Open access peer-reviewed chapter

Sporotrichosis: Quality of YouTube Contents on a Fungal Neglected Tropical Disease

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Ivaan Pitua, Raafidha Raizudheen, Amelia Margaret Namiiro, Lorraine Apili and Felix Bongomin

Submitted: 26 January 2025 Reviewed: 27 May 2025 Published: 12 September 2025

DOI: 10.5772/intechopen.1011320

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Abstract

Sporotrichosis is a chronic fungal infection caused by Sporothrix species, commonly associated with plant handling and zoonotic transmission via infected animals, particularly cats. With YouTube’s growing role as an educational resource, concerns arise regarding the reliability of medical information presented on the platform, particularly for neglected conditions like sporotrichosis. We assessed the quality and reliability of YouTube videos on sporotrichosis evaluated by four independent reviewers using the Global Quality Scale (GQS) and a modified DISCERN tool. The Video Power Index (VPI) was calculated to measure video popularity, and statistical analyses were conducted to explore correlations between video metrics and quality scores. The analysis included 39 videos, with a median GQS of 4.0, indicating high quality, while the median mDISCERN score was 2.83, suggesting moderate reliability. Approximately 37.5% of videos were of low to medium quality, while 60.0% were of high quality; healthcare professionals uploaded 70.0% of the sample videos. There was no significant correlation between video popularity (VPI) and quality scores (GQS or mDISCERN), indicating that popular videos may not provide the most reliable information. While many YouTube videos on sporotrichosis are of high quality, there is a concerning disconnect between video popularity and reliability, highlighting the need for viewers to critically evaluate health information on this platform and for content creators to prioritize accuracy alongside engagement. Sixty percent of YouTube videos on sporotrichosis are of high quality. Seventy percent of high-quality videos were uploaded by healthcare professionals. No correlation was found between video popularity and quality scores. Popular sporotrichosis videos may not be the most reliable.

Keywords

  • sporotrichosis
  • neglected fungal disease
  • youtube
  • quality
  • reliability

1. Introduction

Sporotrichosis is a chronic fungal infection caused by the dimorphic fungus Sporothrix schenckii and its related species. Often referred to as “rose gardener’s disease,” it is commonly associated with handling plants and organic material, which serve as primary sources of infection [1, 2]. Sporotrichosis is traditionally associated with the traumatic implantation of Sporothrix species from environmental sources such as soil or vegetation. However, in recent years, its zoonotic transmission, particularly through domestic cats, has emerged as a significant public health concern. In South America, zoonotic outbreaks caused by Sporothrix brasiliensis have resulted in severe and widespread human infections linked to direct contact with infected felines. It is thus important to recognize sporotrichosis not only as an environmental disease but also as a zoonotic threat, with implications for both human and veterinary health education [1, 3, 4, 5, 6]. The disease primarily affects the skin, subcutaneous tissues, and lymphatic system; however, in severe cases, it can disseminate to other parts of the body, including bones, joints, and the central nervous system [6, 7]. Although sporotrichosis has a global distribution, it is particularly prevalent in tropical and subtropical regions where environmental conditions favor the growth and transmission of Sporothrix species [8, 9].

The expansive range of topics and widespread accessibility of YouTube make it a valuable resource for patients seeking information about specific ailments and medical conditions, including sporotrichosis. However, the accuracy and reliability of the information presented in these videos can be a significant concern. Unlike peer-reviewed scientific literature, YouTube videos are not subjected to rigorous editorial processes, and the information presented may be influenced by the creator’s expertise, biases, or commercial interests [10, 11]. This variability raises concerns about the potential for misinformation and its impact on public health.

Assessing the quality and reliability of YouTube content is crucial, particularly for medical conditions like Sporotrichosis, where timely and accurate information is vital for disease management and prevention. Our study aims to address this need by analyzing the popularity, quality, and reliability of YouTube videos related to Sporotrichosis. Through this analysis, the study seeks to provide insights into the current state of online health information on the disease and to identify areas for improvement in the dissemination of accurate and reliable content on digital platforms such as YouTube.

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2. Materials and methods

2.1 Search strategy

We retrieved YouTube videos using Sporotrichosis as a search term on August 20, 2024, using a YouTube Data API and an R script, which obtained 200 video URLs. The search results were automatically ranked by YouTube’s default “relevance” setting and also included data on view count, like count, comment count, upload date, and video duration. Figure 1 shows the screening criteria.

Figure 1.

Data collection and screening.

2.2 Video assessment

All information was saved in a spreadsheet, and four independent reviewers Ivaan Pitua (IP), Raafidha Raizudheen (RR), Amelia Margaret Namiiro (AMN), and Lorraine Apili (LA) independently assessed the videos’ quality of information and reliability (Appendix A). Reliability was assessed using a 5-point modified DISCERN tool, adapted by Uzun [12]. The quality of the videos was evaluated using the 5-point Global Quality Scale (GQS), developed by Bernard et al. [13] to assess the quality of information presented on websites. Scores of 1–2 points were considered low quality, 3 points indicated moderate quality, and 4–5 points were considered high quality. Disagreements among raters were noted and resolved by an independent opinion from Felix Bongomin (FB). The Video Power Index (VPI) was calculated for each video using the formula: like ratio × view ratio ÷ 100. It has been utilized in prior studies to measure video popularity based on views and likes.

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3. Statistical analysis

Normal distribution was tested using the Shapiro-Wilk test, which indicated there was no normal distribution, as all p < 0.05. Variables were summarized as sums, medians, and interquartile ranges. The inter-rater agreement among the four reviewers for the GQS and mDISCERN scores was assessed using the Interclass Correlation Coefficient (ICC). ICC values <0.5 were categorized as indicating poor reliability; values between 0.5 and 0.75 as moderate reliability; values between 0.75 and 0.9 as good reliability; and values >0.90 as excellent reliability. Spearman’s rho was also used to evaluate the association between video scores and video metrics. The Mann-Whitney U test was conducted to compare continuous variables between the “Low to Medium Quality” and “High Quality” groups. Statistical significance was set at P ≤ 0.05. All statistical analyses were conducted using R version 4.3.2 [14].

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4. Results

Figure 1 shows the data screening of selected videos.

4.1 Descriptive statistics

We included 39 videos in the analysis. The median number of views was 1709.50 (IQR = 6256.75). The median number of likes was 29.50 (IQR = 81.5), while the median number of comments was 3.50 (IQR = 6.00). The median number of days since upload was 1055 (IQR = 1798.25). The median duration of the videos was 7 minutes (IQR = 9.5). The median GQS was 4.0 (IQR = 1.0), and the median mDISCERN score was 2.825 (IQR = 0.5). The VPI had a median value of 1.70 (IQR = 5.02).

About 37.5% (n = 15) of the videos were low to medium quality, while 60.0% (n = 24) were high quality. 70.0% (n = 28) of the videos were uploaded by health professionals, 10.0% (n = 4) by media and organizations, and 17.5% (n = 7) by others. In 70.0% (n = 28) of the videos, treatment options were mentioned. The discussion of treatment options across the videos shows that Itraconazole was mentioned in 24 videos, Potassium iodide in 17 videos, Amphotericin B in 14 videos, and both Terbinafine and surgery were discussed in four videos each.

4.2 Correlations between video matrices and VPI, GQS, and mDISCERN

The ICC of GQS and mDISCERN among the four raters was 0.821 (p < 0.001, 95% CI 0.707–0.897) and 0.786 (p < 0.001, 95% CI 0.650–0.878), respectively. There was a strong positive correlation between VPI and the number of views (r = 0.877, p < 0.001), the number of likes (r = 0.923, p < 0.001), and the number of comments (r = 0.808, p < 0.001). Additionally, the duration in minutes is positively correlated with both GQS (r = 0.522, p = 0.001) and mDISCERN (r = 0.548, p < 0.001) (Table 1).

Video matricesVideo power IndexGlobal quality ScoremDISCERN
Viewsr0.8770.1380.095
p<0.0010.4010.566
Likesr0.9230.0630.051
p0.0010.7040.757
Commentsr0.8080.0460.061
p<0.0010.7850.716
Days since uploadr0.0970.0700.044
p0.5590.6710.792
Duration in minutesr−0.0490.5220.548
p0.768<0.001<0.001

Table 1.

Correlations between video matrices and popularity, quality and reliability tools used.

4.3 Correlations between VPI, GQS, and mDISCERN

The correlations among the variables indicate that the GQS and mDISCERN scores have a strong positive correlation (r = 0.799, p < 0.001). However, the VPI shows no significant correlation with either GQS (r = 0.095, p = 0.566) or mDISCERN (r = 0.082, p = 0.620).

4.4 Association between video quality and continuous variables

There was a significant association between video quality and the GQS (p < 0.001), mDISCERN score (p < 0.001), and video duration (p = 0.001) (Table 2).

