Internet-delivered treatment: its potential as a low-intensity community intervention for adults with symptoms of depression: protocol for a randomized controlled trial

Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study

BACKGROUND

Despite the increasing need for digital services to support geriatric mental health, the development and implementation of digital mental health care systems for older adults have been hindered by a lack of studies involving socially vulnerable older adult users and their caregivers in natural living environments.

OBJECTIVE

This study aims to determine whether digital sensing data on heart rate variability, sleep quality, and physical activity can predict same-day or next-day depressive symptoms among socially vulnerable older adults in their everyday living environments. In addition, this study tested the feasibility of a digital mental health monitoring platform designed to inform older adult users and their community caregivers about day-to-day changes in the health status of older adults.

METHODS

A single-arm, nonrandomized living lab pilot study was conducted with socially vulnerable older adults (n=25), their community caregivers (n=16), and a managerial social worker over a 6-week period during and after the COVID-19 pandemic. Depressive symptoms were assessed daily using the 9-item Patient Health Questionnaire via scripted verbal conversations with a mobile chatbot. Digital biomarkers for depression, including heart rate variability, sleep, and physical activity, were measured using a wearable sensor (Fitbit Sense) that was worn continuously, except during charging times. Daily individualized feedback, using traffic signal signs, on the health status of older adult users regarding stress, sleep, physical activity, and health emergency status was displayed on a mobile app for the users and on a web application for their community caregivers. Multilevel modeling was used to examine whether the digital biomarkers predicted same-day or next-day depressive symptoms. Study staff conducted pre- and postsurveys in person at the homes of older adult users to monitor changes in depressive symptoms, sleep quality, and system usability.

RESULTS

Among the 31 older adult participants, 25 provided data for the living lab and 24 provided data for the pre-post test analysis. The multilevel modeling results showed that increases in daily sleep fragmentation (P=.003) and sleep efficiency (P=.001) compared with one's average were associated with an increased risk of daily depressive symptoms in older adults. The pre-post test results indicated improvements in depressive symptoms (P=.048) and sleep quality (P=.02), but not in the system usability (P=.18).

CONCLUSIONS

The findings suggest that wearable sensors assessing sleep quality may be utilized to predict daily fluctuations in depressive symptoms among socially vulnerable older adults. The results also imply that receiving individualized health feedback and sharing it with community caregivers may help improve the mental health of older adults. However, additional in-person training may be necessary to enhance usability.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06270121; https://clinicaltrials.gov/study/NCT06270121.

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.

The Precision in Psychiatry (PIP) study: Testing an internet-based methodology for accelerating research in treatment prediction and personalisation

BACKGROUND

Evidence-based treatments for depression exist but not all patients benefit from them. Efforts to develop predictive models that can assist clinicians in allocating treatments are ongoing, but there are major issues with acquiring the volume and breadth of data needed to train these models. We examined the feasibility, tolerability, patient characteristics, and data quality of a novel protocol for internet-based treatment research in psychiatry that may help advance this field.

METHODS

A fully internet-based protocol was used to gather repeated observational data from patient cohorts receiving internet-based cognitive behavioural therapy (iCBT) (N = 600) or antidepressant medication treatment (N = 110). At baseline, participants provided > 600 data points of self-report data, spanning socio-demographics, lifestyle, physical health, clinical and other psychological variables and completed 4 cognitive tests. They were followed weekly and completed another detailed clinical and cognitive assessment at week 4. In this paper, we describe our study design, the demographic and clinical characteristics of participants, their treatment adherence, study retention and compliance, the quality of the data gathered, and qualitative feedback from patients on study design and implementation.

RESULTS

Participant retention was 92% at week 3 and 84% for the final assessment. The relatively short study duration of 4 weeks was sufficient to reveal early treatment effects; there were significant reductions in 11 transdiagnostic psychiatric symptoms assessed, with the largest improvement seen for depression. Most participants (66%) reported being distracted at some point during the study, 11% failed 1 or more attention checks and 3% consumed an intoxicating substance. Data quality was nonetheless high, with near perfect 4-week test retest reliability for self-reported height (ICC = 0.97).

CONCLUSIONS

An internet-based methodology can be used efficiently to gather large amounts of detailed patient data during iCBT and antidepressant treatment. Recruitment was rapid, retention was relatively high and data quality was good. This paper provides a template methodology for future internet-based treatment studies, showing that such an approach facilitates data collection at a scale required for machine learning and other data-intensive methods that hope to deliver algorithmic tools that can aid clinical decision-making in psychiatry.

