Evaluating YouTube content on dental lasers: a clinical application–based quality and reliability study

Abstract

Background

Dental laser technology is widely used across multiple clinical fields of dentistry. YouTube is a commonly used information source for both patients and healthcare professionals and may shape health-related perceptions and information-seeking behavior. This study aimed to evaluate the accuracy, reliability, technical quality, and ethical standards of YouTube videos related to dental laser applications.

Methods

A structured YouTube search was conducted using the keywords “dental laser,” “laser in dentistry,” and “laser dentistry.” Of 360 initially screened videos, 121 met the eligibility criteria. Video quality and reliability were evaluated using CQS, mDISCERN, JAMA, VIQI, GQS, and HONcode. Data normality was assessed with the Shapiro–Wilk test; group comparisons were performed using the Kruskal–Wallis and Bonferroni-corrected Mann–Whitney U tests, categorical variables were analyzed using the chi-square test, correlations with Spearman’s rho, and intra- and inter-rater reliability with intraclass correlation coefficients.

Results

Of the evaluated videos, 33 (27.3%) were classified as low quality (0–3 points), 83 (68.6%) as moderate quality (4–6 points), and 5 (4.1%) as high quality (7–9 points). The CQS showed a positive correlation with the mDISCERN (ρ = 0.421; p < 0.001), VIQI (ρ = 0.684; p < 0.001), and GQS (ρ = 0.722; p < 0.001) scores.

Conclusion

The quality and reliability of YouTube videos related to dental laser applications are predominantly low to moderate. There is a clear need for more accurate, comprehensive, and professionally produced videos to support patient education and informed online information seeking, while recognizing that such videos cannot replace evidence-based clinical training, professional guidelines, or manufacturer-specific safety protocols.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-026-08795-5.

Background

Traditionally, health-related information has been conveyed directly to patients by healthcare professionals. However, rapid advances in information technologies have facilitated access to the internet, enabling individuals to obtain medical and dental information through online searches [1]. The YouTube platform provides user-generated video content through both visual and auditory media, allowing complex procedures and concepts to be explained more clearly than in many other information sources. Owing to these features, YouTube has become a widely used platform worldwide, not only among the general public but also among healthcare professionals seeking medical information [2].

Despite its potential for information dissemination, YouTube content also poses concerns regarding accuracy and reliability. There is no effective monitoring mechanism to verify the scientific validity of videos prior to their upload, such as evaluation based on scientific evidence or review by subject-matter experts [3]. The widespread dissemination of inaccurate health-related information may lead patients to develop negative attitudes toward treatments, potentially resulting in delays or errors in diagnostic and therapeutic processes [4].

In modern dentistry, laser technology enhances treatment comfort through several clinical advantages, including reduced collateral tissue damage, high operational precision that enables a minimally invasive approach, effective hemostatic control, and tissue-preserving properties that support biological healing [5]. Currently, dental laser applications are utilized across various clinical disciplines, including endodontics, periodontology, restorative dentistry, dental implantology, and orthodontics [6]. Although previous studies have analyzed YouTube content related to specific dental topics—such as dental implants, orthodontic treatment, and root canal therapy—there is a notable lack of comprehensive research evaluating the quality and reliability of videos focused on laser use in dentistry [7–9]. Given the wide range of clinical indications for dental lasers across multiple dental disciplines, an application-specific approach may fail to capture the overall quality and reliability of online information. Unlike many conventional dental procedures, laser applications require precise knowledge of laser–tissue interactions, appropriate parameter selection, and strict adherence to safety protocols [10]. Consequently, inaccurate or oversimplified online video content related to dental lasers may pose a higher risk of clinical misinformation compared with other dental procedures.

Therefore, the present study aimed to provide a comprehensive and multidimensional evaluation of YouTube videos related to dental lasers by assessing content accuracy, reliability, technical quality, and ethical standards. The study hypothesized that there is no significant difference in the quality and reliability of YouTube videos containing dental laser-related content. Accordingly, it was anticipated that online video content alone may be insufficient as a reliable information source for patients and healthcare professionals seeking information about dental laser applications.

Methods

Study design

This study was designed as a cross-sectional content analysis to evaluate the quality and reliability of YouTube videos related to dental lasers. As the research involved only publicly available online data and did not include human participants, ethics committee approval was not required; nevertheless, the study was conducted in line with the ethical principles of the Declaration of Helsinki and the ethical regulations of the institution.

Search strategy and video selection

Prior to the YouTube search, a preliminary analysis was conducted using Google Trends (https://trends.google.com) to identify the most relevant and frequently used search terms related to dental lasers. The Google Trends query was performed on January 4, 2026, with the following settings: geographic scope = worldwide, time range = 2004–present, category = all categories, and search type = web search. Based on the relative search volume of dental laser–related terms, the keywords “dental laser,” “laser in dentistry,” and “laser dentistry” were selected.

