Determinants of a mobile phone-based Interactive Voice Response (mIVR) system for monitoring childhood illnesses in a rural district of Ghana: Empirical evidence from the UTAUT model

Adjei, Timothy Kwabena; Mohammed, Aliyu; Acheampong, Princess Ruhama; Acquah-Gyan, Emmanuel; Sylverken, Augustina Angelina; Twumasi-Ankrah, Sampson; Owusu, Michael; Owusu‐Dabo, Ellis

doi:10.1371/journal.pone.0248363

Cited by 9 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of the study indicated that the main constructs of UTAUT, PE, and FC significantly influenced the public's intention to adopt telerehabilitation. Some previous studies that have applied the UTAUT model to identify the important factors influencing the use of telemedicine have also established similar results (27)(28)(29). The findings suggested that the individuals' foremost focus when using telerehabilitation remains on whether telerehabilitation can meet their actual rehabilitation needs.…”

Section: Discussionsupporting

confidence: 60%

Understanding the use intention and influencing factors of telerehabilitation in people with rehabilitation needs: a cross-sectional survey

Wang,

Chen,

Gong

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

ObjectiveThis study aimed to investigate the use intention and influencing factors of telerehabilitation in people with rehabilitation needs.MethodsThis cross-sectional survey recruited a total of 183 participants with rehabilitation needs from May 2022 to December 2022. Sociodemographic and medical data were collected by a structured questionnaire. The factors influencing the use intention of telerehabilitation were measured by the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. Multiple hierarchical regression analyses were performed.ResultsA total of 150 valid questionnaires were included for analysis. The results indicated that the use intention of telerehabilitation was overall high in people with rehabilitation needs. Health condition (β = −0.21, p = 0.03), performance expectancy (β = 0.21, p = 0.01), facilitating conditions (β = 0.25, p = 0.03), perceived trust (β = 0.25, p < 0.01), and self-efficacy (β = 0.19, p = 0.04) were significant factors influencing the use intention of telerehabilitation.ConclusionOverall, the use intention of telerehabilitation is high in individuals with rehabilitation needs. Health conditions, performance expectancy, facilitating conditions, perceived trust, and self-efficacy are important factors influencing the use intention of telerehabilitation in individuals with rehabilitation needs.

show abstract

Section: Discussionsupporting

confidence: 60%

Understanding the use intention and influencing factors of telerehabilitation in people with rehabilitation needs: a cross-sectional survey

Wang,

Chen,

Gong

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…FC are referred as a predictor of UB of technologies for caregivers. 61,68,85,87 Similarly, Adjei et al 88 found FC and BI positively and significantly related to UB in a study exploring a mobile technology intended to support caregivers.…”

Section: Discussionmentioning

confidence: 92%

“…These results are similar to previous studies, where high BI and FC are the only predictors of UB. 90 We observed that participants of this evaluation wanted to be updated on the care recipients' health and recreational engagement and involved in care coordination and communication with LTC staff. Similarly, during the qualitative phase, participants highlighted that having technologies such as the mSCS could engage more family members in care activities.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Technology Acceptance of a Mobile Application to Support Family Caregivers in a Long-Term Care Facility

et al. 2022

View full text Add to dashboard Cite

Background: Family caregivers are unpaid individuals who provide care to people with chronic conditions or disabilities. Family caregivers generally do not have formal care-related training. However, they are an essential source of care. Mobile technologies can benefit family caregivers by strengthening communication with care staff and supporting the monitoring of care recipients. Objective: We conducted a mixed-method study to evaluate the acceptance and usability of mobile technology called the Smart Care System. Methods: Using convenience sampling, we recruited 27 family caregivers to evaluate the mobile Smart Care System. In the quantitative phase, we administered initial and exit questionnaires based on the Unified Theory of Acceptance and Use of Technology model. In the qualitative phase, we conducted focus groups to explore family caregivers’ perspectives and opinions on the usability of the mobile Smart Care System. With the quantitative data, we employed univariate, bivariate, and partial least squares analyses, and we used content analysis with the qualitative data. Results: We observed a high level of comfort using digital technologies among participants. On average, participants were caregivers for an average of 6.08 years (SD = 6.63), and their mean age was 56.65 years (SD = 11.62). We observed a high level of technology acceptance among family caregivers (7.69, SD = 2.11). Behavioral intention (β = 0.509, p-value = 0.004) and facilitating conditions (β = 0.310, p-value = 0.049) were statistically significant and related to usage behavior. In terms of qualitative results, participants reported that the mobile application supported care coordination and communication with staff and provided peace of mind to family caregivers. Conclusion: The technology showed a high technology acceptance and intention to use among family caregivers in a long-term care setting. Facilitating conditions influenced acceptance. Therefore, it would be important to identify and optimize these conditions to ensure technology uptake.

