Objectives: The aim of this study was to evaluate the effects of wound healing using injectable platelet-rich fibrin (IPRF) after gingivectomy and gingivoplasty. Materials and methods: In this clinical study, 46 systemically healthy patients with chronic inflammatory gingival enlargement were randomly treated with gingivectomy-gingivoplasty + I-PRF (n=23) or gingivectomy-gingivoplasty alone (n=23). The primary outcome was to evaluate the effect of I-PRF on wound healing over a 3-week follow-up period. Samples collected from gingival crevicular fluid (GCF) were processed using enzyme-linked immunosorbent assay (ELİSA) to measure VEGF and FGF-10 biomarkers. The surgical areas were stained with Mira-2 tone and evaluated in ImageJ. Wound healing was evaluated with Modified Manchester Scar (MMS) scale and Landry, Turnbull, and Howley (LTH) index. Results: VEGF values of the control group at baseline, week 2, and week 3 were significantly higher than the test group. In weeks 2 and 3, FGF-10 values were found to be significantly higher in the control group than the test group. The amount of staining was found to be significantly higher in the control group than in the test group on days 3, 7, and 14. LTH values of the control group were significantly lower than the test group and MMS values were significantly higher than those of the test group. Conclusions: I-PRF applications revealed positive effects on epithelial wound healing after gingivectomy and gingivoplasty operations. Clinical relevance: Platelet concentrates such as I-PRF accelerate wound healing and contribute to the patient’s comfort and quality of life. I-PRF application may have positive effects on wound healing after gingivectomy and gingivoplasty operations.

Objective: This study aimed to develop a consensus-based set of patient questions on dental implant failure and to compare the clarity, quality, accuracy, reliability, and readability of responses generated by 4 widely used AI chatbots: ChatGPT-4, DeepSeek-R1, Microsoft Copilot, and Google Gemini. Methods: Twenty-three expert-validated questions were derived from the EAO 2021 and ICOI Pisa Consensus reports and independently submitted to each AI model under standardized, non-personalized conditions. Responses were assessed using CLEAR criteria, mGQS, a 5-point accuracy scale, the first 8 DISCERN items, and Flesch-based readability indices. Nonparametric tests were used for intermodel comparisons. Results: AI models demonstrated significant variability in performance. Gemini achieved the highest accuracy ( P <0.001), whereas ChatGPT-4 exhibited the highest reliability based on DISCERN scores. Copilot generated the most structurally fluent responses, whereas DeepSeek-R1 offered the best readability. Although CLEAR and mGQS scores were high across all systems, readability and linguistic complexity varied markedly. Accuracy, clarity, and reliability were strongly correlated, whereas readability displayed the expected inverse association with grade-level demand. Conclusions: AI chatbots hold potential as adjunct tools for patient education on implant failure; however, their performance characteristics differ substantially. Gemini excels in accuracy, ChatGPT-4 in reliability, Copilot in fluency, and DeepSeek-R1 in readability. Model-specific guidance and continued refinement are needed to enhance the clinical usefulness and accessibility of AI-generated patient information.

Background This study aims to evaluate the quality, reliability, and content of the information provided in YouTubeTM videos on necrotizing gingivitis (NG), demonstrate the effectiveness of the videos for patients, and help dentists use this platform as a resource to properly guide their patients. Methodology This cross-sectional study was conducted by two experienced periodontologists. They began the study by searching for YouTubeTM videos using the keywords "necrotizing gingivitis" and "trench mouth." Descriptive parameters such as the source of upload, country of origin, duration, upload date, number of likes, dislikes, views, and comments were evaluated. After this initial evaluation, the viewing rate and interaction index were calculated. Videos were categorized into high content (HC) and low content (LC) based on a 7 -point scale. The quality of video content was assessed using the Global Quality Scale (GQS) and the Video Information and Quality Index (VIQI). The data were analyzed using various statistical tests, with a significance level set at p<0.05. Results Initially, 148 videos were screened, and 50 videos on NG that met the inclusion criteria were included in the study. Out of the 50 videos, 28 (56%) were uploaded by healthcare professionals. Overall, 68% of videos (n=34) were classified as HC and 32% (n=16) as LC. The most common topic was clinical symptoms and signs of NG, with 86% (n=43), while NG prevention was the least common topic, with 26% (n=13). Statistically significant differences were found between video duration, time since upload, and VIQI scores according to TCS scores (p<0.05). Video duration and VIQI scores were higher for HC videos compared to LC videos. The time since upload for LC videos was higher than for HC videos. Positive correlations were observed between TCS scores, video duration, and VIQI, as well as between GQS scores, video duration, viewing rate, and VIQI. Conclusions The majority of NG videos on YouTubeTM are useful and comprehensive, but their number is insufficient. Poor -quality and inadequate videos may mislead practitioners and patients. However, this also presents an opportunity for healthcare professionals to leverage YouTubeTM as an educational tool. Periodontologists should upload more comprehensive videos and play a more active role in providing high -quality information.

