Intention to use wearable health devices and its predictors among diabetes mellitus patients in Amhara region referral hospitals, Ethiopia: Using modified UTAUT-2 model

Walle, Agmasie Damtew; Jemere, Adamu Takele; Tilahun, Binyam; Endehabtu, Berhanu Fikadie; Wubante, Sisay Maru; Melaku, Mequannent Sharew; Tegegne, Masresha Derese; Gashu, Kassahun Dessie

doi:10.1016/j.imu.2022.101157

Cited by 24 publications

(37 citation statements)

References 32 publications

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“…In the UTAUT2 model of context, the variables of sex, experience, and age affect the direction or strength of the connection between the exogenous and endogenous factors of intention to use technology (24). But, in this study, the experience was not used as a moderator because the majority of participants were unfamiliar with eLearning-based continuing professional development (53)(54)(55).…”

Section: Moderating Effects Of Intention To Use Elearning Continuing ...mentioning

confidence: 89%

“…points Likert scale and estimate median, participants scores median and above the median were intended, else not intended (53).…”

Section: Sample Size Determinationmentioning

confidence: 99%

“…The unconstrained model assumption showed that there is a moderator or statistical difference in the given variable to in uence exogenous and endogenous variables whereas the constrained model suggests that the variable is a similar effect to in uencing the relationship between exogenous and endogenous variables. If the signi cant difference between was found to be signi cant (chi-square difference > 5 or p-value < 0.05), then the proposed moderator variable was con rmed as moderator (53).…”

Section: Testing Potential Moderationmentioning

confidence: 99%

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Intention to Use eLearning-based Continuing Professional Development and its Predictors among Healthcare Professionals in Amhara Region Referral Hospitals, Ethiopia, 2023: Using modified UTAUT-2 model

Kelkay,

Anteneh,

Wubante

et al. 2023

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Background:Continuing Professional Development (CPD) is provided through in-service programs organized based on competency development and lifelong learning for healthcare professionals to stay fit with the required knowledge and skills. But, healthcare professionals’ financial constraints and tight schedules sending them away from the workplace for CPD training is a challenge. eLearning is becoming the best solution to overcome those barriers and create accessible, efficient, flexible, and convenient professional development. However, evidence is limited on health professionals’ intention to use eLearning-based CPD and its predictors. Hence this study was aimed toassess healthcare professionals’ intention to use eLearning-based CPD and its predictors in Amhara region referral hospitals, Ethiopia 2023. Methods:A cross-sectional study was conducted from March 28 to April 28, 2023. A total of 976 healthcare professionals participated in this study. Proportional allocation and a simple random sampling were used to select participants of the study. UTAUT2 model was applied to develop a theoretical framework. A structured self-administered questionnaire was used and a 5% pretest was performed. Data were entered into Epi data 4.6 and exported to SPSS 26 for descriptive analysis. AMOS 23 SEM was also used to describe and assess the degree and significance of relationships between variables. Results: About 51.8% (506/976) (95% CI: 48.7-55.0) of participants have the intention to use the eLearning for CPD. Performance expectancy (β=0.233, p-value<0.01), effort expectancy (β=0.082, p-value<0.05), facilitating condition (β=0.102, p-value<0.05), hedonic motivation (β=0.199, P-value<0.001), habit (β=0.473, P-value<0.001), and computer literacy (β=0.116, p-value<0.001)had a positive relationship with intention to use eLearning based CPD. Age and gender were also a moderator of habit to use eLearning based on CPD. Conclusion and recommendation: Overall, healthcare professionals' intention to use eLearning-based CPD was found low. Performance expectancy, effort expectancy, facilitating condition, hedonic motivation, habit, and computer literacy had a significantly positive influence on intention to use eLearning-based CPD. The development of a user-friendly eLearning-based CPD development that meets user expectations can enhance the intention to use.

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Section: Moderating Effects Of Intention To Use Elearning Continuing ...mentioning

confidence: 89%

“…points Likert scale and estimate median, participants scores median and above the median were intended, else not intended (53).…”

Section: Sample Size Determinationmentioning

confidence: 99%

Section: Testing Potential Moderationmentioning

confidence: 99%

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Intention to Use eLearning-based Continuing Professional Development and its Predictors among Healthcare Professionals in Amhara Region Referral Hospitals, Ethiopia, 2023: Using modified UTAUT-2 model

Kelkay,

Anteneh,

Wubante

et al. 2023

Preprint

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“…A structured self-administered questionnaire was employed in this study, which has been adapted from a number of studies on the UTAUT2 model (27,28,33,34). The questionnaire consists of two sections.…”

Section: Data Collection Toolsmentioning

confidence: 99%

Intention to use personal health records and associated factors among healthcare providers in Southwest Oromia region referral hospitals, Ethiopia: Using modified unified theory of acceptance and use technology 2 model

