Optimizing a community-based intervention to improve help-seeking for depression care: study protocol for a...

Area of Science:

• Global Mental Health
• Implementation Science
• Community Health Interventions

Background:

• Depression management is effective in primary care, yet treatment gaps persist, especially in low- and middle-income countries (LMICs).
• Demand-side barriers like stigma and lack of awareness hinder mental health service utilization in LMICs.
• This study addresses the need for improved depression care access in Nepal, a LMIC with low treatment-seeking rates.

Purpose of the Study:

• To optimize a community-based intervention using the Multiphase Optimization Strategy (MOST) to enhance depression help-seeking behaviors.
• To identify the active ingredients of the 'Gain Life' intervention for improving mental health care access.
• To inform the design of future large-scale randomized controlled trials for depression interventions in LMICs.

Main Methods:

• A 2x3 factorial randomized controlled trial in two Nepali municipalities.
• Female Community Health Volunteers will use the Community Informant Detection Tool (CIDT) for depression screening.
• The 'Gain Life' intervention, comprising information, service awareness, stigma reduction, and testimonials, will be implemented.

Main Results:

• The primary outcome is the change in help-seeking behavior for depression.
• The study will analyze the effectiveness of different intervention components.
• Sample size is 288 adults (18+ years) residing in selected municipalities meeting CIDT criteria.

Conclusions:

• The MOST framework provides a structured approach to optimize community-based mental health interventions.
• Study findings will guide decisions on proceeding with a full randomized controlled trial or further optimization.
• This research contributes to evidence-based strategies for improving mental health care in resource-limited settings.