| Literature DB >> 34900326 |
Hasifah Kasujja Namatovu1, Tonny Justus Oyana2, Henk Gerard Sol3.
Abstract
Current empirical evidence suggests that successful adoption of eHealth systems improves maternal health outcomes, yet there are still existing gaps in adopting such systems in Uganda. Service delivery in maternal health is operating in a spectrum of inadequacy, hence eHealth adoption cannot ensue. This study set out to explore the challenges that impede eHealth adoption in women's routine antenatal care practices in Uganda. A qualitative approach using semi-structured interviews was employed to document challenges. These challenges were classified based on a unified theory of acceptance and use of technology constructs. One hundred and fifteen expectant mothers, aged between 18 and 49 years, who spoke either English or Luganda were included in the study that took place between January to May 2019. Thematic analysis using template analysis was adopted to analyse qualitative responses. Challenges were categorised based on five principal unified theories of acceptance and use of technology constructs namely: performance expectancy, effort expectancy, social influence, facilitating conditions and behavioural intention. Facilitating conditions had more influence on technology acceptance and adoption than the other four constructs. Specifically, the lack of training prior to using the system, technical support, computers and smart phones had a downhill effect on adoption. Subsequently, the cost of data services, internet intermittency, and the lack of systems that bridge the gap between mothers and health providers further hindered technology uptake. In conclusion, strategies such as co-development, training end-users, garnering support at the national and hospital levels should be advocated to improve user acceptance of technology.Entities:
Keywords: EHealth; adoption; antenatal care; barriers; expectant mothers; unified theory of acceptance and use of technology model
Year: 2021 PMID: 34900326 PMCID: PMC8664308 DOI: 10.1177/20552076211064406
Source DB: PubMed Journal: Digit Health ISSN: 2055-2076
Figure 1.The unified theories of acceptance and use of technology (UTAUT) model.
Interview questions following the five constructs of the UTAUT model.
| Construct | Item | Description |
|---|---|---|
| Performance expectancy | PE1 | Do you consider eHealth systems useful? |
| PE2 | In your opinion, can eHealth technologies improve pregnancy outcomes? | |
| PE3 | Can eHealth systems improve your relationship with health providers? | |
| Effort expectancy | EE1 | Are the eHealth systems easy to navigate? |
| EE2 | Do you find eHealth systems easy to use? | |
| EE3 | Are eHealth systems easy to learn? | |
| EE4 | In your opinion, are eHealth systems easy to understand? | |
| Social influence | SI1 | Do you have anyone within your social circle that supports you to use eHealth systems? |
| SI2 | Are your friends supportive of you to use eHealth systems? | |
| Facilitating conditions | FC1 | What do you find challenging about using eHealth systems for ANC care? |
| FC2 | Have you had prior training before using an eHealth system? | |
| FC3 | Do you get technical support in case of a system failure? | |
| FC4 | How easy is it to access doctors and eHealth services in general? | |
| FC5 | As a user, have you ever participated in the development of any eHealth systems? | |
| Behavioural intention | BI1 | Do you have any intentions of using eHealth systems either now or in the future? |
| BI2 | Would you willingly use the eHealth systems if you trusted them? | |
| BI3 | Would you use an eHealth system if it’s sustainability is guaranteed? |
Overall profile, statistics, and demographic characteristics by Kampala City’s underserved Parishes, Uganda.
| Variables | Total female | Percentage (%) of total population |
|---|---|---|
| Female population size in the six parishes | 75,931 | 52% |
| Females above 18 years with the highest grade completed 4 years of secondary schooling | 6914 | 9% |
| Females above 20 years with the highest grade completed 6 years of secondary schooling | 3627 | 5% |
| Females above 18 years who are illiterate | 3219 | 4% |
| Female working status | 28836.5 | 38% |
| Ever given birth (12–19 years) | 1924 | 3% |
| Female has a phone (18–30 years) | 20,449 | 27% |
| Internet use among females (18–30 years) | 10,870 | 14% |
| Distance to a public health facility ≥ (residing ≥ 5 km) | 2753 | 0.6% |
| Household that owns at least one computer | 6122 | 15% |
Demographics of the respondents.