show abstract

“…A recent survey and qualitative literature on mobile phone–based health interventions in Africa illustrated the differential importance of the UTAUT constructs. A path analysis of UTAUT constructs examined attitudes toward a mobile interactive voice response system for monitoring childhood illness in Ghana and found that performance expectancy, effort expectancy, and social influence were positively associated with behavioral intention to use the technology [ 24 ]. Similarly, a real-world mixed methods acceptability study of an SMS text message–based adherence-monitoring intervention in Uganda concluded that performance expectancy was the key driver of the acceptability of the system [ 9 ].…”

Section: Discussionmentioning

confidence: 99%

Behavioral Predictors of Intention to Use a Text Messaging Reminder System Among People Living With HIV in Rural Uganda: Survey Study

Campbell¹,

Aturinda²,

Mwesigwa³

et al. 2023

JMIR Hum Factors

View full text Add to dashboard Cite

Background The expansion of cellular phones in sub-Saharan Africa spurred the development of SMS text message–based mobile health (mHealth) technology. Numerous SMS text message–based interventions have attempted to increase retention in care for people living with HIV in sub-Saharan Africa. Many of these interventions have failed to scale. Understanding theory-grounded factors leading to mHealth acceptability is needed to create scalable, contextually appropriate, and user-focused interventions to improve longitudinal HIV care for people living with HIV in sub-Saharan Africa. Objective In this study, we aimed to understand the relationship between constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), constructs identified in previous qualitative research, and behavioral intention to use a novel SMS text message–based mHealth intervention designed to improve care retention among people living with HIV initiating treatment in rural Uganda. Methods We conducted a survey of people living with HIV who were newly initiating HIV care in Mbarara, Uganda, and had agreed to use a novel SMS text message–based system that notified them of abnormal laboratory results and reminded them to return to the clinic. Survey items assessed behavioral intention to use the SMS text messaging system; constructs from UTAUT; and demographics, literacy, SMS text messaging experience, HIV status disclosure, and social support. We used factor analysis and logistic regression to estimate the relationships between UTAUT constructs and the behavioral intention to use the SMS text messaging system. Results A total of 249 participants completed the surveys, of whom 115 (46.2%) expressed high behavioral intention to use the SMS text messaging intervention. In a multivariable analysis, we found that performance expectancy (adjusted odds ratio [aOR] of the scaled factor score 5.69, 95% CI 2.64-12.25; P<.001), effort expectancy (aOR of the scaled factor score 4.87, 95% CI 1.75-13.51; P=.002), and social influence (measured as a 1-unit Likert score increase in the perception that clinical staff have been helpful in the use of the SMS text messaging program; aOR 3.03, 95% CI 1.21-7.54; P=.02) were significantly associated with high behavioral intention to use the SMS text messaging program. SMS text messaging experience (aOR/1-unit increase 1.48, 95% CI 1.11-1.96; P=.008) and age (aOR/1-year increase 1.07, 95% CI 1.03-1.13; P=.003) were also significantly associated with increased odds of high intention to use the system. Conclusions Performance expectancy, effort expectancy, and social influence, as well as age and SMS experience, were drivers of high behavioral intention to use an SMS text messaging reminder system among people living with HIV initiating treatment in rural Uganda. These findings highlight salient factors associated with SMS intervention acceptability in this population and indicate attributes that are likely to be key to the successful development and scaling of novel mHealth interventions.

show abstract

Determinants of a mobile phone-based Interactive Voice Response (mIVR) system for monitoring childhood illnesses in a rural district of Ghana: Empirical evidence from the UTAUT model

Cited by 9 publications

References 16 publications

Understanding the use intention and influencing factors of telerehabilitation in people with rehabilitation needs: a cross-sectional survey

Understanding the use intention and influencing factors of telerehabilitation in people with rehabilitation needs: a cross-sectional survey

Technology Acceptance of a Mobile Application to Support Family Caregivers in a Long-Term Care Facility

Behavioral Predictors of Intention to Use a Text Messaging Reminder System Among People Living With HIV in Rural Uganda: Survey Study

Contact Info

Product

Resources

About