Original Research Article
Health Informatics Journal
1–19
Exploring factors influencing © The Author(s) 2023
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acceptability of online capacity sagepub.com/journals-permissions
DOI: 10.1177/14604582231152782
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monitoring and evaluation in Ghana
Samuel KK Dery
Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Legon, Ghana
Frances Baaba da-Costa Vroom
Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Legon, Ghana
Charity K Asem
School of Public Health, College of Health Sciences, University of Ghana, Legon, Ghana
Godwin Adzakpah
Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Legon, Ghana
Department of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences,
University of Cape Coast, Ghana
Abstract
Introduction: Ghana’s multi-sectoral approach towards the management of HIV and AIDS has
resulted in many community-level activities and programs aimed at stopping HIV infections and
reducing the impact of HIV and AIDS. This study seeks to investigate whether Monitoring &
Evaluation (M&E) officers in Ghana will be willing to join in an electronic learning platform which is
web-based as a means of building M&E capacity.
Methods: 123 out of 130 participants were involved in the study. Continuous and categorical
variables were analysed using means and proportions. Structural equation Modelling technique was
used to determine the factors associated with acceptability/intention to use.
Corresponding author:
Godwin Adzakpah, Department of Health Information Management, College of Health and Allied Sciences, School of
Allied Health Sciences, University of Cape Coast, Cape Coast Elmina Highway, Cape Coast +00233, Ghana.
Email: godwin.adzakpah@ucc.edu.gh
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permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.
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2 Health Informatics Journal
Results: The results showed that Attitude toward usage had a positive significant influence on
acceptability/intention to use (AITU). In addition, experience with online learning and Internet
discussion also had a positive influence on perceived usefulness and perceived ease of use re-
spectively. The overall model shows 71% of variation of M&E officers’ attitude toward usage on
acceptability/intention to use online M&E platform as observed by the covariates in the model.
Conclusions: Attitude toward usage was observed to be the strongest determinant of the AITU
online HIV/AIDS M&E platform for monitoring and evaluation activities.
Keywords
monitoring & evaluation, Ghana HIV/AIDS commission, online learning, information and
communication technology, structural equation modelling and technology acceptance model
Introduction
Despite intense international and local efforts to combat the pandemic, the human immunodefi-
ciency virus (HIV) and the acquired immune deficiency syndrome (AIDS) continue to be major
global health tragedies. Even within nations, HIV infections vary by region.1,2 In the fight to contain
the HIV pandemic, these variations in HIV prevalence have significant ramifications. At the end of
2021, 38.4 million people worldwide were infected with HIV. Worldwide, an estimated 0.7% of
adults between the ages of 15 and 49 are infected with HIV, though the extent of the epidemic
continues to vary significantly from country to country.3 Nearly one in every 25 adults (3.4%) in the
WHO African Region are infected with HIV, accounting for more than two-thirds of HIV-positive
individuals worldwide.3
Monitoring and evaluation (M&E) is seen as critical for measuring success of any project. To this
end, designing and implementing an effective national M&E system is essential to Ghana’s HIVand
AIDS response. Monitoring and evaluation is a system that collects, analyses data and produces
information that enable local, regional, national and international stakeholders to measure progress
and impact of programs.4 Monitoring and evaluation capacity building is believed to contribute
directly to improving performance and is known to play an important role in sustaining and
improving programs over time.
Towards enhancing the HIVand AIDS M&E structure at the community level, the Ghana AIDS
Commission (GAC) undertook an in-depth assessment and gap analysis. The analysis revealed gaps
in human capacity with regards to: M&E knowledge and skills, data management and analysis,
indicator definitions, reporting guidelines and local information use.5
A key strategy in Ghana’s M&E Plan is the institutionalization and sustainability of M&E
capacity strengthening. In consultation with the United States, President’s Emergency Plan for
AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC), Ghana’s
HIV and AIDS M&E (GHAME) project was initiated in collaboration with Morehouse School of
Medicine (MSM) and the School of Public Health, University of Ghana (SPH). This grant award
provided a 5-year, culturally competent, M&E training program across all 10 regions of Ghana in
partnership with the Ghana AIDS Commission. This collaboration: (1) assessed current M&E needs
in Ghana, (2) developed an M&E training curriculum specific to Ghana, (3) offered 10-day M&E
workshops to government employees and NGO’s representatives responsible for M&E at the sub-
district, district, regional, and national levels.
