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

NCT ID: NCT04858737

Last Updated: 2024-03-25

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 1054 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-06-01
• Study Completion Date: 2024-12-31

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

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: TRIPLE

Study Groups

e-predicD-Work intervention

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).

Group Type: EXPERIMENTAL

e-predictD-Work intervention

Intervention Type: 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.

m-Health control

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.

Group Type: ACTIVE_COMPARATOR

Brief psychoeducational messages

Intervention Type: 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.

Interventions

e-predictD-Work intervention

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.

Intervention Type: BEHAVIORAL

Brief psychoeducational messages

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.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

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

Exclusion Criteria

• 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.)

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 55 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Preventive Services and Health Promotion Research Network

OTHER

Sponsor Role: collaborator

Institute of Biomedical Research in Málaga (IBIMA)

UNKNOWN

Sponsor Role: collaborator

Andalusian Regional Ministry of Health

OTHER_GOV

Sponsor Role: collaborator

European Regional Development Fund

OTHER

Sponsor Role: collaborator

University of Malaga

OTHER

Sponsor Role: collaborator

The Mediterranean Institute for the Advance of Biotechnology and Health Research

OTHER

Sponsor Role: lead

Responsible Party

Juan Ángel Bellón

PhD, Medicine

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Juan Á Bellón, PhD

Role: PRINCIPAL_INVESTIGATOR

Andalusian Health Service

Locations

Juan Bellon Saameño

Málaga, , Spain

Countries

Spain

Other Identifiers

PI18/01307

Identifier Type: -

Identifier Source: org_study_id