About the Author(s)

Nana K. Ayisi-Boateng Email symbol
Department of Medicine, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Fred S. Sarfo symbol
Department of Medicine, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Douglas A. Opoku symbol
Family Healthcare Services, Allen Clinic, Kumasi, Ghana

Emmanuel K. Nakua symbol
Department of Epidemiology and Biostatistics, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Emmanuel Konadu symbol
University Hospital, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Phyllis Tawiah symbol
Department of Medicine, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Ruth Owusu-Antwi symbol
Department of Psychiatry, Komfo Anokye Teaching Hospital, Kumasi, Ghana

Akye Essuman symbol
School of Medicine, University of Health and Allied Sciences, Ho, Ghana

Bernard Barnie symbol
Department of Surgery, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Charles Mock symbol
Department of Epidemiology, School of Public Health, University of Washington, Washington, United States of America

Peter Donkor symbol
Department of Surgery, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana


Ayisi-Boateng NK, Sarfo FS, Opoku DA, et al. Educational intervention to enhance the knowledge of Ghanaian health workers on Alzheimer’s disease and related dementias. Afr J Prm Health Care Fam Med. 2022;14(1), a3448. https://doi.org/10.4102/phcfm.v14i1.3448

Original Research

Educational intervention to enhance the knowledge of Ghanaian health workers on Alzheimer’s disease and related dementias

Nana K. Ayisi-Boateng, Fred S. Sarfo, Douglas A. Opoku, Emmanuel K. Nakua, Emmanuel Konadu, Phyllis Tawiah, Ruth Owusu-Antwi, Akye Essuman, Bernard Barnie, Charles Mock, Peter Donkor

Received: 24 Jan. 2022; Accepted: 09 Mar. 2022; Published: 26 Apr. 2022

Copyright: © 2022. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background: Alzheimer’s disease and related dementias (ADRDs) pose a major public health challenge in older adults. In sub-Saharan Africa, the burden of ADRD is projected to escalate amidst ill-equipped healthcare workers (HCWs).

Aim: This study aimed to assess ADRD knowledge amongst Ghanaian HCWs and improve gaps identified through a workshop.

Setting: Study was conducted among HCWs attending a workshop in Kumasi, Ghana.

Methods: On 18 August 2021, a workshop on ADRD was organised in Kumasi, Ghana, which was attended by 49 HCWs comprising doctors, nurses, pharmacists, social workers and nutritionists. On arrival, they answered 30 pre-test questions using the Alzheimer’s Disease Knowledge Scale (ADKS). A post-test using the same questionnaire was conducted after participants had been exposed to a 4-h in-person educational content on ADRD delivered by facilitators from family medicine, neurology, geriatrics, psychiatry and public health.

Results: The mean age of participants was 34.6 (± 6.82), mean years of practice was 7.7 (± 5.6) and 38.8% (n = 19) were nurses. The mean score of participants’ overall knowledge was 19.8 (± 4.3) at pre-test and 23.2 (± 4.0) at post-test. Participants’ pre-test and post-test scores improved in all ADKS domains. Factors associated with participants’ knowledge at baseline were profession, professional rank and the highest level of education attained. After adjusting for age and sex, participant’s rank, being a specialist (adjusted β = 14.44; 95% confidence interval [CI] = 7.03, 21.85; p < 0.001) was an independent predictor of knowledge on Alzheimer’s disease.

Conclusion: Existing knowledge gaps in ADRD could be improved via continuous medical education interventions of HCWs to prepare healthcare systems in Africa for the predicted ADRD epidemic.

Keywords: Alzheimer’s; dementia; knowledge; health workers; Ghana.


Alzheimer’s disease and related dementias (ADRDs) is typified as a progressive neurodegenerative disease characterised by cognitive decline, memory loss, impaired judgement and behavioural changes. Globally, about 43.8 million people live with dementia and Alzheimer’s disease is considered the commonest form.1,2 The prevalence of Alzheimer’s disease in older adults ≥ 65 years is reported to be from 2.4% to 15.8%.1 Alzheimer’s disease and related dementias has not been given much attention in developing countries, especially in sub-Saharan Africa. However, because of an ageing population, dementia is becoming more common in Africa with a reported prevalence of 1.0% – 5.3% and Alzheimer’s disease comprises 60.0% of dementia cases.3 Amongst Nigerians, an estimated 2.6% to 6.4% people are living with dementia4,5 and 13.6% of post-stroke survivors in Ghana have vascular dementia.6 It is projected that by 2040, developing countries will account for 71.0% of 81.1 million dementia cases.3,7

The regional differences in prevalence of ADRD may be due to different diagnostic criteria and screening tools, sociocultural dimensions such as stigma, which prevents early report of symptoms and various degrees of awareness or understanding about the disease.8 Changes in anatomy of neurons, establishment of adult brain structure, early life exposures and genetic factors have been postulated to underlie an individual’s risk of developing ADRD.9 However, its exact aetiology remains elusive, there is currently no definitive cure and knowledge about the disease is limited.

