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In late March 2020, South Africa implemented a 5-stage COVID-19 Risk Adjusted Strategy, which included a lockdown that required all residents to remain home to prevent the spread of COVID-19. Due to this lockdown, individuals have been forced to find and use alternatives for accomplishing tasks including shopping, socializing, working, and finding information, and many have turned to the internet and their mobile devices.
This study aimed to describe how South Africans consume and internalize information surrounding the COVID-19 outbreak in order to determine whether the COVID-19 lockdown and social isolation have influenced technology behavior, particularly in terms of health communication and information.
From June 24 to August 24, 2020, people in South Africa were invited to complete a survey through the Upinion mobile app, an online data collection resource. The survey collected information on demographics, and technology use during the lockdown, and COVID-19 knowledge.
There were 405 participants, of which 296 (73.06%) were female. A total of 320 (79.01%) participants had a tertiary school education, 242 (59.75%) were single, and 173 (42.72%) had full-time employment. The lockdown forced 363 (89.63%) participants to use more technology, especially for work (n=140, 24.05%) and social media/communication (n=133, 22.85%). Security or privacy issues (n=46, 38.98%) and unfamiliarity with technology (n=32, 27.12%) were identified as the most common issues faced by the 127 (31.36%) participants who were unsure about using technology prior to the lockdown. Almost all participants (n=392, 96.79%) stated that they would continue using technology after the lockdown. Multimedia (n=215, 53.09%), mobile phone content (n=99, 24.44%), and health organizations and professionals (n=91, 22.47%) were the main sources of COVID-19 information. Most participants (n=282, 69.63%) felt that they had enough information. Two-thirds (n=275, 67.90%) of participants stated that they had used their mobile phones for health information before the lockdown, with web searches (n=109, 26.91%), social media (n=58, 14.32%), and government and institutional websites (n=52; 12.84%) serving as their main sources of information. Overall, the mean COVID-19 knowledge score was 8.8 (out of 10), and 335 (82.72%) had adequate knowledge (scored ≥8). Males were less likely to identify the correct transmission routes, and single participants were less likely to identify the signs and symptoms of the coronavirus. Tertiary school graduates were 4 times more likely to correctly identify the routes and 2 times more likely to identify how to stop the spread of the virus. People aged 43-56 years were 4 times more likely to identify how the coronavirus can be prevented, and participants ≥57 years were 2.6 times more likely to obtain a knowledge score of 10 when compared to those under 29 years of age.
This study has shown that the COVID-19 lockdown has forced people to increase technology use, and people plan to continue using technology after the lockdown is lifted. Increased technology use was seen across a variety of fields; however, barriers including privacy, unfamiliarity, and data costs were identified. This population showed high COVID-19 knowledge, although the use of web searches and social media, instead of government and institutional websites, increases the potential for health misinformation to be spread.
On March 11, 2020, the World Health Organization declared the COVID-19 outbreak a pandemic [
During the lockdown, cases and preventative measures have been well documented and investigated, both globally and in South Africa [
In a sense, this is all forced use of technology since people have limited alternatives to meet their needs, and to engage with this captive audience, many governments and institutions have introduced mobile health (mHealth) interventions to disseminate information during the pandemic [
With all of this electronic communication resulting from COVID-19, researchers have taken the opportunity to investigate how it has influenced digital health, and a variety of studies have already been conducted. Some studies have harnessed big data to predict outbreak hotspots with algorithm-based web mining [
Despite high mobile penetration in low- and middle-income countries [
This South African cross-sectional study was conducted electronically, administered through the Upinion mobile app, an online data collection resource. Participants were included if they were an existing or new Upinion user with current access to surveys on the app, ≥18 years of age, and able to provide online consent. Individuals were excluded if they were not able to access the Upinion app, were younger than 18 years, or refused to participate.
From June 24 to August 24, 2020, existing and new Upinion users were invited to complete a survey through Upinion notifications and advertisements on social media platforms, respectively. Once an individual agreed to participate in the current study, they were able to provide informed consent through the app and then register for the survey group [
A mobile app was used to collect data as this was deemed the easiest way to gather responses, while obeying the lockdown restrictions and ensuring the safety of both participants and data collectors. This method of online distribution of a survey and accompanying electronic consent has been used with increasing frequency, particularly during the COVID-19 pandemic for studies with similar methodologies [
The Upinion messaging and data collection app was developed in 2014 by Upinion, a people-centric research technology company based in the Netherlands, and its use in Southern African Development Community countries is licensed to Opinion Solutions. The app was developed as a way to collect feedback from affected communities in any response effort in order to provide better and more efficient support. It serves as an outlet for those affected by crisis to share their unique problems, needs and solutions, so that nongovernmental organizations have a grass-roots understanding of the situation on the ground, allowing for tailored interventions. This has been used by nonprofit organizations like Oxfam to identify the needs of refugee communities [
The Upinion app.