A structured search of the YouTube platform was conducted on January 4, 2026, using these three keywords. The URLs of the first 120 videos retrieved for each keyword were recorded on the same day to fix the search-result sample before metric extraction. To maximize reproducibility and minimize personalization bias, all searches were performed under standardized conditions: on a single desktop computer running Windows 11 with the Google Chrome browser in private/incognito mode; without signing into any Google or YouTube account; with browser history, cache, and cookies cleared before each search; from a single geographic location (Burdur, Turkey), without using a virtual private network (VPN) or proxy service; on the international YouTube domain (https://www.youtube.com); using the default “relevance” sorting filter; and without applying additional filters for upload date, duration, video type, or content category. The YouTube searches and URL recording were completed within a single day to reduce potential variability related to algorithmic updates and trending content. Because YouTube search results are influenced by relevance- and engagement-based ranking mechanisms, videos appearing in the initial search results were considered most likely to be encountered by users [11]. Therefore, the first 120 videos retrieved for each keyword were screened for eligibility to balance user relevance, methodological feasibility, and sample breadth, yielding a total of 360 videos for initial screening. To assess the robustness of this search-depth threshold, sensitivity analyses were performed by restricting the dataset to the first 50 and first 100 videos retrieved for each keyword; the detailed outputs of these analyses are provided in Supplementary Tables S1 and S2.

Eligibility criteria and screening

Initial eligibility screening was performed by the first reviewer (B.A.). To reduce the risk of selection bias, all exclusion decisions and exclusion reasons were subsequently verified by the second reviewer (M.A.). Any disagreement regarding eligibility was resolved through discussion until consensus was reached. Videos were included in the study if they were presented in the English language, appeared among the first 120 results for each predefined search keyword, and had a duration between 1 and 30 min. Of these, 239 videos were excluded for the following reasons: irrelevant content (n = 17); videos consisting solely of animation or music (n = 17); inadequate audio or visual quality, with a resolution below 240p (n = 5); non-English language (n = 4); video duration shorter than 1 min or longer than 30 min (n = 46); advertisement-only content (n = 29); duplicate videos (n = 106); patient experience–focused videos (n = 9); and academic lectures, seminars, webinars, and conference presentations (n = 6) [8]. Following the application of these criteria, 121 videos were included in the final analysis. Figure 1 illustrates the stepwise process used to identify and select eligible videos for analysis.

Fig. 1.

Video selection flow diagram

Data extraction and video characteristics

For each included video, duration (minutes), upload date, view count, number of likes, number of comments, channel subscriber count, and country of origin were recorded in accordance with the relevant literature [4]. Video metrics were extracted between January 4 and January 6, 2026. The number of days since upload and viewing rate were calculated based on the metric extraction date, with viewing rate defined as total views divided by days since upload × 100. Country of origin was determined using publicly available and verifiable channel- or video-related information, including channel location, institutional or clinic affiliation, video descriptions, visible location-specific information, and available metadata. No country was assigned solely on the basis of language, accent, presenter appearance, or reviewer inference; ambiguous cases were resolved by reviewer consensus.

Video classification

Given the broad spectrum of clinical applications of dental lasers, a stepwise evaluation framework was implemented. In the first phase, videos were categorized according to the predominant clinical application addressed, including soft tissue surgery, hard tissue procedures, endodontic applications, periodontal treatments, tooth whitening, and pain management or biostimulation [6, 12]. This classification ensured that each video was assessed within its relevant clinical context, accounting for the heterogeneity inherent to laser-based dental procedures.

Videos were then further classified according to upload source, target audience, and presenter’s gender [13]. The upload source was categorized as healthcare institutions (universities, hospitals, or clinics), dentists (general dentists or dental specialists), or commercial entities (dental manufacturing or dental supply companies). Regarding the target audience, videos were classified as intended for dentists, patients, or both [14]. Importantly, videos categorized as targeting “dentists” referred to practitioner-oriented YouTube content, such as clinical tips, technique demonstrations, or case discussions directed at general or specialist dental practitioners. These videos were distinct from academic lectures, seminars, webinars, and conference presentations excluded during the initial eligibility screening.

Presenter gender was recorded as an exploratory descriptive variable. Classification was based only on publicly observable and convergent presentation-related information within the video, including explicit self-introduction, pronouns used during the presentation, and channel-provided information when available. Presenters were classified as male or female only when these indicators were mutually consistent, and no attempt was made to infer personal gender identity beyond these public indicators.

Assessment tools

As no single validated instrument comprehensively captures all dimensions of online health information quality, a multidimensional assessment approach was adopted in this study. Each evaluation tool was selected to address a specific aspect of video quality, including clinical content accuracy (CQS), informational reliability (mDISCERN), educational value (GQS), audiovisual and technical quality (VIQI), transparency and credibility (JAMA), and ethical compliance (HONcode). This integrated approach aimed to provide a holistic and clinically meaningful evaluation of YouTube videos related to dental laser applications.

