Short-form video sharing platforms as a source of information for children’s growing pains: A cross-sectional content analysis study

Abstract

Objective

To evaluate the quality, reliability, and educational value of short-form videos pertaining to children’s growing pains on popular social media platforms (TikTok, Rednote, Bilibili, and YouTube).

Methods

A cross-sectional analysis of 200 short-form videos (50 per platform) was conducted using standardized search terms. Video quality was assessed using four validated instruments: modified DISCERN (mDISCERN), the Global Quality Scale (GQS), the Video Information and Quality Index (VIQI), and the Patient Education Materials Assessment Tool (PEMAT). Metadata and user engagement metrics were collected, and statistical analyses included descriptive statistics, group comparisons, and correlation analyses.

Results

TikTok demonstrated superior performance compared to other platforms in reliability (mDISCERN: 3.00 (3.00, 4.00); GQS: 4.00 (3.00, 4.00); median (IQR); p < 0.001), educational value (PEMAT-Understandability: 80.00 (66.70, 92.22); PEMAT-Actionability: 80.00 (60.00, 80.00); median (IQR); p < 0.001), and content comprehensiveness (VIQI-Total score: 14.00 (12.25, 15.00); median (IQR); p < 0.001). Videos created by healthcare professionals showed significantly higher quality scores and more comprehensive clinical content coverage. User engagement metrics such as likes, comments, video duration, and followers showed positive correlations with several video quality scores (r: 0.12–0.56, p < 0.05). However, engagement alone should not be considered a definitive indicator of quality.

Conclusion

In conclusion, while short-form videos represent a valuable educational resource for parents, their quality varies significantly across platforms and creators. Content from healthcare professionals, particularly on TikTok, was found to be more reliable and robust. This underscores the critical role of platform algorithms in quality curation. Future initiatives should therefore encourage professional creator participation and optimize recommendation systems to prioritize informational accuracy.

Keywords

growing pains short-form videos health communication content quality social media

Introduction

Growing pains are a common health issue in children, typically characterized by lower limb pain that is more pronounced during the night or evening.¹ The pain typically resolves spontaneously within several hours. Its etiology remains unclear, and most current studies have not identified specific risk factors. A few studies suggest that growing pains may be associated with musculoskeletal growth, emotional trauma, excessive physical activity, and family history.² Growing pains often affect children’s daily activities and sleep quality, while also causing concern and anxiety among parents.³ Although the condition itself is usually not serious, in some cases, its symptoms may resemble early manifestations of more severe diseases, such as bone tumors, osteoarthritis, or fractures. Therefore, early recognition and proper management are essential.^4,5

With the growth of information technology and social media, short-form video platforms have become a major source for parents seeking information about children’s growing pains. Mainstream short-form video platforms in the Chinese internet landscape, including TikTok, Rednote, Bilibili, and the global platform YouTube, have transformed from entertainment tools into key channels for health knowledge dissemination, capitalizing on their accessibility and large user bases.^6,7 However, the quality of content related to growing pains on these platforms varies significantly. Videos range from professional medical explanations to personal parenting experiences, and the creators’ expertise directly affects the accuracy and reliability of the information.^8,9 Studies indicate that many so-called “educational videos” lack scientific evidence and may even spread misleading information.^10,11 Such content not only fails to help parents correctly understand growing pains but could also lead to delayed diagnosis, inappropriate management, or increased anxiety.¹²

In recent years, researchers have begun to utilize a range of standardized instruments to evaluate the quality of health information on short-form video platforms. These tools include the modified DISCERN (mDISCERN) instrument, the Global Quality Scale (GQS), the Video Information and Quality Index (VIQI), and the Patient Education Materials Assessment Tool (PEMAT). They enable a systematic assessment of video content across multiple dimensions, such as reliability, completeness, medical accuracy, and educational value.^13–16 For instance, a study by He et al., which analyzed child health-related content on a similar platform, found that some videos, despite having high view counts, demonstrated significant shortcomings in their scientific rigor and educational value.¹⁷ These findings highlight a critical challenge: while short-form video platforms provide new pathways for health communication, effectively ensuring the quality of the content remains an urgent and unresolved issue.

The quality and reliability of short-form videos concerning growing pains—a common yet often overlooked pediatric condition—have not been subjected to systematic evaluation, and research in this area remains scarce. This study will evaluate 200 top-relevant videos from TikTok, Rednote, Bilibili, and YouTube, employing the mDISCERN, GQS, VIQI, and PEMAT tools to fill this gap by providing a systematic assessment of their informational quality and reliability.

Methods

Ethical considerations

This study utilized exclusively publicly accessible data from short-form video platforms. No private or personally identifiable user information was collected. All analyses were conducted using anonymized public data. The study did not involve any direct or indirect interaction with platform users, nor did it impact any individuals. As the research does not fall within the scope of human subject research, it was approved by the Ethics Committee after review (ID: 2025/164).

Search strategy and data collection

This study adhered to established methodological guidelines for health research using social media data, which provide a standardized operational framework for healthcare practitioners and researchers.¹⁸ Data were collected from four major short-form video platforms (TikTok, Rednote, Bilibili, and YouTube) between July 12 and 14, 2025. A standardized search protocol was implemented using the keyword “生长痛” on Chinese platforms and “Growing pains” on YouTube. To minimize bias from personalized recommendation algorithms, all searches were conducted in a logged-out state or using newly registered accounts with no browsing history. Results were displayed using each platform’s default sorting algorithm, without applying filters such as “Latest” or “Most Popular,” to simulate the typical viewing experience of an average user.

