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J Gandhara Med Dent Sci
ORIGINAL ARTICLE
:
:
April - June 2026
ASSESSING STAFF READINESS FOR INTEGRATED TUBERCULOSIS DIABETES CARE IN
DIFFERENT DISTRICTS OF PAKISTAN: A CROSS-SECTIONAL STUDY USING THE R = MC²
IMPLEMENTATION FRAMEWORK
Saima Aleem
1
, Saima Afaq
2
, Zeeshan Kibria
3
, Rida Zarkaish
4
, Zohaib Khan
5
How to cite this article
Aleem S, Afaq S, Kibria Z, Zarkaish
R, Khan Z. Assessing Staff Readiness
For Integrated Tuberculosis Diabetes
Care In Different Districts of Pakistan:
A Cross-Sectional Study Using The R
= Mc² Implementation Framework. J
Gandhara Med Dent Sci.
2026;13(2):3-11
Date of Submission: 02-03-2026
Date Revised: 11-03-2026
Date Acceptance: 14-03-2026
2
Associate Professor, Institute of
Public Health & Social Sciences,
Khyber Medical University, Peshawar
3
Additional Director, Oice of
Research Innovation &
Commercializtion, Khyber Medical
University, Peshawar
4
Research Associate, Oce of
Research Innovation &
Commercializtion, Khyber Medical
University, Peshawar
5
Director, Oce of Research
Innovation & Commercialization,
Khyber Medical University, Peshawar
Correspondence
1
Saima Aleem, PhD Scholar, Institute
of Public Health & Social Sciences,
Khyber Medical University, Peshawar
+92-346-9196731
saima.aleem@kmu.edu.pk
ABSTRACT
OBJECTIVES
This study aimed to assess TB sta readiness to integrate diabetes care within
TB services in selected basic medical units in Pakistan using the R = MC²
implementation framework.
METHODOLOGY
We conducted a cross-sectional study to assess sta readiness across 13 TB
Basic Management Units in 5 districts of Pakistan from November 2024 to
April 2025. We conceptualized readiness in three dierent domains, that is,
Motivation, General Capacity, and Capacity for Change, rather than in one
composite index, and we measured it at the construct level. DOTS facilitators
directly involved in TB service delivery completed a structured questionnaire
measuring motivation (12 items), General Capacity (5 items), and Capacity
for Change (4 items). We performed reliability analysis using Cronbach’s
alpha. Although composite scores were calculated to provide descriptive
information, interpretation focused on domain-specic results to maintain
theoretical consistency and construct validity.
RESULTS
Thirteen DOTS facilitators from primary (n=4), secondary (n=5), and
tertiary (n=4) TB facilities participated. Reliability was acceptable for
motivation (α = 0.802) and excellent for General Capacity (α = 0.918), while
Capacity for Change showed moderate reliability (α = 0.548). Motivation
was high (mean = 4.2), whereas General Capacity was lowest (mean = 2.9),
reecting resource, training, and coordination gaps. Capacity for change
was moderate (mean = 3.3). A strong correlation was observed between
General Capacity and Capacity for Change (r = 0.69, 95% CI 0.20–0.90, p <
0.009).
CONCLUSION
The study ndings highlighted that sta in TB BMUs were greatly motivated
to incorporate TB–DM care, yet the capacity limitations constrain the
readiness. Scaling up integrated care should be preceded by strengthening
operational resources, coordination, and implementation support.
KEYWORDS: Tuberculosis, Diabetes Mellitus, Integrated Care,
Organizational Sta Readiness, Implementation Science, Pakistan
INTRODUCTION
Tuberculosis (TB) and diabetes mellitus (DM) represent
two converging global epidemics with profound
implications for public health systems.
1
Individuals
with diabetes have a two- to three-fold higher risk of
developing active TB, and diabetes contributes to
delayed sputum conversion, higher relapse rates, and
poorer treatment outcomes.
2
As the global burden of
non-communicable diseases (NCDs) continues to rise,
the intersection of TB and diabetes poses complex
service delivery challenges that extend beyond
traditional programmatic boundaries.
3,4,5
Effective
management of this comorbidity requires integrated
models of care that link communicable and NCD
services within existing health-system structures.