This survey was adapted from the survey
Upinion has a built-in dashboard to monitor responses in real time; however, the final data set was exported to Excel (Microsoft Corp) for cleaning and coding, then exported to Stata V.15 (StataCorp) for analysis. Demographic information, technology use, and COVID-19 knowledge questions were all described as frequency and percentages. A mean knowledge score (with standard deviation) was also calculated across all 10 knowledge questions, with a score below 6 considered inadequate knowledge, 6-8 considered moderately adequate knowledge, and a score above 8 considered adequate knowledge [
The Pearson chi-square test was used to assess trends of association between outcome variables (COVID-19 knowledge and technology use) and demographic characteristics. Logistic regression models (bivariate [not included in this paper] and multivariable models) were constructed for the outcome variables to control for confounders and identify independent predictors. These predictors were reported as crude (not included in this paper) and adjusted odds ratios (aOR), with 95% CI and
Ethics approval was obtained from the University of the Witwatersrand Human Research Ethics Committee (nonmedical) (reference number 200512). Survey respondents did not receive any compensation for participation.
Participants’ demographic data are presented in
Demographic characteristics.
Characteristic | Participants (N=405), n (%)a | |
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18-28 | 84 (20.74) |
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29-42 | 165 (40.74) |
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43-56 | 110 (27.16) |
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≥57 | 46 (11.36) |
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Female | 296 (73.09) |
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Male | 109 (26.91) |
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Primary school or less | 1 (0.25) |
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Secondary school | 84 (20.74) |
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Tertiary school (any) | 320 (79.01) |
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Married | 163 (40.25) |
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Single | 242 (59.75) |
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Casually employed | 74 (18.27) |
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Full-time employment | 173 (42.72) |
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Student | 29 (7.16) |
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Unemployed | 129 (31.85) |
aPercentages may not add up to 100.00% due to rounding.
A total of 363 (89.63%) participants stated that the lockdown had forced them to use more technology, and the greatest increases in use were for work (n=140, 24.05%), social media/communication (n=133, 22.85%), shopping (n=78, 13.4%), and news and information (n=70, 12.03%). Nearly one-third (n=127, 31.36%) of participants stated that they were unsure about using technology before the lockdown, with security and privacy issues (n=46, 38.98%) and unfamiliarity with technology (n=32, 27.12%) identified as the most common concerns. More than half (n=209, 51.60%) the participants had positive feelings about the increased forced technology use, while almost all (n=392, 96.79%) participants stated that they would continue using technology after the lockdown. When asked about information regarding COVID-19, 282 (69.63%) felt that they had enough information and knowledge, with multimedia (n=215, 53.09%), mobile phone content (n=99, 24.44%), and health organizations and professionals (n=91, 22.47%) as their main source of COVID-19 information. Two-thirds (n=275, 67.90%) of participants stated that they had used their mobile phones for health information before the COVID-19 outbreak, with web searches (n=109, 26.91%), social media posts (n=58,14.32%), government and institutional websites (n=52, 12.84%), and mobile apps (n=58, 14.32%) serving as their main sources of health information (
Technology use.