Due to the head effect in user video selection (preference for videos ranked higher in search results), the first 80 videos from the search results of each platform were included to form the initial sample pool.¹⁹ Inclusion criteria were: (1) video content related to the explanation, symptoms, management, or shared experiences of childhood growing pains. Exclusion criteria were: (1) duplicate content; (2) purely commercial advertisements; (3) videos published less than 7 days prior; (4) irrelevant content (e.g., mentioning “growth” without “pain,” or referring to plant growth); (5) videos without subtitles or audio.

The final sample consisted of 200 videos, with 50 videos selected from each platform based on the inclusion and exclusion criteria and in accordance with their respective ranking order.¹⁹ For each included video, the following metadata were extracted: video title, publisher name, number of likes, comments, favorites, shares, video duration, publisher type, and content theme category.

Primary, secondary, and exploratory outcomes

A multi-level analytical framework was employed to systematically evaluate the quality and content characteristics of short-form videos related to childhood growing pains. The primary outcome consisted of the assessment results derived from four internationally recognized instruments for evaluating video information quality. The selection of these four tools aimed to achieve a complementary and multi-dimensional evaluation of video quality, thereby avoiding the limitations of any single metric. The mDISCERN instrument evaluated information reliability and content quality; the GQS measured overall educational value; the VIQI provided a comprehensive assessment of information accuracy and structural integrity; and the PEMAT analyzed understandability and actionability.

Secondary outcomes focused on user engagement metrics (including number of likes, comments, video duration in seconds, days since publication, and publisher follower count) and the coverage of medical content themes (including pain location, pain pattern, pain severity, commonly affected age, etiology/risk factors, diagnosis/differential diagnosis, and treatment protocols).

Exploratory analyses aimed to investigate: 1) systematic differences in video quality scores (mDISCERN, GQS, VIQI, PEMAT) across different publisher types (e.g., specialist physicians versus individual users); and 2) potential associations between platform algorithm-driven user engagement metrics and video information quality scores, to elucidate the relationship between content quality and dissemination effectiveness.

Video quality assessment tools

The mDISCERN scale is a structured tool for assessing the reliability of health information on short-video/social media platforms.²⁰ It consists of five dichotomous (yes/no) items evaluating: ① clarity of content presentation; ② citation or reliance on reliable sources (e.g., clinical guidelines, academic papers, authoritative institutions); ③ balance and lack of bias (avoiding exaggeration or one-sidedness); ④ provision of additional sources for further verification/learning; and ⑤ mention of uncertainties or controversies (e.g., inconclusive or disputed points). Scoring assigns 1 point for each “yes” and 0 for each “no,” yielding a total score of 0–5, with higher scores indicating greater information reliability.

The GQS is a widely used scoring system for evaluating the educational quality of online videos, effectively measuring the overall quality, comprehensibility, and practical value of video information for viewers.²¹ Scores range from 1 (lowest quality, minimal usefulness) to 5 (excellent quality, highly valuable).

The VIQI is a comprehensive metric specifically developed to assess the quality of information in short-form videos, systematically evaluating content across multiple dimensions including accuracy, completeness, presentation style, and credibility.²²

The PEMAT, developed by the Agency for Healthcare Research and Quality, was used specifically to evaluate the understandability and actionability of video content, measuring the degree to which health information can be comprehended and applied by the average consumer.¹⁵

To control for potential bias, all data collection and preliminary organization were performed by a single researcher. Formal quality assessment of video content was conducted independently by two physicians, each with over five years of clinical experience in pediatrics or pediatric rehabilitation. The assessors initially scored each video independently using the mDISCERN, GQS, VIQI, and PEMAT tools. Subsequently, they discussed and reconciled any discrepancies in their ratings to reach a consensus. For any persistent disagreements, a third senior pediatric chief physician was consulted to arbitrate and provide a final decision. Inter-rater reliability was assessed using Cohen’s kappa coefficient. The evaluation criteria were as follows: κ > 0.8 indicated excellent agreement, 0.6–0.8 good agreement, 0.4–0.6 moderate agreement, and κ ≤ 0.4 poor agreement.²³ Overall, the inter-rater agreement on video quality scores was very high (Cohen’s κ = 0.83).

Statistical analysis

Descriptive statistics were used to summarize the characteristics of all videos, including publisher type, content theme category, and all scoring outcomes. Categorical variables are presented as frequencies (percentages). Continuous variables are presented as mean ± standard deviation if normally distributed, or as median (interquartile range) or median (range) if non-normally distributed. Group comparisons (e.g., specialist physicians vs. individual users) were performed using independent samples t-tests for normally distributed data or Mann-Whitney U tests for non-normally distributed data. Multiple group comparisons were conducted using one-way ANOVA or Kruskal-Wallis tests. Pearson correlation analysis was used to analyze the relationship between video quality scores and user engagement metrics. A p-value < 0.05 was considered statistically significant. All statistical analyses were performed using R software (version 4.3.2) and GraphPad Prism (version 10.0; Dotmatics).

Results

Video characteristics

This study included 50 videos from each of the four platforms (TikTok, Rednote, Bilibili, and YouTube) for analysis (see Figure 1). A comparison of the basic characteristics among the four platforms is presented in Table 1.

Figure 1.

Study flow diagram.

Table 1.

General characteristics of growing pains-related videos across platforms.

