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Despite the growing worries expressed by privacy supporters about the extensive adoption of gait biometrics, research in this field has been moving forward swiftly. Deep learning, a powerful technology that enables computers to learn from data, has found its way into criminal investigations involving gait. In this survey, the literature of gait analysis concerning criminal investigation is discussed with a comprehensive overview of developments in gait analysis with deep neural networks. Firstly, terminologies and factors regarding human gait with scenarios related to crime are discussed. Subsequently, the areas and domains corresponding to criminal investigation that can be tackled by gait analysis are discussed. Also, deep learning methods for gait analysis and how they can be applied in criminal investigations are presented. Then, gait analysis techniques and approaches using deep learning methods including currently available datasets are mentioned. Moreover, crime-related video datasets are presented with literature on deep learning-based anomaly detection with gait human poses. Finally, challenges regarding gait analysis in criminal investigations are presented with open research issues. [ABSTRACT FROM AUTHOR]

Previous research on children with cleft lip and palate (CLP) reported unequivocal findings with regard to language skills, with the majority suggesting persistent difficulties in early childhood. While expressive language deficits improved with age, receptive language skills were consistently lower than peers. Further study investigating the long term and persistent impact of language deficits amongst school-aged children with CLP is warranted. This was a cross-sectional study, aimed to determine the language abilities and explore the associated risk factors in Malay speaking children with CLP in Malaysia. Fifty-two children with CLP aged 7- to 12-year-old participated in this study. Language skills were assessed using the Malay Preschool Language Assessment Tool and the adapted Subway–School–age Language & Assessment Measures. Findings revealed that 14 (26.92%) school-aged children with CLP demonstrated language deficits. Children with CLP performed significantly poorer in reading comprehension (p = 0.031) and narrative (p = 0.026) skills. It was found that the age significantly influenced total receptive language score (β = 0.421, p = 0.003) and total expressive language score (β = 0.477, p = 0.000). Findings suggested that children with CLP may continue to have persistent language deficits into their school-age years. Recommendations for regular monitoring of language performance especially for those from younger age groups is warranted to help maximize school attainment. [ABSTRACT FROM AUTHOR]

Background: Self-management support has been recognized as one of the most essential elements of the Chronic Care Model (CCM). Inspired by the CCM, the EMPOWER-SUSTAIN Global Cardiovascular Risks Self-Management Booklet© was developed to aid and sustain self-management among patients with metabolic syndrome (MetS) in primary care to prevent cardiovascular complications. However, the usability of this booklet among these patients is not known. Therefore, this study aimed to evaluate the usability of this self-management booklet and identify the factors associated with its usability among patients with MetS in primary care. Methods: This cross-sectional study was conducted among patients with MetS attending a university primary care clinic in Selangor, Malaysia. The usability score was measured using a previously translated and validated EMPOWER-SUSTAIN Usability Questionnaire (E-SUQ) with a score of > 68 indicating good usability. Multiple logistic regressions determined the factors associated with its usability. Results: A total of 391 patients participated in this study. More than half (61.4%) had a good usability score of > 68, with a mean (± SD) usability score of 72.8 (± 16.1). Participants with high education levels [secondary education (AOR 2.46, 95% CI 1.04, 5.83) and tertiary education (AOR 2.49, 95% CI 1.04, 5.96)], those who used the booklet at home weekly (AOR 2.94, 95% CI 1.63, 5.33) or daily (AOR 2.73, 95% CI 1.09, 6.85), and those who had social support to use the booklet (AOR 1.64, 95% CI 1.02, 2.64) were significantly associated with good usability of the booklet. Conclusions: The usability of the EMPOWER-SUSTAIN Global Cardiovascular Risks Self-Management Booklet© was good among patients with MetS in this primary care clinic, which supports its widespread use as a patient empowerment tool. The findings of this study also suggest that it is vital to encourage daily or weekly use of this booklet at home, with the support of family members. The focus should also be given to those with lower education to improve the usability of this booklet for this group of patients. [ABSTRACT FROM AUTHOR]

Metabolic syndrome (MetS) generally occurs in adults and becomes more prevalent with age. Most e-health tools are often described as web-based platforms or applications designed for the general public, rather than specifically for MetS patients. Mobile applications, however, have great potential in providing internet-based health education and supporting the self-management of MetS patients, particularly in diet management and physical activity. This study aimed to consolidate the findings on the impact of mobile app interventions in enhancing self-management practices among MetS patients. A comprehensive literature search covering the years 2019 to 2023 was conducted across Science Direct, ProQuest, and PubMed databases. From 16,628 articles analyzed, 11 were selected for review. The interventions were categorized into short-term (> 12 months) and long-term (≥ 12 months). Eleven mobile applications were identified. These applications were primarily free and designed to facilitate the management of diet and physical activity. The study observed significant changes in the components of metabolic syndrome, including weight, blood pressure, waist circumference, body mass index, fasting blood sugar, triglycerides, and High-Density Lipoprotein cholesterol. Furthermore, these mobile applications demonstrated a positive impact on the lifestyle of MetS patients, influencing factors such as eating behavior, physical activity, self-efficacy, sleep quality, and sleep duration. [ABSTRACT FROM AUTHOR]