Video quality, median (IQR)
VariablesLow to medium quality N = 15High quality N = 24p-value
Global Quality Score3.00 (.00)4.00 (.00)< 0.001
mDISCERN2.45 (0.5)3.00 (0.45)< 0.001
Video Power Index2.42 (4.17)1.14 (4.99)0.919
Views2029.50 (4910.00)1419.00 (6708.25)0.665
Likes32.00 (60.75)19.00 (120.00)0.896
Comments4.00 (5.75)3.50 (10.00)0.843
Duration of video (mins)3.00 (4.75)10.00 (8.75)< 0.001
Days since upload778.00 (2847.00)1119.00 (1752.75)0.603

Table 2.

Variables associated with video quality.

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5. Discussion

This study aims to evaluate the quality and reliability of YouTube videos related to sporotrichosis, a subcutaneous fungal neglected tropical disease of global public health significance [15]. YouTube is one of the most visited websites worldwide and has become a popular platform for individuals seeking health-related information [16]. The accessibility of YouTube allows users to easily find videos on a wide range of medical topics [17], including rare conditions such as sporotrichosis. However, the open nature of YouTube, where anyone can upload content, leads to a mix of reliable information and potential misinformation. This lack of content regulation raises concerns, as YouTube does not require health-related videos to undergo expert review [11]. Consequently, the quality and accuracy of information can vary widely, which is particularly problematic given that about 85 million internet users take online health advice without assessing the quality of the content found on the internet [18]. The consequences of relying on such unvetted information can be severe, especially in cases where treatment decisions are influenced by misleading or incorrect content.

Our findings indicate that the majority of videos on sporotrichosis were not only of high quality, with a median GQS of 4.0, but also less reliable, with a modified DISCERN score of 2.825, suggesting that there is a considerable amount of quality information available on YouTube regarding sporotrichosis, though most of it is most likely less reliable. Despite these encouraging results, the study also revealed that video popularity, as measured by the VPI, was strongly correlated with the number of views, likes, and comments but not with GQS or mDISCERN scores. Popular videos are thus not necessarily those with the most accurate or reliable content. In fact, the pursuit of virality can lead to content that prioritizes engagement over accuracy. This disconnection between popularity and quality has been documented in other studies, where videos with sensationalist, compelling headings or oversimplified content attract more viewers than those that are more thorough or scientifically accurate [19]. The implication is that viewers may be misled by the popularity of a video, assuming it to be more trustworthy or informative than it actually is. There were no significant differences in GQS, mDISCERN, and video duration between high-quality and lower-quality videos. Specifically, higher-quality videos tended to be longer, with a median duration of 10 minutes compared to 3 minutes for lower-quality videos, suggesting that more detailed and comprehensive videos—which naturally take longer to produce and watch—are more likely to provide accurate and reliable information, a pattern consistent with the idea that quality health information requires time to present and explain thoroughly. However, the challenge is that longer videos may not attract as many viewers, especially in an era where attention spans are often limited [20, 21]. Of late, shorter videos on YouTube, popularly known as “Shorts,” have garnered more engagement than regular videos [22], though the amount of content released in Shorts is quite limited and may not sufficiently convey all health-related information as a regular full-length video would, creating a tension between the need for thoroughness and the demand for brevity, which content creators must navigate carefully. The implications of our findings are significant for both content creators and viewers. For content creators, there is a clear need to balance accuracy with engagement to ensure that reliable information reaches a broad audience. For viewers, the study emphasizes the importance of critically evaluating the source and content of the information they consume, especially when it concerns health-related topics.

This study had some limitations. While GQS and mDISCERN are validated tools for assessing video quality, they are subjective measures and may not capture all aspects of what constitutes high-quality content. The study did not account for other factors that may influence video quality and reliability, such as visual and audio production quality or the qualifications of the presenter. Another key limitation of this study is the inability to conduct a regional analysis due to the absence of geolocation data. As a result, potential variations in public perceptions or discourse across different geographic areas could not be explored, which limits the generalizability of the findings to specific regional contexts. Future research may address these limitations by incorporating additional metrics and considering other factors that contribute to content quality.

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6. Conclusions

There is a disconnection between video popularity and reliability despite the relatively high quality of videos on sporotrichosis. Viewers have to critically evaluate health information on YouTube, and content creators need to prioritize accuracy alongside engagement.

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Conflict of interest

None declared.

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Funding

None.

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Data availability

The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data on screening is available in Appendix A.

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Appendix

See Table A1.

