Sustainable Upscaling of Depression Prevention
2 other identifiers
interventional
307
1 country
1
Brief Summary
Research shows that online unguided self-help interventions focused on psycho-education, skills training and lifestyle can prevent mild mood complaints from turning into a full-blown depression. These encouraging results are found even though the adherence to these types of interventions is generally low. With this project, the investigators examine whether effectiveness and adherence to online unguided self-help interventions can be increased by additional motivational guidance elements. This is examined by adding three additional components to the intervention: 1) A coach who provides online feedback once a week to provide support. 2) Mobile application to monitor mood and related factors and to receive automated personalized messages, 3) Content based on the principles of motivational interviewing. A secondary aim is to compare the additional effects of the individual components against the additional costs.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable depression
Started Aug 2022
Shorter than P25 for not_applicable depression
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
August 31, 2022
CompletedFirst Submitted
Initial submission to the registry
November 16, 2022
CompletedFirst Posted
Study publicly available on registry
December 1, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
March 31, 2023
CompletedMay 9, 2024
May 1, 2024
7 months
November 16, 2022
May 7, 2024
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Mood improvement
Mood is assessed with the Center for Epidemiological Studies Depression Scale (CES-D). The total score ranges from 0 to 60, with a lower score indicating better mood. The CES-D is assessed at baseline and then again after 6 weeks.
6 weeks
Secondary Outcomes (10)
Adherence to the online self-help intervention
5 weeks
Anxiety Symptoms
6 weeks
Problem Solving Skills
6 weeks
Behavioral activation
6 weeks
Worrying
6 weeks
- +5 more secondary outcomes
Other Outcomes (2)
Costs for each component
5 weeks
Time investment
6 weeks
Study Arms (8)
Condition 1
EXPERIMENTALMoodbuster Life + Mobile Application + Guidance by a coach + Motivational Content
Condition 2
EXPERIMENTALMoodbuster Life + Mobile Application + Guidance by a coach
Condition 3
EXPERIMENTALMoodbuster Life + Mobile Application + Motivational Content
Condition 4
EXPERIMENTALMoodbuster Life + Mobile Application
Condition 5
EXPERIMENTALMoodbuster Life + Guidance by a coach + Motivational Content
Condition 6
EXPERIMENTALMoodbuster Life + Guidance by a coach
Condition 7
EXPERIMENTALMoodbuster Life + Motivational Content
Condition 8
EXPERIMENTALMoodbuster Life
Interventions
All participants get access to the Moodbuster Life intervention. Moodbuster Life is an online self-help intervention that contains 5 web-based modules focusing on lifestyle and coping: psycho-education, behavioral activation, physical activity, problem-solving, and worrying. All participants start with module 1, psycho-education. Next, participants can choose what module they wish to continue with. All modules take about 45 minutes to complete and contain text, exercises, video clips and preparing the home-work assignments. Executing the home-work assignments may take 20 minutes each week.
The participants randomized to receive this component will receive access to a mobile application. The aim of this app is two-folded, (1) used for diary ratings, (2) sending out personalized automated messages. First, the participants will rate their mood, sleep and related factors on a daily basis. The participants are prompted to rate the diary ratings three times a day (morning, afternoon, evening). Moreover, the application graphically pictures progression over time. Second, the application will send personalized automated messages. The content of the messages is informative, affirmative or encouraging. The investigators will use reinforcement learning (RL) to find so-called policies that show best long-term engagement and most sustained improvement of participants' mood. To drive choices, the investigators will use the data mentioned in the advising for the modules as well as behavioral data (mood ratings), data across all users is exploited.
A coach will provide support once per week at a scheduled time to participants who are allocated to receive support. The coaches are psychologists who are not part of the research team. The support will be provided via the Moodbuster Life messaging system and is focused on helping the participant work through the modules, showing empathy and motivating the participants to continue with the modules. The coaching is not aimed at developing a patient-therapist relationship.
Participants who are randomized to this component, receive access to extra content that is based on the principles of motivational interviewing. This includes an extended first module that contains psychoeducation on the importance of motivations and on how persons can motivate themselves to engage with the interventions. Participants are asked about their life goals (long term) and intervention goals (short time) and are guided in how they should formulate these goals to increase the chance of success. Moreover, in each of the 4 modules a short exercise aimed at increasing motivation is included.
Eligibility Criteria
You may qualify if:
- Aged 18 years or older
- Mild to moderate depression as defined by a score between 5 and 15 on the Patient Health Questionnaire - 9 (PHQ-9)
- Adequate written proficiency in the Dutch language
- Have a valid email address and computer with internet access
- In possession of a smartphone
You may not qualify if:
- Current risk for suicide according to the PHQ-9 questionnaire (question 9, score of 1 or higher)
- Currently receiving psychological treatment for depression or another psychiatric disorder in primary or specialized mental health care
- Currently having a psychiatric disorder
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Vrije Universiteit
Amsterdam, Netherlands
Related Publications (13)
Buntrock C, Ebert DD, Lehr D, Smit F, Riper H, Berking M, Cuijpers P. Effect of a Web-Based Guided Self-help Intervention for Prevention of Major Depression in Adults With Subthreshold Depression: A Randomized Clinical Trial. JAMA. 2016 May 3;315(17):1854-63. doi: 10.1001/jama.2016.4326.
