Clinical trial NCT03990792: Personalized Prevention of Depression in Primary Care
Official title: Preventing the Onset of Depression Through a Personalized Intervention Based on ICTs, Risk Prediction Algorithms and Decision Support Systems for Patients and GPs: the e-predictD Study
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Depression
Keywords: Depression
Primary Prevention
Primary Health Care
Randomized controlled trial
mHealth
App
Lead sponsor: The Mediterranean Institute for the Advance of Biotechnology and Health Research
Sponsor class: OTHER
Collaborators: name: Preventive Services and Health Promotion Research Network
name: Institute of Biomedical Research in Málaga (IBIMA)
name: Andalusian Regional Ministry of Health
name: European Regional Development Fund
name: University of Malaga
First posted: 2019-06-19
Enrollment: 663
Sex: ALL
Minimum age (years): 18
Maximum age (years): 55
Standard ages: ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: PREVENTION

Brief summary: The main goal is to design, develop and evaluate a personalized intervention to prevent the onset of depression based on Information and Communications Technology (ICTs), risk predictive algorithms and decision support systems (DSS) for patients and general practitioners (GPs). The specific goals are 1) to design and develop a DSS, called e-predictD-DSS, to elaborate personalized plans to prevent depression; 2) to design and develop an ICT solution that integrates the DSS on the web, a mobile application (App), the risk predictive algorithm, different intervention modules and a monitoring-feedback system; 3) to evaluate the usability and adherence of primary care patients and their GPs with the e-predictD intervention; 4) to evaluate the effectiveness of the e-predictD intervention to reduce the incidence of major depression, depression and anxiety symptoms and the probability of major depression next year; 5) to evaluate the cost-effectiveness and cost-utility of the e-predictD intervention to prevent depression.

Methods: This is a randomized controlled trial with allocation by cluster (GPs), simple blind, two parallel arms (e-predictD vs "active m-Health control") and 1 year follow-up including 720 patients (360 in each arm) and 72 GPs (36 in each arm). Patients will be free of major depression at baseline and aged between 18 and 55 years old. Primary outcome will be the incidence of major depression at 12 months measured by CIDI. As secondary outcomes: depressive and anxiety symptomatology measured by PHQ-9 and GAD-7 and the risk probability of depression measured by predictD algorithm, as well as cost-effectiveness and cost-utility. The e-predictD intervention is multi-component and it is based on a DSS that helps the patients to elaborate their own personalized depression prevention plans, which the patient approves, and implements, and the system monitors offering feedback to the patient and to the GPs. It is an e-Health intervention because it is based on a web and m-Health because it is also implemented on the patient's smartphones through an App. In addition, it integrates a risk algorithm of depression, which is already validated (the predictD algorithm). It also includes an initial GP-patient interview and a specific training for the GP. Finally, a map of potentially useful local community resources to prevent depression will be integrated into the DSS.


Eligibility criteria: Inclusion Criteria:

* PHQ-9 \<10 at baseline
* Moderate-high risk of depression (predictD risk algorithm score ≥ 10%)

Exclusion Criteria:

* Not have a smartphone and internet for personal use
* Unable to speak Spanish
* Documented terminal illness
* Documented cognitive impairment
* Limiting sensory disorder (e.g. deafness)
* Documented serious mental illness (psychosis, bipolar, addictions, etc.)

Primary outcomes:
measure: Incidence of major depression measured by the Composite International Diagnostic Interview (CIDI)
timeFrame: 12 months
Secondary outcomes:
measure: Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9)
timeFrame: 12 months
measure: Anxious symptoms measured by the General Anxiety Questionnaire (GAD-7)
timeFrame: 12 months
measure: Probability of depression (predictD risk algorithm)
timeFrame: 12 months
measure: Cost-effectiveness and cost-utility
timeFrame: 12 months
Other outcomes:
Locations:
city: Barcelona
country: Spain
facility: Juan M. Mendive
city: Jaén
country: Spain
facility: María Isabel Ballesta Rodríguez
city: Linares
country: Spain
facility: Antonina Rodríguez Bayón
city: Málaga
country: Spain
facility: Juan Á Bellón
city: Salamanca
country: Spain
facility: Emiliano Rodríguez
city: Zaragoza
country: Spain
facility: Yolanda López del Hoyo
Study officials:
References: