Search Results (131)

Background: Influenza poses a significant threat to the health of Malaysians, particularly among the elderly population. It results in high levels of illness and mortality, becoming a financial burden on the government. Vaccination is widely recognised as the most effective measure for controlling the spread and impact of influenza. Objectives: This study sought to assess the knowledge, attitudes, and practices (KAP) regarding influenza and influenza vaccination among older adults attending primary healthcare centres in different states of Malaysia. Additionally, the study assessed the level of acceptance for a proposed free annual influenza vaccination program. Methods: A nationwide survey was conducted involving 672 older people aged 60 and above who visited nine primary healthcare centres in Malaysia. These centres were selected using proportionate to population size (PPS) sampling to ensure representation from each zone. Participants completed a validated self-reported questionnaire. Descriptive statistics were used to determine the levels of KAP, and a binomial logistic regression model was used to determine the predictors of acceptance for the proposed free annual vaccination program. Results: Most participants displayed a strong understanding of influenza illness (74.0%) and the vaccine (65.9%). Moreover, 76.4% of respondents exhibited a positive attitude towards influenza vaccination. However, the prevalence of good vaccination practices was relatively low, with only 29.2% of participants having a history of previous vaccination, and just 55.2% of these consistently practicing annual vaccination. The group acceptance rate for the proposed free annual influenza vaccination was 62.3%. Significant predictors of acceptance included a history of previous vaccination (good practice) (OR = 6.438, 95% CI = 1.16–35.71, p < 0.001), a positive attitude towards vaccines (OR = 21.98, 95% CI = 5.44–88.87, p = 0.033), and a good level of knowledge about the influenza vaccine (OR = 0.149, 95% CI = 0.03–0.79, p = 0.026). Conclusions: Increasing the uptake of influenza vaccination among the older population in Malaysia remains a significant challenge. It is recommended that a targeted, free annual influenza vaccination program be implemented for high-risk populations, particularly those with comorbidities and those who have shown greater receptiveness. In addition, health education strategies aimed at raising awareness and understanding of influenza should be prioritised. Strengthening epidemiological data collection and establishing systematic monitoring mechanisms are also essential to support these efforts. Full article

To reduce the risk of COVID-19 infection, transmission and illness during the pandemic, the Department for Education (DfE) issued guidance to schools. However, research on how the school community perceives the impact of the COVID-19 mitigation measures outlined remains limited. This qualitative study aims to explore the effects of school closures and in-school mitigation measures on daily school life, as well as their impact on mental health and wellbeing from the perspective of English secondary school staff and students. Participants were purposively sampled from English secondary schools serving diverse communities participating in the COVID-19 Mapping and Mitigation in Schools study (CoMMinS). Selection ensured representation of staff roles and student demographics. Semi-structured interviews were conducted remotely, and data analysed thematically. Interviews took place between January and August 2021 with participants from five secondary schools (20 staff and 25 students). Both staff and students reported significant disruption to school life, with four themes identified: (1) teaching and learning impact, (2) social impact, (3) safeguarding impact, and (4) and mental health and wellbeing impact. Findings highlight widespread negative effects across every aspect of school life, for both staff and students. This study suggests that COVID-19 mitigation measures in UK secondary schools led to a sense of loss and uncertainty as well as increased self-reported stress among both staff and students. Full article