Despite tuberculosis and its comorbidities being
prioritized in international policy frameworks for
integrated care, the guidelines have been inconsistently
and unevenly translated into routine practice.
6,7
At the
facility level, it is usually dicult to integrate diabetes
care into routine TB treatment and services due to
fragmented health services, vertical funding, and
competing priorities. In addition, integration demands
bi-directional screening, redesigning care pathways, and
the addition of new documentation by frontline
providers. These shifts and transformations occur
within health systems that are already understaed,
have weak supply chains, and lack consistent leadership
backing.
8
Determining the extent to which these
https://doi.org/10.37762/jgmds.13-2.875
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April - June 2026
systems are prepared to change is thus a very important
pre-implementation measure. The eectiveness of
complex health interventions depends on sta
motivation and the organization’s ability to change.
9,10
In the context of TB-diabetes comorbidity, these factors
determine the success or failure of integration eorts.
Evaluating preparedness or readiness before
implementation provides a clear understanding of
whether the workforce, institutional culture, and
infrastructure are ready for transformation.
11
Facilities
with higher readiness scores are more likely to adopt
integrated innovations and sustain them over the long
term. Organizational readiness encompasses both
tangible capacities, such as infrastructure, stang, and
training, and intangible factors, such as leadership
engagement, trust, communication, and shared
vision.
12,13
Provider motivation and accountability can
be maintained by participatory leadership and
identification of change champions.
14,15
In the absence
of such readiness, even well-designed interventions can
lead to implementation fatigue, resistance, and poor
fidelity. Implementation science provides structured
approaches to operationalize readiness assessment. The
R = MC² heuristic, rst proposed by Scaccia et al.
16
,
conceptualizes readiness as the product of Motivation,
General Capacity, and Innovation-Specic Capacity.
This model recognizes that readiness is dynamic and
multi-dimensional, requiring attention not only to
technical skills but also to contextual enablers that
determine whether change eorts take root. By
applying R = MC² to TB service settings (gure 1), this
study advances understanding of how sta motivation
and organizational systems interact to shape
preparedness for integrated TB-diabetes care. The
current study aims to measure the motivation of sta in
the TB basic medical unit to integrate diabetes care
within TB services; assess general and innovation-
specific capacities for change in TB facilities; and
identify contextual factors inuencing readiness for
change in resource-limited environments. Findings will
provide actionable insights for policymakers and
implementers to design targeted capacity-building
interventions, strengthen workforce engagement, and
promote the sustainable integration of TB-diabetes care
in low- and middle-income countries.
Figure 1: Conceptual framework for the current study for
R=MC
2
METHODOLOGY
We employed a cross-sectional study design to assess
the readiness of TB health facility sta to implement
integrated diabetes care. The study used a sta
readiness assessment tool, following the R = MC²
framework, to measure three domains: motivation,
general capacity, and innovation-specic capacity for
change. The study was conducted from November 2024
to April 2025 at 13 TB BMUs across primary,
secondary, and tertiary levels of care in 5 districts
across 2 provinces in Pakistan, representing diverse
geographic, demographic, and health system contexts.
The initial readiness assessment of the same facilities
was conducted, and the ndings are published in a
separate journal. Participants included TB health
facility sta (DOTs) who were directly engaged in
service delivery. Inclusion criteria were: (1) at least six
months of experience in TB service delivery, and (2)
direct involvement in patient management or
coordination of TB-related services. A structured, self-
administered questionnaire was adapted based on
implementation science frameworks, particularly the
Consolidated Framework for Implementation Research
(CFIR) and the Readiness for Integrated Care
Questionnaire (RICQ).
17,18
The adapted and locally
contextualized tool underwent expert validation and
reliability analysis. It assessed three readiness domains-
Motivation, General Capacity, and Capacity for
Change-capturing individual, organizational, and
contextual determinants relevant to DOTS facilitators
within the TB program. Motivation: This domain
evaluated the extent to which DOTS facilitators
perceived integrated TB-diabetes care as important,
appropriate, and benecial to their routine work.
Twelve items measured perceived advantages,
compatibility with existing DOTS practices, alignment
with TB program goals, and leadership encouragement.
