FACULTY OF HEALTH AND APPLIED SCIENCES http://localhost:8080/xmlui/handle/123456789/3 2026-04-12T21:57:31Z 2026-04-12T21:57:31Z Ankamah, Samuel Gyesi, Kwesi Amponsah, Vivian http://localhost:8080/xmlui/handle/123456789/30626 2025-02-10T13:47:29Z 2024-08-30T00:00:00Z

Title: Awareness, knowledge, and attitude towards artificial intelligence: Perspective of medical students in Ghana Authors: Ankamah, Samuel; Gyesi, Kwesi; Amponsah, Vivian Abstract: Abstract The adoption of emerging technologies among university students has become increasingly prevalent in recent years. AI-assisted technologies are gradually permeating medical education and practice to improve healthcare delivery and reduce resource waste. This study aimed to investigate the awareness, use, and perception of AI among medical students in Emmanuel Quaye Archampong Library at the University of Ghana. Using a survey research design, data were collected from medical students at the University of Ghana Medical School. Structured questionnaires were administered to the respondents online using Google Forms. With a total of 1366 respondents, Krejcie and Morgan’s published table was employed to select the study sample size of 302 medical students. Forty-eight (39.0%) medical students agreed that the use of AI-assisted technologies was voluntary without being coerced to use them. More than half of the respondents (50.4%) reported being moderately aware of AI-assisted technologies and adequately understanding the concept of AI. Grammarly and ChatGPT were predominantly used in medical studies, despite the lack of opportunities for training on AI-assisted technologies. It is recommended that regular training and guidance be provided to students to appropriately use AI-assisted technologies in research and learning. Keywords artificial intelligence, technology acceptance model, medical students, academic library, Ghana Description: FACULTY STAFF PUBLICATION

2024-08-30T00:00:00Z Atakro, Confidence Alorse Atakro, Abigail Aboagye, Janet Sintim Blay, Alice Aluwah Addo, Stella Boatemaa Agyare, Dorcas Frempomaa Adatar, Peter Amoa-Gyarteng, Kwaku Gyimah Menlah, Awube Garti, Isabella Boni, George Sedinam Berchie, Osei Kwaku Ansong, Isaac Kwadwo http://localhost:8080/xmlui/handle/123456789/30496 2022-12-09T04:20:57Z 2021-01-18T00:00:00Z

Title: Older people’s challenges and expectations of healthcare in Ghana: A qualitative study Authors: Atakro, Confidence Alorse; Atakro, Abigail; Aboagye, Janet Sintim; Blay, Alice Aluwah; Addo, Stella Boatemaa; Agyare, Dorcas Frempomaa; Adatar, Peter; Amoa-Gyarteng, Kwaku Gyimah; Menlah, Awube; Garti, Isabella; Boni, George Sedinam; Berchie, Osei Kwaku; Ansong, Isaac Kwadwo Abstract: Abstract Background The increase in the number of elderly persons in developing countries has not had a corresponding increase in social and health care support systems for the elderly. There is a substantial difference in the quality of healthcare received by older people in developing and developed Description: STAFF/FACULTY PUBLICATION (E-JOURNAL)

2021-01-18T00:00:00Z Lartey, Agyei Helena Wang, Jianming Lartey, Philip Agyei, James Agyei, Alex Aboagye, Janet Sintim http://localhost:8080/xmlui/handle/123456789/30495 2022-12-09T03:59:49Z 2020-06-18T00:00:00Z