Theoretical background: The study of psychological well-being in children and adolescents living with chronic illness is of particular relevance, as the physical and psychosocial aspects of the illness can have a significant impact on their quality of life. Previous research has highlighted that depression, nonproductive thoughts and various aspects of problematic internet use may be related to life satisfaction and ways of coping with illness. This study aims to examine how depression, nonproductive thoughts, and problematic internet use interact with illness perception and burden to affect psychological well-being and life satisfaction. Methods: A cross-sectional study was conducted with 207 chronically ill children aged 10–18 years. The children, aged between 10 and 18 years old, attended regular check-ups in different specialities (gastroenterology, pulmonology, onco-haematology, and paediatric rehabilitation). A cross-sectional study was carried out using psychological instruments to measure life satisfaction (SWLS), nonproductive thoughts (NPG-K), problematic internet use (PIU-Q), illness perception (PRISM) and illness burden (PRISM-D, IIRS), and depression (BDI-R). Spearman rank correlation analysis was used to explore the associations between variables. Results: Life satisfaction was negatively related to nonproductive thoughts (r = −0.28, p < 0.001), internet obsession (r = −0.20, p < 0.01), and internet neglect (r = −0.20, p = 0.004). Conversely, a positive correlation was found with the PRISM (r = 0.14, p = 0.042), suggesting that less dominance of illness detection is associated with higher life satisfaction. Depression and nonproductive thoughts showed a strong positive relationship (r = 0.49, p < 0.001), and depression and problematic internet use also showed significant correlations for the obsession, neglect and control subscales (r = 0.23–0.29, all p < 0.001). Cluster analysis identified three psychological profiles: ‘positive fighters’, ‘avoidant sufferers’, and ‘negative observers’, distinguished by differences in depression, nonproductive thoughts, illness burden, and well-being. Conclusions: The results suggest that the quality of life of children and adolescents with chronic illness is significantly affected by mental health factors, particularly depression, nonproductive thoughts and problematic internet use. Illness perception and illness-related distress also play a key role in shaping life satisfaction and overall psychosocial well-being. These findings underscore the need for targeted psychological interventions in pediatric chronic care to enhance well-being and promote adaptive coping and suggest that psychological interventions and targeted psychosocial support can significantly improve these children’s quality of life. Further research is needed to explore intervention options and to develop optimal support strategies. Full article

Background: The Standards for the Psychosocial Care of Children with Cancer and their Families provide a framework for the delivery of psychosocial care to families experiencing pediatric cancer. Similarly, the Pediatric Psychosocial Preventative Health Model (PPPHM) guides intervention approaches by identifying three tiers of psychosocial support based on a family’s level of risk. Employing both the Standards and the PPPHM, we developed a comprehensive three-tiered approach to support the psychosocial needs of families in a pediatric oncology setting. Methods: After publication of the Standards, our institution merged existing psychosocial disciplines into one unified Psychosocial Services department. The new department worked to clearly define the role and scope of each discipline’s practice to ensure the psychosocial needs of patients and families were being comprehensively met. Interprofessional workgroups were established to evaluate and enhance the psychosocial services offered to patients, siblings, and caregivers using a three-tiered model of support. Membership included representation from patients and parent/caregiver advisors to ensure their perspectives were included in program development. Results: Over ten new programs have been developed to enhance the support of families facing pediatric cancer. At the Universal tier, new programs available to all families include caregiver and sibling support groups, a caregiver podcast, and a relationship health toolkit and workshop. At the Targeted tier, psychosocial interventions and parent mentor supports were implemented. At the Clinical/Intervention tier, a partnership was developed with an external tele-mental health company to provide mental health services to caregivers with significant needs or preexisting mental health disorders. Conclusions: Given the complex needs of families facing pediatric cancer, use of an interdisciplinary approach is paramount to successful support throughout the treatment trajectory. By leveraging the expertise and strengths of diverse disciplines with the perspectives of patients and families, new psychosocial programs can comprehensively address the unique challenges of patients and families impacted by illness. Full article

In the context of the Italian National Herpes Zoster Vaccine program, an exploratory survey was conducted on a sample of fragile adult patients to investigate the representations of the disease and its prevention to build future local vaccination campaigns. An ad hoc questionnaire was administered to 271 fragile adult patients who had adjuvanted recombinant Herpes Zoster vaccination to detect the following: knowledge and perception of the disease and its risks; information sources and confidence in the information sources used; and perception of the Herpes Zoster vaccination. Fragile adult patients have the representation of Herpes Zoster as a serious disease (86.5%), and they consider themselves informed concerning symptoms and health effects. Women are more fearful of the impact of the disease (Chi-square = 10.03; DF = 3; p-value = 0.018), while those with a higher average age consider themselves less informed (R = −158; p-value = 0.039). The sources of information that contributed to the construction of illness representation are health personnel (73.5%), followed by the web and social web (14.7%), and media such as radio and TV (10.0%). Regarding the vaccine representation, fragile patients are confident about the vaccine and the science behind it and believe everyone should receive it. However, a high percentage (62.9%) fear side effects. Our analysis highlights that vaccination campaigns must be planned based on the target audience, individual and contextual needs, and representations of the disease, particularly when dealing with frail patients, to implement effective preventive interventions. Full article

