Personalized Prevention of Depression in the Workplace (e-pD-Work)

NCT04858737 | Active Not Recruiting

• 1 other identifier: PI18/01307
• Study Type: interventional
• Target: 1,054
• Locations: 1 country
• Sites: 1

Brief Summary

The main goal is to design, develop and evaluate a personalized intervention to prevent depression in the workplace, based on Information and Communication Technologies (ICTs), predictive risk algorithms and decision support systems (DSS) for employed workers. The specific goals are: 1) to design and develop a DSS, called e-predictD-Work-DSS to elaborate personalized plans to prevent depression and its monitoring in the employed working population; 2) to design and develop an ICT solution that integrates the DSS on the web, a mobile application (App), the predictD risk algorithm, different intervention modules (including a work stress management module) and a monitoring-feedback system; 3) to evaluate the usability, adherence, acceptability and satisfaction of employed working population with the e-pD-Work intervention; 4) to evaluate the effectiveness of the e-pD-Work intervention to reduce the incidence of major depression, depression and anxiety symptoms, the probability of major depression next year and to improve quality of life; 5) to evaluate the cost-effectiveness and cost-utility of the e-pD-Work intervention to prevent depression. Methods: This a randomized, double-blind, controlled trial with two parallel arms (e-pD-Work vs active m-Health control) and 12 months follow-up. A total of 3,160 depression-free workers, aged between 18 and 55 years old will be recruited in Spain and randomly assigned to one of the two groups in a 1:1 ratio considering a stratification of age (18-29, 30-39, 40-49, 50-55 years) and sex similar to the Spanish population. Participants, interviewers and statisticians will be blinded to participants' allocation. The e-pD-Work intervention is self-guided, has a biopsychosocial approach and is multi-component (9 modules: physical exercise, improve sleep, expand relationships, solve problems, improve communication, assertiveness, decision making, manage thoughts and reduce work stress). The e-pD-Work intervention will be implemented in the smartphone of the workers and pivot on an already validated risk predictive algorithm and a DSS that helps workers to develop their own personalized depression prevention plans. Primary outcome will be the rate of major depression measured by CIDI. As secondary outcomes: depressive and anxiety symptomatology measured by PHQ-9 and GAD-7 respectively, the risk probability of depression measured by the predictD risk algorithm, quality of life measured by SF-12 and EuroQol, and cost-effectiveness and cost-utility.

Conditions

Depression

Keywords

Depression; Primary prevention; Randomized controlled trial; m-Health; App; Workers

Outcome Measures

Primary Outcomes (1)

• Rate of major depression measured by the Composite International Diagnostic Interview (CIDI)

  Composite International Diagnostic Interview (CIDI) is a structured diagnostic interview that provides current diagnoses of major depression according to DSM

  12 months

Secondary Outcomes (9)

• Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9)

  12 months

• Anxious symptoms measured by the General Anxiety Questionnaire (GAD-7)

  12 months

• Probability of depression measured by the Spanish predictD risk algorithm

  12 months

• Quality of life measured by SF-12

  12 months

• Satisfaction with paid work measured by an adapted version of the Job Content Instrument

  12 months

Study Arms (2)

e-predicD-Work intervention

EXPERIMENTAL

In this arm, worker participants will receive an online personalized intervention to prevent depression based on ICTs, risk predictive algorithms and decision support systems (DSS).

Behavioral: e-predictD-Work intervention

m-Health control

ACTIVE COMPARATOR

In this arm, worker participants will continue receiving the usual care from their health providers. In addition, they will use an App with the same appearance as the e-predictD-Work App but it will only send weekly short messages about stress and general health that will be extracted from brochures and websites of official agencies.

Other: Brief psychoeducational messages

Interventions

e-predictD-Work intervention BEHAVIORAL

The intervention is based on validated risk algorithms to predict depression and includes: 1) Mobile applications as main user's interface; 2) a DSS that helps worker participants to develop their own personalized plans to prevent (PPP) depression; 3) nine intervention modules (the core of the system) including activities to prevent depression, to be proposed by the DSS and chosen by the participants. The intervention is biopsychosocial and multi-component, including the following modules: physical exercise, improve sleep, expand relationships, solve problems, improve communication, assertiveness, decision making, manage thoughts and reduce work stress. Worker participants will implement the recommendations and the tool will monitor these actions, offering feedback to improve their PPP at 6 and 12 months.

e-predicD-Work intervention

Brief psychoeducational messages OTHER

The intervention consists of an App that weekly send short messages about stress and general health that will be extracted from brochures and websites of official agencies.

m-Health control

Eligibility Criteria

• Age: 18 Years - 55 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)

You may qualify if:

• Have a paid employement
• PHQ-9 \<10 at baseline

You may not qualify if:

• Not have a smartphone and internet for personal use
• Sick leave for more than 1 month
• Unable to speak Spanish
• Documented terminal illness
• Documented cognitive impairment
• Documented serious mental illness (psychosis, bipolar, addictions, etc.)

Sponsors & Collaborators

• The Mediterranean Institute for the Advance of Biotechnology and Health Research: lead
• Preventive Services and Health Promotion Research Network: collaborator
• Institute of Biomedical Research in Málaga (IBIMA): collaborator
• Andalusian Regional Ministry of Health: collaborator
• European Regional Development Fund: collaborator
• University of Malaga: collaborator

Study Sites (1)

Juan Bellon Saameño

Málaga, Spain

Location

MeSH Terms

Conditions

Depression; Alzheimer Disease

Condition Hierarchy (Ancestors)

Behavioral Symptoms; Behavior; Dementia; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Tauopathies; Neurodegenerative Diseases; Neurocognitive Disorders; Mental Disorders

Study Officials

• Juan Á Bellón, PhD

  Andalusian Health Service

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: TRIPLE
• Who Masked: PARTICIPANT, INVESTIGATOR, OUTCOMES ASSESSOR
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD, Medicine

Study Record Dates

• First Submitted: April 21, 2021
• First Posted: April 26, 2021
• Study Start: June 1, 2021
• Primary Completion: August 1, 2024
• Study Completion: December 1, 2024
• Last Updated: March 25, 2024

Record last verified: 2024-03

Locations

ES (1)