The Use of Telehealth in Depression Treatment during the Crisis Caused by COVID-19

Throughout the COVID-19 pandemic, there has been increased interest in telehealth as a means of providing care for depression. In this article, we provide an overview of telehealth utilization for the treatment of depression and provide some insight into the rapid shift made to quickly implement these telehealth services into our everyday practices due to COVID-19 personal distancing requirements. We review the application of telehealth in the treatment of depression during the COVID-19 pandemic. The multiple advantages and disadvantages of telehealth in treatment of depression are summarized through the literature, and we analyze the methods to improve the effect and quality of telehealth in depression treatment. It has been highlighted in the current research that against its proven capacity for convenience, its relative cheapness, and its ability to overcome geographic barriers, telehealth has its own shortfalls, including disparities in rural-urban infrastructure and an alleged inability to be exhaustive when intensive interventions are needed. Recommendations for the improvement of telehealth during the COVID-19 pandemic also presuppose that it is infrastructure and human resource intensive and that short-term improvements in its efficiency are largely dependent on the creativity and resourcefulness of physicians to provide custom solutions for patients.

Enrollment and retention of participants in remote digital health studies: a scoping review and framework proposal (Preprint)

Background

Objective

Methods

Results

Conclusions

Why Do Users of Online Mental Health Communities Get Likes and Reposts: A Combination of Text Mining and Empirical Analysis

An online community is one of the important ways for people with mental disorders to receive assistance and obtain support. This study aims to help users with mental disorders to obtain more support and communication through online communities, and to provide community managers with the possible influence mechanisms based on the information adoption model. We obtained a total of 49,047 posts of an online mental health communities in China, over a 40-day period. Then we used a combination of text mining and empirical analysis. Topic and sentiment analysis were used to derive the key variables—the topic of posts that the users care about most, and the emotion scores contained in posts. We then constructed a theoretical model based on the information adoption model. As core independent variables of information quality, on online mental health communities, the topic of social experience in posts (0.368 ***), the topic of emotional expression (0.353 ***), and the sentiment contained in the text (0.002 *) all had significant positive relationships with the number of likes and reposts. This study found that the users of online mental health communities are more attentive to the topics of social experience and emotional expressions, while they also care about the non-linguistic information. This study highlights the importance of helping community users to post on community-related topics, and gives administrators possible ways to help users gain the communication and support they need.

Assessing the Efficacy and Acceptability of a Web-Based Intervention for Resilience Among College Students: Pilot Randomized Controlled Trial

BACKGROUND

College students are at elevated risk for developing mental health problems and face specific barriers around accessing evidence-based treatment. Web-based interventions that focus on mental health promotion and strengthening resilience represent one possible solution. Providing support to users has shown to reduce dropout in these interventions. Further research is needed to assess the efficacy and acceptability of these interventions and explore the viability of automating support.

OBJECTIVE

This study investigated the feasibility of a new web-based resilience program based on positive psychology, provided with human or automated support, in a sample of college students.

METHODS

A 3-armed closed pilot randomized controlled trial design was used. Participants were randomized to the intervention with human support (n=29), intervention with automated support (n=26), or waiting list (n=28) group. Primary outcomes were resilience and well-being, respectively measured by the Connor-Davidson Resilience Scale and Pemberton Happiness Index. Secondary outcomes included measures of depression and anxiety, self-esteem, and stress. Outcomes were self-assessed through online questionnaires. Intention-to-treat and per-protocol analyses were conducted.

RESULTS

All participants demonstrated significant improvements in resilience and related outcomes, including an unexpected improvement in the waiting list group. Within- and between-group effect sizes ranged from small to moderate and within-group effects were typically larger for the human than automated support group. A total of 36 participants began the program and completed 46.46% of it on average. Participants were generally satisfied with the program and found it easy to use.

CONCLUSIONS

Findings support the feasibility of the intervention. Preliminary evidence for the equal benefit of human and automated support needs to be supported by further research with a larger sample. Results of this study will inform the development of a full-scale trial, from which stronger conclusions may be drawn.

TRIAL REGISTRATION

International Standard Randomized Controlled Trial Number (ISRCTN) 11866034; http://www.isrctn.com/ISRCTN11866034.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1016/j.invent.2019.100254.

Usability, Acceptability, and Effectiveness of Web-Based Conversational Agents to Facilitate Problem Solving in Older Adults: Controlled Study

Background

The usability and effectiveness of conversational agents (chatbots) that deliver psychological therapies is under-researched.