Responses were recorded on a 5-point Likert scale (1 =
strongly disagree, 5 = strongly agree), with higher
scores indicating greater motivation to support
integration. This domain corresponds to CFIR
constructs such as relative advantage, compatibility,
and organizational priority. General Capacity: This
domain assessed the structural and organizational
support available to facilitators for implementing
diabetes screening, referral, and follow-up alongside
TB care. It covered leadership commitment, sta skills
and training, availability of essential resources (e.g.,
diagnostic tools and supplies), and coordination
mechanisms between TB and diabetes services. Items
were rated on the same 5-point Likert scale, with higher
scores indicating stronger organizational capacity.
Capacity for Change: This domain examined
facilitators’ adaptability and willingness to implement
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new practices required for TB-diabetes integration.
Four items assessed openness to modifying workows,
perceived adaptability of facilities, availability of
supportive structures such as supervision and guidance,
and support from external stakeholders. Responses
were again rated on a 5-point Likert scale, where higher
scores reected greater readiness to adopt change.
Reliability analysis was conducted rst, followed by a
staff readiness assessment at the selected BMUs, where
an integrated diabetes care package was planned for
implementation. Participants provided informed
consent, and condentiality was ensured.
Questionnaires were administered during o peak hours
in designated areas of the facility to minimize
disruption to clinical activities. Data were entered and
analyzed using SPSS version 29. Consistent with the R
= MC² heuristic, Motivation, General Capacity, and
Capacity for Change were treated as distinct readiness
domains. Each construct was analyzed descriptively at
the domain level. Although composite scores were
calculated for descriptive purposes, interpretation
focused on domain-specic results to maintain
theoretical alignment and construct validity. The scores
were calculated as follows: For each section
(Motivation, Capacity, and Capacity for change), the
mean score was calculated as follows:
Mean Score for Section=∑
Item Scores/Number of Items in Section.
Interpretation of Scores
Overall
Mean Score
Range
Readiness
Level
Interpretation
4.5 - 5.0 Very High
Readiness
The organization‘s sta is well
prepared to integrate diabetes care
into the TB control program.
3.5 - 4.4 High
Readiness
The organization‘s sta is ready,
though some areas need
improvement.
2.5 - 3.4 Moderate
Readiness
The organization sta shows
moderate readiness but requires
signicant improvements in
several areas.
1.5 - 2.4 Low
Readiness
The organization‘s sta is low on
readiness and needs major
improvements before integration
can be achieved.
1.0 - 1.4 Very Low
Readiness
The organization‘s sta is not
ready for integration and needs
substantial development in all
areas.
This study was approved by the Ethics Review
Committee (ERC) of the Institute of Public Health &
Social Sciences, Khyber Medical University, Peshawar
(Ref # KMU/IPHSS/Ethics/2024/EG/200). The
departmental permissions were obtained from the
National and Provincial TB programs to conduct the
study. The authors conducted the study in accordance
with the ethical guidelines of the Declaration of
Helsinki (1964).
RESULTS
The reliability analysis to evaluate the internal
consistency and psychometric adequacy of the three
readiness subscales: Motivation (12 items), General
Capacity (5 items), and Capacity for Change (4 items).
Initially, Cronbach’s alpha coecient was computed for
each subscale. Alpha was then calculated with the usual
formula for Cronbach’s alpha:
This formulation assumes tau-equivalence and serves as
a baseline estimate of reliability. The Motivation scale
showed acceptable internal consistency (Cronbach‘s α
= 0.802), while General Capacity demonstrated
excellent reliability (α = 0.918). Capacity for change
showed moderate internal consistency (α = 0.548).
Item–total analysis indicated that the item "External
stakeholders support our integration eorts" had a very
low corrected item–total correlation (r = 0.081).
Removing this item would increase Cronbach's alpha to
0.708, exceeding the commonly accepted threshold of
0.70. Despite this statistical improvement, the item was
retained for conceptual reasons. Capacity for change
was dened to include both internal adaptability and
external system support inuencing implementation.
External stakeholder engagement is particularly
important for integrating TB and DM services where
inter-program coordination is required. Removing this
item would narrow the construct to internal adaptability
alone, reducing content validity and failing to capture
the multi-dimensional nature of change capacity in
resource-constrained health systems. The tool was then
used to measure the DOTs facilitators' readiness at the
13 TB BMUs, where integrated TB diabetes care was
planned as part of the project.