Dery et al. 3
The GHAME intervention has improved theM&E capacity ofM&E officers and focal persons of
selected implementing partners in Ghana.6 However, high attrition of M&E persons trained coupled
with the high number of people yet to be trained makes this venture very expensive and difficult to
sustain without continuous and adequate funding. According to the Ghana AIDS Commission, this
single course is insufficient to meet the varied needs at various levels of the national M&E structure
due to both its content and location.7
Review of GHAME training reports shows most participants describing the 2-weeks training as
too short. Given that all participants were M&E officers of their respective institutions, a longer
training period would mean they would be out of the office for a longer period. This would be a
difficult option for most institutions that are already battling with inadequate staff. However, with
the advancement and widespread application of information and communication technology (ICT),
online learning and capacity building platforms have evolved to augment traditional face-to-face
teaching methods. The combination of pressure of work, insufficient funding and limited HIV and
AIDS M&E knowledge and skills is the driving force to consider the use of online training. It is
believed that online learning platform for HIVand AIDS M&E would be more cost-effective and a
more sustainable means of capacity building. Jay Cross, (2004) was the first to have introduced what
is known as e-learning or web-based education in 1998.8 Some researchers define e-learning and
online learning as using web-based technologies to deliver content to improve knowledge and
skills.9 According to Rosenberg (2001), e-learning involves the use of internet platforms to carryout
knowledge enhancing activities.10 Other studies have included mobile and wireless applications as
means of providing online learning teachings.11
Currently, there is lack of a web-based capacity training programme in the area of HIVand AIDS
M&E in Ghana. The introduction of an e-learning platform would help build capacity of these HIV
and AIDS M&E officers and focal persons of institutions implementing HIVand AIDS programs in
Ghana. This formative study, therefore, sought to investigate whether M&E officers and focal
persons of institutions implementing HIVand AIDS projects in Ghana will be willing to take part in
a web-based learning platform as means of building their HIVand AIDS M&E capacity. It will also
investigate factors that will influence their participation in such a platform.
Research model and hypotheses development
The conceptual model is rooted in the original TAM12 which relates to the construct perceived
usefulness (PU), perceived ease of use (PEOU) and behavioural intention (BI). The original TAM
was tested together with some additional factors such as Experience with Online Learning (OLC),
Internet usage (IU) and Importance to success (ITS) on attitude toward usage (ATU) and
Acceptability/intention to use (AITU) of online learning platform of M&E officers and focal
persons. The basic TAM is supported with four antecedents. The first two; Experience with Online
Learning (OLC) and Internet usage (IU) precede Perceived usefulness (PU) and the final two;
Internet discussion (ID) and Importance to success (ITS) precede Perceived ease of use (PEOU).12
The proposed conceptual framework/model including eight (8) hypotheses is shown in Figure 1,
and the basis of this model has been provided based on literature.
Perceived ease of use and Perceived usefulness. Perceived ease of use is one’s understanding of system
to be easy and uncomplicated.13 Davis et al., (1989) also explained that PU is one’s perceived usage
of a particular system to be favourable in helping him or her to executive job.13 Some studies done in
the past reported some level of inconsistencies in the outcome of PEOU and PU with respect to
intention to use of a particular system. They indicated that the relationship was statistically
4 Health Informatics Journal
Figure 1. Proposed conceptual path model.
Source: Authors’ construction.
significant14-18 and were in study context, the techniques and the size of the sample used. Based on
this, Mouakket and Bettayeb (2015) emphasized that intension to use was positive and significantly
influenced by PU.19 Another study conducted by Chang and Tung (2008) concluded that PEOUwas
a strong and positive factor of intension to adopt a particular system.20 This was also supported by
Peng et al., (2009).21 In addition, another study confirmed the findings of earlier studies that
intension to use is directly and significantly influenced by PEOU.22 In the study of factors affecting a
web-based systems, researchers postulated that PU is a strong influencer of behavioural intension to
use a system ,15,18 but Chang and Tung (2008) indicated no significant effect of PU on intension to
use web-based learning system.20 However, Tarhini et al., (2016) said that PU and PEOU are major
factors influencing intension to use in an e-learning environment.23 Upon these reviews our study
formulated these hypotheses below:
Hypothesis 1: there is positive association between perceived usefulness (PU) and Attitude
toward usage (ATU) in the adoption of online learning platform of M&E officers and focal
persons of institutions implementing HIV and AIDS projects in Ghana.
Hypothesis 2: there is positive association between Perceived ease of use (PEOU) and perceived
usefulness (PU) in the adoption of online learning platform of M&E officers and focal persons.
Hypothesis 3: there is positive association between Perceived ease of use (PEOU) and attitude
toward usage (ATU) in the adoption of online learning platform of M&E officers and focal
persons.
Dery et al. 5
Acceptability/intention to use and attitude toward usage. The original TAM (specifically, PEOU and
PU) has been well implemented and developed a relationship with the acceptance of technology, and
however boost the attitude towards usage of persons (Davis, 1989). Several studies have been
carried out to support this relationship.13,18,24-28 In addition, the influence of behavioural intension
to use on attitude towards usage has been widely studied within web-based learning
context.12,18,20,22,29-32 Furthermore, behavioural intension to use have a positive significant in-
fluence on attitude towards usage of a technology in theory of planned behaviour (TPB), TAM and
decomposed theory of planned behaviour (DTPB) model. According to Taylor and Todd (1995b),
previous experience of an individual in using a technology will increase his or her motivation and
thereby increasing attitude towards usage.26 In order to be consistent with earlier studies, our study
has also tested the influence of behavioural intension to use on attitude towards usage to ensure
consistency. It has also been observed by Tarhini et al., (2016) that the association between be-
havioural intension to use and attitude towards usage for e-learning cannot be overlooked.23 We
have therefore hypothesised that;
Hypothesis 4: there is positive association between attitude toward usage (ATU) and
Acceptability/Intention to use (AITU) in the adoption of online learning platform of M&E
officers and focal persons.
