Back

TikTok: Empowering Hidradenitis Suppurativa Patients through Social Media Education - A Cross-Sectional Content Analysis

Decker, P.; Ezaldein, H.

2024-10-11 dermatology
10.1101/2024.10.10.24315240 medRxiv
Show abstract

Hidradenitis suppurativa (HS) is a chronic condition characterized by painful, inflamed lumps under the skin in intertriginous areas. While social media platforms like TikTok are increasingly raising public awareness about HS, the quality of the information presented remains challenging to assess. Our study aims to analyze the top one hundred TikTok videos focusing on HS clinical information, treatment options, and patient experiences from 2020 to 2024. We evaluate user engagement data, content characteristics, and assess the quality of health information using a validated DISCERN score. Overall, our study suggests that while TikTok serves as a valuable resource for raising awareness and accessing new information about HS, content from healthcare professionals and scientific research garners higher user engagement and contributes to greater awareness of HS.

Published in SKIN The Journal of Cutaneous Medicine · not in our set (fewer than 10 published preprints to learn from) · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
JMIR Formative Research
◐ 33 papers in training set
Top 0.1%
12.0%
Similar papers in this journal
2
Frontiers in Public Health
○ 148 papers in training set
Top 0.2%
9.8%
Similar papers in this journal
3
Frontiers in Medicine
○ 120 papers in training set
Top 0.1%
8.9%
Similar papers in this journal
4
JMIR Research Protocols
◐ 21 papers in training set
Top 0.1%
7.9%
Similar papers in this journal
5
PLOS ONE
● 5266 papers in training set
Top 23%
6.8%
Similar papers in this journal
6
PLOS Neglected Tropical Diseases
● 466 papers in training set
Top 2%
5.5%
50% of probability mass above
7
BMJ Open
● 601 papers in training set
Top 6%
4.1%
8
Heliyon
○ 152 papers in training set
Top 1%
3.4%
9
Frontiers in Nutrition
○ 24 papers in training set
Top 0.2%
3.1%
10
Diagnostics
○ 50 papers in training set
Top 0.6%
2.8%
11
Computers in Biology and Medicine
○ 128 papers in training set
Top 1%
2.8%
12
International Journal of Environmental Research and Public Health
○ 128 papers in training set
Top 2%
2.1%
13
Journal of Medical Internet Research
◐ 87 papers in training set
Top 1%
2.1%
14
Cureus
○ 68 papers in training set
Top 2%
2.1%
15
JAMA Network Open
● 130 papers in training set
Top 2%
2.1%
16
eClinicalMedicine
○ 77 papers in training set
Top 0.9%
1.7%
17
Scientific Reports
○ 3612 papers in training set
Top 51%
1.7%
18
PLOS Global Public Health
● 344 papers in training set
Top 6%
1.5%
19
PLOS Digital Health
● 106 papers in training set
Top 3%
1.5%
20
JMIR Public Health and Surveillance
◐ 45 papers in training set
Top 1%
1.1%
21
The Journal of Pediatrics
○ 16 papers in training set
Top 0.3%
1.1%
22
International Journal of Medical Informatics
○ 26 papers in training set
Top 1%
0.8%
23
BMC Cancer
○ 67 papers in training set
Top 2%
0.8%
24
DIGITAL HEALTH
○ 17 papers in training set
Top 0.7%
0.8%
25
Informatics in Medicine Unlocked
○ 22 papers in training set
Top 1%
0.8%
26
JMIRx Med
◐ 32 papers in training set
Top 3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.