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Ebaa Al Ozairi,1,2 Husain AlSaraf,1,3 Abdullah Al-Ozairi,1,2 Yasmine Hamdan,1 Batool Camille Al Esmaeel,1 Dalal Alsaeed,1 Mohamed Abdalla,1 Stuart R Gray4 1Clinical Research Unit, Dasman Diabetes Institute, Kuwait City, Kuwait; 2Department of Medicine, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait; 3Geriatrics and Neuropsychiatry Unit, Amiri Hospital, Kuwait City, Kuwait; 4School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UKCorrespondence: Stuart R Gray, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK, Tel +141 330 2569, Email stuart.gray@glasgow.ac.ukPurpose: The aim of this cross-sectional study was to compare the Arabic version of International Physical Activity Questionnaire (IPAQ) measured moderate-to-vigorous physical activity (MVPA) with accelerometer-measured MVPA in people with diabetes.Methods: From 2020 to 2022 physical activity was measured people ≥ 18 years with type 1 or type 2 diabetes in Kuwait. Self-reported MVPA was measured over 7 days with the Arabic version of the IPAQ. During the same 7-day period wrist worn accelerometers were used to objectively measure MVPA. IPAQ MVPA was calculated both including and excluding walking physical activity. MVPA measures were compared by limits of agreement approach, Pearson correlations and concordance correlations.Results: We recruited 240 participants with type 1 diabetes and 343 participants with type 2 diabetes for the study. In people with type 1 diabetes, there were no concordance correlations between IPAQ MVPA, both including (rho = − 0.011 (− 0.038, 0.017), p = 0.444) and excluding (rho = − 0.001 (− 0.067, 0.065), p = 0.978) walking physical activity. MVPA measured by IPAQ was 43.3(− 85.6, 172.2) min/day higher than accelerometer-measured MVPA, when including walking, and 8.88(− 60.4, 78.2) min/day higher, when excluding walking. In people with type 2 diabetes, there were significant positive concordance correlations between IPAQ MVPA, both including (rho = 0.038 (0.02, 0.06), p < 0.001) and excluding (rho = 0.34 (0.27, 0.41), p < 0.001) walking physical activity. MVPA measured by IPAQ was 62.3 (95% CI − 61.5 to 186.0) min/day higher than accelerometer-measured MVPA, when including walking, and 4.0 (95% CI − 34.1 to 42.0) min/day higher, when excluding walking.Conclusion: In people with type 1 or type 2 diabetes, caution should be exercised when using the Arabic version of the IPAQ to measure MVPA.Keywords: metabolic disease, activity, Arab, validation

Background/Objectives: Early and accurate diagnosis of skin cancer improves survival rates; however, dermatologists often struggle with lesion detection due to similar pigmentation. Deep learning and transfer learning models have shown promise in diagnosing skin cancers through image processing. Integrating attention mechanisms (AMs) with deep learning has further enhanced the accuracy of medical image classification. While significant progress has been made, further research is needed to improve the detection accuracy. Previous studies have not explored the integration of attention mechanisms with the pre-trained Xception transfer learning model for binary classification of skin cancer. This study aims to investigate the impact of various attention mechanisms on the Xception model's performance in detecting benign and malignant skin lesions. Methods: We conducted four experiments on the HAM10000 dataset. Three models integrated self-attention (SL), hard attention (HD), and soft attention (SF) mechanisms, while the fourth model used the standard Xception without attention mechanisms. Each mechanism analyzed features from the Xception model uniquely: self-attention examined the input relationships, hard-attention selected elements sparsely, and soft-attention distributed the focus probabilistically. Results: Integrating AMs into the Xception architecture effectively enhanced its performance. The accuracy of the Xception alone was 91.05%. With AMs, the accuracy increased to 94.11% using self-attention, 93.29% with soft attention, and 92.97% with hard attention. Moreover, the proposed models outperformed previous studies in terms of the recall metrics, which are crucial for medical investigations. Conclusions: These findings suggest that AMs can enhance performance in relation to complex medical imaging tasks, potentially supporting earlier diagnosis and improving treatment outcomes.

Objective: Obesity and many of its comorbidities can be improved by nutritional therapy, lifestyle modification, pharmacotherapy, and surgical intervention. Relatively little is known about patients' preferences for the range of obesity treatments. The present study was undertaken to identify factors that may influence these preferences. By evaluating patient-preferred treatment options and factors influencing patients, treatment adherence and efficacy may be improved. Our objective was to identify factors that influence patient preferences and subsequent choice of obesity treatment among those seeking treatment for obesity-related complications., Methods: Participatory action research, using purposeful sampling, was used to recruit 33 patients with obesity complications. Recruitment took place in specialist clinics for non-alcoholic fatty liver disease, diabetes, hypertension, and chronic kidney disease. Sixteen males and 17 females aged 18-70 years with a BMI>35 kg/m 2 were recruited. Prior to the interview, participants watched a 60-min video explaining nutritional therapies, pharmacotherapies, and surgical therapies in equipoise. Data were collected in one-to-one semi-structured interviews using zoom or the telephone; reflective thematic analysis was used., Results: Four themes emerged: 1) structural factors, 2) autonomy, 3) interaction with formal care, and 4) the emotional and physical consequences of obesity. 39% of participants preferred nutritional therapy with support from medical professionals. 27% chose bariatric surgery. 24% chose pharmacotherapy alone, while 6% chose pharmacotherapy combined with nutritional therapy, 3% of participants wanted no intervention., Conclusion: The challenges can be addressed by increasing support for healthcare professionals toward enhancing both their knowledge and the health literacy of patients. Future research should focus on improving access to treatment pathways for patients as well as developing health literacy programs and educational programs for healthcare professionals., Competing Interests: Hilary C. Craig, Part funding of PhD tuition fees from the Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy (SOPHIA) project (www.imisophia.eu). Dalal Alsaeed—no conflict of interest. Suzanne Norris—no conflict of interest. John Holian—no conflict of interest. Cormac Kennedy—no conflict of interest. Alix Feldman—employed by Novo Nordisk. Carel W. le Roux: Consulting fees/Honoria/Support for meetings: NovoNordisk, Eli Lilly, Johnson & Johnson, Boehringer Ingelheim, GI Dynamics, Herbalife. Leadership/fiduciary role in Board: Irish Society for Nutrition and Metabolism (unpaid). Stock Options: Keyron Previous Chief medical officer and Director of the Medical Device Division of Keyron in 2011. Both of these were unremunerated positions. Previous investor in Keyron, which develops endoscopically implantable medical devices intended to mimic the surgical procedures of sleeve gastrectomy and gastric bypass. He continues to provide scientific advice to Keyron for no remuneration., (© 2023 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.)

Aims: To evaluate the effects of pragmatic home-based resistance exercise training on glycated haemoglobin (HbA1c) as well as muscle strength and body composition in people with type 2 diabetes., Materials and Methods: People with type 2 diabetes were randomized (1:1) to usual care or usual care plus home-based resistance exercise for 32 weeks. The changes in HbA1c, body composition, physical function, quality of life, continuous glucose monitoring and liver fat were compared by randomized group using linear regression., Results: This study recruited 120 participants (female: n = 46 [38%], age 60.2 (9.4) years, BMI 31.1 (5.4) kg.m -2 ), 64 to intervention and 56 to usual care. Intention to treat analysis revealed no effect on HbA1c (difference in difference: -0.4 mmol/mol, 95% confidence interval [CI]: -3.26, 2.47; p = 0.78) but the intervention increased the number of push-ups (3.6 push-ups, 95% CI: 0.8, 6.4), arm lean mass (116 g, 95% CI: 6, 227) and leg lean mass (438 g, 95% CI 65, 810) and decreased liver fat (-1.27%, 95% CI -2.17, -0.38), with no differences in other outcomes. Per-protocol analysis revealed similar results., Conclusions: Home-based resistance exercise is unlikely to lower HbA1c in people with type 2 diabetes but may be of benefit for maintaining muscle mass and function and reducing liver fat., (© 2023 The Authors. Diabetes/Metabolism Research and Reviews published by John Wiley & Sons Ltd.)