PMID: 27139058BACKGROUNDSimon GE, VonKorff M, Rutter C, Wagner E. Randomised trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ. 2000 Feb 26;320(7234):550-4. doi: 10.1136/bmj.320.7234.550.
PMID: 10688563BACKGROUNDBatterham PJ, Calear AL. Preferences for Internet-Based Mental Health Interventions in an Adult Online Sample: Findings From an Online Community Survey. JMIR Ment Health. 2017 Jun 30;4(2):e26. doi: 10.2196/mental.7722.
PMID: 28666976RESULTBuntrock C, Ebert D, Lehr D, Riper H, Smit F, Cuijpers P, Berking M. Effectiveness of a web-based cognitive behavioural intervention for subthreshold depression: pragmatic randomised controlled trial. Psychother Psychosom. 2015;84(6):348-58. doi: 10.1159/000438673. Epub 2015 Sep 24.
PMID: 26398885RESULTHassouni, A. E., Hoogendoorn, M., van Otterlo, M., Eiben, A. E., Muhonen, V., & Barbaro, E. (2018). A clustering-based reinforcement learning approach for tailored personalization of e-Health interventions. arXiv preprint arXiv:1804.03592.
RESULTKaryotaki E, Kleiboer A, Smit F, Turner DT, Pastor AM, Andersson G, Berger T, Botella C, Breton JM, Carlbring P, Christensen H, de Graaf E, Griffiths K, Donker T, Farrer L, Huibers MJ, Lenndin J, Mackinnon A, Meyer B, Moritz S, Riper H, Spek V, Vernmark K, Cuijpers P. Predictors of treatment dropout in self-guided web-based interventions for depression: an 'individual patient data' meta-analysis. Psychol Med. 2015 Oct;45(13):2717-26. doi: 10.1017/S0033291715000665. Epub 2015 Apr 17.
PMID: 25881626RESULTKaryotaki E, Riper H, Twisk J, Hoogendoorn A, Kleiboer A, Mira A, Mackinnon A, Meyer B, Botella C, Littlewood E, Andersson G, Christensen H, Klein JP, Schroder J, Breton-Lopez J, Scheider J, Griffiths K, Farrer L, Huibers MJ, Phillips R, Gilbody S, Moritz S, Berger T, Pop V, Spek V, Cuijpers P. Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms: A Meta-analysis of Individual Participant Data. JAMA Psychiatry. 2017 Apr 1;74(4):351-359. doi: 10.1001/jamapsychiatry.2017.0044.
PMID: 28241179RESULTKelders, S. M. (2015, June). Involvement as a working mechanism for persuasive technology. In International Conference on Persuasive Technology (pp. 3-14). Springer, Cham.
RESULTKranzler HR, McKay JR. Personalized treatment of alcohol dependence. Curr Psychiatry Rep. 2012 Oct;14(5):486-93. doi: 10.1007/s11920-012-0296-5.
PMID: 22810115RESULTMohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. J Med Internet Res. 2011 Mar 10;13(1):e30. doi: 10.2196/jmir.1602.
PMID: 21393123RESULTRiper H, Andersson G, Christensen H, Cuijpers P, Lange A, Eysenbach G. Theme issue on e-mental health: a growing field in internet research. J Med Internet Res. 2010 Dec 19;12(5):e74. doi: 10.2196/jmir.1713.
PMID: 21169177RESULTvan Zoonen K, Buntrock C, Ebert DD, Smit F, Reynolds CF 3rd, Beekman AT, Cuijpers P. Preventing the onset of major depressive disorder: a meta-analytic review of psychological interventions. Int J Epidemiol. 2014 Apr;43(2):318-29. doi: 10.1093/ije/dyt175.
PMID: 24760873RESULTWarmerdam L, Riper H, Klein M, van den Ven P, Rocha A, Ricardo Henriques M, Tousset E, Silva H, Andersson G, Cuijpers P. Innovative ICT solutions to improve treatment outcomes for depression: the ICT4Depression project. Stud Health Technol Inform. 2012;181:339-43.
PMID: 22954884RESULT
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Heleen Riper, Prof.dr.
Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit, 1081BT Amsterdam, The Netherlands
- PRINCIPAL INVESTIGATOR
Annet Kleiboer, dr.
Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit, 1081BT Amsterdam, The Netherlands
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- OUTCOMES ASSESSOR
- Masking Details
- Study participants cannot be blinded to the allocation scheme as the participants will know what components are added to their intervention.
- Purpose
- PREVENTION
- Intervention Model
- FACTORIAL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Assistant Professor
Study Record Dates
First Submitted
November 16, 2022
First Posted
December 1, 2022
Study Start
August 31, 2022
Primary Completion
March 31, 2023
Study Completion
March 31, 2023
Last Updated
May 9, 2024
Record last verified: 2024-05
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL
- Time Frame
- Immediately following publication of the main results, no end date.
- Access Criteria
- Accession will be granted through a standardized accession form following review by the project's PI.
Individual participant data (anonymised and encrypted) will be available on request following a standardized data accession form.