Variables	TikTok (n=50)	Rednote (n=50)	Bilibili (n=50)	YouTube (n=50)	P
Likes, median (IQR)	418.50 (122.00,1063.25)	860.00 (131.25,2432.50)	6.50 (1.00,55.75)	216.50 (56.00,480.25)	<0.001
Favorites, median (IQR)a	125.00 (39.00,390.00)	965.00 (113.75,2767.50)	2.50 (0.00,29.00)	-	<0.001
Comments, median (IQR)	44.50 (9.00,233.50)	19.50 (5.00,57.75)	0.00 (0.00,5.75)	7.50 (2.00,30.50)	<0.001
Shares, median (IQR)a	251.00 (67.75,1245.25)	598.00 (73.50,1403.75)	4.00 (0.00,31.50)	-	<0.001
Duration (s), median (IQR)	66.50 (53.50,84.00)	52.50 (42.25,90.75)	78.00 (41.75,142.75)	113.50 (61.00,270.75)	<0.001
Views, median (IQR)a	-	-	647.00 (161.25,5321.25)	13923.50 (5450.25,44831.25)	<0.001
Time Since Publication^b (d), median (IQR)	455.00 (124.00,896.00)	310.00 (149.50,548.75)	757.00 (340.00,1284.75)	1030.00 (683.25,2735.00)	<0.001
Followers, median (IQR)	67141.50 (12079.00,419185.25)	19500.00 (3770.00,136250.00)	474.50 (43.25,11000.00)	92800.00 (11425.00,304250.00)	<0.001
Video Author Type,Number (%)					<0.001
Individual	1 (2.00)	27 (54.00)	17 (34.00)	5 (10.00)
Science Writer	0 (0.00)	12 (24.00)	6 (12.00)	11 (22.00)
Physiotherapist	1 (2.00)	0 (0.00)	4 (8.00)	5 (10.00)
Specialist physicians	48 (96.00)	11 (22.00)	23 (46.00)	29 (58.00)
Pain Location, Number (%)					<0.001
No	9 (18.00)	29 (58.00)	24 (48.00)	4 (8.00)
Yes	41 (82.00)	21 (42.00)	26 (52.00)	46 (92.00)
Pain Pattern, Number (%)					<0.001
No	8 (16.00)	29 (58.00)	28 (56.00)	15 (30.00)
Yes	42 (84.00)	21 (42.00)	22 (44.00)	35 (70.00)
Pain Severity, Number (%)					<0.001
No	14 (28.00)	32 (64.00)	33 (66.00)	18 (36.00)
Yes	36 (72.00)	18 (36.00)	17 (34.00)	32 (64.00)
Common Affected Age,Number (%)					<0.001
No	29 (58.00)	44 (88.00)	33 (66.00)	19 (38.00)
Yes	21 (42.00)	6 (12.00)	17 (34.00)	31 (62.00)
Etiology/Risk Factors,Number (%)					<0.001
No	34 (68.00)	36 (72.00)	29 (58.00)	16 (32.00)
Yes	16 (32.00)	14 (28.00)	21 (42.00)	34 (68.00)
Diagnosis/Differential Diagnosis, Number (%)					<0.001
No	15 (30.00)	33 (66.00)	21 (42.00)	16 (32.00)
Yes	35 (70.00)	17 (34.00)	29 (58.00)	34 (68.00)
Treatment Protocol,Number (%)					0.002
Physiotherapy^c	12 (24.00)	28 (56.00)	16 (32.00)	13 (26.00)
Nutritional Support^d	3 (6.00)	4 (8.00)	6 (12.00)	2 (4.00)
Comprehensive Therapy^e	18 (36.00)	15 (30.00)	16 (32.00)	28 (56.00)
None^f	17 (34.00)	3 (6.00)	12 (24.00)	7 (14.00)

Data are shown as median (IQR) or Number (%).

^aNote. Due to platform data access limitations, Favorites and Shares were analyzed using data exclusively from TikTok, Rednote, and Bilibili, while Views were compared using only data from Bilibili and YouTube.

^bThe time span since video publication varied considerably, which may affect the interpretation and comparability of some data. The therapy categories are classified based on the treatment suggestions commonly found in short-form video content. Their specific measures are summarized as follows:

^cPhysiotherapy: Typically includes local heat application, muscle stretching, joint mobility exercises, massage techniques, and guided home-based functional exercises.

^dNutritional Support: Focuses on supplementation of nutrients related to musculoskeletal health (e.g., vitamin D, calcium, magnesium) or dietary advice to increase intake of relevant nutrients.

^eComprehensive Therapy: Combines multiple approaches such as physiotherapy, nutritional guidance, behavioral adjustments (e.g., routine management, emotional soothing), pain education, and—when necessary—short-term use of analgesic medications (e.g., ibuprofen) under medical supervision.

^fNone: No specific intervention or therapy is recommended in the video.

Significant differences in user engagement were found. Rednote videos had the highest likes (860.00 (131.25, 2432.50); median (IQR); p < 0.001), favorites (965.00 (113.75, 2767.50); median (IQR); p < 0.001), and shares (598.00 (73.50,1403.75); median (IQR); p < 0.001), while Bilibili videos had the lowest on all engagement metrics. TikTok videos received the most comments (44.50 (9.00, 233.50); median (IQR); p < 0.001). Video duration also varied significantly, being longest on YouTube (113.50 (61.00, 270.75) s; median (IQR); p < 0.001) and shortest on Rednote (52.50 (42.25, 90.75) s; median (IQR); p < 0.001). For publisher followers, TikTok and YouTube had the highest median counts, whereas Bilibili had the lowest.

The distribution of publisher types differed significantly. Most videos (48 (96.00); Number (%); p < 0.001) were from specialist physicians on TikTok, while over half (27 (54.00); Number (%); p < 0.001) were from individual users on Rednote. YouTube videos provided the most comprehensive coverage of key clinical information, including pain location (46 (92.00); Number (%); p < 0.001), common affected age (31 (62.00); Number (%); p < 0.001), and etiology/risk factors (34 (68.00); Number (%); p < 0.001). In contrast, information omission was more common on Rednote and Bilibili.