Online learning experience, Internet usage and discussion and Importance to success. According to Ali
et al., (2015a), internet usage and one’s experience have a positive relationship with individual’s
technology acceptance.24 Previous studies have included internet experience as an important factor
to technology acceptance.24,27,33-38 According to Hackbarth et al., (2003), an individual’s per-
ception grows as their internet experience increases.39 In a study conducted by Liao and Cheung
(2001), internet experience was found to have a significant effect on individual’s technology
acceptance, which is very important in determining attitude towards usage.40 Similar research
conducted by Anandarajan et al., (2000) equally underscored the relevance of internet experience in
studies done using TAM.41 Due to limited online learning studies focusing on internet experience,
our study adopted this indicator because of its relevance within the TAM concept as pointed out in
earlier studies. This study therefore hypothesised the following;
Hypothesis 5: there is positive association between Experience with Online Learning (OLC) and
perceived usefulness (PU) in the adoption of online learning platform of M&E officers and focal
persons.
Hypothesis 6: there is positive association between Internet usage (IU) and perceived usefulness
(PU) in the adoption of online learning platform of M&E officers and focal persons.
Hypothesis 7: there is positive association between Internet discussion (ID) and perceived ease
of use (PEOU) in the adoption of online learning platform of M&E officers and focal persons.
Hypothesis 8: there is positive relationship between Importance to success (ITS) and perceived
ease of use (PEOU) in the adoption of online learning platform of M&E officers and focal
persons.
6 Health Informatics Journal
Methods
Data source
The data collection tool was built on the TAM model and was administered to the selected M&E
officers and focal persons to examine perceived usefulness, ease of use, barriers and acceptability of
a web-based learning platform for HIV and AIDS M&E. The study also collected data on re-
spondent’s level of M&E and ICT knowledge, skills and experience. Data collection was done
between November 2016 and January 2017.
Participant selection
Considering the different geographical areas of Ghana, the study was stratified according to the three
ecological zones (Northern, Middle and Southern) of the country. The proportional sampling based
on the total population in the respective zones was used to select the number of participants at
random from each zone. Two groups of M&E officers were selected in each zone for the study. One
group consisted of past GHAME participants and the other future GHAME participants (these were
M&E officers of institutions implementing HIV and AIDS interventions but who had not yet
participated in the GHAME training workshops). The participants were invited through a formal
letter through the heads of the participation institutions. A self-administered questionnaire was
completed by each respondent. In all 123 out of 130 GHAME participants representing 94.6% of
respondents took part in the survey. The Table 1 shows the number of participants selected in each
zone. Four research assistants were trained to administer the questionnaires to participants.
Data collection tools
The main constructs of data collection tool was based on the technology acceptance model (TAM)
as shown in the conceptual path model (Figure 1). The constructs were measured using series of
continuous or Likert scale concepts.13 The data collection tool was based on previous studies with
some revisions to conform to the research objective by adapting the TAM scales.13,42,43 The TAM
model constructs used 44 items that accessed “internet usage” (7 items), “experience with online
learning” (4 items), “perceived usefulness” (10 items), “perceived ease of use” (5 items), “attitude
towards usage” (6 items), “internet discussion” (3 items), “importance to your success” (5 items)
and “acceptability/intention to use” (4 items). The measurement scale for all responses was built on
five-point Likert scale starting from 1 (“strongly disagree”) to 5 (“strongly agree”)44,45; 1 being the
least and 5 being the highest. The questionnaire was developed in English and was administered in
English.
Table 1. Distribution of participants’ selection.
Ecological zone GHAME participants Future GHAME participants Total
Southern zone 35 25 60
Middle zone 21 15 36
Northern zone 19 15 34
Total 75 55 130
Source: Authors’ field work. GHAME = Ghana’s HIV and AIDS M&E.
Dery et al. 7
Inclusion and exclusion criteria
GHAME participants (past and present) at local government Agencies, Health Facilities and Non-
Governmental Organisations were recruited for the study.