Subsequently, video content quality was assessed using a purpose-designed Content Quality Score (CQS). The CQS framework was developed through a structured process based on current clinical guidelines, authoritative textbooks, and recent review articles related to dental laser applications [5, 10]. The initial CQS items were generated to capture clinically relevant domains considered essential for safe and evidence-based use of dental lasers. The draft checklist was reviewed iteratively by the two study authors, both clinicians with experience in dental laser applications, and refined according to clinical relevance, conceptual independence, and applicability to YouTube-based educational content. The finalized nine-item CQS was pilot-tested during the calibration phase using 20 videos that were not included in the final analysis. During this phase, the operational definition of each item was discussed and refined to ensure consistent interpretation before independent evaluations began.

The final scoring system comprised nine criteria: definition and general purpose of dental lasers, laser–tissue interaction mechanisms, clinical indications, contraindications or limitations, procedural steps, advantages, disadvantages, complications or adverse effects, and laser-specific safety considerations, including protective measures (Table 1). Each criterion was scored dichotomously (1 = present, 0 = absent), resulting in a cumulative score ranging from 0 to 9. All CQS criteria were equally weighted to minimize subjectivity and enhance reproducibility. Based on cumulative CQS values, videos were classified as low (0–3), moderate (4–6), or high quality (7–9). As no validated cut-off values were available for dental laser–specific YouTube content, these thresholds were defined a priori by dividing the 9-point CQS range into three approximately equal interpretive categories. This criterion-referenced classification was used to reflect content completeness according to the predefined CQS items rather than the statistical distribution of the present sample. The CQS total score was defined as the primary outcome, and the CQS-based quality category was used as the primary categorical classification of video content quality. In addition to overall CQS reliability, item-level inter-rater agreement for individual CQS criteria was assessed using percentage agreement and Cohen’s kappa based on the two reviewers’ independent pre-consensus ratings.

Table 1.

Content Quality Score (CQS) criteria for dental laser–related videos

Criterion	Description	Score
Definition of dental lasers	Provides a clear definition of dental lasers and their general purpose in dentistry	0 / 1
Laser–tissue interaction mechanism	Explains how laser energy interacts with dental tissues and underlying mechanisms	0 / 1
Clinical indications	Describes appropriate clinical indications relevant to the identified application	0 / 1
Contraindications / limitations	Mentions situations where laser use is contraindicated or limited	0 / 1
Procedural steps	Describes clinical application steps or procedural workflow	0 / 1
Advantages	Explains advantages of laser use compared with conventional techniques	0 / 1
Disadvantages	Discusses disadvantages or limitations of laser use	0 / 1
Complications / adverse effects	Mentions possible complications or adverse effects	0 / 1
Safety considerations	Addresses laser-specific safety measures (e.g., protective eyewear, safety precautions)	0 / 1

The mDISCERN instrument was used to assess the reliability and trustworthiness of the information presented in the videos. The five-item version evaluates key aspects of informational reliability, including clarity, accuracy, balance, use of reliable sources, and discussion of uncertainty or limitations. Each item was scored dichotomously, yielding a total score of 0–5, with higher scores indicating greater reliability [15, 16].

The Global Quality Scale (GQS) was used to evaluate the overall educational quality, information flow, and usefulness of the videos from the viewer’s perspective. This five-point scale ranges from 1, indicating very poor quality and limited educational value, to 5, indicating excellent quality and high usefulness. Higher scores reflect better overall video quality [17, 18].

The Video Information and Quality Index (VIQI) was used to assess audiovisual and informational quality. It evaluates four domains: flow of information, accuracy, overall video quality, and consistency between the video title and content. Each domain was scored from 1 to 5, yielding a total score of 4–20, with higher scores indicating better audiovisual and informational quality [19].

The Journal of the American Medical Association (JAMA) benchmark criteria were used to assess reporting transparency based on authorship, attribution, disclosure, and currency, rather than direct clinical accuracy; each item was scored dichotomously, yielding a total score of 0–4 [20].

The Health On the Net Code (HONcode) was used to assess ethical and transparency-related compliance based on eight principles: authority, complementarity, confidentiality, attribution, justification, transparency, financial disclosure, and advertising policy. Each principle was scored dichotomously, yielding a total score of 0–8, with higher scores indicating better adherence to established ethical standards for online health information [21, 22].