Objective

This study aimed to compare the system usability, acceptability, and effectiveness in older adults of 2 Web-based conversational agents that differ in theoretical orientation and approach.

Methods

In a randomized study, 112 older adults were allocated to 1 of the following 2 fully automated interventions: Manage Your Life Online (MYLO; ie, a chatbot that mimics a therapist using a method of levels approach) and ELIZA (a chatbot that mimics a therapist using a humanistic counseling approach). The primary outcome was problem distress and resolution, with secondary outcome measures of system usability and clinical outcome.

Results

MYLO participants spent significantly longer interacting with the conversational agent. Posthoc tests indicated that MYLO participants had significantly lower problem distress at follow-up. There were no differences between MYLO and ELIZA in terms of problem resolution. MYLO was rated as significantly more helpful and likely to be used again. System usability of both the conversational agents was associated with helpfulness of the agents and the willingness of the participants to reuse. Adherence was high. A total of 12% (7/59) of the MYLO group did not carry out their conversation with the chatbot.

Conclusions

Controlled studies of chatbots need to be conducted in clinical populations across different age groups. The potential integration of chatbots into psychological care in routine services is discussed.

A Culturally Adapted Cognitive Behavioral Internet-Delivered Intervention for Depressive Symptoms: Randomized Controlled Trial

BACKGROUND

Internet-delivered treatments for depressive symptoms have proved to be successful in high-income Western countries. There may be potential for implementing such treatments in low- and middle-income countries such as Colombia, where access to mental health services is limited.

OBJECTIVE

The objective of this study was to assess the efficacy of a culturally adapted cognitive behavioral internet-delivered treatment for college students with depressive symptoms in Colombia.

METHODS

This was a randomized controlled trial with a 3-month follow-up. The program comprised seven modules. A total of 214 Colombian college students were recruited. They were assessed and randomly assigned to either the treatment group (n=107) or a waiting list (WL) control group (n=107). Participants received weekly support from a trained supporter. The primary outcome was symptoms of depression, as measured by the Patient Health Questionnaire - 9, and the secondary outcomes were anxiety symptoms assessed by the Generalized Anxiety Disorder questionnaire - 7. Other measures, including satisfaction with treatment, were evaluated after 7 weeks.

RESULTS

Research attrition and treatment dropouts were high in this study. On average, 7.6 sessions were completed per user. The mean time spent on the program was 3 hours and 18 min. The linear mixed model (LMM) showed significant effects after treatment (t_197.54=-5.189; P<.001) for the treatment group, and these effects were maintained at the 3-month follow-up (t_39.62=4.668; P<.001). Within-group results for the treatment group yielded a large effect size post treatment (d=1.44; P<.001), and this was maintained at the 3-month follow-up (d=1.81; P<.001). In addition, the LMM showed significant differences between the groups (t_197.54=-5.189; P<.001). The results showed a large effect size between the groups (d=0.91; P<.001). In the treatment group, 76.0% (16/107) achieved a reliable change, compared with 32.0% (17/107) in the WL control group. The difference between groups was statistically significant (X²₂=10.5; P=.001).

CONCLUSIONS

This study was the first contribution to investigating the potential impact of a culturally adapted internet-delivered treatment on depressive symptoms for college students as compared with a WL control group in South America. Future research should focus on identifying variables associated both with premature dropout and treatment withdrawal at follow-up.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03062215; https://clinicaltrials.gov/ct2/show/NCT03062215.

Internet-Delivered Cognitive Behavior Therapy as a Prequel to Face-To-Face Therapy for Depression and Anxiety: A Naturalistic Observation

Background: The UK's Improving Access to Psychological Therapies (IAPT) program is a stepped-care model treating individuals with depression and anxiety disorders. Internet-delivered cognitive behavioral therapy (iCBT) is routinely offered to individuals with mild to moderate symptoms, but its applicability to individuals with severe clinical symptoms and requiring a high-intensity intervention is relatively unknown. The current study sought to investigate the potential impacts of using iCBT as a prequel for patients requiring high-intensity treatment (HIT; face-to-face) for depression and anxiety in IAPT. Methods: The study utilized an open study design. One hundred and twenty-four participants who were on a waiting list for high-intensity, face-to-face psychological treatment were offered iCBT. Psychometric data on symptoms of depression, anxiety, and functioning were collected from participants before starting and on finishing iCBT and at the point of service exit. Therapeutic alliance data were collected from patients and clinicians during treatment. Patient pathway data, such as number of treatment sessions and time in treatment, was also collected and incorporated into the analysis. Results: Significant reductions across primary outcome measures of depression and anxiety, as well as improved functioning, were observed from baseline to iCBT treatment exit, and from iCBT exit to service exit. Analysis of the therapeutic alliance data for patients and clinicians illustrated differences in outcome for those who dropped out and those who completed treatment. Discussion: This study illustrates the potential for using iCBT as a prequel to high-intensity therapy for depression and anxiety disorders and is the first of its kind to do so within IAPT stepped care. The results show that iCBT is a valuable option reducing waiting times and enhancing clinical efficiency. The study contributes to the well-established evidence on online psychological treatments worldwide, but further clinical and service development research is necessary to scale these treatments appropriately.