Background: The mental health and wellbeing of people watching the Corona Virus Disease 2019 (COVID-19) pandemic unfold has been discussed widely, with many experiencing feelings of anxiety and depression. The state of mental health of medical staff on the frontlines providing care should be examined; medical staff are overworked to meet the demands of providing care to the rise in cases and deterioration in capacity to meet demands, and this has put them under great psychological pressure. This may lead to an increase in medical errors, affect quality of care, and reduce staff retention rates. Understanding the impact the pandemic has had on healthcare professionals is needed to provide recommendations to prepare for future crises., Objectives: To be able to meet the needs of the medical workforce on the frontlines and inform psychological support interventions and strategies for future pandemics, we aim to identify and explore the psychological impact of COVID-19 in Kuwait on healthcare professionals in close contact with patients., Methods: Using semi-structured interviews, we conducted interviews between February and July 2021 with 20 healthcare professionals across Ministry of Health hospitals who were part of COVID teams. Interviews were transcribed verbatim, and analysis was conducted using principles of thematic framework analysis., Results: Three themes emerged to help prepare future healthcare frontline workers on an individual, organizational, and national level: enhance self-resilience, a better-equipped workforce and healthcare environment, and mitigate stigma and increase public awareness., Conclusion: The results have assisted in highlighting areas of improvement to support the healthcare workforce in the current environment, as well as better prepare them for future pandemics. The findings have also provided insight to recommend targeted interventions. These should improve the psychological wellbeing and help in supporting healthcare professionals to reduce burnout, continue effective care of patients, and enhance resilience., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Alsaeed, Al-Ozairi, Alsarraf, Albarrak and Al Ozairi.)

Background: The outbreak of coronavirus disease 2019 (COVID-19) created unprecedented stress on physicians. Mindfulness is a type of meditation that focuses on being fully present, aware of senses, and emotions in the present moment without analyzing or judging them, and it may help reduce psychological distress in physicians. This study aimed to examine the effectiveness of virtual mindfulness-based intervention (MBI) on physicians' perceived anxiety and depression and different facets of mindfulness., Methods: During the COVID-19 pandemic, an online survey was administered to physicians to assess depression, anxiety, and awareness using the 9-item Patient Health Questionnaire (PHQ-9), 7-item General Anxiety Disorder (GAD-7), and Five-Facets Mindfulness Questionnaire (FFMQ), respectively. Physicians that received the virtual MBI sessions also completed post-questionnaires at a 3-week follow-up time point., Results: A total of 125 physicians responded to the online survey, with 56 completing the MBI. The prevalence of moderate to severe anxiety and depression was 45.0 and 46.7%, respectively. Mindfulness scores were negatively associated with depression ( r = -0.38, P < 0.001) and anxiety ( r = -0.36, p < 0.001). Mindfulness scores for the 56 physicians who received virtual MBI sessions were significantly improved (mean difference ± SD, 17.7 ± 16.1, p = 0.001). Significant reductions were also evidenced in anxiety (4.4 ± 4.2) and depression (4.5 ± 5.1) scores ( p 's < 0.001). There was also an improvement in mindfulness facets of observing (5.1 ± 4.7), describing (2.3 ± 4.3), acting with awareness (2.7 ± 5.3), non-judging of inner experience (3.6 ± 6.1), and non-reactivity to inner experience (3.9 ± 4.0) ( p 's < 0.001). A facet of mindfulness, acting with awareness was most efficiently associated with improved anxiety ( B = -0.3, p = 0.02) and depression ( B = -0.4, p = 0.01)., Conclusion: This study has demonstrated that virtual MBI improved physicians' psychological wellbeing and mindfulness during the crisis. Regular mindfulness practice may help physicians to tolerate and handle unpleasant circumstances, such as future epidemics or pandemics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Al Ozairi, Alsaeed, Al-Ozairi, Irshad, Crane and Almoula.)