Reviewer calibration and reliability assessment

Using these scoring instruments, a total of 121 videos included in the final analysis were evaluated by two reviewers: a pediatric dentist (B.A.) and an endodontist (M.A.), both experienced in dental laser applications. Prior to the formal evaluation, a calibration process was conducted in which 20 videos — not included in the final analysis — were jointly assessed by both reviewers to standardize the interpretation and application of each scoring criterion. During this calibration phase, any disagreement was resolved through discussion based on current clinical guidelines on dental lasers, recent peer-reviewed literature, and standard reference textbooks, and full consensus was reached on the operational definition of each scoring item before independent evaluations began [5, 6, 10, 23–25].

Due to the nature of publicly available YouTube content, complete blinding of reviewers to video characteristics such as channel source, view count, and subscriber numbers was not feasible. However, reviewers were instructed to base their evaluations solely on video content and to disregard popularity-related metrics.

Following calibration, the included videos were independently scored by both reviewers, and inter-rater reliability was assessed using the two reviewers’ independent pre-consensus scores. Intraclass correlation coefficients (ICCs) with 95% confidence intervals were calculated for each scoring system. A two-way random-effects model based on absolute agreement was applied, and single-measure ICCs are reported. ICC values were interpreted according to the criteria proposed by Koo and Li [26] as follows: <0.50 poor, 0.50–0.75 moderate, 0.75–0.90 good, and > 0.90 excellent reliability. Intra-rater reliability was additionally evaluated to assess the temporal consistency of each reviewer’s scoring. For this purpose, a randomly selected subset of 25 videos (approximately 20.7% of the total sample) was re-evaluated by each reviewer independently after a 4-week interval, under identical scoring conditions. Intra-rater ICCs were calculated separately for each reviewer and for each scoring system using a two-way mixed-effects model based on absolute agreement, with single-measure values reported. During the formal evaluation, any discrepancy between the two reviewers’ independent scores was resolved through joint discussion based on the same reference sources used during the calibration phase, and a final consensus score was assigned for each evaluation criterion.

Statistical analysis

Statistical analyses were performed using SPSS Statistics software (IBM Corp., Armonk, NY, USA). Descriptive statistics were presented as frequencies and percentages for categorical variables and as median (interquartile range), minimum, and maximum values for continuous variables because the data were non-normally distributed. Normality was assessed using the Shapiro–Wilk test. Comparisons among three or more independent groups were performed using the Kruskal–Wallis H test, followed by Bonferroni-corrected Mann–Whitney U tests when appropriate. Epsilon-squared (ε²) was calculated as the effect size for Kruskal–Wallis tests. Pearson’s chi-square test was used for categorical variables, and effect sizes were calculated using Cramer’s V. Associations between variables were assessed using Spearman’s rank correlation coefficient. The primary analyses focused on CQS-based quality classification and associations between CQS and established quality or reliability scores, whereas analyses involving video characteristics, engagement metrics, upload source, target audience, presenter gender, and clinical application categories were considered secondary exploratory analyses. To account for potential confounding in engagement-related findings, an exploratory multivariable linear regression model was constructed with CQS total score as the dependent variable; view count, likes, comments, viewing rate, video duration, days since upload, channel subscriber count, upload source, and target audience were entered as predictors. Skewed count variables were log-transformed using ln(x + 1). Overall intra- and inter-rater reliability were assessed using ICCs, while item-level inter-rater agreement for individual CQS criteria was assessed using percentage agreement and Cohen’s kappa. A p-value < 0.05 was considered statistically significant.

Results

A total of 360 YouTube videos were initially screened. After applying the predefined inclusion and exclusion criteria, 121 videos met the eligibility requirements and were included in the final analysis. Inter-rater ICC values indicated moderate to good agreement between the two reviewers across the six scoring systems, ranging from 0.739 for CQS to 0.855 for GQS. Intra-rater ICC values indicated moderate to excellent temporal consistency. For reviewer B.A., ICC values ranged from 0.657 to 1.000, while for reviewer M.A., they ranged from 0.624 to 1.000. Detailed ICC values with 95% confidence intervals are provided in Supplementary Table S3. Item-level inter-rater agreement values for individual CQS criteria are presented in Supplementary Table S4.

The descriptive statistics of video characteristics and assessment scores are summarized in Table 2. Video metrics showed markedly skewed distributions, particularly for view count, likes, comments, viewing rate, and channel subscriber count. Overall, the median CQS was 4, indicating a moderate level of content completeness according to the predefined CQS categories. The median mDISCERN score of 1 suggested low informational reliability, whereas the median GQS score of 3 indicated moderate overall educational quality. The median VIQI score of 14 suggested moderate audiovisual and informational quality, while the median JAMA and HONcode scores indicated limited reporting transparency and ethical compliance.

Table 2.

