Building and Sustaining Interventions for Children (BASIC): Task-sharing Mental Health Care in Low-resource Settings
Phase: NA
Conditions: Grief, Post Traumatic Stress Disorder, Depression
Sponsor: Duke University

 
 
 
 
Advancing successful implementation of task-
shifted mental health care in low- resource 
settings (BASIC): protocol for a stepped wedge 
cluster randomized trial  
 
NCT03243396 
 
 
Published January 8, 2020 

STUDY PROTOCOL
Open Access
Advancing successful implementation of
task-shifted mental health care in low-
resource settings (BASIC): protocol for a
stepped wedge cluster randomized trial
Shannon Dorsey1*
, Christine L. Gray2, Augustine I. Wasonga3, Cyrilla Amanya3, Bryan J. Weiner4,5,
C. Micha Belden2, Prerna Martin1, Rosemary D. Meza1, Andrew K. Weinhold2, Caroline Soi4, Laura K. Murray6,
Leah Lucid1, Elizabeth L. Turner7,8, Robyn Mildon9 and Kathryn Whetten2,10
Abstract
Background: The mental health treatment gap—the difference between those with mental health need and those
who receive treatment—is high in low- and middle-income countries. Task-shifting has been used to address the
shortage of mental health professionals, with a growing body of research demonstrating the effectiveness of
mental health interventions delivered through task-shifting. However, very little research has focused on how to
embed, support, and sustain task-shifting in government-funded systems with potential for scale up. The goal of
the Building and Sustaining Interventions for Children (BASIC) study is to examine implementation policies and
practices that predict adoption, fidelity, and sustainment of a mental health intervention in the education sector via
teacher delivery and the health sector via community health volunteer delivery.
Methods: BASIC is a Hybrid Type II Implementation-Effectiveness trial. The study design is a stepped wedge, cluster
randomized trial involving 7 sequences of 40 schools and 40 communities surrounding the schools. Enrollment
consists of 120 teachers, 120 community health volunteers, up to 80 site leaders, and up to 1280 youth and one of
their primary guardians. The evidence-based mental health intervention is a locally adapted version of Trauma-
focused Cognitive Behavioral Therapy, called Pamoja Tunaweza. Lay counselors are trained and supervised in
Pamoja Tunaweza by local trainers who are experienced in delivering the intervention and who participated in a
Train-the-Trainer model of skills transfer. After the first sequence completes implementation, in-depth interviews are
conducted with initial implementing sites’ counselors and leaders. Findings are used to inform delivery of
implementation facilitation for subsequent sequences’ sites. We use a mixed methods approach including
qualitative comparative analysis to identify necessary and sufficient implementation policies and practices that
predict 3 implementation outcomes of interest: adoption, fidelity, and sustainment. We also examine child mental
health outcomes and cost of the intervention in both the education and health sectors.
Discussion: The BASIC study will provide knowledge about how implementation of task-shifted mental health care can
be supported in government systems that already serve children and adolescents. Knowledge about implementation
policies and practices from BASIC can advance the science of implementation in low-resource contexts.
(Continued on next page)
© The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence: dorsey2@uw.edu
1Department of Psychology, University of Washington Guthrie Hall 119A, Box
351525, Seattle, WA 98195, USA
Full list of author information is available at the end of the article
Dorsey et al. BMC Psychiatry           (2020) 20:10 
https://doi.org/10.1186/s12888-019-2364-4

(Continued from previous page)
Trial registration: Trial Registration: ClinicalTrials.gov Identifier: NCT03243396. Registered 9th August 2017, https://
clinicaltrials.gov/ct2/show/NCT03243396
Keywords: Global mental health, Implementation science, Evidence-based treatment, Task-shifting, Task-sharing, Children,
Adolescents, School-based mental health care, Organizational theory, Implementation climate,
Background
Eighty percent of the world’s population lives in low and
middle-income countries (LMICs), yet very few of the
world’s mental health resources are in LMICs. Mental
health disorders are now estimated to be first (32.4%) in the
global burden of disease for years lost to disability [1]. With
low tax bases and high population needs, governments in
LMICs spend less than 2% of their health budgets on men-
tal health [2], with most resources targeting care for the
adult, seriously mentally ill population. A critical need exists
to identify strategies to address the mental health treatment
gap for children in LMICs that can be scaled up without
substantial new resources, yet limited implementation re-
search has occurred in global mental health [3, 4].
One commonly used strategy for addressing the shortage
of mental health professionals in LMICs and reducing the
mental health treatment gap is task-shifting [5, 6]. Task-
shifting involves using non-specialists or paraprofessionals
(lay counselors) with little to no prior mental health train-
ing or experience to deliver care, under supervision. A
growing body of research and a recent Cochrane review [7]
provide evidence that task-shifted mental health care is an
effective strategy to address the mental health treatment
gap. Randomized controlled trials (RCTs) across culturally
diverse LMICs (e.g., Zambia [8], Uganda [9, 10], India [11],
Southern Iraq [12]) and populations of focus (e.g., adults,
adolescents, displaced persons, rural areas) indicate that
evidence-based treatments (EBTs) can be effectively deliv-
ered. Effect sizes for primary treatment outcomes are
typically medium to large (with a range of comparison con-
ditions). Some studies also have shown effectiveness for
broader outcomes (e.g., infant health in rural Pakistan [13]
when maternal depression was treated). Outcomes appear
to be sustained in trials that included follow-up (e.g., 6–12
months) [13, 14]. Research indicates provider and client ac-
ceptability and satisfaction with EBTs [15–17]. These stud-
ies suggest that EBT delivery via task-shifting is acceptable
and can be effective, although there are some concerns
about feasibility [16], including the necessary ongoing sup-
port for lay counselors and their organizations to success-
fully implement mental health interventions.
The World Health Organization (WHO) suggests “be-
ginning with the end in mind,” only considering solutions
that might be candidates for scale-up and sustainability
within the low-resource context (i.e., limited funding, few
mental health professionals). Task-shifting is a promising
strategy, however, very limited research has focused on
how to embed, support, and effectively sustain EBTs via
task-sharing in government-funded systems in which they
could be scaled up [16]. The lack of research and know-
ledge in this area is a substantial barrier to bridging the
mental health treatment gap and improving population
health and wellbeing.
