| Literature DB >> 32723724 |
Abdulrahman Alghamdi1,2, Khalid Abumelha1,2, Jawad Allarakia1,2, Ahmed Al-Shehri1,2,3.
Abstract
BACKGROUND: Although chemotherapy was first introduced for the treatment of cancer more than 60 years ago, the public understanding and acceptance of chemotherapy is still debatable. To the best of our knowledge, no study has assessed the conversations and misconceptions about chemotherapy as a treatment for cancer on social media platforms among the Arabic-speaking populations.Entities:
Keywords: Arab world; Twitter; cancer; chemotherapy; infodemiology; infoveillance; internet; misconceptions; social media
Year: 2020 PMID: 32723724 PMCID: PMC7424479 DOI: 10.2196/13979
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Descriptions of the different themes of the tweets on chemotherapy and the illustrative tweets.
| Theme of the tweet | Description | Examples of the translated tweets |
| Advice and information | Disseminating true information and advice about chemotherapy | … |
| Experience | Sharing an experience of chemotherapy either by the patients themselves or by the people who surround them | … |
| Misconception | Sharing a false concept or a false idea about chemotherapy | … |
| Prayers and wishes | Saying a prayer or a wish for recovery for people receiving chemotherapy | … |
| Seeking medical information/advice | Asking for medical information about chemotherapy | … |
| Seeking medical/financial help | Asking for medical or financial help for patients receiving chemotherapy | … |
| Offering medical intervention/financial help | Offering medical or financial help for patients needing or receiving chemotherapy. | … |
| Analogy | Using chemotherapy in an analogic way to share an idea or a concept. | … |
| Miscellaneous | Tweets that did not fit any of the other categories. | … |
Description of the categories of the different Twitter users who tweeted on chemotherapy.
| Category of the Twitter user accounts | Description of the Twitter user accounts |
| Patients with cancer/survivors | Accounts of patients with cancer receiving chemotherapy |
| Relatives/friends of patients with cancer | Accounts of a relative or a friend of a patient receiving chemotherapy |
| Cancer specialists | Accounts of people working in the oncology field |
| Health-related accounts | Accounts of an organization in the medical field or of a person working in a medical field other than oncology |
| Media-related accounts | Accounts of media platforms such as newspapers and news channels |
| General users | Accounts of anyone who does not belong to the other categories or who belongs to unidentified accounts. |
Figure 1Overview of the process of collecting and filtering the data.
Frequency analysis of the themes of the tweets on chemotherapy and the Twitter user categories (N=29,904).
| Variable | n (%) | ||
|
| |||
|
| Miscellaneous | 932 (3.1) | |
|
| Advice and information | 1888 (6.3) | |
|
| Experience | 1847 (6.2) | |
|
| Misconception | 2084 (7.0) | |
|
| Prayers and wishes | 20,288 (67.8) | |
|
| Seeking medical information/advice | 487 (1.6) | |
|
| Seeking medical/financial help | 754 (2.5) | |
|
| Offering medical/financial help | 66 (0.2) | |
|
| Analogy | 1556 (5.2) | |
|
| |||
|
| General users | 25,774 (86.2) | |
|
| Patients with cancer/survivors | 854 (2.9) | |
|
| Relatives/friends of patients with cancer | 1913 (6.4) | |
|
| Cancer specialists | 222 (0.7) | |
|
| Health-related accounts | 459 (1.5) | |
|
| Media-related accounts | 680 (2.3) | |
Frequency of the main misconceptions about chemotherapy in the Arabic tweets (n=2084).
| Misconceptions | n (%) |
| Falsified and unrealistic side effects about chemotherapy; the main shared tweet was that “a drop of chemotherapy spilled on a healthy man’s skin would severely burn the skin.” | 1271 (60.9) |
| Chemotherapy causes cancer to spread. | 282 (13.5) |
| Chemotherapy has no therapeutic effect on cancers. | 214 (10.3) |
| Claims that there are natural products/preparations (eg, olive oil, | 170 (8.2) |
| Chemotherapy is prescribed so that pharmaceutical companies and physicians can make huge profits. | 67 (3.2) |
| Claims about some pharmaceutical products (eg, vitamin B17, antibiotics, vitamin C) being more effective than chemotherapy for treating cancers | 47 (2.3) |
| Claims that there are few religious practices (eg, Roqya, Zamzam water intake, seclusion in mosque, fasting from dawn to sunset), which are more effective than chemotherapy for treating cancers | 33 (1.6) |
Comparison of the number of tweets containing misconceptions by any user category and the number of tweets by cancer specialists and health-related accounts during the study period.
| Time period (2017) | Tweets containing misconceptions (n) | Tweets by cancer specialists and health-related accounts (n) |
| May 1-16 | 1616 | 35 |
| May 17-31 | 1992 | 33 |
| June 1-16a | 4365 | 108 |
| June 17-30 | 2561 | 41 |
| July 1-16a | 3441 | 104 |
| July 17-31 | 2854 | 84 |
| August 1-16 | 2486 | 21 |
| August 17-31 | 2758 | 59 |
| September 1-16 | 2026 | 49 |
| September 17-30 | 2670 | 51 |
| October 1-16 | 1372 | 52 |
| October 17-31 | 1761 | 44 |
aNoticeable spikes in the number of tweets containing misconceptions and tweets by cancer specialists and health-related accounts.
Distribution of the themes by the source category.
| Total number of tweets in each user category (n) | Theme-wise tweets | ||||||||
| Miscellaneous, n (%) | Advice and information | Experience | Misconception | Prayers and wishes | Seeking medical advice | Seeking medical/financial help | Offering medical/financial help | Analogy | |
| General users, n=25,774 | 760 (2.9)a | 1120 (4.3)a | 613 (2.4)a | 1864 (7.2)a | 19,294 (74.9)a | 260 (1.0)a | 291 (1.1)a | 35 (0.1)a | 1537 (5.9)a |
| Patients with cancer/survivors, n=854 | 26 (3.0) | 24 (2.8)a | 464 (54.3)a | 7 (0.8)a | 64 (7.5)a | 3 (8.5)a | 183 (21.4)a | 9 (1.1)a | 4 (0.5)a |
| Relatives/friends of patients with cancer, n=1913 | 34 (1.8)a | 42 (2.2)a | 615 (32.1)a | 16 (0.8)a | 821 (42.9)a | 137 (7.2)a | 245 (12.8)a | 0 (0) | 3 (0.2)a |
| Cancer specialists, n=222 | 4 (1.8) | 206 (92.8)a | 5 (2.2) | 0 (0) | 0 (0) | 4 (1.8) | 2 (0.9) | 1 (0.4) | 0 (0) |
| Health-related accounts, n=459 | 46 (10.0)a | 215 (46.8)a | 46 (10.0)a | 21 (4.6) | 85 (18.5)a | 13 (2.8) | 20 (4.4) | 7 (1.5)a | 6 (1.3)a |
| Media-related accounts, n=680 | 62 (9.1)a | 281 (41.3)a | 104 (15.3)a | 176 (25.9)a | 24 (3.5)a | 0 (0) | 13 (1.9) | 14 (2.1)a | 6 (0.9)a |
aStatistically significant at Bonferroni-adjusted P<.001.