Exploring the Relationship Between Usage and Outcomes of an Internet-Based Intervention for Individuals With Depressive Symptoms: Secondary Analysis of Data From a Randomized Controlled Trial

Background

Internet interventions can easily generate objective data about program usage. Increasingly, more studies explore the relationship between usage and outcomes, but they often report different metrics of use, and the findings are mixed. Thus, current evaluations fail to demonstrate which metrics should be considered and how these metrics are related to clinically meaningful change.

Objective

This study aimed to explore the relationship between several usage metrics and outcomes of an internet-based intervention for depression.

Methods

This is a secondary analysis of data from a randomized controlled trial that examined the efficacy of an internet-based cognitive behavioral therapy for depression (Space from Depression) in an adult community sample. All participants who enrolled in the intervention, regardless of meeting the inclusion criteria, were included in this study. Space from Depression is a 7-module supported intervention, delivered over a period of 8 weeks. Different usage metrics (ie, time spent, modules and activities completed, and percentage of program completion) were automatically collected by the platform, and composite variables from these (eg, activities per session) were computed. A breakdown of the usage metrics was obtained by weeks. For the analysis, the sample was divided into those who obtained a reliable change (RC)—and those who did not.

Results

Data from 216 users who completed pre- and posttreatment outcomes were included in the analyses. A total of 89 participants obtained an RC, and 127 participants did not obtain an RC. Those in the RC group significantly spent more time, had more log-ins, used more tools, viewed a higher percentage of the program, and got more reviews from their supporter compared with those who did not obtain an RC. Differences between groups in usage were observed from the first week in advance across the different metrics, although they vanished over time. In the RC group, the usage was higher during the first 4 weeks, and then a significant decrease was observed. Our results showed that specific levels of platform usage, 7 hours total time spent, 15 sessions, 30 tools used, and 50% of program completion, were associated with RC.

Conclusions

Overall, the results showed that those individuals who obtained an RC after the intervention had higher levels of exposure to the platform. The usage during the first half of the intervention was higher, and differences between groups were observed from the first week. This study also showed specific usage levels associated with outcomes that could be tested in controlled studies to inform the minimal usage to establish adherence. These results will help to better understand how to use internet-based interventions and what optimal level of engagement can most affect outcomes.

Trial Registration

ISRCTN Registry ISRCTN03704676; http://www.isrctn.com/ISRCTN03704676

International Registered Report Identifier (IRRID)

RR2-10.1186/1471-244X-14-147

A patient-centred intervention to improve the management of multimorbidity in general practice: the 3D RCT

Background

People with multimorbidity experience impaired quality of life, poor health and a burden from treatment. Their care is often disease-focused rather than patient-centred and tailored to their individual needs.

Objective

To implement and evaluate a patient-centred intervention to improve the management of patients with multimorbidity in general practice.

Design

Pragmatic, cluster randomised controlled trial with parallel process and economic evaluations. Practices were centrally randomised by a statistician blind to practice identifiers, using a computer-generated algorithm.

Setting

Thirty-three general practices in three areas of England and Scotland.

Participants

Practices had at least 4500 patients and two general practitioners (GPs) and used the EMIS (Egton Medical Information Systems) computer system. Patients were aged ≥ 18 years with three or more long-term conditions.

Interventions

The 3D (Dimensions of health, Depression and Drugs) intervention was designed to offer patients continuity of care with a named GP, replacing separate reviews of each long-term condition with comprehensive reviews every 6 months. These focused on individualising care to address patients’ main problems, attention to quality of life, depression and polypharmacy and on disease control and agreeing treatment plans. Control practices provided usual care.