Conceptual framework/approach
“Building and Sustaining Interventions for Children
(BASIC): Task Sharing Mental Health Care in Low-Re-
source
Settings”
builds
on
our
15-year
history
of
collaborations with Ace Africa in Kenya, and recent
work evaluating the effectiveness of Trauma-focused
Cognitive Behavioral Therapy (TF-CBT) [19] (“Pamoja
Tunaweza”) with children who experienced parental
death [20, 21] and have mental health impact. Our goal
is to identify locally sustainable implementation policies
and practices (IPPs) that lead to effective implementa-
tion of task-shifted EBT delivery (Pamoja Tunaweza in
this study) in 2 governmental sectors in Kenya, identified
by our Kenyan partners as potential platforms for scale-
up—Education (via teacher delivery) and Health (via
community health volunteer [CHV] delivery). Both Edu-
cation and Health may be viable sectors for mental
health care delivery, but the IPPs that predict implemen-
tation success and intervention effectiveness in either/
both sectors are unknown. In this study, we identify con-
textually relevant, practical, and actionable IPPs that can
inform implementation planning. We also assess child
outcomes and intervention costs in both sectors.
In 2016, Betancourt and Chambers [4] proposed 5 spe-
cific areas to advance implementation science knowledge
around mental health delivery in LMICs (see Table 1).
Our past work addressed the first 2 areas: identifying
Table 1 Specific areas to advance implementation science
knowledge for mental health delivery in LMICs*
Who should deliver practices?
How should they be trained and supported?
How to sustain and adapt?
Use of technology
Cost per outcomes
*Adapted from Betancourt and Chambers, 2016
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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treatment providers and addressing training and support.
Informed by a theoretical model of effective training (the
Training Transfer Conceptual Model [22–24]), we used
implementation strategies [25] including making training
dynamic, modeling and simulating change, and providing
clinical supervision. BASIC extends this work by broaden-
ing attention to include other organizational factors that
may influence lay counselor EBT delivery in either the
Education or Health sector (latter 3 areas in Table 1).
We use Weiner and colleagues’ organizational theory of
implementation effectiveness (Fig. 1), which posits that
effective implementation (e.g., consistent, high-quality
delivery of EBT) depends on the extent to which EBT de-
liverers experience a positive implementation climate, that
is, a shared understanding that EBT delivery is expected,
supported, and rewarded [26]. The extent to which imple-
mentation climate is positive depends, in turn, on the im-
plementation policies and practices (IPPs) put into place
to support EBT delivery. IPPs can include a wide range of
structures and processes such as workload adjustment,
resource provision, and rewards and/or incentives. The
number, type, and strength of IPPs put into place depends
on the organization’s readiness for change.
Methods
Trial design
We employ an incomplete stepped wedge, cluster ran-
domized controlled trial (SW-CRT) design and mixed
methods. For reporting, we follow the Consolidated
Standards of Reporting Trials (CONSORT) for stepped
wedge cluster-randomized trial designs [27] and the
Standard Protocol Items: Recommendations for Inter-
ventional Trials (SPIRIT) guidelines (Additional file 1)
[28]. We conduct a Hybrid Type II Implementation-
Effectiveness trial [29] in both the Education and Health
sectors in Bungoma South Sub-County in Kenya. All
137 primary schools in Bungoma South agreed to par-
ticipate, and 40 schools were randomly selected. The
surrounding community in which each school is nested
is the health sector setting for the trial. The school and
the surrounding community are considered a “village
cluster.” Each of the 40 “village clusters” has 1 team of
teachers and 1 team of CHVs delivering Pamoja Tuna-
weza (TF-CBT [19]). The CHV role in the Kenyan
Health sector is that of extending health services from
health facilities to communities, under the supervision of
a community health extension worker (CHEW). We ran-
domly order the 40 clusters and begin with 10 clusters
in the first of 7 sequences of the SW-CRT (see Fig. 2),
with 3 teachers and 3 CHVs in each cluster (totaling 240
providers) and up to 16 youth per sector per cluster (to-
taling 1280 youth) over the 7 sequences. The sample size
of 40 schools and 40 surrounding communities is se-
lected to allow for examining outcomes at the site/
organization level. This sample size also provides suffi-
cient numbers of counselors by type (teachers, CHVs)
and youth so that we are sufficiently powered to answer
study questions (see Aim 3; Power/Sample Size Calcula-
tion section).
Overview of study aims
In Aim 1, we investigate TF-CBT implementation in the
first sequence of the SW-CRT to identify actionable (i.e.,
modifiable) IPPs associated with successful implementa-
tion in schools and communities with different attri-
butes (see Table 2). We then use these findings to inform
implementation facilitation for subsequent sites (clusters
that initiate intervention in sequences 2–7; 5 schools and
communities per cluster) with BASIC collaborative teams
(BCTs) comprised of Ace Africa staff and selected
teachers/CHVs. To facilitate implementation, we leverage
aspects of community development team models by Cham-
berlain [30] and Aarons [31] in the United States (US). In
Aim 2, we test identified IPPs from the initial sequence,
and other IPPs that emerge in subsequent sequences, as
mechanisms of adoption and fidelity. We also examine IPPs
that predict sustainment for the subset of sites (20 in each
sector) that are followed for at least 2 years after the initial
implementation year. In Aim 3, we examine TF-CBT effect-
iveness (child outcomes) and cost for each sector.
Fig. 1 Determinants of Implementation Effectiveness*Legend: *Adapted from Weiner et al., 2009
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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Study setting
In 2010 the Kenyan government began a decentralization
process [32]. Kenya is divided into 47 counties that have
significant political decision-making, organizational power,
and funding. Kenya’s newly enacted National Mental
Health Policy demonstrates a commitment to mental
health [33–35]. Bungoma County is the third most popu-
lated county in Kenya with 1.7 million residents. Within
Bungoma County, the study takes place in Bungoma South
Sub-County (Fig. 3), which contains both urban and rural
areas. Important for population health, nearly 50% of
Bungoma County’s population are children < 15 years.
