# PRIDE SSA - Partnerships in Research to Implement and Disseminate Sustainable and Scalable Evidence Based Practices in sub-Saharan Africa

> **NIH NIH U19** · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · 2020 · $342,400

## Abstract

Addressing the global mental health (MH) treatment and research gaps requires scaling up efficacious
treatments using feasible, sustainable venues that leverage existing platforms supported by sustaining policies.
The PRIDE: sub Saharan Africa MH Hub established a collaborative network of researchers, community-
advocates, service providers and policy makers across Sub-Saharan Africa to build capacity and conduct
implementation research to sustainably scale-up MH services. This hub may generate templates for other LMICs as
well. In the parent grant, the Scale Up Research evaluates strategies and costs of scaling up an innovative,
sustainable MH integrated stepped-care community approach for mental and substance use disorders in
Mozambique. We leverage Mozambique’s task-shifting strategy which trained psychiatric technicians (PsyTs) to
provide MH care throughout the country. Our partnership between researchers, providers, and community and
policy stakeholders will scale-up a cost-effective and sustainable program and inform policy applicable to other
LMICs. PRIDE is optimally poised to respond to the RFA in ways that could be transformative to the diagnosis
and treatment of age-related neurocognitive disorders ranging from mild cognitive impairment (MCI) to
Alzheimer’s Disease in LMICs, offering a cost-effective scalable tool to the field. Identifying elderly at risk for
dementing illnesses is particularly challenging in LMICs. Even where professionals are available, traditional
neuropsychological batteries for evaluating dementia or MCI require hours to administer and scoring and
interpretation by highly trained personnel. The University of Pennsylvania (Penn) computerized neurocognitive
battery (PennCNB) offers an alternative approach optimally suitable for LMICs. PennCNB is a compilation of
neuroscience-based tests that have been validated with functional neuroimaging and in clinical settings and
takes less than an hour to administer. It has an established factorial structure and is sensitive to sex differences,
age effects, and the presence of neurocognitive deficits across the lifespan. The Penn group will leverage on a
current R01 (MH117014; PI: Gur, RC; “Creating an adaptive screening tool for detecting neurocognitive deficits
and psychopathology across the lifespan”, 5/1/19-2/28/23) and deploy a computer adaptive testing (CAT) version of
the PennCNB (PennCNB-CAT). PennCNB-CAT uses innovative methods that incorporate item response theory
to substantially cut administration time to about 30-35 minutes, without loss of information or reliability. We will
deploy the PennCNB-CAT in a sample of 500 patients and healthy controls from the Mozambique sites of the
PRIDE, of whom 200 will be recruited from clinics for the elderly. This pilot study will allow establishing the feasibility
of administration and the ability of the battery to detect age associated cognitive decline as well as MCI, AD and
other dementing disorders. If successful, this proj...

## Key facts

- **NIH application ID:** 10123814
- **Project number:** 3U19MH113203-04S2
- **Recipient organization:** NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
- **Principal Investigator:** Maria A Oquendo
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $342,400
- **Award type:** 3
- **Project period:** 2017-05-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10123814

## Citation

> US National Institutes of Health, RePORTER application 10123814, PRIDE SSA - Partnerships in Research to Implement and Disseminate Sustainable and Scalable Evidence Based Practices in sub-Saharan Africa (3U19MH113203-04S2). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10123814. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*