Outcome measures

Primary outcome – health-related quality of life (assessed using the EuroQol-5 Dimensions, five-level version) after 15 months. Secondary outcomes – measures of illness burden, treatment burden and patient-centred care. We assessed cost-effectiveness from a NHS and a social care perspective.

Results

Thirty-three practices (1546 patients) were randomised from May to December 2015 [16 practices (797 patients) to the 3D intervention, 17 practices (749 patients) to usual care]. All participants were included in the primary outcome analysis by imputing missing data. There was no evidence of difference between trial arms in health-related quality of life {adjusted difference in means 0.00 [95% confidence interval (CI) –0.02 to 0.02]; p = 0.93}, illness burden or treatment burden. However, patients reported significant benefits from the 3D intervention in all measures of patient-centred care. Qualitative data suggested that both patients and staff welcomed having more time, continuity of care and the patient-centred approach. The economic analysis found no meaningful differences between the intervention and usual care in either quality-adjusted life-years [(QALYs) adjusted mean QALY difference 0.007, 95% CI –0.009 to 0.023] or costs (adjusted mean difference £126, 95% CI –£739 to £991), with wide uncertainty around point estimates. The cost-effectiveness acceptability curve suggested that the intervention was unlikely to be either more or less cost-effective than usual care. Seventy-eight patients died (46 in the intervention arm and 32 in the usual-care arm), with no evidence of difference between trial arms; no deaths appeared to be associated with the intervention.

Limitations

In this pragmatic trial, the implementation of the intervention was incomplete: 49% of patients received two 3D reviews over 15 months, whereas 75% received at least one review.

Conclusions

The 3D approach reflected international consensus about how to improve care for multimorbidity. Although it achieved the aim of providing more patient-centred care, this was not associated with benefits in quality of life, illness burden or treatment burden. The intervention was no more or less cost-effective than usual care. Modifications to the 3D approach might improve its effectiveness. Evaluation is needed based on whole-system change over a longer period of time.

Trial registration

Current Controlled Trials ISRCTN06180958.

Funding

This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 7, No. 5. See the NIHR Journals Library website for further project information.

Supported Internet-Delivered Cognitive Behavior Treatment for Adults with Severe Depressive Symptoms: A Secondary Analysis

BACKGROUND

Depression is a highly prevalent mental health issue that exacts significant economic, societal, personal, and interpersonal costs. Innovative internet-delivered interventions have been designed to increase accessibility to and cost-effectiveness of treatments. These treatments have mainly targeted mild to moderate levels of depression. The increased risk associated with severe depression, particularly of suicidal ideation often results in this population being excluded from research studies. As a result, the effectiveness of internet-delivered cognitive behavioral therapy (iCBT) in more severely depressed cohorts is less researched.

OBJECTIVE

The aim of this study is to examine the effect of iCBT on symptoms of severe depression, comorbid symptoms of anxiety, and levels of work and social functioning.

METHODS

Retrospective consent was provided by participants with elevated scores (>28 severe depression symptoms) on the Beck Depression Inventory (BDI-II) who accessed an iCBT intervention (Space from Depression) with support for up to 8 weeks. Data were collected at baseline, posttreatment, and 3-month follow-up on the primary outcome (BDI-II), and secondary outcomes (the Generalized Anxiety Disorder-7 and the Work and Social Adjustment Scale).

RESULTS

A significant change was observed on all measures between pre- and postmeasurement and maintained at 3-month follow-up. Clinical improvement was observed for participants on the BDI-II from pre- to postmeasurement, and suicidal ideation also reduced from pre- to postmeasurement.

CONCLUSIONS

Users of Space from Depression with symptoms of severe depression were found to have decreased symptoms of depression and anxiety and increased levels of work and social functioning. The intervention also demonstrated its potential to decrease suicidal ideation. Further investigation is required to determine why some individuals improve, and others do not. iCBT may have the potential to be used as an adjunct treatment for severe depression symptoms, but participants may require further treatment if they receive iCBT as a standalone intervention. Although promising, further research incorporating control groups is needed to support the utility of Space from Depression for use in or as an adjunct to treatment for severe depression.

Assessing the efficacy of a culturally adapted cognitive behavioural internet-delivered treatment for depression: protocol for a randomised controlled trial

BACKGROUND

Depression is the principal cause of disability in the world. High prevalence rates of depression in general populations and college students have been found worldwide and in various cultural groups. Low-intensity cognitive behavioural internet-delivered treatment has demonstrated efficacy in high-income-countries (HICs). However little is known of their potential for adaptation and efficacy in low and middle-income countries.