Mental health professionals are largely unavailable. In the
Bungoma Township, there are 2 psychiatric nurses and 1
psychiatrist.
Intervention description
We selected TF-CBT, a child/adolescent EBT for psycho-
social sequelae of trauma exposure (e.g., posttraumatic
stress [PTS], depressive symptoms, anxiety), as it has the
strongest empirical base [36, 37]. There are over 15 RCTs
[37], including 1 in Zambia by team members[8]. A feasi-
bility study in Tanzania demonstrated initial acceptability
of TF-CBT for lay counselors, guardians, and children,
with promising clinical outcomes [20]. In this feasibility
study and the recently completed RCT in Tanzania and
Kenya, The Pamoja Tunaweza intervention was 12 weeks
in duration. Each week, 8 children and 1 of their guardians
met concurrently and separately, with joint child-guardian
activities in the final 4 sessions [20, 38]. TF-CBT was de-
livered via 3-counselor teams, with 2 counselors leading
the child group, and 1 leading the guardian group. TF-
CBT components (psychoeducation, parenting, relaxation,
affective modulation, cognitive coping, in vivo exposure
planning, and grief-specific skills) were delivered in
groups, and 2 to 3 individual sessions mid-group were
Fig. 2 BASIC Stepped Wedge Design and TimelineLegend: Figure 2 depicts the overall study design of the incomplete stepped wedge cluster-
randomized trial, including measurement time points for each sequence. A sequence is a group of clusters that initiate the intervention in the
same time period. A step is the specific time point that participants receive the intervention and cross over from being treatment-naïve to having
received treatment
Table 2 Specific implementation policies and practices (IPPs)
Supervision participation
Workload adjustment
Resource provision
Work flexibility
Rewards/Incentives
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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used for the imaginal exposure component (i.e., talking
about/processing traumatic events).
Brief version of TF-CBT
More recent work (2015–16) involved testing a short-
ened 8-session version of TF-CBT (vs. 12 sessions) in
Bungoma South, to be responsive to calls in implemen-
tation science and global health for greater intervention
efficiency with the idea that simpler, shorter interven-
tions [39] may be better candidates for scale-up, even if
they come with a drop in effect size. This 8-session
version, designed collaboratively with the Ace Africa
counselors, includes all TF-CBT elements integrated into
fewer sessions. A pilot study with 63 youth provided pre-
liminary support for using the 8-session version in the
BASIC trial, with BASIC providing a rigorous test.
Participant eligibility and selection
Counselors and site leaders
Given the 3-counselor structure for group TF-CBT, and
40 sites for each sector, we enroll 120 teachers from
Education and 120 CHVs from Health. Following an ini-
tial BASIC sensitization meeting with each site, Ace Africa
works with site leadership to recruit 3 lay counselors. Sites
begin delivering TF-CBT at different times, given the SW-
CRT design. We recruit one leader at each site to partici-
pate in the study but not to deliver TF-CBT (i.e., head
teachers and sometimes deputy teachers in schools; com-
munity health extension workers [CHEWs] in the health
facility to which the CHVs are connected). Teachers who
participate are selected based on being viewed as good
with children experiencing difficulties, and ideally are
not teachers of potential participants (to minimize any
Fig. 3 Bungoma South Sub-CountyLegend: Figure created using material from two sources: Boundaries:Updated November 2017 by Field
Information and Coordination Support Section (FICSS), Division of Programme Support and Management (DPSM), UNHCR.https://data.humdata.
org/dataset/ken-administrative-boundariesWater bodies:Added December 2007 by World Resources Institute (WRI), Nature’s Benefits in Kenya.
https://www.wri.org/resources/data-sets/kenya-gis-data
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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discomfort for children due to teaching and counseling
overlap). Teachers deliver TF-CBT during the school
week, in classrooms, during a 1-hour games time slot.
CHVs are selected using similar criteria (i.e., good with
children experiencing difficulties) and deliver TF-CBT
at a time convenient for them. Delivery can occur in
schools or other community spaces.
Youth and guardians
All single- (1-parent died) or double-orphaned children
(both parents died; UNICEF definitions [40]) ages 11–14
in the area served by the identified school (n~ 40–50 per
cluster) are enumerated in lists provided by both the
schools and communities. The lists are then divided by
sex. Within each sex, children are randomly ordered to
be screened for PTS and prolonged grief using the same
established brief screener and eligibility scores from the
prior RCT. Children can screen in from child- or
guardian-reported PTS symptoms or child-reported pro-
longed grief symptoms. TF-CBT groups are single sex,
with up to 8 children per group. Once 16 children
within a single sex screen in (or list has been exhausted),
the study investigators use a computerized random
number generator to randomize children to receive TF-
CBT through Education or Health. The random assign-
ment lists are then shared with the local interviewers
who enroll and consent participants, and those inter-
viewers call participants to inform participants of the
group to which they have been randomly assigned,
along with corresponding logistical details. In each of
the 40 clusters, up to 32 children (16 girls; 16 boys) and
1 of their primary guardians receive the intervention.
Trained local interviewers obtain informed consent
from all participants in person at the time of enrollment.
For child participants, interviewers obtain both guardian
permission and child assent.
BASIC procedures
Once clusters within a sequence are scheduled to begin im-
plementation, children are screened for TF-CBT eligibility.
Teacher (embedded in the schools) and CHV teams (em-
bedded in villages, via Health) are trained in TF-CBT and
begin practice and supervision. They then provide 2 se-
quential 8-week TF-CBT groups (girls and boys, mapping
onto 2 consecutive trimesters for schools; order of deliver-
ing girl or boy groups first alternates each calendar year).
By the end of the study, this results in 40 sites per sector
(80 total), 120 counselors per sector (240 total, given
counselor teams of 3 in each site), and up to 640 children
per sector (up to 1280 total) receiving TF-CBT (see Table
3).