Video quality

Based on the results of video quality assessment tools, significant differences in video quality were observed across platforms. TikTok demonstrated the best performance across multiple quality metrics, with the highest median scores in mDISCERN (3.00 (3.00,4.00); median (IQR); p < 0.001), GQS (4.00 (3.00,4.00); median (IQR); p < 0.001), and VIQI-P (4.00 (4.00,4.00); median (IQR); p < 0.001). Its VIQI-Total score (14.00 (12.25,15.00); median (IQR); p < 0.001), PEMAT-U (80.00 (66.70,92.22); median (IQR); p < 0.001), and PEMAT-A (80.00 (60.00,80.00); median (IQR); p < 0.001) were also significantly higher than other platforms. In contrast, Bilibili showed the poorest overall video quality, with the lowest scores in VIQI-F (2.00 (1.00,2.00); median (IQR); p < 0.001) and VIQI-T (10.00 (8.00,12.00); median (IQR); p < 0.001). A detailed comparison of video quality scores among the four platforms is provided in Table 2.

Table 2.

Quality assessment scores of growing pains-related videos across platforms.

Variables	TikTok (n=50)	Rednote (n=50)	Bilibili (n=50)	YouTube (n = 50)	P
mDISCERN, median (IQR)	3.00 (3.00,4.00)	2.00 (2.00,3.00)	2.00 (1.25,3.00)	2.50 (1.25,3.00)	<0.001
GQS, median (IQR)	4.00 (3.00,4.00)	3.00 (3.00,4.00)	3.00 (2.00,4.00)	3.00 (2.00,4.00)	<0.001
VIQI-F, median (IQR)	3.00 (3.00,3.00)	3.00 (3.00,4.00)	2.00 (1.00,2.00)	3.00 (2.00,3.00)	<0.001
VIQI-A, median (IQR)	4.00 (3.00,4.00)	3.00 (2.25,4.00)	3.00 (2.00,3.00)	3.00 (2.00,4.00)	<0.001
VIQI-Q, median (IQR)	3.00 (2.00,3.00)	2.00 (2.00,3.00)	2.00 (2.00,3.00)	2.00 (2.00,3.00)	0.019
VIQI-P, median (IQR)	4.00 (4.00,4.00)	3.50 (2.00,4.00)	3.00 (2.00,4.00)	3.00 (2.25,4.00)	<0.001
VIQI-T, median (IQR)	14.00 (12.25,15.00)	12.00 (10.00,15.00)	10.00 (8.00,12.00)	12.00 (9.00,14.00)	<0.001
PEMAT-U, median (IQR)	80.00 (66.70,92.22)	75.00 (62.95,87.50)	61.50 (46.20,74.98)	66.70 (57.40,78.10)	<0.001
PEMAT-A, median (IQR)	80.00 (60.00,80.00)	60.00 (40.00,80.00)	60.00 (40.00,60.00)	60.00 (40.00,80.00)	<0.001

Data are shown as median (IQR).

Note. Scoring ranges: mDISCERN 0–5; GQS 1–5; VIQI-F/VIQI-A/VIQI-Q/VIQI-P 1–5 each; VIQI-T 4–20 (sum of four domains); PEMAT-U 0–100%; PEMAT-A 0–100%.

Abbreviation: GQS, Global Quality Scale; VIQI-F, Video Information and Quality Index - Flow of Information; VIQI-A, Video Information and Quality Index - Accuracy; VIQI-Q, Video Information and Quality Index - Visual Quality; VIQI-P, Video Information and Quality Index - Precision; VIQI-T, Video Information and Quality Index - Total Score; PEMAT-U, Patient Education Materials Assessment Tool - Understandability; PEMAT-A, Patient Education Materials Assessment Tool - Actionability.

Video characteristics and quality by publisher type

Analysis of video characteristics revealed notable differences between individual creators and professional publishers (Table 3). While no statistically significant differences were observed in user engagement metrics, professionals produced significantly longer videos (74.00 (53.00, 129.00) s vs 54.50 (41.25, 89.50) s; median (IQR); p = 0.007) and had substantially higher follower counts (49850.00 (2940.50, 279750.00) vs 3829.00 (299.00, 16000.00); median (IQR); p < 0.001). Additionally, videos from professional publishers had been available for a longer duration (719.00 (213.25, 1169.50) d vs 347.00 (149.50, 863.00) d; median (IQR); p = 0.049). Engagement metrics across detailed publisher categories are compared in Figure 2.

Table 3.

General characteristics of growing pains-related videos by publisher type.

Variables	Individuals (n=50)	Professionals (n=150)	P
Likes, median (IQR)	338.00 (46.50, 2110.50)	184.50 (30.00, 598.75)	0.361
Favorites^a, median (IQR)	298.00 (16.00, 1912.00)	68.00 (13.00, 456.00)	0.207
Comments, median (IQR)	6.00 (0.00, 37.00)	14.50 (2.00, 55.50)	0.061
Shares^a, median (IQR)	193.00 (9.00, 971.00)	104.00 (9.00, 838.00)	0.939
Duration (s), median (IQR)	54.50 (41.25, 89.50)	74.00 (53.00, 129.00)	0.007
Views^a, median (IQR)	2812.00 (94.25, 26362.75)	6419.00 (930.75, 29860.75)	0.176
Time Since Publication^b (d), median (IQR)	347.00 (149.50, 863.00)	719.00 (213.25, 1169.50)	0.049
Followers, median (IQR)	3829.00 (299.00, 16000.00)	49850.00 (2940.50, 279750.00)	<0.001
Platform resource, Number (%)			<0.001
TikTok	1 (2.00)	49 (32.67)
Rednote	27 (54.00)	23 (15.33)
Bilibili	17 (34.00)	33 (22.00)
YouTube	5 (10.00)	45 (30.00)
Pain Location, Number (%)			<0.001
No	36 (72.00)	30 (20.00)
Yes	14 (28.00)	120 (80.00)
Pain Pattern, Number (%)			<0.001
No	37 (74.00)	43 (28.67)
Yes	13 (26.00)	107 (71.33)
Pain Severity, Number (%)			<0.001
No	45 (90.00)	52 (34.67)
Yes	5 (10.00)	98 (65.33)
Common Affected Age,Number (%)			<0.001
No	44 (88.00)	81 (54.00)
Yes	6 (12.00)	69 (46.00)
Etiology/Risk Factors,Number (%)			<0.001
No	41 (82.00)	74 (49.33)
Yes	9 (18.00)	76 (50.67)
Diagnosis/Differential Diagnosis, Number (%)			<0.001
No	34 (68.00)	51 (34.00)
Yes	16 (32.00)	99 (66.00)
Treatment Protocol, Number (%)			<0.001
Physiotherapy^c	34 (68.00)	35 (23.33)
Nutritional Support^d	4 (8.00)	11 (7.33)
Comprehensive Therapy^e	6 (12.00)	71 (47.33)
None^f	6 (12.00)	33 (22.00)

Data are shown as median (IQR) or Number (%).

