Impact of income and financial subsidies on oral health care utilization among persons with disabilities in Singapore.

BACKGROUND/AIM(S): Globally, studies have shown that the dental disease burden among persons with intellectual and/or developmental disabilities (IDD) is high and can be attributed to lower utilization levels of dental services. The aim of the study was to assess the influence of income and financial subsidies on the utilization of dental care services among persons with IDD in Singapore. METHODS: Between August 2020 and August 2021, a cross-sectional study was conducted via centres offering Early Intervention Programme for Infants and Children, special education schools and adult associations in Singapore serving persons with IDD. A sample of 591 caregivers of children and adults with IDD completed the survey. Data on sociodemographic information, oral health behaviours and dental utilization were collected. Financial subsidy status was assessed by the uptake of a government-funded, opt-in Community Health Assist Scheme (CHAS) for low-income families that provided a fixed subsidy amount for dental services in the primary care setting. Statistical analysis was carried out using univariable, multiple logistic regression and modified Poisson regression. Propensity score matching was carried out in R version 4.0.2 to assess the impact of financial subsidies on oral health care utilization among persons with IDD. RESULTS: Compared to those with lower gross monthly household incomes, the adjusted prevalence ratios of having at least one dental visit in the past year, having at least one preventive dental visit in the past year, and visiting the dentist at least once a year for persons with IDD with gross monthly household incomes of above SGD$4000 were 1.28 (95% CI 1.08-1.52), 1.48 (95% CI 1.14-1.92) and 1.36 (95% CI 1.09-1.70), respectively. Among those who were eligible for CHAS Blue subsidies (247 participants), 160 (62.0%) took up the CHAS Blue scheme and 96 (35.4%) visited the dentist at least yearly. There was no statistically significant difference in the utilization of dental services among individuals enrolled in the CHAS Blue subsidy scheme among those eligible for CHAS Blue subsidies. CONCLUSION: Higher household income was associated with a higher prevalence of dental visits in the past year, preventive dental visits in the past year, and at least yearly dental visits. CHAS Blue subsidies alone had limited impact on dental utilization among persons with IDD who were eligible for subsidies.

Development of a dental diet-tracking mobile app for improved caries-related dietary behaviours: Key features and pilot evaluation of quality.

Objective: Diet significantly contributes to dental decay (caries) yet monitoring and modifying patients' diets is a challenge for many dental practitioners. While many oral health and diet-tracking mHealth apps are available, few focus on the dietary risk factors for caries. This study aims to present the development and key features of a dental-specific mobile app for diet monitoring and dietary behaviour change to prevent caries, and pilot data from initial user evaluation. Methods: A mobile app incorporating a novel photo recognition algorithm and a localised database of 208,718 images for food item identification was developed. The design and development process were iterative and incorporated several behaviour change techniques commonly used in mHealth. Pilot evaluation of app quality was assessed using the end-user version of the Mobile Application Rating Scale (uMARS). Results: User feedback from the beta-testing of the prototype app spurred the improvement of the photo recognition algorithm and addition of more user-centric features. Other key features of the final app include real-time prompts to drive actionable behaviour change, goal setting, comprehensive oral health education modules, and visual metrics for caries-related dietary factors (sugar intake, meal frequency, etc.). The final app scored an overall mean (standard deviation) of 3.6 (0.5) out of 5 on the uMARS scale. Conclusion: We developed a novel diet-tracking mobile app tailored for oral health, addressing a gap in the mHealth landscape. Pilot user evaluations indicated good app quality, suggesting its potential as a useful clinical tool for dentists and empowering patients for self-monitoring and behavioural management.

Microbial biomarkers as a predictor of periodontal treatment response: A systematic review.

To evaluate the prognostic accuracy of microbial biomarkers and their associations with the response to active periodontal treatment (APT) and supportive periodontal therapy (SPT). Microbial dysbiosis plays a crucial role in the disease processes of periodontitis. Biomarkers based on microbial composition may offer additional prognostic value, supplementing the limitations of current clinical parameters. While these microbial biomarkers have been clinically evaluated, there is a lack of consensus regarding their prognostic accuracy. A structured search strategy was applied to MEDLINE (PubMed), Cochrane Library, and Embase on 1/11/2022 to identify relevant publications. Prospective clinical studies involving either APT or SPT, with at least 3-month follow-up were included. There were no restrictions on the type of microbial compositional analysis. 1918 unique records were retrieved, and 13 studies (comprising 943 adult patients) were included. Heterogeneity of the studies precluded a meta-analysis, and none of the included studies had performed the sequence analysis of the periodontal microbiome. Seven and six studies reported on response to APT and SPT, respectively. The prognostic accuracy of the microbial biomarkers for APT and SPT was examined in only two and four studies, respectively. Microbial biomarkers had limited predictive accuracy for APT and inconsistent associations for different species across studies. For SPT, elevated abundance of periodontal pathogens at the start of SPT was predictive of subsequent periodontal progression. Similarly, persistent high pathogen loads were consistently associated with progressive periodontitis, defined as an increased pocket probing depth or clinical attachment loss. While there was insufficient evidence to support the clinical use of microbial biomarkers as prognostic tools for active periodontal treatment outcomes, biomarkers that quantify periodontal pathogen loads may offer prognostic value for predicting progressive periodontitis in the subsequent supportive periodontal therapy phase. Additional research will be required to translate information regarding subgingival biofilm composition and phenotype into clinically relevant prognostic tools.

Contemporary English Pain Descriptors as Detected on Social Media Using Artificial Intelligence and Emotion Analytics Algorithms: Cross-sectional Study.

BACKGROUND: Pain description is fundamental to health care. The McGill Pain Questionnaire (MPQ) has been validated as a tool for the multidimensional measurement of pain; however, its use relies heavily on language proficiency. Although the MPQ has remained unchanged since its inception, the English language has evolved significantly since then. The advent of the internet and social media has allowed for the generation of a staggering amount of publicly available data, allowing linguistic analysis at a scale never seen before. OBJECTIVE: The aim of this study is to use social media data to examine the relevance of pain descriptors from the existing MPQ, identify novel contemporary English descriptors for pain among users of social media, and suggest a modification for a new MPQ for future validation and testing. METHODS: All posts from social media platforms from January 1, 2019, to December 31, 2019, were extracted. Artificial intelligence and emotion analytics algorithms (Crystalace and CrystalFeel) were used to measure the emotional properties of the text, including sarcasm, anger, fear, sadness, joy, and valence. Word2Vec was used to identify new pain descriptors associated with the original descriptors from the MPQ. Analysis of count and pain intensity formed the basis for proposing new pain descriptors and determining the order of pain descriptors within each subclass. RESULTS: A total of 118 new associated words were found via Word2Vec. Of these 118 words, 49 (41.5%) words had a count of at least 110, which corresponded to the count of the bottom 10% (8/78) of the original MPQ pain descriptors. The count and intensity of pain descriptors were used to formulate the inclusion criteria for a new pain questionnaire. For the suggested new pain questionnaire, 11 existing pain descriptors were removed, 13 new descriptors were added to existing subclasses, and a new Psychological subclass comprising 9 descriptors was added. CONCLUSIONS: This study presents a novel methodology using social media data to identify new pain descriptors and can be repeated at regular intervals to ensure the relevance of pain questionnaires. The original MPQ contains several potentially outdated pain descriptors and is inadequate for reporting the psychological aspects of pain. Further research is needed to examine the reliability and validity of the revised MPQ.