Prior to cross over, each cluster serves as its own control
(allowing for within-cluster within-subject analyses) and
as a control for clusters in the other sequences that receive
intervention in the same time period (allowing for
between-subject between-cluster analyses and to control
for seasonal and other time effects). Counselors and
leaders in each cluster participate in yearly assessments, as
well as an assessment after they have delivered the 2
sequential TF-CBT groups (1 for each sex). Children
participate in a baseline, end of treatment, and up to 3
annual post-treatment follow-up visits, depending on their
sequence. The open cohort design allows counselors, chil-
dren, and guardians enrolled in a period prior to the one
in which they initiate their intervention to be replaced if
not available or not eligible (e.g., child age > 14) when their
cluster crosses over (i.e., TF-CBT starts) [33, 41].
Trainer training
Ace Africa has 5 experienced TF-CBT counselors from
the RCT who serve as trainers and supervisors (termed
“local trainers”) for counselors in schools and villages.
This team co-developed and piloted the 8-session ver-
sion of TF-CBT for group modality and parental-death
focus. Ace Africa counselors participate in a Train-the-
Trainer (TTT) training led by the first author. The TTT
includes active and experiential strategies to facilitate
adult learning and skill acquisition, following recom-
mendations from reviews of provider training [42, 43].
Following the TTT, the local trainers have 2 months to
refine training plans, practice training, and receive sup-
port. Local trainers receive weekly group supervision
from TF-CBT experts on the study team during their
first year in this role (1–1.5 hours per week, via Skype
audio). In year 2 and forward, they continue to receive
weekly support, but the focus is more on monitoring
participant safety and logistics (i.e., monitoring imple-
mentation, applying the established safety protocol, and
study timelines).
Counselor training and supervision
Following the Apprenticeship Model [44], local trainers
provide 5–6 days of training for lay counselors (with separ-
ate trainings for teachers and CHVs). Using the same for-
mat of the TTT, lay counselors first receive didactic
training and manuals for each session (i.e., “step sheets”
for session delivery). Next, they participate in an experien-
tial activity when relevant (e.g., trying cognitive coping),
discuss benefits to build buy-in, read the steps one-by-one
Table 3 Participant Distribution
Education
Health
Sites
40
40
Counselors
120
120
Groups
80
80
Youth
640
640
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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as a group, and then observe the trainer(s) modeling the
skills while following along on the step sheets. Finally,
trainees break into small groups and practice with
both trainer and peer feedback.
Supervision/intervention quality assurance procedures
Following the in-person training, 1 local trainer begins
weekly supervision with each counselor team. Supervision
involves discussing the past session and role-playing up-
coming sessions. Supervision is delivered via a mix of in-
person and use of audio or video (e.g., phone call, review
of videotaped role-play) with some support provided via
text messaging, following remote supervision procedures
from the RCT. Local trainers look for strong counselors
who may be candidates for future TF-CBT leadership
positions (e.g., future supervisors themselves, BASIC col-
laborative team members; see Aim 1 Procedures). In the
sustainment phase, supervision occurs less frequently
(e.g., 1 x/month), and is less frequently provided in-
person.
Fidelity monitoring
Counselors complete a brief report for each session that
includes child/guardian attendance, a self-report on fi-
delity to the session, and a brief note on participant re-
sponse. Reports are reviewed by local trainers to inform
supervision. Local trainers conduct live observation of
groups 2x/month to both inform supervision and con-
duct fidelity monitoring during the initial implementa-
tion year and strive for 1x/month during sustainment.
Data sources
Implementation policies and practices (IPPs)
For Aim 1/Sequence 1, IPPs are measured via quantita-
tive measures and from qualitative interviews with
counselors and leaders from selected sites participating
in the case comparison analysis (see Aim 1). For Aim
2/Sequences 2–7, IPPs are measured using work plans
and follow-up forms from implementation facilitation
meetings (see Aim 2).
Primary study outcomes
The primary outcomes of interest are TF-CBT adoption,
fidelity, and sustainment. Adoption is defined as delivery
of 2 on-site 8-session TF-CBT groups by a 3-counselor
team and is measured by counselor self-report (and con-
firmed by supervisors). Fidelity includes assessment of ad-
herence and competency and is primarily measured by
supervisors’ observations of TF-CBT groups using 1–6
ratings on adherence and 1–6 ratings on competence.
Each week, even when live observation does not occur,
the supervisor completes the same adherence and fidelity
ratings (1–6) based on review of counselor reports and
supervision interactions with the counselors. Based on
studies that examined sustainment of other health inter-
ventions in African countries [41] and sustainment re-
views [45, 46], we define sustainment as maintained
delivery 2 years after the study intervention period (2
groups delivered within a calendar year, with at least 80%
capacity as compared to their group enrollment during
initial implementation).
Secondary study outcomes
We use brief, validated measures from our prior work in
Kenya (already translated, back-translated, vetted for ap-
propriateness/understanding, and Institutional Review
Board (IRB)-approved [Duke Health & Kenya IRBs] to
assess children’s mental health from both child and
guardian perspective (e.g., trauma exposure, PTS, pro-
longed grief), and other relevant outcomes and con-
structs (e.g., strengths and difficulties, substance use,
child-guardian relationship, and social support). Also in-
cluded are several measures to address the priorities of
interest to Kenyan policy makers due to value and/or
high societal cost (e.g., orphan stigma, excessive labor,
and HIV-risk behavior [at post-intervention follow-up
for children ≥age 16]).
Cost
We take a payer’s perspective and measure both direct
and indirect costs for each sector, including those that
have
been
paid
for
from
grant
funding,
excluding
research-related costs. Costs are allocated to their funding
mechanism and each listed explicitly so that policy makers
can assess both total costs and cost elements so that they
can work with Education and Health to reduce or increase
costs (understanding associated outcomes). Direct costs to
the Education sector include teacher salaries, administra-
tive salaries, supplies provided, salary of teachers who fill-
in for the teachers providing the intervention, communi-
cation costs, transportation costs for trainings and super-
vision, and any incidentals that they may provide to
caregivers or children. Direct costs to the Health sector
are similar with the added cost of a stipend for the CHVs.
Indirect costs to the Education and Health sectors that
will need to be covered in the future are the costs of the
salaries and benefits of local trainers, supervision, and the
training costs including training time and venue rental.