Analysis
Data entry and cleaning for the quantitative data was done using Microsoft Access 2010 while
STATAVersion 15 was used for the analysis. Thorough observation of study participants was done
to have complete understanding of the data set. Test for normality of data was carried out using
Shapiro-Wilk and Bartlett test to determine the symmetry of all continuous data. Continuous and
categorical variables were analysed using means and percentages. We also reported means and their
standard deviations as well. The reliability of the variables in the dataset were assessed by examining
Cronbach’s alpha coefficient. Goodness of fit Indices for Scale Validity Tests was conducted using chi-
square statistic (Additional file 2). The chi-square test of statistic is a natural index used to measure the
goodness-of-fit between data and themodel.46 Test of associations to determine the most striking factors
that affects acceptance and other various categorical variables of interest were conducted using the
Likelihood Ratio test. Principal component analysis with a varimax rotation method was employed to
classify the principal predictors of acceptability/intention to useM&Eonline platform forM&E capacity
building (Additional file 1). A statistical reliability test (Additional file 1) was also done to evaluate the
internal consistency of the survey items using Cronbach’s alpha reliability coefficients.44 A model fit
indices test using goodness of fit was also determined to know whether the model has the capacity to
predict how accurate the model fits the set of observations.44 Structural Equation Modelling technique
was employed to assess themodel and construct validitywas also examined by scrutinising the results of
the model. STATAversion 15 was used to calculate the path coefficients and test the model hypothesis.
A p-value of less than 0.05 was used as basis for considering a statistically significant model.
Results
Background information, M&E and IT experience of participants
123 representing 94.6% out of the total of 130 participants took part in the survey. Table 2 shows the
percentage distribution of participants with respect to demographic characteristics. The majority of
participants were men 94 (76.4%) compared to women 29 (23.6%). The descriptive analysis re-
vealed a mean age of 33.2 years and standard deviation of 7.97. Majority of the participants came
from the local government agencies 70 (58.3%) whilst 38 (31.7%) and 12 (10%) were from non-
governmental organisations and health facilities respectively. Seventy-four (74) (61.2%) of the
participants hold first degree, 36 (29.8%) hold certificates higher than first degree and the rest 11
(9%) hold diploma certificates. The average years of experience in theM&E job was 3.89 years with
standard deviation of 2.94 (Additional file 3 - Table 7). 74.59% of the participants received formal
training in M&E whilst 25.41% were not. Concerning the training rating, 56.12% of participants
rated the training very good, 25.51% said it was good and 15.31% said it was excellent respectively.
Only 3.06% said it was fair. 47.1% of participants indicated that they have a very good knowledge of
M&E, 39% said they have good knowledge of M&E and 4.2% indicated having excellent
knowledge of M&E. 10.1% however said they have a fair knowledge of M&E (Additional file 3 -
Table 7). In the area of M&E skills rating, outcome of responses were not different from that of
knowledge of M&E. When the participants were asked whether they will continue a career in M&E,
8 Health Informatics Journal
Table 2. Background information of participants.
Variable Frequency Percent
Organisation
Local government agencies 70 58.33
Health facilities 12 10.00
Non-governmental organisations 38 31.67
Age of respondents [mean (SD)]a 33.18 (7.97)
Gender
Female 29 23.58
Male 94 76.42
Educational level completed
University 110 89.43
Others (Secondary, training college & polytechnic 13 10.57
Highest qualification
Below first degree (diploma and HND) 11 9.09
First degree 74 61.16
Above first degree 36 29.75
Source: Authors’ estimation. Data are presented as numbers and percentages.
amean and standard deviation.
the majority, 87.1% indicated that they will continue a career in M&E whilst 3.5% said no. Only
9.5% indicated they do not know whether they will continue a career in an M&E or not (Additional
file 3 - Table 7). Additional file 4 (Table 8) shows the distribution of IT experience and internet
usage. 99.2% of the participants either have access to laptop or a desktop computer. On average, the
participants use the computer 6.5 times per week. Concerning what they use the computer for, the
participants indicated that they use the computer for business/work (91.1%), sending/receiving email
(89.4), studying (88.6%), social networking (69.9%), and entertainment (51.2%) respectively. On the
type of computer training acquired, majority had their training through self-guided learning about
computers (69.9%), followed by short courses on computer use (58.5%), Course on computers or ITas
part of another discipline or subject (41.5%), workshops or conferences on computers or IT (30.1%)
and Computer science or IT related field (18.7%) respectively. 90.2% of participants also have a good
computer usage skill whilst 6.6% rated fair and 3.3% rated poor computer usage skills. Over 90% of
the participants own a computer (laptop or desktop) and smartphone/tablet. (Additional file 4 - Table
8). Additional file 5 describes descriptive statistics, reliability and Spearman’s rank correlations
between study constructs (IU, experience with online learning (OLC), perceived usefulness (PU),
PEOU, attitude towards usage (ATU), internet discussion (ID), important to your success (ITS) and
acceptability/intention to use (AITU)). The mean score ranges from 2.62 for IU to 4.36 for AITU. The
study shows that OLC, PU, PEOU, ATU, ID, and ITS have significantly positive relationship with
AITU. IU was not positively associated with AITU (Additional file 5).