Undoubtedly, healthcare workers’ (HCWs’) knowledge of ADRD makes a significant difference in early detection, effective intervention, support for carers and progression of the disease. At least 25% of cases of ADRD with mild manifestations are missed at the primary care level.1 A study has predicted a 9.2 million decline in number of ADRD cases if an intervention is provided to achieve at least a one-year delay in disease onset and progression.10 However, there are knowledge gaps and a lack of awareness amongst HCWs about the disease and this has been documented elsewhere.11 The authors therefore sought to assess Ghanaian HCW’s knowledge on ADRD before and after participating in a workshop on the subject. They also solicited their resolutions and recommendations on measures to enhance knowledge and minimise the impact of the disease.


Study design

This was a pre- and post-test cross-sectional study involving a sample of healthcare professionals working in both public and private facilities in Kumasi, Ghana. Participants included doctors, nurses, pharmacists, social workers, nutritionists and public health practitioners working in primary, secondary and tertiary institutions who were invited to attend a workshop on ADRD on 18 August 2021.

Workshop proceedings and data collection

As participants reported to the venue, they were welcomed and, after registration, a pre-test questionnaire using the Alzheimer’s Disease Knowledge Scale (ADKS) was shared with them. The ADKS is a 30 true-false questions validated tool, which has previously been used in other studies.12,13 Participants voluntarily provided answers to the questionnaire that were returned to workshop organisers before presentations by facilitators. The facilitators were a family physician, a neurologist, a geriatrician, a psychiatrist and a public health specialist. Topics treated ranged from epidemiology of the disease, clinical manifestations, diagnosis and treatment, providing support for families and carers and mental health issues associated with ADRD. After the presentations, a post-test using the same ADKS questionnaire was conducted to determine any change in participants’ knowledge.

Participants were placed in five heterogeneous groups of maximum ten members who listed personal resolutions on how they would apply the knowledge acquired during the workshop in their daily work and also provided a list of recommendations to policymakers on how to better address ADRD in Ghana.

Statistical analysis

Demographic data were obtained from participants and the scores from the ADKS questionnaire. Data were entered into an excel spreadsheet for data quality management. Two independent data officers cleaned the data to ensure that there were no wrong and double entries. The data were merged and later checked for consistency. The data were exported to STATA version 16 for analysis. Mean and standard deviations were calculated. A t-test or one-way analysis of variance (ANOVA) test was conducted to assess the difference in health workers’ knowledge on Alzheimer’s disease using the ADKS at both pre-test and post-test. Univariate and multivariate linear regression analyses were performed to determine the independent predictors of health workers’ knowledge on Alzheimer’s disease. In the multivariate linear regression model (model 2), we adjusted for age and sex together with significant variables in the univariate model (model 1). In all analyses, p-values ≤ 0.05 were considered as significant at a 95% confidence interval (CI).

Ethical considerations

Ethical approval was obtained from the Committee on Human Research Publications and Ethics at the School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana (CHRPE/AP/122/21).


Demographic characteristics of participants

The mean age of participants was 34.6 (± 6.8) years with a minimum age of 22 years and a maximum age of 50 years. More than half (51.0%, n = 25) of the participants were females. About 38.8% (n = 19) of the participants were nurses whilst over 24.5% of the participants were medical officers and pharmacists. The mean years of practice was 7.7 (± 5.6) with almost half (44.9%, n = 22) of the participants having practiced for between 1 and 5 years. Majority (59.2%, n = 29) of the participants were involved in the management of patients with Alzheimer’s disease (Table 1).

TABLE 1: Demographic characteristics of participants (N = 49).
Participants’ knowledge on Alzheimer’s disease

With a maximum score of 30, the overall mean score of participants’ knowledge as measured by the ADKS was 19.8 (± 4.3) at pre-test and 23.2 (± 4.0) at post-test. There was an increase in the proportion of participants who had correct answers in all the seven domains of risk factors (6.12% vs 26.53%), symptoms (18.37% vs. 20.41%), course (26.53% vs 36.73%), assessment and diagnosis (38.78% vs 69.39%), treatment and management (57.14% vs. 65.31%) caregiving (2.04% vs. 36.73%) and life impact (42.86% vs. 67.35%).