Covariates
At baseline, we collect data on organizational, leader,
and counselor characteristics that may affect interven-
tion implementation and/or intervention effectiveness.
At the organizational level, covariates include staffing
(number of teachers or CHVs), size (number of children
in the school; size of the community), and existing pro-
grams. Organizational information is mostly collected
via interviews with the site leader (head teacher/deputy
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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teacher or CHEW) using a measure designed for the
purposes of this study. We also use standardized mea-
sures designed to capture organizational readiness [47]
and implementation climate [48] that were reviewed for
appropriateness by Kenyan partners and translated/back-
translated to ensure construct validity. At the leadership-
level, we assess general leadership [49] and implementation-
specific leadership [50], also using standardized measures for
which we followed similar procedures as the organizational
measures. At the counselor-level, we capture demographics
(e.g., age, sex), background characteristics (e.g., years in role,
education), any training in, or past experience with
mental health, and participation in supervision (e.g.,
dose). When possible, we also assess other implementa-
tion constructs using existing measures developed for
use in low-resource contexts [51] and/or standardized
measures reviewed and translated for appropriateness
to assess intervention acceptability, feasibility [52], and
perceived intervention effectiveness [51]. For theorized
important constructs for which existing scales are not
available or are not relevant (i.e., behavioral control, be-
havioral
intentions,
self-efficacy,
appropriateness,
innovation-values fit), we followed measure construc-
tion guidelines from the Theoretical Domains Frame-
work [53, 54].
We also assess child, guardian, and community-level co-
variates that may impact implementation or intervention
effectiveness. At the child- or guardian-level, these include
child and guardian demographics (e.g., child age, sex, tribe)
and background characteristics (e.g., child and guardian
health, household composition, educational status, eco-
nomic status, etc.). We assess several community-level
characteristics (e.g., total number of orphans ages 11–14,
main
occupations
in
communities,
perceived
social
mobility).
Aim 1: identify actionable IPPs that predict adoption
(delivery) and fidelity (high-quality delivery) after 10 sites
in each sector implement TF-CBT
Aim 1 procedures
The goal of Aim 1 is to identify IPPs from the initial 10
schools and 10 communities in Sequence 1 (see Fig. 2)
to both guide implementation support for subsequent
sites (Aim 1a) and to generate testable hypotheses about
IPPs that may predict implementation success, which
will be tested in Aim 2 using data from all sites (40
schools; 40 villages). Following delivery of TF-CBT in
Sequence 1 (10 sites in each sector), we conduct a case
comparison analysis in which we identify 6 sites per sec-
tor (12 total) that represent unique aspects of the sites
(e.g., urban vs. rural; higher/lower levels of leader sup-
port; student-teacher ratio) that might result in different
ways in which sites successfully implement TF-CBT.
Each site (school or village) is considered a case. Both
qualitative and quantitative data are collected from
counselors (N = 36) and leaders (N = 12) to understand
barriers and facilitators to TF-CBT implementation and
IPPs that are unique to each sector (Education vs.
Health), overlapping across sectors, and those that may
be related to site characteristics (e.g., rural location;
small school).
Aim 1 analyses
We use a case comparison analysis, in which mixed
methods are used to understand IPPs associated with
successful implementation in Education and Health. A
subset of successfully implementing sites (6/10 schools;
6/10 communities) are selected for heterogeniety on
demographic and other characteristics (e.g., large school
vs. small schools; urban vs. rural communities) to ex-
plore how implementation processes differ, such as the
number and type of IPPs deployed as well as variation in
how IPPs are deployed (e.g., whether leadership took dif-
ferent forms in different cases). We code data from in-
terviews with counselors (teachers; CHVs) using a
deductive approach [55] to identify IPPs from Weiner’s
organizational theory of implementation effectiveness
[26] and the literature [56]. Other IPPs that emerge dur-
ing interview review are also incorporated into the code-
book. All interviews are double-coded and discrepancies
are reconciled through discussion to consensus [55]. In
order to achieve convergence [55], qualitative data are
examined alongside quantitative data on organizational,
leader, and counselor-level constructs.
Following the case comparison analysis, the Ace Africa,
University of Washington (UW), and Duke teams review
and discuss findings. A priority is establishing straightfor-
ward, simple language for implementation constructs (e.g.,
implementation climate) that can be understood by all
stakeholders. A 3-day BASIC Collaborative Team (BCT)
meeting is then held with BASIC participants and stake-
holders with the goal of collaboratively building plans for
implementation facilitation for subsequent sequences. The
BCT includes Ace Africa, UW, and Duke study members
and local trainers, selected counselors and leaders from
high-performing sites in Sequence 1, and other stake-
holders (Ministry officials). The Ace Africa team presents
results from Sequence 1 sites, orients the BCT to goals
(provide future sites with support), and presents identified
barriers and IPPs, including attention to variation by sec-
tor and site (urban/rural). Members split into Education
and Health teams to discuss identified IPPs and generate
additional ideas for actionable IPPs that would be practical
in their setting. Ace Africa members facilitate this work,
ensuring the focus remains on actionable IPPs (i.e., prac-
tical and feasible strategies; not those requiring new fund-
ing or resources). BCT members also collaborate on
developing the appropriate timeline for implementation
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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facilitation visits (i.e., frequency, timing), materials to
guide facilitation (called "coaching" locally) for each visit,
which IPPs should be prioritized (among those used in
Sequence 1 sites), and which IPPs need to be addressed at
which visits. By the end of the retreat, we have a list of
IPPs for each sector from which sites could select IPPs for
their own implementation planning, and a plan for facili-
tation visit frequency (6 meetings) and timing (e.g., before
TF-CBT training, immediately post-training, early in de-
livery, planning for sustainment).
Implementation facilitation for new sites
A subset of BCT-attendees is selected as the initial im-
plementation facilitators for sites in Sequences 2–7. One
local Ace Africa trainer and 1 counselor from an experi-
enced site (teacher or CHV) form a facilitation team that
supports new sites in implementation. Leaders (head
teachers, CHEWs) from experienced sites also are in-
cluded in facilitation, but due to job demands, primarily
connect with new leaders by phone (vs. in-person). Dur-
ing each visit, facilitators support new sites in developing
tailored plans to support implementation using IPPs
identified in the BCT.