Results of hypothesis testing of individual parameter estimates of factors affecting
acceptability/intention to use HIV/AIDS M&E online learning platform (Direct/Indirect/
Total Effects) using Structural Equation Modelling (SEM)
Direct effect. The variable approximations test the statistical significance and power of each of the
formulated hypothesis in the model. The exogenous (independent) factors may directly or indirectly
Dery et al. 9
Table 3. Individual parameter estimates: Direct/indirect/total effects.
Direct effects Indirect effects Total effects
Endogenous Exploratory Path Path Path
variables variables coefficient p-value (95% CI) coefficient p-value [95% CI] coefficient p-value [95% CI]
Perceived Perceived ease of 0.14 (0.21) 0.032* (0.01–0.27) — — — 0.14 (0.21) 0.032* (0.01–0.27)
usefulness (PU) use (PEOU)
Experience with 0.28 (0.41) 0.002* (0.10–0.46) — — — 0.28 (0.41) 0.002* (0.10–0.46)
online learning
(OLC)
Internet usage 
0.20 (
0.23) 0.106 (-0.45–0.04) — — — 
0.20 (
0.23) 0.106 (
0.45–0.04)
(IU)
Internet — — — 0.10 (0.24) 0.033* (0.01–0.20) 0.10 (0.24) 0.033* (0.01–0.20)
discussion (ID)
Importance to — — — 
0.01 (
0.03) 0.425 (
0.04–0.02) 
0.01 (
0.03) 0.425 (
0.04–0.02)
your success
(ITS)
Attitude toward Perceived 1.25 (0.65) p < 0.001** (0.58–1.93) — — — 1.25 (0.65) p < 0.001** (0.58–1.93)
usage (ATU) usefulness
(PU)
Perceived ease of 0.27 (0.31) 0.004* (0.09–0.46) 0.18 (0.20) 0.018* (0.03–0.32) 0.45 (0.51) p < 0.001** (0.23–0.66)
use (PEOU)
Experience with — — — 0.35 (0.39) p < 0.001** (0.16–0.54) 0.35 (0.39) p < 0.001** (0.16–0.54)
online learning
(OLC)
Internet usage — — — 
0.25 (
0.15) 0.092 (
0.55-0.04) 
0.25 (
0.15) 0.092 (
0.55-0.04)
(IU)
Internet — — — 0.33 (0.40) p < 0.001** (0.16–0.50) 0.33 (0.40) p < 0.001** (0.16–0.49)
discussion (ID)
Importance to — — — 
0.04 (
0.04) 0.412 (
0.13–0.05) 
0.04 (
0.04) 0.412 (
0.13–0.05)
your success
(ITS)
Perceived ease of Internet 0.73 (0.79) p < 0.001** (0.53–0.94) — — — 0.73 (0.79) p < 0.001** (0.53–0.94)
use (PEOU) discussion (ID)
Importance to 
0.08 (
0.09) 0.413 (
0.29–0.12) — — — 
0.08 (
0.09) 0.413 (
0.30–0.12)
your success
(ITS)
(continued)
10 Health Informatics Journal
Table 3. (continued)
Direct effects Indirect effects Total effects
Endogenous Exploratory Path Path Path
variables variables coefficient p-value (95% CI) coefficient p-value [95% CI] coefficient p-value [95% CI]
Acceptability/ Perceived — — — 1.06 (0.54) p < 0.001** (0.47–1.65) 1.06 (0.54) p < 0.001** (0.47–1.65)
Intention to usefulness
use (AITU) (PU)
Attitude toward 0.85 (0.84) p < 0.001** (0.65–1.05) — — — 0.85 (0.84) p < 0.001** (0.65–1.05)
usage (ATU)
Perceived ease of — — — 0.38 (0.43) p < 0.001** (0.19–0.57) 0.38 (0.43) p < 0.001** (0.19–0.57)
use (PEOU)
Experience with — — — 0.30 (0.33) p < 0.001** (0.13–0.46) 0.30 (0.33) p < 0.001** (0.13–0.46)
online learning
(OLC)
Internet usage — — — 
0.21 (
0.22) 0.094 (-0.47–0.04) 
0.21 (
0.22) 0.094 (
0.47–0.04)
(IU)
Internet — — — 0.28 (0.34) p < 0.001** (0.13–0.43) 0.28 (0.34) p < 0.001** (0.13–0.43)
discussion (ID)
Importance to — — — 
0.03 (
0.04) 0.412 (
0.11–0.04) 
0.03 (
0.04) 0.412 (
0.11–0.04)
your success
(ITS)
Source: Authors’ estimation. CI: Confidence interval; Standardized path coefficient estimates are in parentheses. Statistical significance: *p < 0.05; **p < 0.001.
