Short Summary
Depression affects hundreds of millions of people globally, with the largest treatment gaps in LMICs
Guided digital self-help combines evidence-based psychological support with light human guidance, enabling care to be delivered at scale and at low cost
Strong evidence and early implementation experience suggest this model can meaningfully expand access to care where specialist services are scarce
The Problem
What’s the problem?
Depression is one of the leading causes of disability worldwide
Over 300 million people are affected globally, with LMICs bearing the majority of the burden
The WHO estimates that around 75% of people with depression in LMICs receive no treatment
Why does it matter?
Untreated depression reduces wellbeing, and makes it harder to function at home, at work, and in the community
The scale of unmet need is large, and without new delivery models, the treatment gap is unlikely to close
Neglectedness:
The gap is driven largely by a shortage of trained providers. Low-income countries average around 1.1 mental health workers per 100,000 people, compared to roughly 67 per 100,000 in high-income countries
Traditional face-to-face psychotherapy cannot scale to meet population-level needs in these settings
The Solution
What’s the proposed solution?
A digital guided self-help program based on WHO’s Step-by-Step model
Participants would complete short, structured self-help modules via WhatsApp
Light human support would be provided through brief check-ins with trained lay counselors
The program is designed to be low-cost, scalable, and deliverable in resource-constrained settings
Why do we trust this solution?
Meta analyses show guided self-help achieves effects comparable to face-to-face therapy in many settings
Five randomized controlled trials of Step-by-Step in LMICs show statistically significant improvements over enhanced usual care
Kaya Guides, an AIM-incubated charity, has demonstrated that this model can be implemented in practice
How robust is the evidence?
The evidence includes randomized controlled trials and meta-analyses
Key limitations include high attrition, reliance on self-reported outcomes, and short follow-up periods, which are common in digital mental health research
The Impact
What impact could this have?
Our model assumes the charity reaches 100,000 people per year at scale, with ~25,000 completing the full program
At this scale, we estimate an average of ~14,000 DALYs averted each year, including household spillover effects
Based on conservative modeling, we estimate effects of ~0.14 DALYs or ~0.54 WELLBYs per person reached
Estimated cost-effectiveness:
This intervention meets our bar for cost-effectiveness across all modeled countries and methods used
Average modeled cost-effectiveness is ~$97 per DALY averted or ~$25 per WELLBY at scale
Ideal Founder Profile
Who is best suited to do this? *
The ideal founders would combine technical expertise in digital product development and management, a background in psychology or public health, as well as operational, scaling, marketing and outreach experience
What might our ideal candidate look like?
The following backgrounds would be useful for co-founders or early hires:
Mental health or public health background: Understanding of mental health interventions, familiarity with evidence-based approaches, and the ability to train and supervise lay counselors
Technical skills: Experience in digital product development, which could help reduce costs and improve delivery efficiency
Digital product management: Experience with messaging platforms, chatbot development, and user engagement optimization
Operations and scaling: Ability to manage a distributed workforce, establish quality assurance systems, and support growth over time
Cultural competency: Understanding of local context, ability to adapt content appropriately, and relevant language skills for localization
*We think candidates with the following skills will have a comparative advantage/be especially promising for founding this idea, but we would like to still encourage applicants from people who do not match this criteria who are enthusiastic about this idea and believe they may be well-suited for reasons not captured here
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