METHODS

Study (1) involves the cultural adaptation of the Space from Depression cognitive-behaviour internet-delivered programme with an asynchronous support for depressive symptoms. This includes initial researcher/clinician adaptation and the integration of cultural assessment feedback of the programme by a panel of experts and users through the theoretically-based Cultural Relevance Questionnaire (CRQ). Study (2) describes the implementation of the culturally adapted intervention using a randomised controlled trial methodology. The efficacy trial will include an active treatment group and a waiting-list control group of participants meeting eligibility criteria (mild to moderate depression symptoms). The active condition will consist of 7 weekly modules of internet-delivered cognitive behavioural therapy (iCBT) Space from Depression, with post-session feedback support. The primary outcome will be the Patient Health Questionnaire (PHQ-9). The study also involves collection of client reported significant events and client satisfaction with the internet-delivered treatment. Data will be collected at baseline and at post-treatment (week 7), and at follow-up (week 20/3 months). Analysis will be conducted on the intention-to-treat basis.

DISCUSSION

The study seeks to establish a theoretically robust methodology for culturally adapting internet-delivered interventions for mental health disorders and to evaluate the efficacy of a culturally adapted internet-delivered treatment for depression in Colombia, with support. The study will be a first contribution to a method for culturally adapting internet-delivered interventions and also a first to examine the efficacy of such an adapted intervention in Latin America.

TRIAL REGISTRATION

Clinical trials NCT03062215. Retrospectively registered 14th February 2017.

Navigating the challenges of digital health innovation: considerations and solutions in developing online and smartphone-application-based interventions for mental health disorders

This article presents an analysis of challenges and considerations when developing digital mental health innovations. Recommendations include collaborative working between clinicians, researchers, industry and service users in order to successfully navigate challenges and to ensure e-therapies are engaging, acceptable, evidence based, scalable and sustainable.

Defining and Predicting Patterns of Early Response in a Web-Based Intervention for Depression

Background

Web-based interventions for individuals with depressive disorders have been a recent focus of research and may be an effective adjunct to face-to-face psychotherapy or pharmacological treatment.

Objective

The aim of our study was to examine the early change patterns in Web-based interventions to identify differential effects.

Methods

We applied piecewise growth mixture modeling (PGMM) to identify different latent classes of early change in individuals with mild-to-moderate depression (n=409) who underwent a CBT-based web intervention for depression.

Results

Overall, three latent classes were identified (N=409): Two early response classes (n=158, n=185) and one early deterioration class (n=66). Latent classes differed in terms of outcome (P<.001) and adherence (P=.03) in regard to the number of modules (number of modules with a duration of at least 10 minutes) and the number of assessments (P<.001), but not in regard to the overall amount of time using the system. Class membership significantly improved outcome prediction by 24.8% over patient intake characteristics (P<.001) and significantly added to the prediction of adherence (P=.04).

Conclusions

These findings suggest that in Web-based interventions outcome and adherence can be predicted by patterns of early change, which can inform treatment decisions and potentially help optimize the allocation of scarce clinical resources.

Predictors of depression severity in a treatment-seeking sample

Background/Objective: Depression is a common mental health disorder and an emerging public health concern. Few studies have investigated prevalence and predictors of depression severity in the Irish context. To investigate the relative contribution of known risk factors that predicts depression severity in a treatment-seeking sample of adults in Ireland. Method: As part of a randomised controlled trial of an internet-delivered intervention for depression participants (N = 641) completed online screening questionnaires including BDI-II and information associated with common predictors of depression. Results: The mean score on the BDI-II was 24.13 (SD = 11.20). Several factors were shown to predict greater severity of depression in the sample including female gender, younger age, unemployment, being single or partnered as opposed to married, previous diagnosis of depression, recent experience of life stressors. Alcohol use, recent losses, knowing a suicide completer, education level, type of employment and income level were not found to be significant. Conclusions: The study contributes to the profiling of the incidence and predictors of severity of depression in an Irish context. The results confirm some of the known risk factors and highlight the need for further research to be carried out on screening for depression and increasing access to interventions.

Acceptability, satisfaction and perceived efficacy of "Space from Depression" an internet-delivered treatment for depression

BACKGROUND

There are clear advantages to internet-delivered interventions for depression. Users' perspectives on the acceptability, satisfaction, and efficacy of an internet-delivered treatment for depression can inform future developments in the area.

METHODS

Respondents (n = 281) were participants in an 8 week supported internet-delivered Cognitive Behaviour Therapy treatment for depressive symptoms. Self-report online questionnaires gathered quantitative and qualitative data on the user experience.