Background: The aim of the current study was to determine the prevalence of low muscle strength and to evaluate physical activity and sleep characteristics in people with type 2 diabetes in Kuwait. Additionally, equivalent data from the UK Biobank cohort were compared., Methods: People with type 2 diabetes from the UK Biobank (n = 23,570) and Kuwaiti cohorts (n = 3,135) were included in this cross-sectional study. Self-reported sleep, physical activity, and muscle strength were compared between the cohorts, using linear and logistic regression, with adjustments for age, sex, and duration of diabetes., Results: Physical activity levels (-937 (-1,097, -851) Met-min/week: standardized B-coefficient -0.42 (-0.47, -0.37)) and grip strength (3.2 (-3.58, -2.82) kg: standardized B-coefficient (-0.29 (-0.32, -0.26)) were lower in the Kuwaiti cohort, and the odds of having short sleep (OR 1.32 (1.19,1.46), being classed as inactive (OR 8.70 (7.59, 9.98), and having muscle weakness (OR 1.88 (1.69, 2.09) were higher. These analyses were adjusted for age, sex, and duration of diabetes., Conclusions: The aim of the current study was to determine the prevalence of low muscle strength and to evaluate physical activity and sleep characteristics in people with type 2 diabetes in Kuwait. Additionally, equivalent data from the UK Biobank cohort were compared., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Al Ozairi, Alsaeed, Al Roudhan, Voase, Pell, Ho, Abdulla and Gray.)

Although many dietary and lifestyle interventions have been proposed, the concept of total dietary replacement (TDR) to achieve remission of type 2 diabetes in the Gulf region is new. With the high levels of obesity and type 2 diabetes in the region, offering TDR to patients for weight loss and remission of type 2 diabetes would assist in achieving health outcomes. The aim of the current study was to explore and understand remission of type 2 diabetes and TDR from the perspectives of dietitians to identify challenges and recommend solutions for implementation in Kuwait. A qualitative approach utilizing focus groups was chosen to explore the topic. Purposive sampling was used to gain experiences from a diverse sample across primary, secondary, and tertiary specialized diabetes centers. Discussions were audio-recorded and transcribed verbatim. Grounded theory using an iterative approach was applied to analyze the data. Three focus groups with a total of 17 participants achieved data saturation. The sample was varied in terms of workplace and years of experience. The three emerging themes were motivation to use the TDR approach, perceived challenges of TDR, and suggestions to improve and adapt approaches for Kuwait. Dietitians reported that remission of type 2 diabetes is a great motivator for patients to undergo TDR, although various factors were identified that may affect uptake including age, level of education, and social and cultural environment. By understanding dietitians' perspectives, it has provided insight on views regarding the implementation of TDR to achieve remission in Kuwait and how best to tailor approaches by focusing on patient support needs and adopting a flexible approach., Competing Interests: The authors have declared that no competing interests exist.

Alzheimer's disease is the most common form of dementia and the fifth-leading cause of death among people over the age of 65. In addition, based on official records, cases of death from Alzheimer's disease have increased significantly. Hence, early diagnosis of Alzheimer's disease can increase patients' survival rates. Machine learning methods on magnetic resonance imaging have been used in the diagnosis of Alzheimer's disease to accelerate the diagnosis process and assist physicians. However, in conventional machine learning techniques, using handcrafted feature extraction methods on MRI images is complicated, requiring the involvement of an expert user. Therefore, implementing deep learning as an automatic feature extraction method could minimize the need for feature extraction and automate the process. In this study, we propose a pre-trained CNN deep learning model ResNet50 as an automatic feature extraction method for diagnosing Alzheimer's disease using MRI images. Then, the performance of a CNN with conventional Softmax, SVM, and RF evaluated using different metric measures such as accuracy. The result showed that our model outperformed other state-of-the-art models by achieving the higher accuracy, with an accuracy range of 85.7% to 99% for models with MRI ADNI dataset.

Background: Colorectal and prostate cancers are the most common types of cancer in men worldwide. To diagnose colorectal and prostate cancer, a pathologist performs a histological analysis on needle biopsy samples. This manual process is time-consuming and error-prone, resulting in high intra- and interobserver variability, which affects diagnosis reliability., Objective: This study aims to develop an automatic computerized system for diagnosing colorectal and prostate tumors by using images of biopsy samples to reduce time and diagnosis error rates associated with human analysis., Methods: In this study, we proposed a convolutional neural network (CNN) model for classifying colorectal and prostate tumors from multispectral images of biopsy samples. The key idea was to remove the last block of the convolutional layers and halve the number of filters per layer., Results: Our results showed excellent performance, with an average test accuracy of 99.8% and 99.5% for the prostate and colorectal data sets, respectively. The system showed excellent performance when compared with pretrained CNNs and other classification methods, as it avoids the preprocessing phase while using a single CNN model for the whole classification task. Overall, the proposed CNN architecture was globally the best-performing system for classifying colorectal and prostate tumor images., Conclusions: The proposed CNN architecture was detailed and compared with previously trained network models used as feature extractors. These CNNs were also compared with other classification techniques. As opposed to pretrained CNNs and other classification approaches, the proposed CNN yielded excellent results. The computational complexity of the CNNs was also investigated, and it was shown that the proposed CNN is better at classifying images than pretrained networks because it does not require preprocessing. Thus, the overall analysis was that the proposed CNN architecture was globally the best-performing system for classifying colorectal and prostate tumor images., (©Remy Peyret, Duaa alSaeed, Fouad Khelifi, Nadia Al-Ghreimil, Heyam Al-Baity, Ahmed Bouridane. Originally published in JMIR Bioinformatics and Biotechnology (https://bioinform.jmir.org), 09.02.2022.)