Dery et al. 11
affect the endogenous (dependent) variables. The standardized approximations give room to the
authors to determine the relative contribution of predictor variable to each outcome variable of
interest and as well as compare across groups.47
Table 3 shows standardized direct and indirect influence of the independent variables on the
dependent variables. Perceived usefulness (PU) had a positive influence on Attitude toward usage
(ATU) of HIV/AIDS M&E online learning platform by M&E officers and focal persons in Ghana
(path coefficient = 1.25; p < 0.001). This means that a unit change in perceived usefulness (PU) will
increase Attitude toward usage (ATU) of HIV/AIDS M&E online learning platform by 1.25. This
supports hypothesis 1 that there is positive relationship between perceived usefulness (PU) and
attitude toward usage (ATU) in the adoption of HIV/AIDS M&E online learning platform (Table 3;
Figure 2).
The analysis also revealed that a unit change in Perceived ease of use (PEOU) will significantly
increase Perceived usefulness (PU) by 0.14 with p-value = 0.032. This supports hypothesis 2 that
there is positive relationship between Perceived ease of use (PEOU) and perceived usefulness (PU)
in the adoption of HIV/AIDS M&E online learning platform (Table 3; Figure 2). Perceived ease of
use (PEOU) also had a positive statistically significant influence on Attitude toward usage (ATU)
with path coefficient of 0.27 and p-value = 0.004 in the adoption of HIV/AIDSM&E online learning
platform of M&E officers and HIV and AIDS focal persons of institutions implementing HIV and
AIDS projects in Ghana. This supports hypothesis 3 that there is positive relationship between
perceived ease of use (PEOU) and attitude toward usage (ATU) in the adoption of HIV/AIDS M&E
online learning platform.
Figure 2. Structural equation modelling path diagram of latent variables.
LR Chi2 (894) = 1609.38; p < 0.0001.
Overall R2 = 0.71.
Statistical significance: *p < 0.05; **p < 0.001.
Source: Authors’ estimation.
12 Health Informatics Journal
The analysis shows that a unit change in Attitude toward usage (ATU) will significantly increase
Acceptability/Intention to Use (AITU) HIV/AIDS M&E online learning platform by 0.85 with
p-value <0.0001. This supports hypothesis 4 that there is a positive relationship between attitude
toward usage (ATU) and Acceptability/Intention to use (AITU)) HIV/AIDS M&E online learning
platform (Table 3; Figure 2).
Further analysis also shows that, a unit change in experience with online Learning (OLC) will
significantly increase perceived usefulness (PU) of HIV/AIDS M&E online learning platform by
0.28 with p-value = 0.0002. This supports hypothesis 5 that there is positive relationship between
Experience with online Learning (OLC) and perceived usefulness (PU) of HIV/AIDS M&E online
learning platform (Table 3; Figure 2).
Internet Usage (IU) did not have any significant influence on Perceived usefulness (PU) with path
coefficient of
0.20 and p-value = 0.106. We therefore reject hypothesis 6 and conclude that there is
no positive relationship between Internet usage (IU) and perceived usefulness (PU) of HIV/AIDS
M&E online learning platform (Table 3; Figure 2).
Internet Discussion (ID) however, had a positive influence on PEOU with path coefficient
of 0.73 and p-value <0.001. A unit change in Internet Discussion (ID) will significantly
increase PEOU of HIV/AIDS M&E online learning platform by 0.73 with p-value <0.001.
This supports hypothesis 7 that there is positive relationship between Internet discussion (ID)
and perceived ease of use (PEOU) of HIV/AIDS M&E online learning platform (Table 3;
Figure 2).
Importance to your success (ITS) did not have a significant influence on Perceived ease of use
(PEOU) of HIV/AIDS M&E online learning platform with path coefficient of 
0.08 and p-value =
0.413. We therefore reject hypothesis 8 and conclude that there is no positive relationship between
Importance to success (ITS) and perceived ease of use (PEOU) of HIV/AIDS M&E online learning
platform of M&E officers and HIV/AIDS focal persons of institutions implementing HIV/AIDS
projects in Ghana (Table 3; Figure 2).
Figure 2 shows R-squared values for each of the dependent parameters. PEOU accounted for
63% of the variation in PU. The combinations of PEOU and PU also accounted for 52% variation in
ATU of HIV/AIDSM&E online learning platform. The overall model shows 71% of the variation of
HIV/AIDS M&E officers and focal persons’ AITU HIV/AIDS M&E online learning platform as
captured by the independent variables in the model (Table 3; Figure 2).
Indirect effect. Standardized indirect effects are summarized in Table 3 to throw more light on the
indirect effect of each of the independent variable on the dependent variable. OLC had indirect
influence on ATU of HIV/AIDSM&E online learning platform, which was mediated by PU. IU had
indirect influence on ATU, mediated by PEOU. PU and PEOU had a positive statistically significant
indirect influence on AITU, all mediated by ATU. OLC had statistically significant indirect in-
fluence on AITU, which was mediated by PU and ATU. Also, IU had positive significant indirect
influence on AITU HIV/AIDS M&E online learning platform, which was mediated by PEOU and
ATU. Indirect influence are additions to any direct influence that the exogenous variables may have
on endogenous variables (Table 3).