7
Across the 13 TB Basic
Management Units, DOTS facilitators reported
consistently high motivation to integrate diabetes care
into TB services (Table 1), with 92.4% agreed or
strongly agreed that integration would improve TB
treatment outcomes (46.2% agree; 46.2% strongly
agree), 100% agreed that integration would enhance
service eciency and t well with current practices,
and 92.3% agreed that sta could clearly see patient
benets. Additionally, 76.9% strongly agreed that clear
incentives are needed to support integration.
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Table 1: TB BMUs Sta Motivation for Integrated TB-DM Care
150428
S.
No
Item Strongly
Disagree
(1)
Disagree
(2)
Neutra
l (3)
Agree
(4)
Strong
ly Agre
e (5)
M1
Integrating
diabetes care
into TB control
will improve
patient
outcomes in TB
treatment.
0 (0%) 0 (0%)
1 (7.7
%)
6 (46.2
%)
6 (46.2
%)
M2
Integrated
TBDB care will
enhance the
efciency of
our health
services.
0 (0%)
0 (0%)
7 (53.8
%)
M3
This integration
will provide our
organization
with a competitiv
e advantage.
0 (0%) 0 (0%)
8 (61.5
%)
5 (38.5
%)
M4
Integrating
diabetes care
will t well
with our current
practices.
0 (0%)
9 (69.2
%)
4 (30.8
%)
M5
This integration
aligns with the
Provincial TB
Control Program
organization's
mission and
values.
0 (0%)
3 (23.1
%)
8 (61.5
%)
2 (15.4
%)
M6
Our staff believe
s that this
integration
will be benecial
0 (0%) 1 (7.7%
)
6 (46.2
%)
5 (38.5
%)
M7
Integrating
diabetes care is
a top priority
for our
organization.
0 (0%) 2 (15.4
%)
1 (7.7%
)
7 (53.8
%)
3 (21.3
%)
M8
The provincial
TB program
actively supports
the integration of
diabetes care.
0 (0%) 3 (21.3
%)
M9
There should be
clear incentives
for integrating
diabetes care
into TB control.
0 (0%) 1 (7.7%
)
2 (15.4
%)
10 (76.
9%)
M
10
The benets of
integrating
diabetes care
will be visible
quickly.
0 (0%) 2 (15.4
%)
8 (61.5
%)
3 (21.3
%)
M
11
Successful
integration in
other
organizations
can inspire
condence in
our team.
0 (0%) 1 (7.7%)
8 (61.5
%)
4 (30.8
%)
0 (0%)
6 (46.2
%)
0 (0%)
0 (0%) 0 (0%)
0 (0%)
1 (7.7%
)
2 (15.4
%)
1 (7.7%
)
7 (53.8
%)
0 (0%)
0 (0%)
0 (0%)
M
12
Staff members
can easily see
how this
integration will
benet patients.
0 (0%)
0 (0%)
1 (7.7%)
8 (61.5
%)
4 (30.8
%)
In contrast, General Capacity was weaker and more
heterogeneous (Table 2). While 53.8% reported active
leadership support for integrated care, only 53.9%
indicated that sta had the required skills, and the same
proportion reported inadequate resources. Additionally,
53.9% disagreed that TB and diabetes services have
clear coordination and communication channels,
highlighting structural and organizational gaps.
Table 2: TB BMU Sta General Capacity for Integrated TBDM
Care
S.
No
Item Strongly
Disagree
(1)
Disagr
ee (2)
Neutra
l (3)
Agree
(4)
Stron
gly A
gree
(5)
C1
Leaders in PTP
actively support
integrated care
initiatives and are
committed to
providing necessar
y resources.
2 (15.4
%)
3 (23.1
%)
1(7.7
%)
7 (53.
8%)
0 (0%
)
C2
Our staff has the
necessary skills to
manage both TB
and diabetes, with
training programs
and continuous
education for
ongoing learning.