Notably, participants with correct responses for several individual questions were low at baseline. The questions included: When people with Alzheimer’s disease begin to have difficulty taking care of themselves, caregivers should take over right away (40.82% of participants responded correctly). It has been scientifically proven that mental exercise can prevent a person from getting Alzheimer’s disease (38.78%) and tremor or shaking of the hands or arms is a common symptom in people with Alzheimer’s disease (44.90%). Post-test scores for these questions and majority of others improved (Table 2).

TABLE 2: Alzheimer’s Disease Knowledge Scale domains and proportion of participants with correct answers at pre-test and post-test.
TABLE 2 (Continues ...): Alzheimer’s Disease Knowledge Scale domains and proportion of participants with correct answers at pre-test and post-test.

However, there were some individual questions for which the proportion of participants with correct responses dropped on the post-test. These were people in their 30s can have Alzheimer’s disease (51.02% vs 48.98%), trouble in handling money or paying bills is a common early symptom of Alzheimer’s disease (71.43% vs 57.14%), once people have Alzheimer’s disease, they are no longer capable of making informed decisions about their own care (59.18% vs 48.98%) and after symptoms of Alzheimer’s disease appear, the average life expectancy is 6 to 12 years (65.31% vs 51.02%) (Table 2).

Relationship between demographic characteristics and participants’ knowledge on Alzheimer’s disease at pre-test and post-test

At pre-test and post-test, factors associated with participants’ knowledge were their profession (p = 0.007; p < 0.001), professional rank (p = 0.008; p < 0.001) and the highest level of education attained (p = 0.007; p = 0.008) (Table 3).

TABLE 3: Demographic characteristics and their relationship with Alzheimer’s knowledge at pre-test and post-test.
Predictors of participants’ knowledge on Alzheimer’s disease at both pre-test and post-test

The results of the multiple linear regression after adjusting for age and sex showed that participant’s rank was an independent predictor of knowledge on Alzheimer’s disease using ADKS at pre-test. Specialist (adjusted [adj] β = 14.44; 95% CI = 7.03, 21.85; p < 0.001) and medical officer/pharmacist (adj β = 13.99; 95% CI = 6.87, 21.10; p < 0.001) were the most significant predictors of participant’s knowledge. This model explained about 40.9% variance of participant’s knowledge on Alzheimer’s disease using ADKS at pre-test (Table 4).

TABLE 4: Linear regression model predicting the overall knowledge of Alzheimer’s disease at pre-test.

At post-test, in model 2, after adjusting for age and sex, the results showed that participant’s rank was independently associated with knowledge on Alzheimer’s disease using ADKS. Specialist (adj β = 7.04; 95% CI = 0.40, 13.68; p = 0.039) was independently associated with high knowledge score. This model explained about 42.9% variance of participant’s knowledge on Alzheimer’s disease using ADKS at post-test (Table 5).

TABLE 5: Regression model predicting the overall knowledge of Alzheimer’s disease at post-test.
Participants’ resolutions and recommendations

From the five groups with interprofessional representation, some resolutions and recommendations made included the need for greater multidisciplinary and multisectorial collaboration, increased public education on ADRD, provision of financial and social support and expansion of geriatric services to cater for people living with ADRD and their families (Table 6).

TABLE 6: Participants’ resolutions and recommendations.


By 2050, the number of people living with ADRD is projected to hit 106.8 million10 and this calls for increased awareness, identification of knowledge gaps and institution of appropriate educational interventions for relevant stakeholders. Comparable with our findings, an earlier study found the ADKS questionnaire to be a useful tool in identifying education needs of health workers and assessing effectiveness of education efforts.12 In this study, in which 59.2% of the participants indicated some involvement in managing patients with Alzheimer’s disease, their mean ADKS at pre-test was 19.8 (± 4.28) and this significantly increased to 23.2 (± 4.01). These mean scores amongst HCWs were higher than 11.7 ± 3.02 obtained amongst elderly Egyptians14 but lower than 20.15 to 27.40 reported by Carpenter et al in the United States.13 Our participants’ knowledge scores increased in all seven ADKS domains. In a previous study, domains with significant ADKS scores were assessment, treatment and management and the participants recorded the least scores in the risk factors and prevention domains.13