PRINCIPLE FINDINGS

Most respondents were satisfied with the programme (n = 191), felt supported (n = 203), reported positive gains and impact resulting from use of the programme, and perceived these to be likely to be lasting effects (n = 149). Flexibility and accessibility were the most liked aspects. A small number of respondents felt their needs were not met by the intervention (n = 64); for this group suggestions for improvements centred on the programme's structure and how supporter feedback is delivered.

CONCLUSION

Results will deepen the understanding of users' experience and inform the development and implementation of evidence-based internet-delivered interventions.

Acceptability and proof of concept of internet-delivered treatment for depression, anxiety, and stress in university students: protocol for an open feasibility trial

BACKGROUND

In recent years, university counseling and mental health services have reported an increase in the number of clients seeking services and in yearly visits. This trend has been observed at many universities, indicating that behavioral and mental health issues pose significant problems for many college students. The aim of this study is to assess the acceptability and proof of concept of internet-delivered treatment for depression, anxiety, and stress for university students.

METHODS/DESIGN

The study is an open feasibility trial of the SilverCloud programs for depression (Space from Depression), anxiety (Space from Anxiety), and stress (Space from Stress). All three are 8-module internet-delivered CBT (iCBT) intervention programs. Participants are assigned a supporter who provides weekly feedback on progress and exercises. Participants will complete the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and stress subscale of the Depression, Anxiety, Stress Scale-21 (DASS-21) as the outcome measures for the depression, anxiety, and stress interventions, respectively. Other outcomes include measures of acceptability of, and satisfaction, with the intervention. Data will be collected at baseline, 8 weeks and 3-month follow-up.

DISCUSSION

It is anticipated that the study will inform the researchers and service personnel of the programs' potential to reduce depression, anxiety, and stress in a student population as well as the protocols to be employed in a future trial. In addition, it will provide insight into students' engagement with the programs, their user experience, and their satisfaction with the online delivery format.

Online intervention, 'MePlusMe', supporting mood, wellbeing, study skills, and everyday functioning in students in higher education: a protocol for a feasibility study

Background

Psychological and study skill difficulties faced by students in higher education can lead to poor academic performance, sub-optimal mental health, reduced study satisfaction, and drop out from study. At the same time, higher education institutions’ support services are costly, oversubscribed, and struggle to meet demand whilst facing budget reductions. The purpose of the proposed study is to evaluate the acceptability of a new online intervention, MePlusMe, aimed at students in higher education facing mild to moderate psychological and/or study skill difficulties. The study will also assess the feasibility of proposed recruitment and outcome assessment protocols for a future trial of effectiveness. The system supports self-management strategies alongside ongoing monitoring facilitated by a messaging service, as well as featuring a built-in community of student users. It is based on current clinical guidelines for the management of common mental health problems, together with best practice from the educational field.

Methods/design

Two hundred and forty two students will be recruited to a within-subjects, repeated measures study conducted over 8 weeks. Self-report measures of depression and anxiety symptoms, mental wellbeing, academic self-efficacy, and everyday functioning will be collected at baseline, and then at 2, 4, and 8 weeks. During this period, students will have access to the intervention system. UK higher education institutions Bournemouth University and University of Warwick will participate in the study. Data on student satisfaction and engagement will also be collected. Study findings will help to determine the most appropriate primary outcome and the required sample size for a future trial.

Discussion

This study will evaluate the acceptability of an online intervention system for students facing psychological and/or study skill difficulties and will test recruitment procedures and outcome measures for a future trial of effectiveness. The system is designed to be implemented as a stand-alone service or a service complementary to student support services, which is accessible to the majority of students and effective in improving student experience at higher education institutions.

The Space From Heart Disease Intervention for People With Cardiovascular Disease and Distress: A Mixed-Methods Study

Background

Poor self-management of symptoms and psychological distress leads to worse outcomes and excess health service use in cardiovascular disease (CVD). Online-delivered therapy is effective, but generic interventions lack relevance for people with specific long-term conditions, such as cardiovascular disease.

Objective

To develop a comprehensive online CVD-specific intervention to improve both self-management and well-being, and to test acceptability and feasibility.

Methods

Informed by the Medical Research Council (MRC) guidance for the development of complex interventions, we adapted an existing evidence-based generic intervention for depression and anxiety for people with CVD. Content was informed by a literature review of existing resources and trial evidence, and the findings of a focus group study. Think-aloud usability testing was conducted to identify improvements to design and content. Acceptability and feasibility were tested in a cross-sectional study.