Introduction: To investigate type 2 diabetes as a risk factor for COVID-19 death following hospital admission in Kuwait., Methods: A retrospective cohort study using data from a central hospital that cared for all hospitalized COVID-19 patients in Kuwait. We investigated the association between type 2 diabetes, with COVID-19 mortality using multiply imputed logistic regression and calculated the population attributable fraction., Results: A total of 5333 patients were admitted with COVID-19, of whom 244 died (4.6%). Diabetes prevalence was 24.8%, but 53.7% of those who died had diabetes. After adjusting for age, sex, ethnicity and other comorbidities, diabetes was associated with death (OR 1.70 [95% CI 1.23, 2.34]) and admission to the intensive care unit more than 3 days after initial admission (OR 1.78 [95% CI 1.17, 2.70]). Assuming causality, the population attributable fraction for type 2 diabetes in COVID-19 death was 19.6% (95% CI 10.8, 35.6)., Conclusion: Type 2 diabetes is a strong risk factor for COVID-19 death in the Middle East. Given the high prevalence of type 2 diabetes in the Middle East, as well as many Western countries, the public health implications are considerable., (© 2021 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)

Medicines management is known to be an integral part of the role of family caregivers; it also contributes to the burden and stress of caregivers' experience. As dementia progresses, new challenges arise as a consequence, which negatively affects the ability of people living with dementia (PLWD) regarding practical decision making and may lead to a change of setting. The aim of this study is to identify and explore changes in medicines management and associated caregiver burden as dementia progresses. To examine medicines management and related issues across severities, a qualitative approach utilising face-to-face and telephone interviews with PLWD and their family caregivers in both the community and care-home setting in London was used. Follow-up interviews with family caregivers were also conducted to gain additional insight into change over time. Eleven family caregivers, ten PLWD, and eight care-home staff were interviewed in 2016. Findings identified how key changes along dementia progression affect medication use. These include changes to caregiver burden, respecting the PLWD's autonomy and decline in capacity, scheduling and administration, choice of formulation, interactions with and between providers, and information needs. The findings assist in informing recommendations to optimise medication use and alleviate caregiver burden.