Aim 2. Identify causal conditions that explain
implementation success in both sectors
The goal of Aim 2 is to identify causal conditions of
adoption and fidelity, including hypothesized IPPs from
Aim 1 (some targeted in implementation facilitation)
and any additional IPPs that emerged during implemen-
tation in all sites (Aim 2a). We also identify causal con-
ditions that predict sustainment in both sectors (Aim
2b). We examine sustainment for the subset followed for
2 years after the initial implementation year (20 in each
sector). We expect that causal conditions that predict
adoption, fidelity, and sustainment will include: 1) IPPs
targeted by implementation facilitation (e.g., workload
adjustment so counselors can provide TF-CBT), 2)
other, non-targeted implementation factors from our
conceptual model (e.g., organizational climate), and 3)
additional important, but less actionable constructs (e.g.,
leadership turnover; delays in salary provision).
Aim 2 analyses
For Aim 2, we use generalized-set qualitative comparative
analysis (QCA) [57]. QCA is a configurational approach
that uses Boolean algebra to investigate logical relation-
ships between causal conditions and an outcome of
interest [58, 59]. QCA enables work with small samples
[58, 60–64], and assumes causality is complex [58, 62, 65,
66]. This complexity occurs via equifinality (i.e., multiple
causal pathways to same outcome), and/or conjunctural
causation (i.e. pathways in which combinations of causal
conditions result in the outcome of interest) [58]. QCA is
particularly appropriate for investigating which causal
conditions are necessary, and which combinations of
causal conditions are sufficient to produce the outcome
(e.g. acceptable fidelity) in small samples [58, 66]. Accept-
able fidelity in some schools may require IPPs A and B,
combined with specific individual-counselor characteristics,
but other schools may require IPPs B and C (but not A).
For example, Table 4 illustrates the necessity of supervi-
sion (a causal condition present in all cases of acceptable
fidelity), and the sufficiency of supervision with varying
counselor characteristics (e.g., positive intention), otherl
IPPs (e.g. workload adjustment and/or resources), and
varying organizational context (e.g., positive organizational
climate,
and/or
positive
organizational
readiness
for
change, and/or positive innovation-values fit). In Health,
some combinations (“recipes”) may overlap with Educa-
tion, while others may be unique.
We will investigate necessary and sufficient causal con-
ditions and pathways that explain adoption, fidelity, and
sustainment of TF-CBT using Boolean minimization [67]
procedures. We follow the QCA procedural protocol out-
lined by Thiem [68] for elimination of redundant causal
conditions (variables) by transforming the raw data into a
data matrix (truth table), minimization of the truth table
to a prime implicant (PI) chart, and decomposition of the
PI chart to investigate necessary causal conditions. The
minimum number of cases required to identify a set of
conditions that lead to the outcome of interest will be set
to 1 to maximize inclusiveness [58]. We will evaluate
coverage, how much of the outcome is explained by each
causal pathway and the solution term, and consistency, the
degree to which sites exhibiting a specific combination of
Table 4 Examples of Possible Combinations of Constructs Resulting in High Fidelity
Intention
Implementation Policies and Procedures
Organizational Context
High
Fidelity
Positive
Intention
High
Supervision
Leader Signals
Support
Workload
Adjustment
Resources
High Org.
Readiness
Positive
Implementation
Climate
Positive Innovation
Values Fit
Case 1
No
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Case 2
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Case 3
No
Yes
No
Yes
Yes
No
Yes
Yes
Yes
Case 4
Yes
Yes
No
Yes
Yes
Yes
No
No
Yes
Dorsey et al. BMC Psychiatry           (2020) 20:10 
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conditions also exhibit the outcome of interest, as outlined
by Schneider and Wagemann [69]. We will report on
model ambiguity [70, 71] and present empirical results
using the parsimonious solution type to avoid the poten-
tial for reporting results that claim causal relationships
with no evidence [72].
Aim 3. Test TF-CBT effectiveness (child mental health,
functioning) and cost in both sectors
Results from Aim 3 will be needed to influence policy
changes. Understanding TF-CBT’s effectiveness when
delivered in Health and Education is important. Know-
ing the cost in Education and Health is critical for
decision-making of interested government sectors to
continue TF-CBT scale-up throughout the county and
country. We select a cost accounting and comparison
approach due to its flexibility, ease of use, ability to
easily identify item-by-item costs and change the out-
come of interest as desired by local policy makers and
implementers. We measure costs of the intervention for
improvement in children’s mental health outcomes. We
will also provide the costs of the intervention as imple-
mented by teachers and CHVs with the societal benefits
of school retention, passage of the exam to enter sec-
ondary school, and fewer high-risk sexual activities. In
low-resource settings, even seemingly small differences
in cost are important.
Aim 3 analyses: TF-CBT effectiveness
A combination of within-cluster within-child and between-
cluster between-child data is used to assess intervention
effectiveness on child outcomes. We will examine theoret-
ically relevant covariates and, importantly, include imple-
mentation outcomes from Aim 2 (i.e., adoption, fidelity).
For statistical models, we will use a stepped-wedge analytic
approach that leverages the staged scale-up of TF-CBT
[73]. Continuous child outcomes will be assessed using lin-
ear mixed models. Dichotomous child outcomes will be
assessed using generalized linear mixed models with a log
or logit link for relative effects and with an identity link for
absolute effects if models converge. We will analyze the
unit increment or decrement (or probability for dichotom-
ous measures) of an outcome (e.g. PTS) at a given time,
with fixed effects for time and intervention status and ran-
dom effects for cluster and child. All analyses are intent-to-
treat. Because there are 2 different sectors for delivery
(Education and Health) and a comparison condition, inter-
vention status is a 3-level factor to be modeled as 2 dummy
variables. We will evaluate change in pairwise correlation
of within-child repeated measures over time, as well as
pairwise correlations between different children in the
same cluster at different time points. We will include
random slopes for interaction of child with time or of clus-
ter with time, as appropriate [74, 75]. Correct correlation
structure specification is important to avoid bias in
estimated effects [74, 75]. Additional analyses will
explore potentially relevant interactions that may indi-
cate effects within sector.