Results

Focus group participants (n=10) agreed that no existing resource met all their needs. Improvements such as "collapse and expand" features were added based on findings that participants’ information needs varied, and specific information, such as detecting heart attacks and when to seek help, was added. Think-aloud testing (n=2) led to changes in font size and design changes around navigation. All participants of the cross-sectional study (10/10, 100%) were able to access and use the intervention. Reported satisfaction was good, although the intervention was perceived to lack relevance for people without comorbid psychological distress.

Conclusions

We have developed an evidence-based, theory-informed, user-led online intervention for improving self-management and well-being in CVD. The use of multiple evaluation tests informed improvements to content and usability. Preliminary acceptability and feasibility has been demonstrated. The Space from Heart Disease intervention is now ready to be tested for effectiveness. This work has also identified that people with CVD symptoms and comorbid distress would be the most appropriate sample for a future randomized controlled trial to evaluate its effectiveness.

Expectations among patients and health professionals regarding Web-based interventions for depression in primary care: a qualitative study

BACKGROUND

One-quarter of the world's population will suffer from depression symptoms at some point in their lives. Mental health services in developed countries are overburdened. Therefore, cost-effective interventions that provide mental health care solutions such as Web-based psychotherapy programs have been proposed.

OBJECTIVE

The intent of the study was to identify expectations regarding Web-based psychotherapy for the treatment of depression in primary care among patients and health professionals that might facilitate or hinder its effects.

METHODS

The expectations of untreated patients and health professionals were examined by means of interviews and focus groups. There were 43 participants (20 patients with mild and moderate levels of depression, 11 primary care physicians, and 12 managers; 22 of them for interviews and 21 for groups). A thematic content analysis from the grounded theory for interviews, and an analysis of the discursive positions of participants based on the sociological model for groups were performed. Interpretations were achieved by agreement between three independent analysts.

RESULTS

All participants showed a good general acceptance of Web-based psychotherapy, appreciating possible advantages and improvements. Patients, physicians, and managers shared the same conceptualization of their expectations, although highlighting different aspects. Patients focused on the need for individualized and personalized interaction, while professionals highlighted the need for the standardization of the program. Physicians were concerned with extra workload, while managers were worried about optimizing cost-effectiveness.

CONCLUSIONS

Expectations of the different participants can conflict with each other. Finding a balanced position among them is needed if we are to harmoniously implement effective Web-based interventions for depression in routine clinical practice.

Analyzing engagement in a web-based intervention platform through visualizing log-data

Background

Engagement has emerged as a significant cross-cutting concern within the development of Web-based interventions. There have been calls to institute a more rigorous approach to the design of Web-based interventions, to increase both the quantity and quality of engagement. One approach would be to use log-data to better understand the process of engagement and patterns of use. However, an important challenge lies in organizing log-data for productive analysis.

Objective

Our aim was to conduct an initial exploration of the use of visualizations of log-data to enhance understanding of engagement with Web-based interventions.

Methods

We applied exploratory sequential data analysis to highlight sequential aspects of the log data, such as time or module number, to provide insights into engagement. After applying a number of processing steps, a range of visualizations were generated from the log-data. We then examined the usefulness of these visualizations for understanding the engagement of individual users and the engagement of cohorts of users. The visualizations created are illustrated with two datasets drawn from studies using the SilverCloud Platform: (1) a small, detailed dataset with interviews (n=19) and (2) a large dataset (n=326) with 44,838 logged events.

Results

We present four exploratory visualizations of user engagement with a Web-based intervention, including Navigation Graph, Stripe Graph, Start–Finish Graph, and Next Action Heat Map. The first represents individual usage and the last three, specific aspects of cohort usage. We provide examples of each with a discussion of salient features.

Conclusions

Log-data analysis through data visualization is an alternative way of exploring user engagement with Web-based interventions, which can yield different insights than more commonly used summative measures. We describe how understanding the process of engagement through visualizations can support the development and evaluation of Web-based interventions. Specifically, we show how visualizations can (1) allow inspection of content or feature usage in a temporal relationship to the overall program at different levels of granularity, (2) detect different patterns of use to consider personalization in the design process, (3) detect usability issues, (4) enable exploratory analysis to support the design of statistical queries to summarize the data, (5) provide new opportunities for real-time evaluation, and (6) examine assumptions about interactivity that underlie many summative measures in this field.