Total effects. There is evidence that PU, ATU, PEOU, OLC and ID had a statistically significant
influence on AITU of HIV/AIDS M&E online learning platform (Table 3). PEOU had a
positive statistically significant influence on ATU with a total path coefficient of 0.45 and
Dery et al. 13
p-value <0.001. This outcome shows that a unit change in PEOU will increase ATU of M&E
online learning platform by 0.45. This supports hypothesis 3 that there is positive relationship
between perceived ease of use (PEOU) and attitude toward usage (ATU) in the adoption of
M&E online learning platform. There was no statistical evidence of IU and ITS having any
influence on AITU of HIV/AIDS M&E online learning platform (Table 3).
Discussion and implications
Discussion
Information technology is key to online learning development. The progress in the internet ap-
plications and online-related tools have impacted the increase of online learning.48 This study
sought to explore the Acceptability for an Online Capacity Building Platform for HIV and AIDS
Monitoring and Evaluation (M&E) in Ghana. Well-built ICT tools give a platform to improve skills,
knowledge transfer and have control over data.49–51
The technology acceptance model cannot be looked at without M&E officers’ attitude
towards a particular system.52,53 The TAM determines factors of M&E officers’ behavioural
intentions to use a new technology. Research suggest that the desire to use any system is
determined by the person’s attitude.54,55 The results from this study supports this relationship,
as it indicate that attitude towards an online learning platform has a positive significant influence
on intention to use the M&E online learning platform. In addition, the attitude of the individual
is affected by how useful the new system would help them achieve their goals. The study found
that, PU has a positive influence on M&E officers’ attitude towards the M&E online learning
platform. This outcome is supported by other studies.54,55 It is imperative that future im-
plementation of M&E online learning platform to enhance M&E capacity building would focus
on the users. This approach is necessary because the user perceived the system to be useful and
thereby serving their purpose.56–58
Studies have also shown that ATU is significantly influenced by Perceived ease of use
(PEOU).40,49–51 This study confirms this outcome that perceived ease of use (PEOU) has a positive
influence on M&E officers’ attitude toward usage (ATU) of M&E online learning platform. Once
the systems is seen to be flexible and free from difficulties, M&E officers would develop a fa-
vourable attitude towards it.59 Every user has his/her own way of perceiving any new technology.
They would develop a positive attitude towards the system once they see it to be flexible. So it is
important that users of the system would be engaged in when it comes to implementation of this
laudable project. PEOU is the extent to which one trust that using the system would be easy and free
from hustle.60 These findings are in agreement with a study conducted by Shanaq and Bani-Domi
(2010) for 28 teachers and 118 students, which revealed that they both have positive attitude toward
e-learning.61 The findings are also consistent with similar studies13,45,59 which indicated that PEOU
has a significant effect on both PU and ATU. M&E officers and focal persons who find online
learning platform easy to use could explain this significant effect and are likely to have favourable
attitudes toward the perceived usefulness of the M&E online learning platform. According to Shroff
et al., (2011), “users’ positive feelings toward the perceived ease of use of technology are correlated
with continual use of the technology”.59 This research did not establish a significant relationship
between importance to your success (ITS) and acceptability/intention to use M&E online learning
platform.
14 Health Informatics Journal
A person’s attitude is influenced by the manner in which they presumed a technology would be
useful to them. Once they consider the technology to be appropriate and useful, they show a positive
attitude towards it. Therefore, attitude toward usage (ATU) has a positive influence on
Acceptability/Intention to use (AITU).59,62–64 This findings is also supported by our study that, there
is a positive relationship between M&E officers’ attitude toward usage (ATU) and Acceptability/
Intention to use (AITU) M&E online learning platform. It is important to note that combined factors
such as individual performance and effort positively affect acceptability/Intention to use (AITU) a
new system.54 In a nutshell, perceived usefulness and perceived ease of use mediated by attitude
towards usage would influence acceptability/Intention to use (AITU) of the new M&E online
learning platform.
Concerning M&E officers’ Experience with Online Learning (OLC), our result show that OLC
has a positive significant relationship with PU of the M&E online learning platform. This finding is
consistent with previous studies that found positive relationship between experience and perceived
usefulness.65–68 They reported that when users feel adequate they are more likely to find a system to
be useful. So, in the e-learning environment, there is need to enhance the capacity of users in a
timely manner to boost their confidence to use the new technology. In this study, the M&E officers’
experience with online learning facilities with additional technical support would urge them to
perceive the M&E online learning platform to be useful. The results of our study show no rela-
tionship between M&E officers’ Internet usage (IU) and PU of M&E online learning platform. This
is consistent with some previous studies.33,69–71 The relationship between IU and PU is a clear
indication for further research. The insignificant relationship between internet usage and perceived
usefulness of M&E online learning platform shows experience associated with internet usage may
not be a factor related to M&E officers’ perceived usefulness of online learning platform. From the
HIV/AIDS M&E online learning platform implementation point of view, it is a welcoming finding
since perceived usefulness of a well-built M&E e-learning platform may not be link to previous
internet usage experience.