Handling missing data
We will use available data to examine patterns and pre-
dictors of missingness both by sequence and condition
to assess potential for biased estimated treatment effects.
Because likelihood-based modeling approaches are valid
under the missing at random assumption, including the
situation where predictors measured at time of enroll-
ment are predictive of missing outcomes, our primary
analytic approach can provide valid inference if covari-
ates predictive of missingness are included in the model.
We will perform sensitivity analyses that adjust for those
covariates. If we identify evidence that the missing at
random assumption is violated, alternative pattern mix-
ture approaches will be used as sensitivity analyses [76].
Power/sample size calculation
The SW-CRT design may be more efficient than other
cluster trials, particularly when intracluster correlation
coefficients (ICC) are high [77, 78]. To assess sensitivity
to underlying assumptions, we used the Shiny CRT Cal-
culator [79] to calculate power for standardized effect
sizes for an incomplete SW-CRT cohort design with 40
clusters (12 youth per sector per cluster) randomly
assigned to 7 sequences under 3 different correlation
structures. Detailed specifications and assumptions are
included in Additional file 2 [79–83]. The power to de-
tect effect sizes as low as .25 at the 2-tailed .05 level of sig-
nificance
was
estimated
to
be
99%
assuming
an
exchangeable correlation structure, 95% assuming 2-
period decay, and 92% assuming discrete time decay.
Study power is very good, even with the most flexible
model (discrete time decay).
Aim 3 analyses: cost accounting
Direct and indirect costs of TF-CBT will be collected
systematically from schools (e.g., salaries, fringe, mate-
rials provided, room costs, teacher substitution for
missed classes, etc.), CHEWs, CHVs, and Ace Africa
(e.g., air time, supervisor salary and fringe, transporta-
tion costs, etc.). Costs will be summarized by category
to allow policy makers and future implementers to
easily identify what costs can be altered or might vary
depending on context.
Detailed data management procedures, composition of
the data monitoring committee, unintended effects, pro-
cedures for auditing trial conduct and communicating
protocol modifications, model consent forms, and ques-
tionnaires can be found in our IRB protocols.
Dorsey et al. BMC Psychiatry           (2020) 20:10 
Page 10 of 14

Dissemination
Sharing early findings with participants, ministry leaders
and other stakeholders is built into the design of BASIC
with the BCTs and implementation
facilitation. In
addition, communications via reports and in-person dis-
cussions with ministry leaders, community leaders, site
leaders, and participants enable audience-specific dis-
semination of findings. Peer-reviewed publications and
conference abstracts will adhere to journal and profes-
sional standards for authorship and will include all rele-
vant collaborators. The data are sensitive in nature and
may not be sufficiently “de-identifiable” as to remain
useful while maintaining confidentiality. To the extent
data are de-identifiable, we will make data available in
accordance with IRB and National Institutes of Health
guidance.
Discussion
This study is the next step in our research agenda of
testing the effectiveness of EBTs in successive stages that
systematically increase local expertise and responsibility
and decrease external expert involvement. The goal is to
learn what makes an “enabling” context—that is, what
policies and practices are necessary for supporting
the delivery of mental health interventions. Our ultimate
goal is to enhance knowledge around effective, feasible,
and
sustainable
implementation
strategies
in
low-
resource contexts globally. We leverage the increasing
body of evidence supporting community-based, collab-
orative approaches to provide implementation support,
given their substantial promise for local ownership, over-
sight, and fit with the cultural context. These approaches
offer a potentially sustainable avenue in low-resource
settings where budgets are constrained and monetary in-
centives are low. To our knowledge, this is the first study
to examine questions related to scale-up and sustainability
of a child-focused EBT in both Education and Health, and
one of few global implementation studies that includes an
organizational focus and a focus on sustainment. In a sus-
tainability review of health interventions in Sub-Saharan
Africa, none focused on mental health and most focused
on what was sustained, not by whom or how [41].
The rollout of TF-CBT in Education and Health to
date has been welcomed, with all sites expressing
interest in TF-CBT training and adoption. From early
qualitative interviews and responses on quantitative
scales from the first 10 clusters beginning implemen-
tation in Sequence 1, teachers and CHVs trained in
TF-CBT seem to find the intervention acceptable, be-
lieve it will have benefits for children, and have noted
the applicability of the skills for their own lives and
community. We have observed inter-ministerial col-
laboration that appears to support implementation,
with ministries working together to provide TF-CBT
to their community (e.g., schools offering classrooms
to
CHVs
for
holding
groups;
CHVs
supporting
teachers with outreach to guardians in the community).
Ace Africa supervisors have creatively used technology to
facilitate supervision and lessen the need and cost of in-
person supervision by using short message service (SMS)
and WhatsApp to communicate, and sometimes to review
counselors’ practice (e.g., reviewing an audio recording of
counselors’ practice role play, uploaded using WhatsApp).
The implementation facilitation teams initiated facilitation
smoothly after the BCT, and Ace Africa supervisors anec-
dotally report that the facilitation intervention, initiated for
Sequence 2 clusters, seems to be beneficial.
However, there have been practical challenges, includ-
ing higher than expected costs for a few implementation
activities. Hosting training for teachers and CHVs (train-
ing venue, catering, transportation reimbursements) has
been more expensive than expected. Transportation for
supervisors to meet with their counselors in-person on
occasion, and to observe groups, has also been costly.
Due to our focus on children who are parentally-
bereaved, small schools with fewer students do not
always have as many orphaned children in need of men-
tal health care and groups may consist of fewer than 8
children, lowering the overall child sample in our study.
