Quality Assessment of YouTube Videos on Complementary and Alternative Medicine (CAM) for Cancer Using a Newly Developed Tool Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1177/15347354241293417
Background: The global burden of cancer continues to rise and complementary and alternative medicine (CAM) is attracting a lot of interest. However, quality of online information on CAM, particularly on platforms like YouTube, remains questionable. This study aimed to create a comprehensive assessment tool to assess the quality of CAM-related YouTube videos, crucial for informed decision-making in oncology. Methods: The assessment tool was developed by adapting existing criteria for website content analysis to video rating. A YouTube search was conducted using German-language terms related to CAM (“complementary medicine (CM) for cancer” and “alternative medicine (AM) for cancer”). In total 25 videos were assessed based on the defined criteria and assigned to five different types of providers (journalism, healthcare organization, hospital or health insurance, independent person, non-medical organization). Statistical analysis was conducted using IBM SPSS Statistics 27. Results: Interrater reliability analysis showed an Intraclass Correlation Coefficient (ICC) of .91, indicating good to excellent agreement. The average video result was of poor quality, with none of the videos meeting all criteria. The videos achieved a mean rating of 38.2 points (SD: 6.5 points; possible range: 20-60 points). Journalism-based videos showed the most views per days, particularly surpassing those from hospitals or health insurance providers (Kruskal-Wallis-Test: z = 3.14, P = .02). However, there was no statistically significant correlation between video quality and the type of provider or interaction indices. Videos retrieved under the search term “CM” generally scored higher in quality than those under “AM” (Mann-Whitney U test: U = 39.5, P = .04). Nonetheless, "CM" videos were less frequently viewed (Mann-Whitney U test: U = 31.0, P = .01). Conclusion: This study, the first of its kind focusing on CAM in cancer care emphasized the challenges in identifying credible sources on social media platforms such as YouTube. The developed assessment tool offers a more detailed evaluation method for health-related videos but requires further refinement and testing. Collaboration between healthcare and media entities is suggested to improve the dissemination of reliable information on platforms like YouTube.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/15347354241293417
- OA Status
- gold
- Cited By
- 2
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403880638
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403880638Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1177/15347354241293417Digital Object Identifier
- Title
-
Quality Assessment of YouTube Videos on Complementary and Alternative Medicine (CAM) for Cancer Using a Newly Developed ToolWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-01Full publication date if available
- Authors
-
Sophia Huchel, Alina Grumt, Christian Keinki, Judith Buentzel, Lukas Käsmann, Jutta HuebnerList of authors in order
- Landing page
-
https://doi.org/10.1177/15347354241293417Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1177/15347354241293417Direct OA link when available
- Concepts
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Intraclass correlation, Quality (philosophy), Test (biology), Descriptive statistics, Inter-rater reliability, Video quality, Quality assurance, Medicine, Health care, Family medicine, Psychology, Rating scale, Statistics, Operations management, Economics, Epistemology, Paleontology, Economic growth, External quality assessment, Biology, Psychometrics, Mathematics, Developmental psychology, Clinical psychology, Philosophy, Pathology, Metric (unit)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
- References (count)
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50Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.improve | 324 |
| abstract_inverted_index.meeting | 166 |
| abstract_inverted_index.person, | 124 |
| abstract_inverted_index.points; | 180 |
| abstract_inverted_index.quality | 22, 47, 218, 238 |
| abstract_inverted_index.rating. | 74 |
| abstract_inverted_index.related | 83 |
| abstract_inverted_index.remains | 33 |
| abstract_inverted_index.sources | 288 |
| abstract_inverted_index.videos, | 51 |
| abstract_inverted_index.website | 69 |
| abstract_inverted_index.However, | 21, 209 |
| abstract_inverted_index.Methods: | 58 |
| abstract_inverted_index.Results: | 136 |
| abstract_inverted_index.YouTube, | 32 |
| abstract_inverted_index.YouTube. | 295, 333 |
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| abstract_inverted_index.adapting | 65 |
| abstract_inverted_index.analysis | 71, 128, 139 |
| abstract_inverted_index.assessed | 102 |
| abstract_inverted_index.assigned | 109 |
| abstract_inverted_index.credible | 287 |
| abstract_inverted_index.criteria | 67, 107 |
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| abstract_inverted_index.entities | 320 |
| abstract_inverted_index.existing | 66 |
| abstract_inverted_index.focusing | 276 |
| abstract_inverted_index.hospital | 119 |
| abstract_inverted_index.indices. | 226 |
| abstract_inverted_index.informed | 54 |
| abstract_inverted_index.medicine | 13, 87, 93 |
| abstract_inverted_index.points). | 184 |
| abstract_inverted_index.possible | 181 |
| abstract_inverted_index.provider | 223 |
| abstract_inverted_index.quality, | 160 |
| abstract_inverted_index.reliable | 328 |
| abstract_inverted_index.requires | 310 |
| abstract_inverted_index.testing. | 314 |
| abstract_inverted_index.“AM” | 242 |
| abstract_inverted_index.“CM” | 233 |
| abstract_inverted_index.cancer” | 90 |
| abstract_inverted_index.conducted | 79, 130 |
| abstract_inverted_index.continues | 6 |
| abstract_inverted_index.criteria. | 168 |
| abstract_inverted_index.developed | 63, 297 |
| abstract_inverted_index.different | 112 |
| abstract_inverted_index.excellent | 151 |
| abstract_inverted_index.generally | 234 |
| abstract_inverted_index.hospitals | 197 |
| abstract_inverted_index.insurance | 200 |
| abstract_inverted_index.interest. | 20 |
| abstract_inverted_index.oncology. | 57 |
| abstract_inverted_index.platforms | 30, 292, 331 |
| abstract_inverted_index.providers | 115, 201 |
| abstract_inverted_index.retrieved | 228 |
| abstract_inverted_index.suggested | 322 |
| abstract_inverted_index.Interrater | 137 |
| abstract_inverted_index.Intraclass | 142 |
| abstract_inverted_index.Statistics | 134 |
| abstract_inverted_index.agreement. | 152 |
| abstract_inverted_index.assessment | 42, 60, 298 |
| abstract_inverted_index.attracting | 16 |
| abstract_inverted_index.challenges | 284 |
| abstract_inverted_index.emphasized | 282 |
| abstract_inverted_index.evaluation | 304 |
| abstract_inverted_index.frequently | 257 |
| abstract_inverted_index.healthcare | 117, 317 |
| abstract_inverted_index.indicating | 148 |
| abstract_inverted_index.insurance, | 122 |
| abstract_inverted_index.refinement | 312 |
| abstract_inverted_index.surpassing | 194 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.CAM-related | 49 |
| abstract_inverted_index.Coefficient | 144 |
| abstract_inverted_index.Conclusion: | 268 |
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| abstract_inverted_index.identifying | 286 |
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| abstract_inverted_index.information | 25, 329 |
| abstract_inverted_index.interaction | 225 |
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| abstract_inverted_index.Nonetheless, | 252 |
| abstract_inverted_index.particularly | 28, 193 |
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| abstract_inverted_index.comprehensive | 41 |
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| abstract_inverted_index.German-language | 81 |
| abstract_inverted_index.decision-making | 55 |
| abstract_inverted_index.Journalism-based | 185 |
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| abstract_inverted_index.(Kruskal-Wallis-Test: | 202 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.86458875 |
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| citation_normalized_percentile.is_in_top_10_percent | True |