Dube,

Asemahagn,

Mulu

et al. 2023

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Introduction: The growing integration of vastly diversified technologies in the healthcare industry has made it necessary to collect organized and accurate data to support an informed decision in healthcare. The literature has revealed that the magnitude of intention to use personal health records among healthcare providers is low. Therefore, this study aimed to assess healthcare providers' intentions to use personal health records and its factors in Ethiopia. Methods A facility-based cross-sectional study was conducted among 781 healthcare providers in referral hospitals in the Southwest Oromia region, Ethiopia. A simple sampling technique was used to select the study participants among healthcare providers. A pretested self-administered questionnaire was used to collect the data. Data were entered and cleaned using Epidata 4.6, and descriptive data were analyzed using SPSS 25. The degree of correlation between exogenous and endogenous variables was described and validated using structural equation modeling using AMOS 26. Results A total of 736 healthcare providers (94.2% response rate) participated in the study. The proportion of intention to use personal health records was 57.6%, 95% CI (53.9–61.2). Performance expectancy (β = 0.325, P < 0.01), effort expectancy (β = 0.289, P < 0.01), social influence (β = 0.216, P < 0.01), and facilitating condition (β = 0.242, P < 0.01) had a positive direct relationship with intention to use personal health records. Age (β = 0.269, P = 0.040, β = 0.272, P < 0.001, β = 0.326, P < 0.001) was a moderator variable between performance expectancy, social influence, facilitating conditions, and intention to use personal health records. Conclusions Overall, healthcare providers intention to use personal health records were promising. Performance expectancy, effort expectancy, social influence, and facilitating conditions were statistically significant factors of intention to use personal health records among healthcare providers. The relationship between performance expectancy, social influence, facilitating conditions, and intention to use PHRs was positively moderated by age. Thus, implementers need to give priority to enhancing the provision of a better system, the knowledge and skills of healthcare providers, and awareness creation among staff by providing continuous training.

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“…In this study standard structured Amharic language questionnaire were used. The tool that we were used in this study has been adapted from different studies which were done by using UTAUT2 (15,72). The rst part focuses on participants' socio-demographic characteristics contains 9 question, health related 3 question and the third part contains 31 question that enables to measure the constructs and also the constructs were measured using ve-point Likert scale, in which 1 denoting for strongly disagree, 2 denoting disagree 3 neutral, 4 agree and 5 denoting for strongly agree.…”

Section: Data Collection Toolsmentioning

confidence: 99%

Intention to Use Patient Portal and Its Predictors Among Diabetic Patients Enrolled in Referral Hospitals, Amhara Regional State, Northwest Ethiopia, 2023: Utaut2 Modeling

Abebe

Tilahun

Derese

et al. 2023

Preprint

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Background Patient portal technology is increasingly utilized in the health care system for diabetes management, as means of communication and information-sharing tools and it has the potential to improve access, quality, and outcomes for diabetic patients. However, its adaption is relatively low and patients’ intention towards patient portal is unknown. This study aims to fill this gap by determining the intention to use the patient portal and its predictors among diabetic patients in Ethiopia. Method An institution-based cross-sectional study was conducted on 1078 diabetes patients from April 3 to May 8 in eight referral hospitals Amhara region, Ethiopia 2023. Sample was proportionally allocated for each hospital and participants were selected by using a systematic random sampling method. The data were collected in the same period in all hospitals by using interviewer-administered questioner; by kobo collect mobile app. Descriptive statistics were done using SPSS version 26. The degree of association between exogenous and endogenous variables was assessed and validated using structural equation modeling by AMOS version 21. Result A total of 1037 (96.2% response rate) diabetic patients participated in the study. Of them 407(39.25%), 95% CI: [36.4–42.2] were found to have an intention to use patient portal. Digital literacy (β = 0.312, 95% CI: [0.154–0.465], p < 0.01) performance expectancy (β = 0.303, 95% CI: [0.185–0.420], p < 0.01) effort expectancy (β = 0.25 95% CI: [0.131–0.392], p < 0.01) facilitating condition (β = 0.22 95% CI: [0.081–0.36], p < 0.01) and habit (β = 0.111 95% CI: [-0.009-0.227], p < 0.05) were significantly associated with intention to use patient portal. Effort expectancy and facilitating condition were positively moderated by gender. Conclusion This study found that diabetes patient’s intention to use patient portal was low. Intervention in digital literacy, performance expectancy, effort expectancy, facilitating conditions and habit are needed to improve diabetic patient’s intention to use the patient portal.

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Intention to use wearable health devices and its predictors among diabetes mellitus patients in Amhara region referral hospitals, Ethiopia: Using modified UTAUT-2 model

Cited by 24 publications

References 32 publications

Intention to Use eLearning-based Continuing Professional Development and its Predictors among Healthcare Professionals in Amhara Region Referral Hospitals, Ethiopia, 2023: Using modified UTAUT-2 model

Intention to Use eLearning-based Continuing Professional Development and its Predictors among Healthcare Professionals in Amhara Region Referral Hospitals, Ethiopia, 2023: Using modified UTAUT-2 model

Intention to use personal health records and associated factors among healthcare providers in Southwest Oromia region referral hospitals, Ethiopia: Using modified unified theory of acceptance and use technology 2 model

Intention to Use Patient Portal and Its Predictors Among Diabetic Patients Enrolled in Referral Hospitals, Amhara Regional State, Northwest Ethiopia, 2023: Utaut2 Modeling

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