0
(0%)
5 (38.5
%)
1 (7.7
%)
6 (46.2
%)
1 (7.7
.%)
C3
Our organization
has sufcient
resources (e.g.,
nancial,
technological,
medical
equipment, and
supplies) to
support integrated
care.
2 (15.4
%)
5 (38.5%
)
2 (15.4
%)
C4
We have access to
external resources
to aid in the
integration
process.
1 (7.7%
)
5 (38.5%
)
3 (23.1
%)
4 (30.8
%)
0 (0
%)
C5
There is a clear
plan for
coordinating care
between the TB
and diabetes
departments, and
communication
channels are
established to
6 (46.2
%)
2 (15.4
%)
2 (15.
4%)
1 (7.7%
)
1 (7.7%
)
1 (7.
7%)
4 (30.8
%)
ensure smooth
coordination.
Capacity for change was moderate (Table 3): 69.2% of
respondents said that facilities are exible and can
change quickly, and 77.0% said that sta are receptive
to new practices. Nevertheless, only 38.5% reported
having sucient support systems during transition, and
46.2% were neutral about external stakeholder support.
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Table 3: TB BMU Sta Capacity for Change for Integrated TB-
DM Care
S.
No
Item Stron
gly
Disag
ree (1)
Disagr
ee (2)
Neu
tral
(3)
Agr
ee
(4)
Stro
ngly
Agre
e (5)
C
C
1
Our health facility
is exible and can
adapt quickly to
changes.
1
(7.7%
)
2
(15.4%
)
1
(7.7
%)
9
(69.
2%)
0
(0
%)
C
C
2
We, as sta
members, are open
to adopting new
practices.
0
(0%)
1
(7.7%)
2
(15.
4%)
8
(61.
5%)
2
(15
.4
%)
C
C
3
We have a support
system in place for
sta during the
transition period.
0
(0%)
5
(38.5%
)
3
(23.
1%)
5
(38.
5%)
0
(0
%)
C
C
4
External
stakeholders
support our
integration eorts.
1
(7.7%
)
4
(30.8%
)
6
(46.
2%)
0
(0%)
2
(15
.4
%)
Box plots (Figure 2) show the median, interquartile
range, and overall spread of Motivation, General
Capacity, and Capacity for Change scores across the
13 facilities.
Figure 2: Distribution of Organizational Sta Readiness Domains
across Selected TB Facilities
Composite MC² scores are presented in Table 4 only as
descriptive information and were not used for
interpretation or classication, consistent with
2
construct-level proling recommended in the R = MC
framework.
Table 4: Readiness Domains Scores (MC²) Across Facilities
Facility
Staff
Motivation
(M)
General
Capacity
(C)
Capacity
for Change
(CC)
Readiness
Score
(MC
2
)
Primary 4.25 3.40 3.50 50.57
Primary 4.00 1.80 2.50 18.0
Primary 3.42 2.00 3.00 20.52
Primary 4.42 4.40 4.25 82.65
Secondary 4.17 3.80 3.75 59.42
Secondary 3.83 2.60 3.00 29.87
Secondary 4.00 4.00 3.50 56.0
Secondary 4.50 2.00 2.75 24.75
Secondary 4.08 3.00 3.25 39.78
Tertiary 5.00 3.80 3.75 71.25
Tertiary 4.83 1.20 3.00 17.38
Tertiary 4.08 3.40 3.50 48.55
Tertiary 3.92 2.00 3.75 29.40
Inter-Domain Relationships among Readiness Constructs
To examine the internal structure of organizational
readiness, Motivation, General Capacity, and Capacity
for Change were analysed as separate domains. Pearson
correlation analysis showed weak associations of
Motivation with General Capacity (r = 0.14, 95% CI
−0.45 to 0.64) and Capacity for Change (r = 0.07, 95%
CI −0.50 to 0.60), indicating that sta motivation was
largely independent of facility structural capacity. In
contrast, General Capacity and Capacity for Change
were strongly correlated (r = 0.69, 95% CI 0.20 to 0.90,
p < 0.009), suggesting that facilities with stronger
infrastructure and organizational support report greater
adaptability to change. Due to the small sample size,
these findings should be considered exploratory.