Background: Whilst skeletal muscles' primary role is allowing movement, it has important metabolic roles, including in glycemic control. Indeed, evidence indicates that low muscle mass and function are associated with an increased risk of type 2 diabetes, highlighting its importance in the development of metabolic disease., Methods: In this mini-review, we detail the evidence highlighting the importance of muscle in type 2 diabetes and the efficacy of resistance exercise in improving glycemic control alongside our approach to increase uptake of such exercise in people with type 2 diabetes. This summary is based in the authors' knowledge of the filed supplemented by a Pubmed search using the terms "muscle," "glycemic control," "HbA1c," "type 2 diabetes," and "resistance exercise.", Results: The main strategy to increases muscle mass is to perform resistance exercise and, although the quality of evidence is low, such exercise appears effective in reducing Glycated Haemoglobin (HbA1c) in people with type 2 diabetes. However, to increase participation we need to improve our understanding of barriers and facilitators to such exercise. Current data indicate that barriers are similar to those reported for aerobic exercise, with additional resistance exercise specific barriers of looking to muscular, increase risk of cardiovascular event, having access to specialized equipment and knowledge of how to use it., Conclusions: The development of simple resistance exercises that can be performed anywhere, that use little or no equipment and are effective in reducing HbA1c will be, in our opinion, key to increasing the number of people with type 2 diabetes performing resistance exercise., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The massive scale of social media platforms requires an automatic solution for detecting hate speech. These automatic solutions will help reduce the need for manual analysis of content. Most previous literature has cast the hate speech detection problem as a supervised text classification task using classical machine learning methods or, more recently, deep learning methods. However, work investigating this problem in Arabic cyberspace is still limited compared to the published work on English text., Objective: This study aims to identify hate speech related to the COVID-19 pandemic posted by Twitter users in the Arab region and to discover the main issues discussed in tweets containing hate speech., Methods: We used the ArCOV-19 dataset, an ongoing collection of Arabic tweets related to COVID-19, starting from January 27, 2020. Tweets were analyzed for hate speech using a pretrained convolutional neural network (CNN) model; each tweet was given a score between 0 and 1, with 1 being the most hateful text. We also used nonnegative matrix factorization to discover the main issues and topics discussed in hate tweets., Results: The analysis of hate speech in Twitter data in the Arab region identified that the number of non-hate tweets greatly exceeded the number of hate tweets, where the percentage of hate tweets among COVID-19 related tweets was 3.2% (11,743/547,554). The analysis also revealed that the majority of hate tweets (8385/11,743, 71.4%) contained a low level of hate based on the score provided by the CNN. This study identified Saudi Arabia as the Arab country from which the most COVID-19 hate tweets originated during the pandemic. Furthermore, we showed that the largest number of hate tweets appeared during the time period of March 1-30, 2020, representing 51.9% of all hate tweets (6095/11,743). Contrary to what was anticipated, in the Arab region, it was found that the spread of COVID-19-related hate speech on Twitter was weakly related with the dissemination of the pandemic based on the Pearson correlation coefficient (r=0.1982, P=.50). The study also identified the commonly discussed topics in hate tweets during the pandemic. Analysis of the 7 extracted topics showed that 6 of the 7 identified topics were related to hate speech against China and Iran. Arab users also discussed topics related to political conflicts in the Arab region during the COVID-19 pandemic., Conclusions: The COVID-19 pandemic poses serious public health challenges to nations worldwide. During the COVID-19 pandemic, frequent use of social media can contribute to the spread of hate speech. Hate speech on the web can have a negative impact on society, and hate speech may have a direct correlation with real hate crimes, which increases the threat associated with being targeted by hate speech and abusive language. This study is the first to analyze hate speech in the context of Arabic COVID-19-related tweets in the Arab region., (©Raghad Alshalan, Hend Al-Khalifa, Duaa Alsaeed, Heyam Al-Baity, Shahad Alshalan. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.12.2020.)

An amendment to this paper has been published and can be accessed via the original article.

Background: Resistance exercise is known to be effective in reducing glycated haemoglobin (HbA1c) in people with type 2 diabetes. However, studies, so far, have employed supervised resistance exercise in a laboratory or gym facility which limits the future translation of such exercise in to clinical practice and recommendations. Our primary aim, therefore, is to test the hypothesis, in a randomized controlled trial, that home-based resistance exercise training and gym-based resistance exercise training both reduce HbA1c levels in people with type 2 diabetes compared to control. We will also investigate the effects of home- and gym-based resistance exercise training on muscle strength and body composition., Methods: The current study is a three-arm randomised controlled trial which will be conducted with 150 eligible people with type 2 diabetes to compare home-and gym-based resistance exercise training with usual care in Kuwait. The interventions will be delivered by exercise specialists and last for 32 weeks. The primary outcomes are HbA1c with secondary outcomes measuring muscle function, body composition, physical activity and quality of life., Discussion: Ethical approval has been granted by the Dasman Diabetes Institute ethical review committee (RA/197/2019). Study findings will be disseminated through presentation at scientific conferences and in scientific journals., Trial Registration: NCT04136730: Retrospectively registered on 21 October 2019.