The ADKS is predicted to produce different scores for various categories of health workers, based on their experience and theoretical knowledge.12 In our study, type of profession and years of practice did not impact the ADKS scores. However, a participant’s rank was an independent predictor of pre- and post-test scores. Those with post-graduate medical qualification, considered specialists and comprised 18.4% of the participants, recorded the highest overall scores. These were specialists in family medicine, internal medicine and psychiatry who practice at primary, secondary and tertiary level facilities. This implies that in our setting, specialists can lead capacity-building efforts across various levels of care. It also suggests the need to intensify education interventions for the 81.6% HCWs below the specialist rank. The bulk of these HCWs work in primary care settings. Perhaps, the 4-h duration of the workshop was inadequate and this category of HCWs may benefit from a more prolonged training engagement.

The baseline (pre-test) scores and the improvement in scores in both content areas and in specific questions point towards areas that might need extra attention in future efforts to build knowledge on ADRD in the HCW in Ghana and other similar countries.

Resolutions shared by the participants are quite insightful and critical to addressing ADRD challenges, which may be provider-related, patient-related or health system-related. Participants recommended inclusion of medications for managing ADRD in the National Health Insurance Scheme (NHIS) and provision of financial support for families living with the disease. With an estimated $156 billion worldwide direct cost of dementia and a projection of higher costs in developing countries,8 there is the need for system-based financial cushioning. In spite of its challenges, Ghana’s NHIS and health insurance schemes in other parts of the world have been a source of financial reprieve for the poor and vulnerable.15,16 Another recommendation by participants is the provision of geriatric services at various health institutions in Ghana and creation of an aged-friendly and supportive environment. This calls for intense education. An interprofessional, team-based approach in which various categories of health workers are trained and their expertise harnessed was an important recommendation by our participants and this has been touted as an innovative strategy.17,18 Our workshop, which assembled a wide spectrum of health workers, has therefore provided a foundation for future collaborations in ADRD-related activities in Ghana.

Strengths and limitations

The findings of this study are very relevant, as to our knowledge, this is the first to be carried out in sub-Saharan Africa using ADKS among HCWs whose role in addressing the looming ADRD epidemic cannot be overemphasised. The sociodemographic and professional characteristics of the participants were varied and quite representative of HCWs in Ghana. Previous studies have been undertaken in Egypt and the United States amongst different populations. Unlike these earlier studies, ours goes beyond highlighting domains with knowledge gaps to analysing pre- and post-test scores after a training session. Our study is limited by the relatively small sample size and the 4-h engagement with participants. In addition, being a cross-sectional study, we are limited in our ability to generalise our findings. Future studies should target a larger population of participants.


Knowledge gaps on ADRD exist amongst Ghanaian HCWs and educational intervention where local expertise help train a sample of HCWs improved scores on ADRD by four units. Amongst others, we have recommended NHIS funding of ADRD management, intensification of education at the primary care level, expansion of geriatric services and interprofessional collaboration. Increased awareness amongst the general population and training of a critical mass of health professionals are needed to care for sufferers and support families grappling with the debilitating effects of ADRD.


We are grateful to all the healthcare workers who attended the workshop and participated in the knowledge assessment using the Alzheimer’s Disease Knowledge Score (ADKS) questionnaire.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors’ contributions

P.D. and C.M. secured funding for this project. N.K.A.-B., F.S.S., P.T., R.O.-A. and E.K.N. facilitated the workshop. N.K.A.-B., F.S.S., D.A.O. and E.K. were involved in data collection, data analysis and preparation of the first draft of manuscript. P.T., A.E., B.B. and C.M. assisted with the review and final editing of the article. All authors reviewed and approved the final manuscript for submission.

Funding information

This study was supported by the Fogarty International Center, National Institute on Aging of the National Institutes of Health under Award Number D43 TW 007267-15S1. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Health.

Data availability

Data associated with this manuscript are available upon reasonable request from the corresponding author, N.K.A.-B.


The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.