Descriptive statistics of video characteristics and assessment scores

Variable	Median (IQR)	Minimum	Maximum
View count	411 (69–3095)	5	295,608
Likes	2 (0–25)	0	2200
Viewing rate	20.77 (3.59–176.15)	0.23	9263.80
Number of comments	0 (0–1)	0	390
Video duration (min)	2 (1–3)	1	15
Days since upload	2246 (1616–3427)	22	6375
Channel subscriber count	295 (12–2160)	0	2,270,000
CQS	4 (3–5)	1	9
mDISCERN	1 (1–1)	1	5
JAMA	2 (2–2)	1	4
VIQI	14 (13–15)	10	19
HONcode	2 (2–3)	1	4
GQS	3 (3–4)	1	5

Values are presented as median (interquartile range), minimum, and maximum because the variables were non-normally distributed

CQS Content Quality Score, GQS Global Quality Scale, VIQI Video Information and Quality Index, JAMA Journal of the American Medical Association, HONcode Health On the Net Code

The United States was the most common country of origin (n = 88, 72.7%), followed by China (n = 18, 14.9%) and India (n = 6, 5.0%); the remaining videos originated from Canada, Australia, Bangladesh, and the United Kingdom. Regarding upload source, healthcare institutions accounted for the largest proportion of videos (n = 71, 58.7%), followed by commercial entities (n = 29, 24.0%) and dentists (n = 21, 17.4%). Patient-oriented videos constituted the largest target-audience group (n = 74, 61.2%), and male presenters were more common (n = 71, 58.7%) than female presenters (n = 50, 41.3%).

The most frequently addressed clinical applications were hard tissue procedures (n = 44, 36.4%), periodontal treatments (n = 39, 32.2%), and soft tissue surgery (n = 25, 20.7%), whereas endodontic applications (n = 6, 5.0%), pain management/biostimulation (n = 5, 4.1%), and tooth whitening (n = 2, 1.7%) were less frequently represented. Quality and reliability scores were also compared across the six clinical application categories. No statistically significant differences were observed among clinical application categories in terms of CQS, mDISCERN, JAMA, VIQI, or HONcode scores. Although GQS showed a statistically significant overall difference across clinical applications (H = 12.071; p = 0.034; ε² = 0.061), Bonferroni-corrected post hoc pairwise comparisons did not reveal any statistically significant differences. Detailed clinical application–based analyses are presented in Supplementary Tables S5 and S6.

Based on the CQS classification, most videos were categorized as moderate quality (n = 83; 68.6%), indicating partial coverage of the predefined dental laser content domains. Low-quality videos, reflecting limited content completeness, accounted for 33 videos (27.3%), whereas high-quality videos, representing comprehensive coverage of most CQS domains, were rare (n = 5; 4.1%). The distribution of individual CQS items is shown in Fig. 2. Clinical indications and advantages were the most frequently reported items, each present in 119 videos (98.3%), followed by the definition of dental lasers in 115 videos (95.0%). Laser–tissue interaction was addressed in 62 videos (51.2%), and procedural steps were described in 52 videos (43.0%). In contrast, safety considerations were mentioned in only 15 videos (12.4%), disadvantages or limitations in 11 videos (9.1%), contraindications or limitations in 5 videos (4.1%), and complications or adverse effects in 1 video (0.8%).

Fig. 2.

Distribution of individual Content Quality Score items

The distribution of categorical video characteristics according to CQS quality groups is presented in Table 3. No statistically significant associations were observed between CQS quality level and upload source (χ² = 8.11, p = 0.088) or target audience (χ² = 9.00, p = 0.061). In contrast, presenter gender demonstrated a statistically significant association with CQS quality groups (χ² = 7.84, p = 0.020), with a small-to-moderate effect size (Cramer’s V = 0.25). Videos presented by female presenters showed a higher proportion of moderate- and high-quality content compared with those presented by male presenters.

Table 3.

Distribution of categorical variables according to CQS quality groups

Parameter	Group	Low quality n (%)	Moderate quality n (%)	High quality n (%)	χ²	p; Cramer’s V
Upload source	Healthcare institution	25 (35.2)	42 (59.2)	4 (5.6)	8.11	0.088; 0.18
	Dentist	4 (19.0)	16 (76.2)	1 (4.8)
	Commercial	4 (13.8)	25 (86.2)	0 (0.0)
Target audience	Dentists	3 (9.7)	26 (83.9)	2 (6.4)	9.00	0.061; 0.19
	Patients	27 (36.5)	45 (60.8)	2 (2.7)
	Both	3 (18.8)	12 (75.0)	1 (6.2)
Presenter gender	Male	26 (36.6)	43 (60.6)	2 (2.8)	7.84	0.020; 0.25*
	Female	7 (14.0)	40 (80.0)	3 (6.0)

Values are presented as n (%). Row percentages are shown. χ²: Pearson chi-square test. Cramer’s V indicates effect size