This pre-Ramadan workshop was aimed at educating and counselling people with type 1 diabetes, who graduated from the Dose Adjustment for Normal Eating (DAFNE) Kuwait programme, on safe fasting practices as well as determining their views on the challenges associated with fasting. The workshop also served as a pilot for a Ramadan-specific module to inform its implementation in all DAFNE programmes with the goal of meeting the needs of Muslim DAFNE graduates wishing to fast safely. A 2-day workshop (5 hours each) was conducted at DAFNE Kuwait 3 days before the start of Ramadan 2018 and all DAFNE graduates were invited to attend. The workshop consisted of group discussions about fasting-related challenges, followed by three interactive lectures and hands-on experience with popular Ramadan dishes. A qualitative approach was employed to determine the experiences of the participants with fasting by conducting three focus group discussions. The discussions were recorded via handwritten notes and analysed thematically. Seventy-two people with type 1 diabetes attended and 47 participated in the group discussions. Participants discussed their past experiences with fasting and the associated challenges, and shared practices adopted over the years. In addition, they confirmed the positive impact of DAFNE on their fasting experiences. The workshop provided a platform for people with type 1 diabetes to share their experiences with fasting and learn how to fast safely. Furthermore, it provided preliminary information that can be further explored to inform recommendations for safer fasting practices and the implementation of a specific fasting curriculum for people with type 1 diabetes., (© 2019 John Wiley & Sons Ltd.)

Brain computer interfaces are currently considered to greatly enhance assistive technologies and improve the experiences of people with special needs in the workplace. The proposed adaptive control model for smart offices provides a complete prototype that senses an environment's temperature and lighting and responds to users' feelings in terms of their comfort and engagement levels. The model comprises the following components: (a) sensors to sense the environment, including temperature and brightness sensors, and a headset that collects electroencephalogram (EEG) signals, which represent workers' comfort levels; (b) an application that analyzes workers' feelings regarding their willingness to adjust to a space based on an analysis of collected data and that determines workers' attention levels and, thus, engagement; and (c) actuators to adjust the temperature and/or lighting. This research implemented independent component analysis to remove eye movement artifacts from the EEG signals and used an engagement index to calculate engagement levels. This research is expected to add value to research on smart city infrastructures and on assistive technologies to increase productivity in smart offices., Competing Interests: The authors declare no conflicts of interest.

Background and Aims: Although people with type 1 diabetes are exempt from fasting the month of Ramadan due to the risk to their health, many wish to fast nonetheless. Little is known about the impact of structured education on the fasting experiences of people with type 1 diabetes. This study aimed to explore how the Dose Adjustment for Normal Eating (DAFNE) course affected people with type 1 diabetes' fasting experiences to provide insight into the benefits of structured education for people wishing to fast while managing their diabetes., Methods: Semi-structured interviews were conducted with 40 DAFNE graduates who fasted Ramadan. The purposive sample was selected from the DAFNE registry at Dasman Diabetes Institute in Kuwait. The interviews were transcribed verbatim and analysed thematically in an iterative process. Topics discussed included fasting experiences prior to attending the DAFNE course, fasting experiences this year, and how DAFNE affected their fasting., Results: Five themes emerged; (1) Reduction in fluctuations and complications, (2) Improvement in confidence and self-reliance, (3) Tailored support for dose and pump programming adjustments, (4) Positive effect on wellbeing, and (5) Encouraging informed-decision making about fasting., Conclusions: The findings have provided insight into the impact of DAFNE structured education on the fasting experiences of people with type 1 diabetes and has shown how overall, DAFNE had enhanced the quality of fasting. In addition, by assisting them in fulfilling their fasting wishes, DAFNE has had a positive effect on their wellbeing., (Copyright © 2019. Published by Elsevier B.V.)

Dementia is fast becoming a global concern due to a demographic shift towards an older population. Many studies have shown that caring for a family member or friend has a profound and negative impact on the physical, emotional and psychosocial aspects of the caregivers' life. One significant activity that a family caregiver undertakes is assistance with the management of medicines. This review was undertaken to ascertain what the issues are that affect optimal medicines use from the perspectives of people living with dementia and their caregivers, both in the community and care home settings. A literature search was conducted using electronic databases, employing a combination of search terms. A total of 16 studies met the inclusion criteria. Six broad themes were identified, together with some recommendations to improve medicines use in people with dementia. Challenges to medicines use centred on medicines management and administration, the impact on the caregiver and care recipient, their partnership and interface with formal care. Future research should focus on developing targeted interventions that can overcome these challenges to achieve optimal medicines use., (Copyright © 2015 Elsevier B.V. All rights reserved.)