  1. Hendrie HC. Epidemiology of dementia and Alzheimer’s disease. Am J Geriatr Psychiatry. 1998;6(2 SUPPL.):S3–S18. https://doi.org/10.1097/00019442-199821001-00002
  2. Nichols E, Szoeke CEI, Vollset SE, et al. Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):88–106. https://doi.org/10.1016/S1474-4422(18)30403-4
  3. Kalaria RN, Maestre GE, Arizaga R, et al. Alzheimer’s disease and vascular dementia in developing countries: Prevalence, management, and risk factors. Lancet Neurol. 2008;7(9):812–826. https://doi.org/10.1016/S1474-4422(08)70169-8
  4. George-Carey R, Adeloye D, Chan KY, et al. An estimate of the prevalence of dementia in Africa: A systematic analysis. J Glob Health. 2012;2(2):1–13. https://doi.org/10.7189/jogh.02.020401
  5. Ochayi B, Thacher TD. Risk factors for dementia in central Nigeria. Aging Ment Heal. 2006;10(6):616–620. https://doi.org/10.1080/13607860600736182
  6. Sarfo FS, Akassi J, Adamu S, Obese V, Ovbiagele B. Burden and predictors of poststroke cognitive impairment in a sample of Ghanaian stroke survivors. J Stroke Cerebrovasc Dis. 2017;26(11):2553–2562. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.05.041
  7. Ferri CP, Prince M, Brayne C. Alzheimer’s disease international. Global prevalence of dementia: A Delphi consensus study. Lancet. 2005;366(9503):2112–2117. https://doi.org/10.1016/S0140-6736(05)67889-0
  8. Wimo A, Jonsson L, Winblad B. An estimate of the worldwide prevalence and direct costs of dementia in 2003. Dement Geriatr Cogn Disord. 2006;21(3):175–181. https://doi.org/10.1159/000090733
  9. Seifan A, Schelke M, Obeng-Aduasare Y, Isaacson R. Early life epidemiology of Alzheimer’s disease – A critical review. Neuroepidemiology. 2015;45(4):237–254. https://doi.org/10.1159/000439568
  10. Brookmeyer R, Johnson E, Ziegler-Graham K, Arrighi HM. Forecasting the global burden of Alzheimer’s disease. Alzheimers Dement. 2007;3(3):186–191. https://doi.org/10.1016/j.jalz.2007.04.381
  11. Rust TB, See SK. Knowledge about aging and Alzheimer disease: A comparison of professional caregivers and noncaregivers. Educ Gerontol. 2007;33(4):349–364. https://doi.org/10.1080/03601270701199065
  12. Carpenter BD, Balsis S, Otilingam PG, Hanson PK, Gatz M. The Alzheimer’s disease knowledge scale: Development and psychometric properties. Gerontologist. 2009;49(2):236–247. https://doi.org/10.1093/geront/gnp023
  13. Carpenter BD, Zoller SM, Balsis S, Otilingam PG, Gatz M. Demographic and contextual factors related to knowledge about Alzheimer’s disease. Am J Alzheimers Dis Other Demen. 2011;26(2):121–126. https://doi.org/10.1177/1533317510394157
  14. El-masry R, Elwasify M, Khafagi M. Adaptation and reliability of the Arabic version of Alzheimer’s Disease Knowledge Scale (ADKS) among sample of middle aged and elderly Egyptians attending outpatient clinics in Mansoura University Hospital. Egypt J Community Med. 2018;36(4):59–69. https://doi.org/10.21608/ejcm.2018.22997
  15. Christmals C Dela, Aidam K. Implementation of the National Health Insurance Scheme (NHIS) in Ghana: Lessons for South Africa and low-and middle-income countries. Risk Manag Healthc Policy. 2020;13:1879–1904. https://doi.org/10.2147/RMHP.S245615
  16. Castillo-Laborde C, Aguilera-Sanhueza X, Hirmas-Adauy M, et al. Health insurance scheme performance and effects on health and health inequalities in Chile. MEDICC Rev. 2017;19(2–3):57–64. https://doi.org/10.37757/MR2017.V19.N2-3.10
  17. Lingler J, Mulvaney E, Jacobs C, Berrio-Thomas S, Morris JM. O4-03-05: Interprofessional team training for early identification of ADRD. Alzheimers Dement. 2018;14(7S_Part_26):2018. https://doi.org/10.1016/j.jalz.2018.06.2925
  18. Arms T, Rowan N, Eusse A. Interprofessional approaches to symptoms of dementia. Gerontologist. 2015;55(Suppl_2):298–299. https://doi.org/10.1093/geront/gnv597.03


Crossref Citations

1. Validation of the mild cognitive impairment health literacy assessment scale (MCI-HLA scale) in middle-aged and older adults
Fengping Han, Yang Hu, Ying Feng, Li Qian, Jing Sun
Asian Journal of Psychiatry  vol: 89  first page: 103771  year: 2023  
doi: 10.1016/j.ajp.2023.103771