Technology questions | Participants (N=405), n (%)a | |||
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Yes | 363 (89.63) | ||
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No | 42 (10.37) | ||
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Job searching | 33 (5.67) | |
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Social media/communication | 133 (22.85) | |
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Education | 58 (9.97) | |
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Shopping | 78 (13.40) | |
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Entertainment | 48 (8.25) | |
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Work | 140 (24.05) | |
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News and information | 70 (12.03) | |
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Banking | 16 (2.75) | |
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Religion | 6 (1.03) | |
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Yes | 127 (31.36) | ||
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No | 278 (68.64) | ||
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Security/privacy issues | 46 (38.98) | |
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Unfamiliar with technology | 32 (27.12) | |
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Lack of personal connection/accountability | 16 (13.56) | |
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Cost of data and devices | 10 (8.47) | |
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Reliability issues | 14 (11.86) | |
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Positive feelings | 209 (51.60) | ||
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Neutral/mixed feelings | 129 (31.85) | ||
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Negative feelings | 67 (16.54) | ||
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Yes | 392 (96.79) | ||
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No | 13 (3.21) | ||
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Yes | 282 (69.63) | ||
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No | 123 (30.37) | ||
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Health organizations and professionals | 91 (22.47) | ||
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Mobile phone content | 99 (24.44) | ||
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Multimedia (radio, television, newspaper) | 215 (53.09) | ||
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Yes | 275 (67.90) | ||
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No | 130 (32.10) | ||
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1 (0.25) | ||
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Government/institutional websites | 52 (12.84) | |
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Messaging platforms (WhatsApp, SMS) | 17 (4.20) | |
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Mobile apps | 38 (9.38) | |
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Social media posts | 58 (14.32) | |
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Web searches (Google) | 109 (26.91) |
aPercentages may not add up to 100.00% due to rounding.
Logistic regression analysis identified relationships between demographics and 4 technology use variables (
Regarding the main source of COVID-19 information, multimedia, health organizations and professionals, and mobile phone content all had demographic associations. Tertiary school graduates were less likely to use multimedia as their main source of COVID-19 information compared to those with primary or secondary school education (aOR 0.536; 95% CI 0.319-0.900,
The associations seen among participants who responded that they had enough information or knowledge about COVID-19 included age, being male, being single, and having a tertiary education.
The 57-70–year-old group were approximately 6 times (aOR 5.661; 95% CI 1.894-16.925,
The oldest age group and students were the least likely to use their phone for health information prior to the pandemic (older adults: aOR 0.184; 95% CI 0.075-0.449,
When asked about COVID-19, 358 (88.40%) participants correctly identified it as a contagious respiratory virus, and 392 (96.79%) correctly stated that it was transmitted through respiratory droplets. Over three-quarters (n=319, 78.77%) of participants correctly chose all the ways that the virus could be spread; the rest thought it was only spread by coughing or sneezing (n=52, 18.84%), by touching objects that have COVID-19 droplets on them (n=17, 4.2%), or through close contact with an infected individual (n=16, 3.95%). All of the common COVID-19 symptoms (cough, sore throat, fever, and shortness of breath) were correctly identified by 379 (93.58%) participants; the same percentage correctly identified all encouraged prevention techniques (avoid touching one’s face, avoid contact with sick people, and wash hands thoroughly). When asked about handwashing duration, 20 seconds was correctly selected by the majority (n=340, 83.95%). For the question on how to stop the spread of COVID-19, 368 (90.86%) correctly chose social distancing, self-isolation, and regular handwashing as their response, and when asked how to stop the chance of spreading the virus, 383 (94.57%) correctly chose coughing and sneezing into their elbow, social distancing and self-isolation, and regular handwashing as their response. Most participants (n=308, 76.05%) correctly stated that they would call the emergency hotline or WhatsApp support line if they thought they had COVID-19 symptoms, although 79 (19.51%) incorrectly stated that they would rush to the nearest hospital for testing. Lastly, practicing social distancing, self-isolation, and washing one’s hands thoroughly were all correctly identified by 369 (91.11%) participants as the key to prevent the spread of COVID-19 (
Structured COVID-19 questionnaire.