^bThe time span since video publication varied considerably, which may affect the interpretation and comparability of some data.

The therapy categories are classified based on the treatment suggestions commonly found in short-form video content. Their specific measures are summarized as follows:

^cPhysiotherapy: Typically includes local heat application, muscle stretching, joint mobility exercises, massage techniques, and guided home-based functional exercises.

^dNutritional Support: Focuses on supplementation of nutrients related to musculoskeletal health (e.g., vitamin D, calcium, magnesium) or dietary advice to increase intake of relevant nutrients.

^fNone: No specific intervention or therapy is recommended in the video.

Figure 2.

Comparison of user engagement metrics by publisher type.

Substantial disparities were evident in clinical content coverage. Professional-created videos demonstrated significantly better coverage across all clinical domains, including pain location (120 (80.00) vs 14 (28.00); Number (%); p < 0.001), pain pattern (107 (71.33) vs 13 (26.00); Number (%); p < 0.001), pain severity (98 (65.33) vs 5 (10.20); Number (%); p < 0.001), and diagnosis/differential diagnosis (99 (66.00) vs 16 (32.00); Number (%); p < 0.001). Treatment approaches also varied considerably, with professionals more frequently recommending comprehensive therapy (71 (47.33) vs 6 (12.00); Number (%); p < 0.001), while individual creators predominantly focused on physiotherapy (34 (68.00) vs 35 (23.33); Number (%); p < 0.001). Clinical content metrics across detailed publisher categories are compared in Figure 3.

Figure 3.

Comparison of clinical content coverage by publisher type.

Quality assessment demonstrated superior performance in professional-created videos across multiple validated instruments (Table 4). Professionals achieved significantly higher scores in mDISCERN (3.00 (2.00, 4.00) vs 2.00 (1.00, 2.00); median (IQR); p < 0.001), GQS (4.00 (3.00, 4.00) vs 2.50 (2.00, 3.00); median (IQR); p < 0.001), and VIQI-T scores (13.00 (10.00, 14.00) vs 10.00 (7.25, 11.75); median (IQR); p < 0.001). Both PEMAT-U (71.40 (61.50, 87.50) vs 60.75 (46.20, 74.58); median (IQR); p < 0.001) and PEMAT-A (60.00 (57.10, 80.00) vs 55.00 (40.00, 60.00); median (IQR); p < 0.001) were significantly better in professional-created videos. Video quality metrics across detailed publisher categories are compared in Figure 4.

Table 4.

Quality assessment scores of growing pains-related videos by publisher type.

Variables	Individuals (n=50)	Professionals (n=150)	P
mDISCERN, median (IQR)	2.00 (1.00, 2.00)	3.00 (2.00, 4.00)	<0.001
GQS, median (IQR)	2.50 (2.00, 3.00)	4.00 (3.00, 4.00)	<0.001
VIQI-F, median (IQR)	3.00 (2.00, 4.00)	3.00 (2.00, 3.00)	0.512
VIQI-A, median (IQR)	2.00 (2.00, 3.00)	4.00 (3.00, 4.00)	<0.001
VIQI-Q, median (IQR)	2.00 (2.00, 2.75)	3.00 (2.00, 3.00)	<0.001
VIQI-P, median (IQR)	2.00 (2.00, 3.00)	4.00 (3.00, 4.00)	<0.001
VIQI-T, median (IQR)	10.00 (7.25, 11.75)	13.00 (10.00, 14.00)	<0.001
PEMAT-U, median (IQR)	60.75 (46.20, 74.58)	71.40 (61.50, 87.50)	<0.001
PEMAT-A, median (IQR)	55.00 (40.00, 60.00)	60.00 (57.10, 80.00)	<0.001

Data are shown as median (IQR).

Note. Scoring ranges: mDISCERN 0–5; GQS 1–5; VIQI-F/VIQI-A/VIQI-Q/VIQI-P 1–5 each; VIQI-T 4–20 (sum of four domains); PEMAT-U 0–100%; PEMAT-A 0–100%.

Figure 4.

Comparison of video quality by publisher type.

Correlation analysis

Pearson correlation analysis revealed significant positive correlations between engagement metrics and quality assessment scores. Specifically, comments, video duration, and follower count showed significant positive correlations with mDISCERN, GQS, VIQI-T, PEMAT-U, and PEMAT-A scores. However, the correlation between likes and mDISCERN score was not statistically significant. In contrast, time since publication demonstrated no significant correlation with any quality assessment scores. Detailed results are presented in Figure 5.

Figure 5.

Correlation analysis between engagement metrics and video quality scores.

Discussion

This study represents the first systematic assessment of the quality, reliability, and educational value of video content regarding growing pains in children on mainstream Chinese short-form video platforms. The results reveal significant disparities in information quality across different platforms and creator sources, reflecting both prevalent trends and specific challenges in health information dissemination through social media. This research addresses a critical gap in the existing literature.