*p < 0.05

Additional analyses were performed to evaluate the relationships between CQS, video characteristics, engagement metrics, and established assessment tools. In exploratory comparisons across CQS categories, several video-related and engagement metrics differed significantly, including view count, likes, comments, channel subscriber count, viewing rate, and video duration; detailed results are presented in Supplementary Table S7. Moderate-quality videos showed numerically higher median values for several engagement-related metrics, including likes, view count, comments, channel subscriber count, and viewing rate. However, significant post hoc differences were observed mainly between moderate- and low-quality videos, and this pattern should not be interpreted as indicating that higher engagement reflects higher content quality. CQS was positively associated with mDISCERN, VIQI, and GQS scores, whereas no significant association was observed with JAMA or HONcode scores; detailed results are presented in Supplementary Table S8. This pattern suggests that mDISCERN, VIQI, and GQS were more closely aligned with content completeness as measured by CQS, whereas JAMA and HONcode may reflect different dimensions of video quality, such as reporting transparency, source attribution, disclosure, and ethical compliance, rather than dental laser–specific content accuracy. In the exploratory multivariable linear regression model including engagement metrics and potential confounders, only video duration remained independently associated with CQS, while view count, likes, comments, viewing rate, and channel subscriber count were not independent predictors. The multivariable regression results are presented in Supplementary Table S9.

Discussion

The present study aimed to provide a comprehensive and multidimensional evaluation of YouTube videos addressing dental laser applications. The findings showed that most included videos were classified as moderate quality, whereas high-quality videos were rare. Overall assessment scores indicated limited content completeness, low informational reliability, and limited transparency or ethical compliance. Therefore, the initial null hypothesis that there would be no significant difference in the quality and reliability of dental laser–related YouTube videos was partially rejected. Significant associations were observed between CQS and several established assessment tools, including mDISCERN, VIQI, and GQS. In addition, presenter gender was associated with CQS quality categories, and video duration remained independently associated with CQS in the multivariable regression model. These findings suggest that the quality and reliability of dental laser–related YouTube content are variable and may be influenced by selected video-related and presentation-related factors, although these associations should be interpreted cautiously because of the exploratory and cross-sectional design of the study.

Dental lasers are utilized across multiple clinical domains in dentistry, including soft- and hard-tissue surgery, endodontic procedures, periodontal therapy, tooth whitening, biostimulation, and pain management. Because their safe and effective use requires accurate knowledge of laser–tissue interactions, parameter selection, clinical indications, and safety protocols, comprehensive and clinically accurate online information is particularly relevant for both clinicians and patients [12]. Previous YouTube-based evaluations of dental laser content have focused on specific clinical applications rather than the broader spectrum of clinical use. Tok and Ayranci [9] evaluated videos on laser use in root canal treatment and reported predominantly poor or very poor quality, with only 14% categorized as good quality. Similarly, Meseli et al. [27] evaluated videos on laser-assisted gummy smile surgery and reported generally low content quality. To the best of our knowledge, no previous study has comprehensively evaluated YouTube content on dental lasers across multiple clinical applications. Therefore, the existing YouTube-based literature on dental lasers remains application-specific [9, 27], and a comprehensive multidimensional evaluation across multiple dental laser applications, as undertaken in the present study, addresses an important gap in this body of work.

The analysis of videos based on their main clinical application revealed that hard tissue procedures (n = 44, 36.4%), periodontal treatments (n = 39, 32.2%), and soft tissue surgery (n = 25, 20.7%) were the most frequently represented categories, whereas endodontic applications (n = 6, 5.0%), pain management/biostimulation (n = 5, 4.1%), and tooth whitening (n = 2, 1.7%) were markedly underrepresented. This imbalance may reflect differences in clinical familiarity, technological accessibility, and the suitability of each procedure for video-based presentation. Periodontal, soft tissue, and hard tissue laser applications often involve visible procedural steps, hemostasis, tissue removal, or clinical before–after changes, making them more suitable for educational or demonstration-based YouTube content [5, 10, 23]. In contrast, endodontic laser applications are generally more technically complex and less visually intuitive because they occur primarily within the root canal system and require detailed explanation of wavelength-specific parameters, irrigation protocols, fiber placement, and safety considerations [24]. Tooth whitening was the least represented application, possibly because laser-assisted whitening is often presented in promotional rather than educational formats [25]. From a clinical perspective, this uneven distribution suggests that YouTube may not provide a balanced representation of the full scope of dental laser applications and may expose viewers more frequently to visually demonstrable procedures than to technically demanding applications requiring detailed explanation of indications, limitations, complications, and safety protocols. The gap in coverage also extended to emerging preventive approaches; although silver diamine fluoride has been evaluated as a YouTube topic [28], no video in the present sample specifically addressed its combined use with dental lasers, suggesting an opportunity for academic and professional contributors to produce evidence-based content on emerging preventive laser protocols.