Background: Stigma can have a significant impact on the lives of those inflicted, and stigmatisation can occur at any time when individuals commonly label behaviours and characteristics of others as offensive. Many attributes, such as homosexuality, ethnicity, race, and mental illness, have been explored using existing instruments. However, there are currently no standardised measures of stigma towards specific behaviours such as naturism. Naturism is the practice of public nudity without any intention of sexual stimulation. Though a global phenomenon, data suggest that almost seven million individuals in the UK alone identify as naturists. The rising figures of those engaging in stigmatised behaviour and the negative representations of this in the media contribute to the necessity for standardised instruments to measure stigma towards naturism. Method: The Naturism Stigma Scale (NSS) was adapted from the Depression Stigma Scale. This 18-item scale has two subscales which measure personal and perceived stigma. The sample consisted of 449 participants recruited by convenience sampling. Results: The analysis indicated that the scale had high reliability for both subscales (Personal Cronbach’s α = 0.91, Perceived Cronbach’s α = 0.93). It can be concluded that the NSS is a reliable psychometric instrument. Conclusions: Overall, this research assists in further understanding the stigma towards this minority group. Further research is necessary to explore the psychometric properties of NSS among different community samples. Full article

Major depressive disorder (MDD) is a prevalent mental illness characterized by persistent sadness, loss of interest in activities, and significant functional impairment. It poses severe risks to individuals’ physical and psychological well-being. The development of automated diagnostic systems for MDD is essential to improve diagnostic accuracy and efficiency. Electroencephalography (EEG) has been extensively utilized in MDD diagnostic research. However, studies employing deep learning methods still face several challenges, such as difficulty in extracting effective information from EEG signals and risks of data leakage due to experimental designs. These issues result in limited generalization capabilities when models are tested on unseen individuals, thereby restricting their practical application. In this study, we propose a novel deep learning approach, termed TSF-MDD, which integrates temporal, spatial, and frequency-domain information. TSF-MDD first applies a data reconstruction scheme to obtain a four-dimensional temporal–spatial–frequency representation of EEG signals. These data are then processed by a model based on 3D-CNN and CapsNet, enabling comprehensive feature extraction across domains. Finally, a subject-independent data partitioning strategy is employed during training and testing to eliminate data leakage. The proposed approach achieves an accuracy of 92.1%, precision of 90.0%, recall of 94.9%, and F1-score of 92.4%, respectively, on the Mumtaz2016 public dataset. The results demonstrate that TSF-MDD exhibits excellent generalization performance. Full article

Neonatal mortality remains a critical global challenge, particularly in resource-limited settings with restricted access to advanced diagnostic tools. Early detection of life-threatening conditions like Sepsis and Respiratory Distress Syndrome (RDS), which significantly contribute to neonatal deaths, is crucial for timely interventions and improved survival rates. This study investigates the use of newborn cry sounds, specifically the expiratory segments (the most informative parts of cry signals) as non-invasive biomarkers for early disease diagnosis. We utilized an expanded and balanced cry dataset, applying Self-Supervised Learning (SSL) models—wav2vec 2.0, WavLM, and HuBERT—to extract feature representations directly from raw cry audio signals. This eliminates the need for manual feature extraction while effectively capturing complex patterns associated with sepsis and RDS. A classifier consisting of a single fully connected layer was placed on top of the SSL models to classify newborns into Healthy, Sepsis, or RDS groups. We fine-tuned the SSL models and classifiers by optimizing hyperparameters using two learning rate strategies: linear and annealing. Results demonstrate that the annealing strategy consistently outperformed the linear strategy, with wav2vec 2.0 achieving the highest accuracy of approximately 90% (89.76%). These findings highlight the potential of integrating this method into Newborn Cry Diagnosis Systems (NCDSs). Such systems could assist medical staff in identifying critically ill newborns, prioritizing care, and improving neonatal outcomes through timely interventions. Full article