Evaluations using standardized tools such as mDISCERN, GQS, VIQI and PEMAT consistently indicate that videos related to growing pains on TikTok significantly outperform those on Rednote, Bilibili, and YouTube in terms of information reliability, overall quality, and accuracy. This finding aligns with conclusions from multiple previous studies,^24–26 further establishing TikTok’s leading position in the field of pediatric health science communication. The observed differences highlight the direct impact of platform operation models, content moderation standards, and creator ecosystems on the quality of health information. They also provide critical insights for the targeted delivery of public health education strategies.

Short-form videos about growing pains on TikTok generally demonstrate high quality, which is closely tied to the platform’s creator verification mechanism. This system, through the review and labeling of medical professional qualifications, has significantly increased the proportion of certified medical creators, thereby ensuring content professionalism and credibility at the source.^27–30 This finding aligns with existing research conclusions: content published by verified professional medical creators (e.g., doctors, medical institutions) typically exhibits significantly higher information quality compared to unverified sources. For instance, a study on YouTube videos about pediatric appendicitis revealed that videos posted by verified hospital or doctor accounts scored notably higher in terms of information accuracy and content reliability than those from individual or non-professional channels.³¹ In contrast, content from non-professional creators commonly exhibits notable limitations. These include insufficient coverage of core diagnostic elements for growing pains—such as pain patterns, location, and relationship to activity—often leading to potential misinterpretation by parents. Furthermore, such videos frequently recommend interventions lacking robust evidence-based support, such as overemphasizing specific physical therapies or nutritional supplements. These shortcomings are consistent with findings from multiple previous studies,^32,33 underscoring the indispensable role of professional creators in ensuring the accuracy of health information.

In terms of content dimensions, high-quality videos on growing pains typically cover a comprehensive knowledge chain—from symptoms and etiology to diagnosis, differential diagnosis, and management. These videos not only detail core symptoms, including pain location (primarily lower limbs), pattern (e.g., nocturnal occurrence), severity, and common age groups, but also explore potential causes, emphasize key points for differential diagnosis (e.g., distinguishing from juvenile idiopathic arthritis), and provide non-pharmacological management advice.^34–36 This comprehensiveness is crucial for helping parents establish an accurate understanding. It is noteworthy that the very definition and etiology of “growing pains” remain subjects of academic discussion. Several studies have pointed out that most existing studies do not conclusively establish a direct link between the pain and growth.^37–39 Therefore, videos that acknowledge these academic uncertainties or diagnostic complexities, rather than presenting oversimplified conclusions, hold greater scientific value. This approach also aligns with the core requirements for objectivity and comprehensiveness in health information quality assessment tools, such as mDISCERN.¹⁴

When evaluating the effectiveness of health communication through short-form videos, it is essential to recognize that the quality advantage of professional content must be considered alongside its reach among the target audience.⁴⁰ If high-quality videos fail to reach parents who are actively seeking information about growing pains, their practical educational value may be limited. It is noteworthy that while videos created by individual users are generally shorter and cover medical content more superficially, their everyday language and relatable presentation may be better suited to fragmented consumption patterns. This highlights the inherent tension between quality and accessibility in health information dissemination, while also underscoring the complexity of research based on social media data: the dynamic nature of platform ecosystems and data heterogeneity necessitate appropriate caution in interpreting findings. Alongside advocating for content professionalism, equal attention should be paid to aligning dissemination strategies with the cognitive habits of the audience.

Moreover, the format of TikTok videos—moderate in length and brisk in pace—significantly enhances the effectiveness of health science communication. By breaking down complex medical knowledge into digestible, visual segments, these videos align with modern users’ information consumption habits. Research has indicated that health content on short-form video platforms often employs narrative techniques to make specialized knowledge more accessible.⁴¹ However, the risks of misinformation or oversimplification inherent in fragmented communication must be acknowledged.⁴² Successful growing pain videos strike a balance between accessibility and medical rigor by efficiently organizing key information within a limited duration and ensuring accurate presentation. This effective communication model helps ensure that professional pediatric knowledge reaches a broader parent audience, thereby contributing positively to public health literacy.

Notably, our study found a significant positive correlation between user interaction metrics (likes, comments, follower counts, video length) and video quality scores, suggesting that audience engagement data may partially reflect the educational value of content. This finding offers insights for potentially using such data in the rapid screening of health information quality. However, interaction metrics alone are not sufficient indicators of quality, as some highly interactive videos may still lack scientific rigor.^43,44 Therefore, platform recommendation algorithms should seek a balance between user preference and content professionalism to avoid reinforcing a “high-engagement but low-quality” dissemination bias.

This study has several limitations. First, the sample was limited to 200 videos (50 per platform) from four platforms (TikTok, Rednote, Bilibili, and YouTube) and did not include content in additional languages or from more regions, which may affect the generalizability and cross-cultural applicability of the findings. Future research should expand the sample size and include a wider variety of platforms and languages. Second, although we employed four validated assessment tools (mDISCERN, GQS, VIQI, PEMAT) and two physicians independently assessed the videos, with a third senior pediatrician consulted to arbitrate when necessary, some degree of subjective bias remains inevitable. Subsequent studies could develop automated assessment tools better suited to short-form videos, possibly incorporating natural language processing for quantitative content analysis. Furthermore, the cross-sectional design limits our ability to capture the dynamic nature of social media content; ongoing updates to platform algorithms and user-generated content may affect the long-term validity of the conclusions. Longitudinal studies are recommended to continuously track trends in video quality over time.

Conclusion

Short-form video platforms have become a significant channel for the public to access child health information. However, fully realizing their potential in public health education still requires collaborative efforts from all stakeholders to comprehensively enhance content quality. Ensuring the credibility, clarity, and actionability of growing pains and related health videos is crucial for optimizing health education outcomes and assisting parents in scientifically managing children’s growing pains.