| Number that participated and returned questionnaires | Number/percent of mothers | |||||
|---|---|---|---|---|---|---|
| Mengo Kisenyi | Kasubi Kawaala | Komamboga | Kitebi | Kiswa | Total | |
| Number of respondents | 15 (13%) | 24 (21%) | 33 (29%) | 28 (24%) | 15 (13%) | 115 (100%) |
| Education level | ||||||
| Primary | 8 (53%) | 9 (38%) | 13 (39%) | 12 (43%) | 8 (53%) | 50 (44%) |
| Secondary | 3 (20%) | 2 (8%) | 9 (27%) | 9 (32%) | 5 (33%) | 28 (24%) |
| University | 0 (0%) | 2 (8%) | 2 (6%) | 0 (0%) | 0 (0%) | 4 (4%) |
| 4 (27%) | 11 (46%) | 9 (27%) | 7 (25%) | 2 (13%) | 33 (29%) | |
| Age | ||||||
| 18–30 years | 9 (60%) | 10(42%) | 23(70%) | 17(61%) | 6(40%) | 65 (57%) |
| 31–40 years | 6 (40%) | 10(42%) | 6(18%) | 8(29%) | 6(40%) | 36 (31%) |
| 41–49 years | 0 (0%) | 4(17%) | 4(12%) | 3(11%) | 3(20%) | 14 (12%) |
| Parity | ||||||
| None | 2 (13%) | 5 (21%) | 5 (15%) | 7 (25%) | 5 (33%) | 24 (21%) |
| 1–3 | 7 (47%) | 14 (58%) | 21 (64%) | 12 (41%) | 8 (53%) | 62 (54%) |
| 4–5 | 5 (33%) | 5 (21%) | 7 (21%) | 9 (32%) | 0 (0%) | 26 (23%) |
| Above 5 | 1 (7%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (13%) | 3 (3%) |
| Marital status | ||||||
| Married | 5(33%) | 5 (21%) | 9 (27%) | 15 (54%) | 5(33%) | 39(33%) |
| Single | 7 (47%) | 6 (25%) | 11 (33%) | 6 (21%) | 3 (20%) | 33 (29%) |
| Co-habiting | 2 (13%) | 5 (21%) | 10 (30%) | 5 (18%) | 6 (40%) | 28 (24%) |
| Divorced | 0(0%) | 4 (17%) | 2 (6%) | 0 (0%) | 0 (0%) | 6 (5%) |
| Separated | 1 (7%) | 4 (17%) | 1 (3%) | 2 (7%) | 1 (7%) | 9 (8%) |
| Employment status | ||||||
| Employed | 5 (33%) | 5 (22%) | 12 (36%) | 10 (36%) | 7 (47%) | 39 (34%) |
| Unemployed | 10 (67%) | 18 (78%) | 21 (64%) | 18 (64%) | 8 (53%) | 75 (66%) |
| eHealth use in ANC | ||||||
| Yes | 0 (0%) | 6 (25%) | 5 (15%) | 2 (7%) | 0 (0%) | 13 (11%) |
| No | 15 (100%) | 18 (75%) | 28 (85%) | 26 (93%) | 15 (100%) | 102 (89%) |
| eHealth use in other health services | ||||||
| Yes | 2 (13%) | 5 (21%) | 9 (27%) | 4 (14%) | 1 (7%) | 21 (18%) |
| No | 13 (87%) | 19 (79%) | 24 (73%) | 24 (86%) | 14 (93%) | 94 (82%) |
| ICT devices used to access ANC services | ||||||
| Handheld devices | 0 (0%) | 5 (21%) | 5 (15%) | 0 (0%) | 0 (0%) | 10 (9%) |
| Computers | 0 (0%) | 1 (4%) | 0 (0%) | 2 (7%) | 0 (0%) | 3 (3%) |
| None | 15 (100%) | 18 (75%) | 28 (85%) | 26 (93%) | 15 (100%) | 102 (89%) |
Figure 2.Final version template.
Figure 3.Expectant mother's opinions on the challenges that bar eHealth adoption in routine antenatal care practices.