Title: Modeling and predictionof hypertension in Komfo Anokye Teaching Hospital (KATH), Ghana Authors: Lartey, Agyei Helena; Wang, Jianming; Lartey, Philip; Agyei, James; Agyei, Alex; Aboagye, Janet Sintim Abstract: To explore the temporal trends of hypertension in a Ghana population and to predict future values, which will, in turn, help control and reduce the risk of hypertension-related health events. We enrolled 108,100 cases with essential hypertension from January 2015 to December 2019 at the Komfo Anokye Teaching Hospital (KATH), Ghana. The Box-Jenkins Autoregressive Integrated Moving Average model (ARIMA) was used to identify trends and forecast data from a specified time series. The root mean square error (RMSE), Q-statistic, residual variance (RV), and Akaike’s information criteria (AIC) were used to assess the performance of the model. The most optimal model was ARIMA(1, 1, 0) with RV(7061), RMSE(82.6155), AIC(693.48), Q-value(19.187), parameter(-0.4034) and constant(188.6501). The best fitting model was Yt = (1-0.4034)Yt-1 -0.4034Yt-2 +1801.6670. The model estimated an increase in hypertension cases for the next period, which was a critical input in managerial and administrative decision making. The forecast was accurate enough to allow for better planning and control than could be accomplished without the forecast. Keywords:Hypertension, Forecast, ARIMA, RMSE, RV, AIC Description: STAFF/FACULTY PUBLICATION (E-JOURNAL)

2020-06-18T00:00:00Z Atakro, Confidence Alorse Addo, Stella Boatemaa Aboagye, Janet Sintim Menlah, Awube Garti, Isabella Amoa-Gyarteng, Kwaku Gyimah Sarpong, Theresa Adatara, Peter Kumah, Kwasi Junior Asare, Bernard Bediako Mensah, Ami Korkor Lutterodt, Squiter Hans Boni, George Sedinam http://localhost:8080/xmlui/handle/123456789/30494 2022-12-09T03:47:43Z 2019-01-01T00:00:00Z

Title: Contributing factors to unsafe abortion practices among women of reproductive age at selected district hospitals in the Ashanti region of Ghana Authors: Atakro, Confidence Alorse; Addo, Stella Boatemaa; Aboagye, Janet Sintim; Menlah, Awube; Garti, Isabella; Amoa-Gyarteng, Kwaku Gyimah; Sarpong, Theresa; Adatara, Peter; Kumah, Kwasi Junior; Asare, Bernard Bediako; Mensah, Ami Korkor; Lutterodt, Squiter Hans; Boni, George Sedinam Abstract: Abstract Background: Despite the existence of an abortion law and a safe abortion policy in Ghana, the Ghana Statistical Service found that 15% of all women in the reproductive age group (15–49 years) have practiced unsafe abortions. The objective of this study was to explore factors that contribute to the high incidence of unsafe abortion practices in the Ashanti Region of Ghana. Methods: A qualitative descriptive study design was used to assess factors that contribute to unsafe abortion practices. Purposive sampling technique was employed in selecting participants. Data were collected through key informant interviews and focus group discussions. One hundred and eleven participants were involved in the study. Data analysis was carried out through qualitative content analysis. Results: Seven thematic categories were elicited from data collected. The categories are: a) Lack of knowledge of safe abortion services; b) Socio-economic conditions as a perceived influence for unsafe abortion practices; c) Safe abortion as a perceived religious and cultural taboo in Ghana; d) Stigma of unplanned pregnancy; e) A desire to bear children only after marriage; f) Avoiding parental/guardian disappointment and resentment; g) A desire to pursue education. Conclusions: Evidence available in this study suggests that several factors are responsible for unsafe abortion practices in Ghana. Lack of knowledge on safe abortion services, poor socio-economic conditions, cultural and religious beliefs, a stigma of unplanned pregnancy, a desire to bear children only after marriage, attempts to avoid parental/guardian disappointment and resentment, and a desire to pursue education were cited by participants as situations that contributed to unsafe abortion practices. Measures such as Aunty Jane, Ms. Rose and Women Help Women programmes can be publicised to reduce maternal morbidity and mortality that occur as a result of unsafe abortions in Ghana. Improvement in family planning education in educational institutions needs to be considered in order to reduce the rate of unwanted pregnancies among young women in school. Keywords: Unsafe, Abortion, Ghana, Law, Taboo, Stigma, Unplanned, Abortion policy, Ashanti Description: STAFF/FACULTY PUBLICATION (E-JOURNAL)

2019-01-01T00:00:00Z