Footnotes

ORCID iDs

Haisu Li

Chuan Zhong

Ethical considerations

Author contributions

Dan Zhou: Writing - Original Draft, Writing - Review & Editing, Conceptualization, Investigation, Data Curation, Methodology, Supervision, Formal Analysis, Project Administration, Validation, Visualization.

Zhuqing Ren: Writing - Review & Editing, Conceptualization, Investigation, Methodology, Supervision, Validation.

Jiayi Jiang: Writing - Review & Editing, Conceptualization, Investigation, Methodology, Supervision, Validation.

Haisu Li: Writing - Review & Editing, Software, Data Curation, Validation, Visualization.

Chuan Zhong: Writing - Review & Editing, Conceptualization, Investigation, Methodology, Supervision, Formal Analysis, Project Administration, Validation.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Datasets generated during and/or analyzed in the current study are available upon reasonable request to the corresponding author.*

Guarantor

Chuan Zhong is the guarantor of this study and takes responsibility for the overall content and integrity of the research.

References

Pavone

Vescio

Valenti

, et al. Growing pains: What do we know about etiology? A systematic review. World J Orthop 2019; 10(4): 192–205. https://doi.org/10.5312/wjo.v10.i4.192

O'Keeffe

Kamper

Montgomery

, et al. Defining Growing Pains: A Scoping Review. Pediatrics 2022; 150(2): e2021052578. https://doi.org/10.1542/peds.2021-052578

Donnelly

Bott

Bui

, et al. Common Pediatric Pain Disorders and Their Clinical Associations. Clin J Pain 2017; 33(12): 1131–1140. https://doi.org/10.1097/AJP.0000000000000496

Lehman

Carl

. Growing Pains. Sports Health 2017; 9(2): 132–138. https://doi.org/10.1177/1941738117692533

Zhang

Leng

, et al. An exploration of clinical features and factors associated with pain frequency and pain intensity in children with growing pains: a cross-sectional study from Chongqing, China. Pain Rep 2024; 9(4): e1164. https://doi.org/10.1097/PR9.0000000000001164

Guo

Ding

Zhang

, et al. Quality Assessment of Radiotherapy Health Information on Short-Form Video Platforms of TikTok and Bilibili: Cross-Sectional Study. JMIR Cancer 2025; 11: e73455. https://doi.org/10.2196/73455

Zhang

Jie

, et al. Analyzing dissemination, quality, and reliability of Chinese brain tumor-related short videos on TikTok and Bilibili: a cross-sectional study. Front Neurol 2024; 15: 1404038. https://doi.org/10.3389/fneur.2024.1404038

Grosberg

Grinvald

Reuveni

, et al. Frequent Surfing on Social Health Networks is Associated With Increased Knowledge and Patient Health Activation. J Med Internet Res 2016; 18(8): e212. https://doi.org/10.2196/jmir.5832

Sury

Zygmuntowicz

Dziubla

. The representation of the child on social media: interpretive content analysis of parental trolling TikTok videos. Polska Myśl Pedagogiczna 2024; 10: 219–239.

10.

Yeung

AWK

Tosevska

Klager

, et al. Medical and Health-Related Misinformation on Social Media: Bibliometric Study of the Scientific Literature. J Med Internet Res 2022; 24(1): e28152. https://doi.org/10.2196/28152

11.

Suarez-Lledo

Alvarez-Galvez

. Prevalence of Health Misinformation on Social Media: Systematic Review. J Med Internet Res 2021; 23(1): e17187. https://doi.org/10.2196/17187

12.

Kbaier

Kane

McJury

, et al. Prevalence of Health Misinformation on Social Media-Challenges and Mitigation Before, During, and Beyond the COVID-19 Pandemic: Scoping Literature Review. J Med Internet Res 2024; 26: e38786. https://doi.org/10.2196/38786

13.

Ouyang

Lin

, et al. Evaluation of the measurement properties of online health information quality assessment tools: A systematic review. Int J Nurs Sci 2025; 12(2): 130–136. https://doi.org/10.1016/j.ijnss.2025.02.015

14.

Charnock

Shepperd

Needham

, et al. DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health 1999; 53(2): 105–111. https://doi.org/10.1136/jech.53.2.105

15.

Shoemaker

Wolf

Brach

. Development of the Patient Education Materials Assessment Tool (PEMAT): a new measure of understandability and actionability for print and audiovisual patient information. Patient Educ Couns 2014; 96(3): 395–403. https://doi.org/10.1016/j.pec.2014.05.027

16.

Nagpal

Karimianpour

Mukhija

, et al. YouTube videos as a source of medical information during the Ebola hemorrhagic fever epidemic. Springerplus 2015; 4: 457. https://doi.org/10.1186/s40064-015-1251-9

17.

Yang

Liu

, et al. Quality and reliability of pediatric pneumonia related short videos on mainstream platforms: cross-sectional study. BMC Public Health 2025; 25(1): 1896. https://doi.org/10.1186/s12889-025-22963-2

18.

D'Souza

Hooten

Murad

. A Proposed Approach for Conducting Studies That Use Data From Social Media Platforms. Mayo Clin Proc 2021; 96(8): 2218–2229. https://doi.org/10.1016/j.mayocp.2021.02.010

19.

Gurler

Buyukceran

. Assessment of the Medical Reliability of Videos on Social Media: Detailed Analysis of the Quality and Usability of Four Social Media Platforms (Facebook, Instagram, Twitter, and YouTube). Healthcare (Basel) 2022; 10(10): 1836. https://doi.org/10.3390/healthcare10101836

20.

Singh

. YouTube for information on rheumatoid arthritis—a wake-up call? J Rheumatol 2012; 39(5): 899–903. https://doi.org/10.3899/jrheum.111114

21.