Video codesViewsLikesDislikesCommentsLikesRatioViewsRatioVPIYeardaysAfterUploadDurationGQS_RGQS_AGQS_PGQS_LGQS
168364807100.0001.5081.508201245331343344
232755605100.0004.3384.33820227555154434
3610000.0510.00ac020201207322222
440402100.0000.1320.1322023303132233
52351700100.0003.0523.052202477123233
67823303100.0001.2801.2802021611233333
7491224441298.3878.8508.7082023555333333
821602803100.0003.0643.0642021705633433
95698594693.6511.3411.25620124249343333
1010,3215205100.0009.6199.61920201073233433
11105300100.0000.4100.4102023256243434
12741033011100.0001.7781.77820134167343434
13568400100.0000.1780.17820153186234444
141513700100.0000.3930.393201438521444434
15754802100.0000.2870.287201626241044444
164601212014100.00034.85634.8562024132844444
1713251802100.0000.7800.780201816991544544
1824,517558132697.72323.41622.883202010471054545
195282303100.0000.1260.126201341891532333
20380000.0620.0002021610742333
21410600100.0000.4520.45220219071053434
22320000.3720.000202486644444
235782002100.0002.5242.5242023229954434
241899312293.9391.7311.62620201097643333
25555904100.0000.7580.75820217323643434
2623,78833815795.75122.37821.427202010632043434
27350000.1350.00020232591053444
2867528622797.7273.2313.157201720901144444
29170000.0470.0002023362122333
3025,5681574997.5165.7175.57520124472434333
3175361423797.9319.6259.4252022783544444
32550000.1730.00020233181654444
3334559208100.0004.9864.9862022693133223
3415202308100.0001.7861.78620218511143333
3513,3582191095.6334.7374.53020162820533444
36174900100.0000.2510.25120216921643534
375701203100.0000.4120.41220191383644444
38807615391494.4446.0815.74320191328644534
39267800100.0000.2270.227202011751044544
Video codesGQS_CartegoryAIMS_RAIMS_AAIMS_PAIMS_LRELIABLESOURCES_RRELIABLESOURCES_ARELIABLESOURCES_PRELIABLESOURCES_LBALANCED_RBALANCED_ABALANCED_PBALANCED_LPT_REFERENCE_RPT_REFERENCE_A
1243344444433321
2254534444445221
3121232323222411
4121233333322211
5131234224331331
6142213334332211
7133234344322331
8133444444344321
9142224344333321
10132433243324311
11243434444334231
12243424344434241
13244443344333321
14243444334433321
15233443444334421
16244444444434435
17254544544445451
18254445554544441
19132333234334341
20142424234333312
21254445344433351
22244445444332311
23254444444444231
24144344334433321
25243434343333221
26242334334433321
27253445344435351
28244444544443431
29131324243332222
30133433333433411
31244444344433431
32251445444444351
33144114233422341
34142334344423321
35233434354334311
36252445344434441
37241444434443331
38243434344434321
39244544444444341
Video codesPT_REFERENCE_PPT_REFERENCE_LUNCERTAINITY_RUNCERTAINITY_AUNCERTAINITY_PUNCERTAINITY_LmDiscern_RmDiscern_AmDiscern_PmDISCERN_LmDiscernmDiscern_5TreatmentMentioned
11131211712131313.752.751
24141411914221116.53.31
3121111888139.251.850
411112110810109.51.91
511311116871210.752.150
6112131131011910.752.150
72121211510121212.252.451
81131311513161314.252.851
91131211610121112.252.451
101121411281711122.41
1111313117121611142.81
12512141181121101531
132332211513151514.52.91
141131211711131313.52.71
151132511413181414.752.951
1634324118181917183.61
174442512216231719.53.91
1844414123152117193.81
19113151169161213.252.651
201141311610141112.752.551
211141312312151315.753.151
2211313116131413142.80
231131411914171215.53.11
241131211712121313.52.71
251131411611161013.252.650
261131211710121212.752.550
275241512311231417.753.551
2811333118171514163.20
293131221591410122.40
301231411411151313.252.650
31213131181216141531
322252512412191417.253.451
3311311119108911.52.30
34213141179161213.52.71
351421411311181514.252.851
36112131201016141531
371331311811141514.52.91
383131411711191214.752.951
3944415120142216183.60

Table A1.

Data extraction form summarizing the assessment of included YouTube videos on Sporotrichosis.

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Written By

Ivaan Pitua, Raafidha Raizudheen, Amelia Margaret Namiiro, Lorraine Apili and Felix Bongomin

Submitted: 26 January 2025 Reviewed: 27 May 2025 Published: 12 September 2025