Table 5: Exploratory Correlation among Readiness Domains
Comparison r P-Value 95% CI
Motivation and
General Capacity
0.136 0.658 -0.453 to
0.636
Motivation and
Capacity for Change
0.069 0.823 -0.503 to
0.595
General Capacity and
Capacity for Change
0.694 0.009 0.203 to
0.895
Figure 3: Composite Radar Plot (Mean Score Across Sta)
The composite radar plot (Figure 3) shows that
motivation had the highest mean score (4.2), indicating
strong sta support for TB–DM integration. General
Capacity was the lowest (2.9), reecting resource and
training gaps, while Capacity for Change was moderate
(3.3). Overall, high motivation is limited by weaker
operational capacity.
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The overlaid radar plot (Figure 4) shows consistently
high motivation across sta, while General Capacity is
lower and more variable, indicating uneven structural
support. Capacity for change shows moderate variation.
Overall, motivation is strong, General Capacity is the
main barrier, and Capacity for Change is moderate.
Figure 4: Sta Readiness to Change Overlaid Composite Radar
Plot
Figure 5: Heat map of Readiness Domains across TB BMUs Sta
The heatmap displays the distribution of the three
readiness domains across the 13 sta respondents. It
displays color gradients to indicate the size of each
domain score. Motivation scores were consistently high
across sta, whereas General Capacity showed greater
variability with several lower scores. Most respondents
demonstrated moderate capacity for change.
DISCUSSION
This study provides one of the rst empirically
grounded TB sta readiness proles for integrating
diabetes care within tuberculosis (TB) services in
Pakistan, using the R = MC² heuristic, which divides
readiness into three categories: Motivation, General
Capacity, and Capacity for Change. The analysis of
DOTS facilitators showed that sta motivation was
consistently high, General Capacity was the weakest
and most variable, and Capacity for Change was
intermediate. The imbalance between willingness and
operational capacity suggests an area that implementers
and policymakers may prioritize to improve TB sta
readiness to initiate integrated TB-diabetes care in low-
resource environments. The scores for motivation were
clustered in the upper range across facilities and sta,
indicating strong endorsement of the benets of
integration, perceived patient value, and alignment with
the organization's mission. The trend is similar to the
results of integrated-care readiness research in
healthcare and hospital systems.
19
In such studies, there
is a varied level of intrinsic motivation and capacity of
healthcare workers to implement patient-centered
innovations, despite the lack of structural supports or
low facility readiness.
20,21,22
Similar endorsement in
LMIC contexts has also been observed in integration
efforts involving HIV-NCD services and maternal
health.
22,23,24
From a theoretical perspective, R = MC²
conceptualizes readiness as multiplicative rather than
additive.
25,26
Lack of capacity cannot be compensated
for solely by high motivation. When capacity drops to
near zero, preparedness fails no matter the people's
motivation. Our ndings support this observation.
Despite a high level of motivation and commitment to
integration among almost all DOTS facilitators, many
facilities still scored moderately in readiness due to
structural and resource decits. It is worth noting that
the lack of dierentiation in motivation makes it less
helpful for distinguishing between sta. This nding is
consistent with the organizational change literature,
which suggests that commitment to change is a
common pattern that lacks predictive power for
implementation success unless structural preparedness
is also present.
27
Thus, while motivation constitutes an
enabling condition, it does not explain variation in
readiness across facilities in this study. The high
motivation observed may reect broader contextual
factors. In Pakistan, TB is managed through a vertical
program with highly standardized protocols and donor-
supported performance monitoring. Such systems may
foster normative commitment and a sense of program
identity, thereby enhancing the willingness to embrace
complementary innovations. However, when resources
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are not matched, this motivational capital can
deteriorate over time. General Capacity was the most
heterogeneous and weakest dimension. Scores ranged
widely from 1.20 to 4.40. This trend suggests that
overall capacity may play an important role in
explaining variation in sta and facility readiness.
28
The organizational readiness theory highlights the fact
that general capacity entails leadership participation,
infrastructure, workforce competencies, and sucient
resources. The empirical literature consistently nds
that resource constraints and poorly aligned workows
are the greatest barriers to integrating chronic disease
services into a communicable disease platform.
29
Among the most important bottlenecks in TB-DM
dynamics are the lack of glucometers, supply chain
disruptions, and ambiguous referral pathways, which
limit sta capacity.