In the present study, 68.6% of YouTube videos were classified as moderate quality, 27.3% as low quality, and only 4.1% as high quality. The predominance of moderate-quality videos suggests that most videos provided some basic information about dental lasers but failed to comprehensively address all clinically important domains. This pattern is also supported by the item-level CQS distribution: general and audience-friendly topics such as clinical indications and advantages were frequently mentioned, whereas safety considerations, contraindications or limitations, and complications or adverse effects were rarely addressed. Therefore, the scarcity of high-quality videos may reflect a tendency for YouTube content to emphasize easily understandable or promotional aspects of dental lasers while underrepresenting more technical and safety-related information required for comprehensive clinical education. Similar patterns of predominantly low-to-moderate quality and limited high-quality content have been reported in previous YouTube-based dental studies evaluating zygomatic implants, denture care, and root canal treatment in children [14, 29, 30]. Collectively, these findings indicate that dental-related content on YouTube is predominantly of low to moderate quality, whereas high-quality content remains scarce. Although YouTube serves as a widely accessible source of health information, it lacks standardized quality control mechanisms and demonstrates substantial variability in content reliability.

With respect to categorical variables across CQS quality groups, no statistically significant associations were identified between upload source or target audience and content quality classification (p > 0.05), suggesting that these structural characteristics alone may not sufficiently explain variations in content quality. In contrast, presenter gender was significantly associated with CQS quality categories (p = 0.020), with a small-to-moderate effect size (Cramer’s V = 0.25). Videos presented by female speakers were more frequently classified within the moderate-quality group. A comparable association between presenter gender and content score was reported by Isleyen and Aydemir in their evaluation of YouTube videos on labial frenectomy [13]. One possible explanation is that presenter gender may indirectly reflect differences in communication style, content organization, presentation detail, or production context rather than a direct effect of gender itself, which is consistent with previous health communication literature on physician–patient communication patterns [31]. However, the present finding may also have been influenced by unmeasured factors such as clinical topic, professional background, upload source, intended audience, or production quality. Therefore, this association should be regarded as exploratory and hypothesis-generating rather than as evidence of causality.

In exploratory analyses of video characteristics and engagement metrics, several engagement-related variables differed across CQS categories, including view count, likes, comments, channel subscriber count, viewing rate, and video duration (Supplementary Table S7). However, these findings should be interpreted cautiously because engagement metrics on YouTube are influenced by video age, channel size, audience, upload source, and platform exposure, which are not direct indicators of content quality. In the exploratory multivariable regression model, only video duration remained independently associated with CQS, whereas view count, likes, comments, viewing rate, and channel subscriber count were not independent predictors (Supplementary Table S9). This suggests that the apparent relationship between viewer engagement and content quality may be partly influenced by exposure-related and channel-level factors rather than content quality alone. From an interpretive perspective, the greater engagement observed for moderate-quality videos may reflect their tendency to combine basic clinical information with more accessible, less technically dense, and viewer-friendly presentation formats, whereas high-quality videos may include more detailed technical and safety-related content that is less immediately engaging for general viewers. Therefore, YouTube engagement may reflect accessibility, visibility, and audience appeal more than clinical completeness. Consistent with previous YouTube-based dental studies suggesting that longer videos may provide more detailed information and achieve higher quality scores [32, 33], the positive association between video duration and CQS in the present study may reflect the greater opportunity that longer videos provide to cover dental laser–related topics in more detail. However, this relationship should not be interpreted as evidence of a direct causal link between video duration and content quality.

The comparison of external quality assessment tools across CQS categories demonstrated statistically significant differences in mDISCERN, GQS, and VIQI scores, with higher scores generally observed in videos classified as higher quality according to CQS (p < 0.001). Specifically, videos categorized as high quality according to CQS exhibited significantly higher reliability (mDISCERN), overall educational quality (GQS), and audiovisual and informational quality (VIQI) scores compared with moderate- and low-quality groups. This pattern provides indirect support for the construct-related interpretability and discriminatory performance of the CQS classification within the present dataset, indicating that it aligns with established multidimensional quality evaluation instruments. In contrast, JAMA and HONcode scores did not differ significantly among CQS groups (p > 0.05). This pattern may be explained by the different constructs assessed by these instruments: CQS, mDISCERN, GQS, and VIQI primarily evaluate content-level features of the video, including clinical completeness, informational reliability, educational value, and audiovisual/informational quality, whereas JAMA and HONcode primarily assess source-level transparency and ethical reporting indicators, such as authorship, attribution, disclosure, and ethical compliance. Therefore, JAMA and HONcode should be interpreted as complementary indicators of transparency and ethical reporting standards rather than direct measures of dental laser–specific clinical accuracy.