Introduction: Cardiovascular diseases (CVD) remain the world's leading cause of death. About half of Malaysian adults have at least 2 risk factors; thus, rigorous primary preventions are crucial to prevent the first cardiovascular (CV) event. This study aimed to determine the achievement of treatment targets and factors associated with it among high CV risk individuals. Methods: This cross-sectional study included 390 participants from a primary care clinic in Selangor, Malaysia, between February and June 2022. The inclusion criteria were high-CV risk individuals, that is, Framingham risk score >20%, diabetes without target organ damage, stage 3 kidney disease, and very high levels of low-density lipoprotein cholesterol (LDL-C) >4.9 mmol/L or blood pressure (BP) >180/110 mmHg. Individuals with existing CVD were excluded. The treatment targets were BP <140/90 mmHg (≤135/75 for diabetics), LDL-C <2.6 mmol/L, and HbA1c ≤6.5%. Multiple logistic regressions determined the association between sociodemographic, clinical characteristics, health literacy, and medication adherence with the achievements of each target. Results: About 7.2% achieved all treatment targets. Of these, 35.1% reached systolic and diastolic (46.7%) BP targets. About 60.2% and 28.2% achieved optimal LDL-C and HbA1c, respectively. Working participants had lower odds of having optimal systolic (aOR = 0.34, 95% CI: 0.13-0.90) and diastolic (aOR = 0.41, 95% CI: 0.17-0.96) BP. Those who adhered to treatments were more likely to achieve LDL-C and HbA1c targets; (aOR = 1.72, 95% CI: 1.10-2.69) and (aOR = 2.46, 95% CI: 1.25-4.83), respectively. Conclusions: The control of risk factors among high CV risk patients in this study was suboptimal. Urgent measures such as improving medication adherence are warranted. [ABSTRACT FROM AUTHOR]

Background: Fatigue significantly affects daily functioning in persons with disabilities. Fatigue management can be challenging, and the information provided during routine physician visits to manage fatigue can be overwhelming. One way to address fatigue is to increase knowledge, skills, and confidence for self-management (ie, patient activation). Self-management programs have shown promising effects in targeting fatigue in persons with disabilities. However, satisfaction with self-management programs is low for persons with disabilities, and tailoring interventions to personalized needs has been recommended. SMS text messaging is increasingly being used to implement health behavior change interventions in a person’s natural environment. Little has been done to link mobile health approaches with patient activation and self-management to address fatigue in persons with disabilities. Objective: This study aimed to develop and test a mobile phone–based fatigue self-management SMS text messaging intervention targeting patient activation in 3 groups of persons with disabilities: persons with multiple sclerosis, persons who had a stroke, and persons with a spinal cord injury. Methods: We used evidence-based resources and input from a consumer advisory board (CAB; composed of 2 participants from each of the 3 disability groups) and a neurologist to develop the intervention. The study was conducted using a 4-step process: development of the initial SMS text messaging library and categorization of the content into 9 content areas, review and modification of the SMS text messages by the neurologist and CAB, integration of the content library into a digital platform, and utility testing by CAB members. Results: A total of 6 CAB participants rated SMS text messages covering 9 domain areas of fatigue self-management with good clarity (mean ratings=3.5-5.0 out of 5) and relevance (mean ratings=3.2-5.0 out of 5). Overall, SMS text messaging content was reported by CAB participants as helpful, clear, and well suited for a mobile health intervention. The CAB reached consensus on the time of day that SMS text messages should be sent (morning) and their frequency (once per day). This feedback led the research team to narrow down the program to deliver 48 SMS text messages, 1 per day, Monday through Thursday only, a total of 4 SMS text messages per week, over a 12-week period. The final set of SMS text messages was programmed into a digital platform with a predefined delivery schedule. The usability of the intervention was high, with 55 (83%) out of 66 responses endorsing the highest rating. Conclusions: This study demonstrates a step-by-step process for developing a fatigue self-management SMS text messaging intervention for persons with disabilities. For this population, whose access to health services is often limited, this intervention provides an alternative delivery model to increase access to fatigue information and deliver content that aligns with the person’s needs. [ABSTRACT FROM AUTHOR]

A software development process comprises all the steps necessary to produce a software product. This research proposes a new process for developing augmented reality serious games (ARSGs), which comprises three phases: analysis, configuration, and generation. The analysis phase involves examining the standard project structure of a typical serious game to identify the applicable actions to which AR content can be added. The configuration phase involves configuring the AR features and the AR library to be integrated into the game structure. Finally, the generation phase entails inserting the AR code in the game structure, as well as all the files necessary to in-corporate AR features in the game. Our process allows generating ARSGs step by step, both easily and rapidly. To implement this process, we propose an ARSG development software architecture. The underlying assumption of this architecture is that software development tools are essential validation elements of the software generation process. By implementing our ARSG development process through a software architecture, we provide users with a formal, automated method for creating ARSGs. The ARSG development process and the architecture, collectively called ZeusAR, are not dependent on specific software development technologies and/or programming languages. To perform a proof-of-concept of our process, we developed an ARSG generator tool based on the proposed architecture and conducted a case study in which geometry ARSGs are developed to help high school students learn about geometric shapes and their properties. We conducted a qualitative evaluation of the ZeusAR tool through a System-Usability-Scale (SUS) based survey, which was administered to a group of geometry teachers to evaluate the tool's characteristics, such as ease of use and ease of configuration. Additionally, a group of software developers and professors assessed the performance of the ZeusAR tool in terms of game development time. [ABSTRACT FROM AUTHOR]