COVID-19 questions | Participants (N=405), n (%)a | ||
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It is a bioweapon | 11 (2.72) | |
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It is a sexually transmitted infection | 4 (0.99) | |
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It is a very contagious respiratory virus | 358 (88.40) | |
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It is just another term for the common cold | 22 (5.43) | |
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It is transmitted through respiratory droplets | 10 (2.47) | |
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It is transmitted by eating Chinese food | 4 (0.99) | |
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It is transmitted through direct blood contact | 6 (1.48) | |
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It is transmitted through respiratory droplets | 392 (96.79) | |
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It is transmitted through sexual intercourse | 3 (0.74) | |
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By touching objects that have COVID-19 respiratory droplets | 17 (4.20) | |
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Through close contact with an infected individual | 16 (3.95) | |
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Through coughing or sneezing | 52 (12.84) | |
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All of the above | 319 (78.77) | |
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(Blank) | 1 (0.25) | |
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Cough and sore throat | 11 (2.72) | |
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Fever | 15 (3.70) | |
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Shortness of breath | 12 (2.96) | |
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All of the above |
367 (90.62) | |
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Avoid touching your face | 8 (1.98) | |
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Avoiding contact with sick people | 7 (1.73) | |
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Wash your hands thoroughly | 11 (2.72) | |
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All of the above | 379 (93.58) | |
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5 seconds | 5 (1.23) | |
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10 seconds | 17 (4.20) | |
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20 seconds | 340 (83.95) | |
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1 minute | 43 (10.62) | |
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Practice social distancing | 17 (4.20) | |
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Practice social distancing and wash your hands thoroughly | 1 (0.25) | |
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Self-isolate | 16 (3.95) | |
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Self-isolate and practice social distancing | 1 (0.25) | |
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Wash your hands thoroughly | 2 (0.49) | |
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All of the above | 368 (90.86) | |
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Cough or sneeze into a tissue or your elbow | 4 (0.99) | |
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Self-isolate and practice social distancing | 13 (3.21) | |
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Wash your hands thoroughly | 5 (1.23) | |
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All of the above | 383 (94.57) | |
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Call the emergency hotline or WhatsApp support line | 308 (76.05) | |
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Go to the pharmacy to get medication | 9 (2.22) | |
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Rush to the nearest hospital for testing | 79 (19.51) | |
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Stay in close physical contact with friends/family for support | 8 (1.98) | |
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(Blank) | 1 (0.25) | |
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Practice social distancing | 10 (2.47) | |
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Self-isolate | 18 (4.44) | |
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Wash your hands thoroughly | 7 (1.73) | |
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All of the above | 369 (91.11) | |
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Inadequate (score ≤5) | 19 (4.69) | |
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Moderately adequate (score=6,7) | 51 (12.59) | |
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Adequate (score ≥8) | 335 (82.72) |
aPercentages may not add up to 100.00% due to rounding.
Overall, the mean knowledge score was 8.8 (SD 1.53). There were only 19 (4.69%) participants with inadequate knowledge, 51 (12.59%) with moderately adequate knowledge, and 335 (82.72%) with adequate knowledge (
Logistic regression analysis identified relationships between demographics and 4 COVID-19 knowledge variables. Males were less likely to identify the correct transmission routes of COVID-19 (aOR 0.216; 95% CI 0.063-0.744,
Lastly, association analyses conducted separately between demographics and the outcome variables (COVID-19 knowledge scores and technology use) only identified a significant relationship in participants ≥57 years being 2.6 times more likely to obtain a knowledge score of 10 (aOR 2.60; 95% CI 1.1-6.0,
This study is the first to describe how South Africans interact with technology and consume health information during the current COVID-19 outbreak. Our findings were in line with a similar study from India [
The rise in South African technology use has also been validated by the nation’s data usage, which increased by more than one-third over the first few days of the lockdown [
Government or institutional websites [
Misinformation may have disproportionately affected participants under the age of 29 years, especially when compared to those above 57 years. The older group was less likely to use their mobile as the main source of health information, yet they were 6 times more likely to have enough COVID-19 information, and 2.6 times more likely to obtain a knowledge score of 10. In South Africa, youth under 30 years are almost 20% more likely to use their phone to access the internet than their parents, which would expose the younger age group to more online misinformation than the oldest age group [
This study has also reiterated some known barriers to mobile use in South Africa, such as security and privacy issues, unfamiliarity with technology, and data costs. Due to an increase in data usage, some local networks have temporarily lowered data costs [
A selection bias may be present due to the device and data requirements needed to access this survey, which was conducted online via a convenience sample. As this survey was adapted from a pre-existing survey, it was not validated or pilot tested in South Africa before this study. Furthermore, participants were asked to self-report their technology use, and no measurements were taken to validate these statements.
This study has shown that the COVID-19 lockdown has forced many people to increase technology use, and almost all participants will continue to use technology post lockdown. Increased technology use was seen across a variety of fields; however, well-known barriers were cited, including privacy and security concerns, unfamiliarity with technology, and data costs. This population showed high COVID-19 knowledge, but the use of web searches and social media posts, instead of government and institutional websites, provides the potential for health misinformation about COVID-19 to be spread. This was particularly evident in some subdemographic groups, including participants under 29 years, single participants, participants without tertiary education, and males. These groups should be targeted with further education and preventative measures.
Technology use during the COVID-19 lockdown survey.
Logistic regressions of technology use.
Logistic regressions of COVID-19 knowledge.
adjusted odds ratio
International Electrotechnical Commission
International Organization for Standardization
mobile health
The authors would like to thank all of the survey participants.
None declared.