS

Internet-based interventions are effective in the treatment of a broad range of mental disorders. The best evidence is available for depression and anxiety disorders. A set of criteria is proposed for the evaluation of available internet-based interventions using a checklist. These criteria have to be developed further with input from other stakeholders.

DISCUSSION

When taking these quality criteria into account, evidence-based interventions available on the internet can make an important contribution to improvement of the care of patients with mental disorders.

Effects of a Psychological Internet Intervention in the Treatment of Mild to Moderate Depressive Symptoms: Results of the EVIDENT Study, a Randomized Controlled Trial

BACKGROUND

Mild to moderate depressive symptoms are common but often remain unrecognized and treated inadequately. We hypothesized that an Internet intervention in addition to usual care is superior to care as usual alone (CAU) in the treatment of mild to moderate depressive symptoms in adults.

METHODS

This trial was controlled, randomized and assessor-blinded. Participants with mild to moderate depressive symptoms (Patient Health Questionnaire, PHQ-9, score 5-14) were recruited from clinical and non-clinical settings and randomized to either CAU or a 12-week Internet intervention (Deprexis) adjunctive to usual care. Outcomes were assessed at baseline, 3 months (post-assessment) and 6 months (follow-up). The primary outcome measure was self-rated depression severity (PHQ-9). The main analysis was based on the intention-to-treat principle and used linear mixed models.

RESULTS

A total of 1,013 participants were randomized. Changes in PHQ-9 from baseline differed signixFB01;cantly between groups (t825 = 6.12, p < 0.001 for the main effect of group). The post-assessment between-group effect size in favour of the intervention was d = 0.39 (95% CI: 0.13-0.64). It was stable at follow-up, with d = 0.32 (95% CI: 0.06-0.69). The rate of participants experiencing at least minimally clinically important PHQ-9 change at the post-assessment was higher in the intervention group (35.6 vs. 20.2%) with a number needed to treat of 7 (95% CI: 5-10).

CONCLUSIONS

The Internet intervention examined in this trial was superior to CAU alone in reducing mild to moderate depressive symptoms. The magnitude of the effect is clinically important and has public health implications.