Discussions with regards to the internet and importance of e-learning platforms have been
deemed to be part of a person’s subjective norms. Internet discussion was found to be associated
with perceived ease of use of M&E online learning platform. Abdad et al., (2009) indicated that
individuals will use an e-learning platform with little peer pressure once they have high expectations
of it serving their communication purposes.33 This accounts for the high influence of ID on PEOU in
this study. Since there is limited studies investigating subjective factors influencing PEOU, further
research is required to examine these subjective norms influence on PEOU. This study found no
relationship between importance to success (ITS) and perceived ease of use (PEOU) of HIV/AIDS
M&E online learning platform.
Implications
In planning for a new online training platform, the programme implementing partners should take
into consideration the view of the users of the system and explore their possible acceptance of the
systems. The results of this study show that attitude towards an online learning platform, perceived
usefulness, and ease of use of the system all have significant influence on intention to use the M&E
online learning platform. This suggest that future implementation of M&E online learning platform
to enhanceM&E capacity building would focus on the users. This approach is necessary because the
user perceived the system to be useful and thereby serving their purpose. Once the system is seen to
be flexible and free from difficulties, M&E officers would develop a favourable attitude towards it.
So, it is important that users of the system would be engaged when it comes to implementation of
Dery et al. 15
this M&E online learning platform project. In addition, programme implementers can enhance user
acceptability of M&E online learning platform by engaging M&E officers in the design and
implementation process by evaluating their perception (PU, PEOU) about the M&E online learning
platform at key stages of the design process and take measures to correct any negative perception
that may arise. The results also show that experience with online learning (OLC) has a positive
significant relationship with PU of the M&E online learning platform. It shows that M&E officers
who have computer related capabilities trust themselves to be in the position to use the M&E online
learning platform and see the system as an easy to use. This call for programme implementing
partners as part of building capacity for M&E to invest in infrastructure for Internet and related
technologies and equipment to facilitate online learning, meetings, and discussions.
The strength and limitation of the study
The strength of this research is the method of analysis applied, which is the structural equation
modelling (SEM). The SEM was applied because of the advantages it has over the multiple re-
gression method to determine the extent of effect of the independent variable on the dependent
variable. SEM is able to show both the direct and indirect effect of the independent variables on the
dependent variable as compared to multiple regression method. An important limitation of the study
is small sample involved in the study making it difficult to draw a general conclusion for the entire
country. This is as a results of the targeted training for only persons involved in the monitoring and
evaluation of HIV/AIDS activities across the country. Another limitation is that the model did not
adjust for potential confounders such as age, gender, educational level and organisational type
because SEM is a system of relations among latent and measured variables and not demographic
characteristics.72
Conclusion and recommendations
Our study sought to explore the Acceptability for an Online Capacity Building Platform for HIVand
AIDS M&E in Ghana. This study has shown that the M&E Officers and focal persons have high
acceptability for an online capacity building platform for M&E. The M&E online learning platform
is part of e-learning technologies, which when utilised in addition to face-to-face training pro-
gramme, has the potential to provide a more sustainable M&E capacity building for HIVand AIDS
in Ghana.
Despite the findings, we recommend that future study must be done to confirm the validity of the
model. It is obvious that several factors may have influence on acceptability/Intention to use M&E
online platform for capacity building and satisfaction in online learning environments. Additional
perfection of the proposed model may ascertain other factors that influence the quality of M&E
online learning for capacity building. For instance, there are some course content factors such as
course content, structure, designs and instructor experience that have not been examined in this
research. Addressing these shortfalls would enhance the generalization of the findings to other M&E
training approaches.
Acknowledgements
The authors wish to thank Ghana AIDS Commission (GAC), United States President’s Emergency Plan for
AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC), Morehouse School of
16 Health Informatics Journal
Medicine (MSM) and the School of Public Health, University of Ghana (SPH) for all the support provided for
the study to be carried out.
Authors’ Contributions
The study was conceptualised and designed by SKKD. CKA undertook literature review for the study and
coordinated the field data collection. GA and SKKD undertook the analysis, interpreted the results and
produced manuscript in line with the journal’s guidelines. FBDV and SKD reviewed the manuscript. All
authors thoroughly reviewed the draft manuscript and approved the final version.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or
publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or pub-
lication of this article: This work was supported by the UJMT Fogarty Global Health Fellows Program.
Ethical Consideration
The research was reviewed and approved by Institutional Review Board (IRB) of Noguchi Memorial Institute
for Medical Research, University of Ghana. The Institutional Review Board (IRB) number issued is 083/15-16.
Study participants gave a written informed consent.
ORCID iD
Godwin Adzakpah  https://orcid.org/0000-0002-6916-6733
Supplemental Material
Supplemental material for this article is available online.
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