Background This study aimed to assess the reliability, quality, and content of the information provided by YouTubeTM videos on oral health during pregnancy to reveal the effectiveness of the videos for patients. Methodology This cross-sectional study was conducted by two experienced dental specialists. They initiated the study by searching for YouTubeTM videos using the keyword 'pregnancy oral health'. The videos were then assessed based on various parameters, including origin, type, number of days since upload, duration, number of views, number of likes and dislikes, and number of comments. The specialists also calculated the interaction index and viewing rate. The reliability and quality of the videos were evaluated using the global quality scale (GQS) and modified DISCERN (mDISCERN) scales, while the content was assessed with the comprehensiveness tailor-made index. The data were analyzed with the Shapiro -Wilk, the Kruskal-Wallis, the post -hoc Bonferroni, and Fisher's exact tests. The significance level was set at P < 0.05. Results After reviewing initially 224 videos, 129 were included in the study. Health professionals were the publishers of most videos. A statistically significant positive correlation was found between content scores and video duration, number of comments, interaction index, and total DISCERN scores (p<0.05) (r=0.445, r=0.186, r=0.552, r=0.241, r=0.200, r=0.681, respectively). Statistically significant associations were found between GQS scores, video duration, number of comments, and total mDISCERN scores (p<0.05) (r=0.510, r=225, r=0.156, r=0.768, respectively). Statistically significant relationships were identified between the total content score, video source, and GQS (p<0.05). According to the total content score, 57.4% of the videos had a score of 2, 35.7% had a score of 1, and only 7% had a score of 0. Conclusions This study's findings underscore the significant variability in the scientific accuracy, content, and quality of health information on the Internet, particularly on YouTubeTM. It reveals that, while there are videos that provide rich content and high -quality information, there are also poor -quality and inadequate videos that may mislead patients. Health professionals should be aware of misinformation found on YouTubeTM and ensure that patients always have access to accurate and reliable information.

This cross-sectional study aimed to develop a measurement tool to assess dental health workers’ attitudes towards patient safety. The candidate items for the questionnaire were developed and assessed for content validity by an expert panel. The reliability and validity of the Patient Safety Attitude Scale were examined by administering the finalized items to a sample of 312 dental healthcare professionals in Province Ankara. Participation was voluntary, and data were collected via the SurveyMonkey web platform. SPSS 26 and AMOS 24 were used for reliability and validity analysis. The study found that most dental healthcare workers, with a mean age of 30.4 years and 74.4% female, reported moderate to high workloads, while only 7.1% had a light workload. Among them, 41% had received patient safety training, and 54.8% had witnessed a medical error. Factor analysis identified two factors: ‘risk management’ and ‘ethical attitude,’ together explaining 53.09% of the variance. The Cronbach’s alpha value for the overall scale was 0.911, with ‘risk management’ (CA = 0.896) and ‘ethical attitude’ (CA = 0.692) demonstrating adequate internal consistency. A weak positive correlation was observed between patient safety attitudes and ethical knowledge, with higher safety scores among women and trained participants. This study develops and validates a Patient Safety Attitude Scale in Dentistry Practices that can be used.