Temple College

ABSTRACTAimTo examine whether the oral microbiota of e‐cigarette users differs from that of never smokers and current smokers.Materials and MethodsPubMed, Scopus and Web of Science were searched on 27 August 2025. Human studies using molecular methods to compare oral microbiota in saliva, subgingival plaque and oral mucosal swabs among e‐cigarette users, never smokers and current smokers were included. Primary outcomes were alpha diversity, beta diversity and differential taxonomic abundance. Risk of bias was assessed using JBI tools and certainty of evidence using GRADE.ResultsTwelve studies were included; most were cross‐sectional and heterogeneous in design, exposure and samples. Alpha diversity findings were inconsistent across samples, whereas beta diversity more consistently indicated distinct microbial communities in e‐cigarette users compared with never smokers and current smokers. Taxonomic differences were heterogeneous and sample‐dependent, with some enrichment of genera such as Veillonella, Leptotrichia, and Fusobacterium compared with never smokers.ConclusionsElectronic cigarette use is associated with sample‐specific oral microbiota differences that partly overlap with, but differ from, those observed in never smokers and current smokers. However, the certainty of evidence is very low due to predominantly cross‐sectional designs and methodological limitations, underscoring the need for longitudinal studies with standardised exposure and protocols.

Parents of children on the autism spectrum face challenging treatment-related decisions, often with limited knowledge about available options. Shared Decision Making (SDM), a process where clinicians, patients, and families collaborate to make decisions based on evidence and preferences, can assist parents in navigating these choices. However, little is known about the use of SDM interventions for autism-related parental decisions. A systematic and scoping review was conducted across four databases (PubMed, Embase, Web of Science, and PsycInfo), and grey literature in two clinical trial registries. Study selection was conducted in two phases: title and abstract screening and full-text screening. From 7,610 records identified, two studies were included from Australia and Italy, describing multicomponent SDM interventions for parents of young children (< 18 years) on the autism spectrum. Both interventions demonstrated improvements in SDM-related outcomes, including parents' knowledge of autism treatments (such as speech pathology services and Early Intensive Behavior Intervention) and parents' involvement in treatment discussions. This review reveals a critical gap in SDM intervention research for autism parental decision-making. Despite the critical role parents play in autism treatment decisions, evidence-based SDM interventions remain scarce. This finding is significant given the well-established benefits of SDM in other healthcare populations and underscores the urgent need to develop and rigorously evaluate SDM interventions tailored to autism care contexts that support parents in making informed decisions about their children's care.Systematic review registration: A protocol was registered on PROSPERO.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive and fatal neurological disease that leads to death within 2-5 years of diagnosis for more than 80% of people living with ALS (PLWALS). The American Academy of Neurology (AAN) developed practice parameters-general principles to guide clinicians in managing ALS-encouraging multidisciplinary care (MDC) but does not recommend specific healthcare delivery models. Three healthcare delivery models have evolved: a traditional model, a triage model, and a non-triage model. This study aims to describe preferences for and satisfaction with various models, among PLWALS and their caregivers (CALS), along with their perceptions of how their care aligns with AAN guidelines. A cross-sectional observational study utilizing a web-based survey was distributed via email to PLWALS and CALS. Three multi-assessment questionnaires were developed and tailored for PLWALS, CALS, and former CALS. Best-worst scaling (object case) data were analyzed using a best-minus-worst approach and descriptive statistics were calculated from means, t-tests and chi-square. The combined sample included 378 respondents: 254 PLWALS (67.20%) and 124 CALS (32.80%; composed of 79 current caregivers [20.90%] and 45 former caregivers [11.90%]). The mean respondent age was 61.09 years (SD 11.1). The majority of the sample was white (92.86%), insured by Medicare (61.11%), and married/partnered (79.10%). Respondents preferred a non-triage model the most and a traditional model the least; 88.20% (CI: 84.92-91.49) were extremely likely to choose a non-triage model if given the choice and 83.12% (CI: 79.29-86.92) of respondents ranked non-triage as most preferred. A traditional model was ranked as the least preferred model in 75.28% (CI: 70.78-79.78) of respondents. The most important factors driving respondent preferences were ALS expertise and team-based care. Overall, respondents are satisfied with their care teams. PLWALS utilizing non-triage MDC models reported more adherence to quality care measures compared with those utilizing triage and traditional models. Respondent preference for non-triage models is consistent with the importance they place on the features of non-triage models. However, these findings should be understood in the context of our sample in which a large majority of respondents were receiving care via a non-triage model. To ensure ALS care delivery is patient-centered, practice parameters that aim to guide clinicians in managing ALS should provide more guidance to MDCs to deliver care aligned with patient preferences and values. Efforts should focus on sustainable financial models that can better facilitate non-triage models of care.

Sign Language Recognition (SLR) systems have gained significant popularity in recent years. Despite the existence of various Deep Learning (DL) models to classify sign languages, the deployment of these models on resource-constrained devices remains a challenge. Majority of the research on SLR focuses on popular sign languages, such as American Sign Language (ASL), German Sign Language (GSL) etc., while Kannada Sign Language (KSL) remains significantly underexplored. This study focuses on creating a word-level custom dataset of 33 classes consisting of 2319 videos and training three DL models, namely, LSTM, BiLSTM, and Encoder-only Transformer for dynamic KSL recognition. Trained models were then optimized with quantization techniques and converted to .tflite format, for efficient deployment on resource-constrained devices like smartphones. Dynamic Post Training Quantization (PTQ) model, for the BiLSTM model achieved the highest accuracy of 95.71%, followed by the LSTM model with 94.7%, and the Transformer-based architecture achieved 94.19%. Transformer model deployed on smartphone achieved the smallest inference time of 16.2 ms with a model size of 1097.77 KB, followed by LSTM recording 19.6 ms as inference time with a model size of 1254.49 KB and BiLSTM recording the highest inference time of 27.8 ms with a model size of 3862.01 KB.

Pursuing compassionate goals (i.e., seeking to improve others' well-being) has generally been linked with positive emotional and relational well-being, whereas self-image goals (i.e., striving to maintain or enhance how one is perceived by others) tend to be associated with poorer well-being. However, limited research has examined these goals in the context of parenting. In this 9-day daily experience study (N = 270), we investigated whether compassionate and self-image goals in relation to children were associated with parental well-being, parenting, and child adjustment. We also tested whether empathic and negative emotions mediate these associations. Results showed that parents who pursued compassionate goals reported more optimal well-being (e.g., greater positive emotions, lower stress) and more positive parenting and child adjustment (e.g., more supportive parenting, fewer negative child behaviors) both overall and across the week, in part due to their association with greater empathic emotions and lower negative emotions. Conversely, self-image goals were largely unrelated to well-being, parenting, and child adjustment. These findings suggest that parents' efforts to support their children's well-being are associated with their own well-being, parenting, and child adjustment. (PsycInfo Database Record (c) 2026 APA, all rights reserved).