30
The present study's ndings
strongly echo those patterns. Although leaders were
seen as moderately supportive, a signicant number of
respondents reported inadequate resources and unclear
coordination mechanisms. These results are consistent
with ndings from integrated NCD screening programs
in LMICs, where the readiness gaps were mostly
structural rather than attitudinal.
6,31
The observed visual
association between general capacity and composite
readiness in our study may indicate that general
capacity can mediate the relationship between
Motivation and implementation behavior.
32
In another
way, motivation can only be converted into readiness
when there is adequate operational scaolding.
33
Without that support, motivated sta members might
experience a disconnect between their perceptions of
what is important and what they can actually do. This
may result in frustration or burnout.
34
In our study,
Capacity for Change occupied an intermediate position,
indicating moderate openness to new workows and
adaptability. The mid-range scores are also in line with
the available literature, which indicates that medical
personnel tend to describe openness to change when it
is associated with perceived patient benet, despite
their readiness to do so.
35
However, workload pressures
and supervisory climate appear to inuence adaptive
capacity strongly, facilitating or limiting adaptability.
36
In settings where stang is already stretched,
adaptability can reach a level of fatigue with change
and with insucient operational support, despite
overall sta readiness to embrace new practices.
37
Our
empirical data also suggests that perceived external
stakeholder support is relatively weaker than internal
adaptability, which is of paramount importance. This
distinction is critical. Integration of DM care into
routine TB services in Pakistan requires coordination
among traditionally separate vertical programs, which
are often funded and managed independently.
Fragmented governance may weaken inter-programme
prospects for successful organisational change even
trust and shared responsibility, potentially limiting the
when internal employees are prepared to contribute.
WHO guidelines emphasize bidirectional screening for
TB-diabetes, yet implementation remains uneven.
38
This study shows that the main barrier is not sta
resistance but limited operational capacity. Using the R
= MC² framework, the study provides a theory-based
assessment of sta readiness and validates key
constructs through facility-level comparisons and visual
analyses. Findings highlight strong sta motivation but
inadequate resources, training, coordination, and
infrastructure. For eective TB-DM integration in
Pakistan, programs should strengthen capacity through
targeted training, diagnostic tools, workow redesign,
and supervisory support. Policies should align TB and
NCD funding, incorporate routine readiness
assessments, and treat sta readiness as a continuous
management tool for sustainable scale-up.
LIMITATIONS
The cross-sectional design captures readiness as a static
construct. During implementation, readiness is likely to
evolve due to its dynamic nature. The sample size and
inclusion of selected facilities may limit generalizability
and statistical inference. Self-reported responses may
introduce social desirability bias, particularly in the
Motivation domain, where low variance suggests
possible ceiling eects.
CONCLUSIONS
This study indicates that frontline workers in Pakistan‘s
TB program are generally motivated to integrate
diabetes care; however, operational and structural
limitations reduce overall readiness. The gap between
staff motivation and infrastructure highlights that
motivation alone cannot drive system-wide change.
Policymakers should prioritize capacity building and
structural support to translate TB–DM integration from
policy into practice, even in resource-constrained health
systems.
CONFLICT OF INTEREST: None
FUNDING SOURCES: This Ph.D. research of
Dr. Saima Aleem is supported by the Higher
Education Commission of Pakistan (Reference#
20-GCF-770/RGM/R&ID/HEC/2021).
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Saima Aleem - Concept & Design; Data Acquisition; Data
Analysis/interpretation; Drafting Manuscript; Critical
Revision; Final; Approval
Saima Afaq- Concept & Design; Data Acquisition; Drafting
Manuscript; Critical Revision; Supervision; Final; Approval
Zeeshan Kibria - Concept & Design; Data Acquisition; Data
Analysis/interpretation; Drafting Manuscript; Critical
Revision; Final; Approval
Rida Zarkaish - Concept & Design; Data Acquisition; Data
Analysis/interpretation; Drafting Manuscript; Final; Approval
Zohaib Khan - Concept & Design; Data Acquisition; Drafting
Manuscript; Supervision; Final; Approval
Assessing Sta Readiness for Integrated Tuberculosis