Bernard

Langille

Hughes

, et al. A systematic review of patient inflammatory bowel disease information resources on the World Wide Web. Am J Gastroenterol 2007; 102(9): 2070–2077. https://doi.org/10.1111/j.1572-0241.2007.01325.x

22.

Lena

Dindaroğlu

. Lingual orthodontic treatment: a YouTube™ video analysis. Angle Orthod 2018; 88(2): 208–214. https://doi.org/10.2319/090717-602.1

23.

McHugh

. Interrater reliability: the kappa statistic. Biochem Med (Zagreb) 2012; 22(3): 276–282.

24.

Dong

Lin

, et al. Beyond virality: evaluating evidence-based content delivery in social media-based pediatric orthodontic education. BMC Oral Health 2025; 25(1): 1603. https://doi.org/10.1186/s12903-025-06998-w

25.

Zheng

Tong

Wan

, et al. Quality and Reliability of Liver Cancer-Related Short Chinese Videos on TikTok and Bilibili: Cross-Sectional Content Analysis Study. J Med Internet Res 2023; 25: e47210. https://doi.org/10.2196/47210

26.

Liu

Chen

Lin

, et al. YouTube/Bilibili/TikTok videos as sources of medical information on laryngeal carcinoma: cross-sectional content analysis study. BMC Public Health 2024; 24(1): 1594. https://doi.org/10.1186/s12889-024-19077-6

27.

Kirkpatrick

Lawrie

. TikTok as a Source of Health Information and Misinformation for Young Women in the United States: Survey Study. JMIR Infodemiology 2024; 4: e54663. https://doi.org/10.2196/54663

28.

Zeng

Grgurevic

Diyab

, et al. #WhatIEatinaDay: The Quality, Accuracy, and Engagement of Nutrition Content on TikTok. Nutrients 2025; 17(5): 781. https://doi.org/10.3390/nu17050781

29.

Chan

Sounderajah

Daniels

, et al. The Reliability and Quality of YouTube Videos as a Source of Public Health Information Regarding COVID-19 Vaccination: Cross-sectional Study. JMIR Public Health Surveill 2021; 7(7): e29942. https://doi.org/10.2196/29942

30.

Gerçeker Demircan

Kesimal

. Educational quality and reliability of YouTube videos on behçet's uveitis: Higher quality in videos created by physicians. Eur J Ophthalmol 2025; 35(6): 2305–2311. https://doi.org/10.1177/11206721251343656

31.

Çoşkun

Demir

. Analysing YouTube as a health resource: quality and reliability of videos on pediatric appendicitis. BMC Med Educ 2025; 25(1): 1229. https://doi.org/10.1186/s12909-025-07869-2

32.

Rudisill

Saleh

Hornung

, et al. YouTube as a source of information on pediatric scoliosis: a reliability and educational quality analysis. Spine Deform 2023; 11(1): 3–9. https://doi.org/10.1007/s43390-022-00569-7

33.

Chang

Lee

Park

. The Quality, Reliability, and Accuracy of Videos Regarding Exercises and Management for Dysphagia in Pediatric Populations Uploaded on YouTube. Children (Basel) 2022; 9(10): 1514. https://doi.org/10.3390/children9101514

34.

Alcantara

Davis

. The chiropractic care of children with “growing pains”: a case series and systematic review of the literature. Complement Ther Clin Pract 2011; 17(1): 28–32. https://doi.org/10.1016/j.ctcp.2010.08.006

35.

Uziel

Hashkes

. Growing pains in children. Pediatr Rheumatol Online J 2007; 5: 5. https://doi.org/10.1186/1546-0096-5-5

36.

Simakajornboon

Dye

Walters

. Restless Legs Syndrome/Willis-Ekbom Disease and Growing Pains in Children and Adolescents. Sleep Med Clin 2015; 10(3): 311–322. https://doi.org/10.1016/j.jsmc.2015.05.014

37.

Rosen

AEV

Ursitti

Stella

, et al. Restless legs syndrome and growing pains in childhood: understanding the link. Front Neurol 2025; 16: 1603694. https://doi.org/10.3389/fneur.2025.1603694

38.

Liao

Wang

Lee

, et al. Clinical, laboratory characteristics and growth outcomes of children with growing pains. Sci Rep 2022; 12(1): 14835. https://doi.org/10.1038/s41598-022-19285-3

39.

Adolf

Braun

Meurer

. Wachstumsschmerzen: Ursprung, Bedeutung und Behandlung [Growing Pains: Cause, Significance and Treatment]. Orthopade 2019; 48(6): 461–468. https://doi.org/10.1007/s00132-019-03745-2

40.

Roberts-Lewis

Baxter

Mein

, et al. Examining the Effectiveness of Social Media for the Dissemination of Research Evidence for Health and Social Care Practitioners: Systematic Review and Meta-Analysis. J Med Internet Res 2024; 26: e51418. https://doi.org/10.2196/51418

41.

Che

, et al. The quality and reliability of short videos about hypertension on TikTok: a cross-sectional study. Sci Rep 2025; 15(1): 25042. https://doi.org/10.1038/s41598-025-08680-1

42.

Birkun

. Misinformation on first aid for seizures communicated through the fastest growing social media platform: A cross-sectional study of TikTok content. Epilepsy Behav 2024; 161: 110116. https://doi.org/10.1016/j.yebeh.2024.110116

43.

Hao

Liu

Lian

, et al. Evaluating the quality of TikTok videos on coronary artery disease using various scales to examine correlations with video characteristics and high-quality content. Sci Rep 2025; 15(1): 9189. https://doi.org/10.1038/s41598-025-93986-3

44.

Heales

Gunasinghe

Melrose

, et al. A systematic review of the quality and engagement of TikTok videos of resistance exercises for the management of lateral elbow tendinopathy. J Hand Ther 2025; 38(4): 834–840. https://doi.org/10.1016/j.jht.2025.02.016