| Literature DB >> 32442138 |
Vanja Kopilaš1, Srećko Gajović2.
Abstract
BACKGROUND: Online interactions within a closed WhatsApp group can influence the attitudes and behaviors of the users in relation to health issues.Entities:
Keywords: 5G mobile networks; infodemic; infodemiology; instant messaging; participatory web; rumor; virality
Mesh:
Year: 2020 PMID: 32442138 PMCID: PMC7445615 DOI: 10.2196/17051
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Characteristics of the 205 members of the WhatsApp group.
| Member characteristics | n (%) | |
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| Women | 106 (52) |
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| Men | 99 (48) |
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| Current student | 5 (2) |
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| University degree | 187 (91) |
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| PhD | 75 (37) |
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| Medical doctor | 125 (61) |
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| Medical doctor with specialization | 97 (47) |
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| Engineer | 12 (6) |
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| Electronic engineer | 8 (4) |
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| Retired | 4 (2) |
| PhD with an academic position at a university | 50 (24) | |
Figure 1Number and time distribution of the members entering the discussion, as indicated by their first message.
Timing and extent of the different features of WhatsApp group events by the 205 members.
| WhatsApp group events | 1 hour | 4 hours | 10 hours (up until the first night) | 26 hours | Total | |
| Members who posted their first message, n | 18 | 42 | 64 | 76 | 81 | |
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| All messages | 30 | 72 | 103 | 126 | 133 |
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| Administrator messages | 8 | 17 | 21 | 26 | 28 |
| Members who declared that they signed the petition, n | 0 | 16 | 37 | 46 | 47 | |
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| Total | 11 | 40 | 65 | 79 | 83 |
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| Left the group after signing the petition | 0 | 7 | 14 | 17 | 17 |
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| Total | 2 | 5 | 8 | 11 | 13 |
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| Positive responses | 2 | 5 | 8 | 11 | 13 |
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| Negative responses | 0 | 0 | 0 | 0 | 0 |
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| Total | 10 | 26 | 35 | 40 | 49 |
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| Positive feelings | 9 | 24 | 33 | 35 | 44 |
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| Negative feelings | 1 | 2 | 2 | 5 | 5 |
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| Total | 5 | 12 | 14 | 19 | 19 |
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| Rumors | 2 | 7 | 8 | 12 | 12 |
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| Not rumors | 3 | 5 | 6 | 7 | 7 |
Figure 2Number of members and the time distribution of their messages declaring they signed the petition.
Figure 3Number and time distribution of the messages from the members versus those from the administrator.
Figure 4Number and time distribution of messages from the members supporting the administrator and of positive (emotionally) emojis posted.
Figure 5Number and time distribution of messages elaborating the group topic (influence of technology on health) that contained a rumor versus equivalent messages that did not contain a rumor.
Figure 6Number and time distribution of members who left the group.