Finally, while expected from the literature and our own
experience [15], guardian attendance at groups has been
more inconsistent than child attendance, given that
many guardians are busy with livelihood-generating ac-
tivities, and some send children to schools that are not
their village school (if another school has better aca-
demic performance). Thus, guardians may not be in
close walking distance to schools, hindering participation
in TF-CBT sessions. To engage guardians, counselors
often do more outreach and provide individual make-up
sessions for guardians. While this addresses the clinical
challenge, it adds burden to counselors, increasing the
time they spend delivering TF-CBT.
The potential promise of task-sharing for closing the
mental health treatment gap goes unrealized if evidence-
based guidance to inform scale-up and sustainment is
unavailable. Results from the BASIC trial should provide
information that will be beneficial for organizations,
their leaders, ministry officials, and policy makers look-
ing to implement mental health therapies into existing
systems. Our focus on identifying policies and practices
that support implementation in two different sectors
within a low-resource context should generate pragmatic
guidance for how to support mental health service deliv-
ery that could be broadly applicable.
Trial status
At the time of manuscript submission (October 2019), the
study is ongoing; we are in the early stages of data
Dorsey et al. BMC Psychiatry           (2020) 20:10 
Page 11 of 14

collection. We have enrolled children and guardians for Se-
quences 1–3 (20 of 40 clusters), as well as counselors and
site leaders for all sequences. Additionally, implementation
facilitation for Sequences 2 and 3 have begun; Sequence 4
will commence in January 2020.
Supplementary information
Supplementary information accompanies this paper at https://doi.org/10.
1186/s12888-019-2364-4.
Additional file 1. SPIRIT protocol checklist.
Additional file 2. Specifications of power calculations.
Abbreviations
BASIC: Building and Sustaining Interventions for Children; BCT(s): BASIC
Collaborative Teams; CHEW(s): Community health extension workers;
CHV(s): Community health volunteers; CONSORT: Consolidated Standards of
Reporting Trials; EBT(s): Evidence-based treatments; HIV: Human
Immunodeficiency Virus; ICC: Intracluster correlation coefficient;
IPP(s): Implementation policies and practices; IRB: Institutional Review Board;
KEMRI: Kenya Medical Research Institute; LMIC(s): Low- and middle-income
countries; MPI(s): Multiple Principle Investigators; NIMH: National Institutes of
Mental Health; PI: Prime implicant; PTS: Posttraumatic stress; QCA: Qualitative
comparative analysis; RCT(s): Randomized controlled trials; RDAC: Research
Design and Analysis Core; SMS: Short message service; SPIRIT: Standard
Protocol Items: Recommendations for Interventional Trials; SW-CRT: Stepped
wedge, cluster randomized controlled trial; TF-CB: Trauma-focused Cognitive
Behavioral Therapy; TTT: Train-the-Trainer; UNICEF: United Nations Children
Fund; US: United States; UW: University of Washington; WHO: World Health
Organization
Acknowledgements
We thank the Ace Africa TF-CBT supervisors and interviewers: Elijah Agala,
Lilian Aluka, Oliver Hillary, Moses Malaba, Emmanuel Muli, Micah Nalianya,
Bernard Nabalia, Michael Nangila, Sheila Nderitu, Daisy Okoth, Omariba Nya-
boke, Victor
Shalakha, Annette Sulungai, Sylvia Wafula, and Nelly Wandera. We also thank
the Research Design and Analysis Core (RDAC) in the Duke Global Health
Institute at Duke University and Eric Green, for support with design and
analysis. We are grateful to the Ministry of Health, Ministry of Education,
Teachers Service Commission, participating schools, communities, children,
and families who are taking part in BASIC.
Authors’ contributions
Study concept and design: SD, KW, AIW, CA, BJW, CLG, and MB. Drafting of
the manuscript: SD, KW, CLG, AIW, CA, MB, PM, RDM, AW, CS, LL, BJW, ELT,
LKM, and RM. Administrative, Technical, or Material Support: SD, AIW, CS, and
RM. Study supervision: SD, LL, KW, CS, and AW. All authors have read and
approved the manuscript.
Funding
Funding for this research project was supported by a grant to the first and
last authors by the National Institute of Mental Health (R01 MH112633;
Dorsey & Whetten, MPIs) and an NIMH-funded Diversity Supplement
(MH112633; Meza). The Center for Evidence and Implementation provided
additional funding to support BASIC. The funders/sponsor have no role in
study design or analysis.
Availability of data and materials
The data generated from this study will be available from the corresponding
author on reasonable request.
Ethics approval and consent to participate
All participants will provide informed consent prior to study participation.
Written informed assent is obtained from children; the caregiver provides
written informed consent for their own participation and permission for the
child to participate. The Institutional Review Boards of Duke Health (Protocol
# Pro00081913) and the Kenya Medical Research Institute (KEMRI) (Protocol #
598) have approved the trial.
Consent for publication
Not applicable.
Competing interests
Dorsey and Murray have received honoraria for providing TF-CBT training
and have received grant funding to test TF-CBT. Whetten also has received
grant funding to test TF-CBT. Other authors declare that they have no com-
peting interests.
Author details
1Department of Psychology, University of Washington Guthrie Hall 119A, Box
351525, Seattle, WA 98195, USA. 2Center for Health Policy and Inequalities
Research, Duke Global Health Institute, Duke University, Campus Box 90392,
Durham, NC 27710, USA. 3Research Department, Ace Africa Kenya, P.O. Box
1185, Bungoma 50200, Kenya. 4Department of Global Health, University of
Washington, Harris Hydraulics Laboratory, 1510 San Juan Road, Seattle, WA
98195, USA. 5Department of Health Services, School of Public Health,
University of Washington, Box 357965, Seattle, WA 98195, USA. 6Department
of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N.
Broadway, 8th floor, Baltimore, MD 21205, USA. 7Department of Biostatistics
and Bioinformatics, Duke University School of Medicine, Duke University,
Durham, NC 27710, USA. 8Duke Global Health Institute, Duke University,
Campus Box 90519, Durham, NC 27708, USA. 9Centre for Evidence and
Implementation, 33 Lincoln Square South, Carlton, Victoria 3053, Australia.
10Terry Sanford Institute of Public Policy, Duke University, Box 90239,
Durham, NC 27708, USA.
Received: 28 October 2019 Accepted: 15 November 2019
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