Taken together, the results obtained from the different assessment tools indicate that the limitations of YouTube videos on dental lasers are multidimensional. The CQS findings showed that most videos provided only partial coverage of dental laser–specific clinical content, particularly because safety considerations, contraindications, and complications were rarely addressed. The low mDISCERN scores further suggested limited informational reliability, while the moderate GQS and VIQI scores indicated that some videos may appear educationally useful or technically acceptable despite incomplete clinical content. The JAMA and HONcode score distributions also indicated limited reporting transparency, source attribution, disclosure, and ethical compliance. Therefore, video quality should not be interpreted from a single perspective: a video may have acceptable audiovisual presentation or viewer-oriented educational flow but still lack clinical completeness, reliability, transparency, or ethical reporting standards. From a clinical perspective, incomplete or oversimplified dental laser videos may contribute to unrealistic treatment expectations, underestimation of contraindications and adverse effects, inappropriate self-directed treatment preferences, or delayed consultation with qualified dental professionals. This is particularly important for dental lasers because safe use depends on wavelength-specific parameters, tissue interaction principles, protective measures, and operator training. Given that most included videos were patient-oriented, YouTube should be regarded as a supplementary source of introductory information rather than as a basis for clinical decision-making. Dental laser use requires formal clinical training, wavelength- and device-specific parameter selection, adherence to professional guidelines, and manufacturer-specific safety protocols; therefore, online videos should not be considered substitutes for clinical education, professional judgment, or official safety instructions.

The present study has several strengths. To the best of our knowledge, it is the first study to comprehensively evaluate YouTube content on dental lasers across multiple clinical applications rather than focusing on a single procedure. The multidimensional assessment framework enabled evaluation of content accuracy, reliability, technical quality, and ethical standards. In addition, standardized search conditions, predefined eligibility criteria, reviewer calibration, independent scoring by two clinicians, and reliability analyses strengthened the methodological rigor and reproducibility of the study.

This study has several limitations. First, its cross-sectional design reflects YouTube content at a single time point, whereas video availability, engagement metrics, search rankings, and platform algorithms are dynamic and may change over time. Although search conditions were standardized to reduce personalization bias, results may still vary according to geographic location, user behavior, and algorithmic updates. Second, only English-language videos and broad dental laser–related search terms were included; therefore, non-English, region-specific, and procedure-specific content may not be fully represented, and specialized clinical videos may have been underrepresented. Third, although multiple assessment tools were used, some scoring systems involve subjective judgment despite calibration and reliability assessment. In addition, the CQS was a purpose-designed, guideline-informed checklist rather than a previously validated instrument; formal external content validation by an independent expert panel was not performed, and equal weighting of CQS items may not fully reflect the greater clinical importance of safety considerations, contraindications, and complications. Therefore, future studies should refine the CQS and test its external validity in independent dental laser–related video samples before it is applied more broadly. Fourth, although an exploratory multivariable regression model was used to adjust for selected exposure-related factors, residual confounding from unmeasured YouTube algorithmic recommendation patterns, viewer behavior, and temporal changes in platform visibility remains possible. Finally, presenter gender was classified using publicly observable information and treated only as an exploratory descriptive variable; moreover, due to the cross-sectional design, observed associations should be interpreted cautiously and not as evidence of causality.

Conclusions

This analysis reveals that YouTube content related to dental laser applications is largely characterized by limited depth and variable reliability, with only a small fraction of videos providing comprehensive and high-quality information. Although the platform offers wide accessibility, the educational value of the available material appears inconsistent. As dental laser technologies continue to expand across multiple clinical fields, the presence of well-structured, evidence-based, and professionally developed video resources becomes increasingly important. Improving the quality of online audiovisual materials may support patient education and informed discussions with dental professionals; however, such content should be used only as a supplementary resource and not as a substitute for evidence-based clinical training, professional guidelines, or manufacturer-specific safety protocols.

Abbreviations

CQS

Content Quality Score

GQS

Global Quality Scale

HONcode

Health on the Net Code

JAMA

Journal of the American Medical Association

mDISCERN

modified DISCERN

VIQI

Video Information and Quality Index

ICC

Intraclass correlation coefficient

SPSS

Statistical Package for the Social Sciences

Authors’ contributions

B.A.: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Writing –original draft. M.A.: Methodology, Validation, Investigation, Writing – review & editing. All authors read and approved the final manuscript.

Funding

This research received no funding.

Data availability

The datasets generated and analyzed during the current study are provided as Supplementary Datasets S1 and S2. Supplementary Dataset S1 includes screened video records, video URLs and IDs, search keywords, inclusion and exclusion coding, extracted video metrics, and video classification variables. Supplementary Dataset S2 includes clinical application categories, item-level CQS scores, total assessment scores, and final consensus scores.

Declarations

Ethics approval and consent to participate

Not applicable. No human or animal subjects were involved in this research. As the study relied exclusively on publicly available online data, ethical approval was not needed, and obtaining formal informed consent was not required.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.