Objectives: Computer-aided schizophrenia (SZ) detection methods mainly depend on electroencephalogram and brain magnetic resonance images, which both capture physical signals from patients’ brains. These inspection techniques take too much time and affect patients’ compliance and cooperation, while difficult for clinicians to comprehend the principle of detection decisions. This study proposes a novel method using face diagnosis images based on traditional Chinese medicine principles, providing a non-invasive, efficient, and interpretable alternative for SZ detection. Methods: An innovative face diagnosis image analysis method for SZ detection, which learns feature representations based on Vision Transformer (ViT) directly from face diagnosis images. It provides a face features distribution visualization and quantitative importance of each facial region and is proposed to supplement interpretation and to increase efficiency in SZ detection while keeping a high detection accuracy. Results: A benchmarking platform comprising 921 face diagnostic images, 6 benchmark methods, and 4 evaluation metrics was established. The experimental results demonstrate that our method significantly improves SZ detection performance with a 3–10% increase in accuracy scores. Additionally, it is found that facial regions rank in descending order according to importance in SZ detection as eyes, mouth, forehead, cheeks, and nose, which is exactly consistent with the clinical traditional Chinese medicine experience. Conclusions: Our method fully leverages semantic feature representations of first-introduced face diagnosis images in SZ, offering strong interpretability and visualization capabilities. It not only opens a new path for SZ detection but also brings new tools and concepts to the research and application in the field of mental illness. Full article

Background: Optimum efficiency and responsiveness to callers of mental health helplines can only be achieved if call priority is accurately identified. Currently, call operators making a triage assessment rely heavily on their clinical judgment and experience. Due to the significant morbidity and mortality associated with mental illness, there is an urgent need to identify callers to helplines who have a high level of distress and need to be seen by a clinician who can offer interventions for treatment. This study delves into the potential of using machine learning (ML) to estimate call priority from the properties of the callers’ voices rather than evaluating the spoken words. Method: Phone callers’ speech is first isolated using existing APIs, then features or representations are extracted from the raw speech. These are then fed into a series of deep learning neural networks to classify priority level from the audio representation. Results: Development of a deep learning neural network architecture that instantly determines positive and negative levels in the input speech segments. A total of 459 call records from a mental health helpline were investigated. The final ML model achieved a balanced accuracy of 92% correct identification of both positive and negative instances of call priority. Conclusions: The priority level provides an estimate of voice quality in terms of positive or negative demeanor that can be simultaneously displayed using a web interface on a computer or smartphone. Full article

Hepatitis C virus (HCV) disproportionately affects certain sub-populations, including people with experience of incarceration (PWEI). Little is known about how perceptions of HCV and treatment have changed despite simplifications in testing and treatment in carceral settings. Nineteen semi-structured interviews were conducted with people living with or having a history of HCV infection released from Quebec provincial prison. Interviews were guided by the Common Sense Self-Regulation Model (CS-SRM) and aimed to explore cognitive and emotional representations of HCV and coping strategies. Among the 19 participants, seven (37%) were diagnosed with HCV in prison and 14 (74%) had previously received HCV treatment. Participants’ HCV illness perceptions were influenced by fear (of HCV transmission, death, and the well-being of family) and stigma (related to HCV, injection drug use, and incarceration). While some sought education and social and professional support, others self-isolated or engaged in high-risk behaviors to cope. Despite advances in HCV treatment, PWEI continue to experience various forms of stigma and fear surrounding their HCV diagnosis, resulting in delayed HCV care. These findings provide insights into how prison-based healthcare providers can better utilize HCV illness perceptions to evaluate willingness to engage in HCV care among PWEI. Full article

This paper addresses the facility location problem under a mill pricing policy, integrating customers’ behavior through the concept of preferences. The problem is modeled as a bilevel optimization problem, where the existence of ties in customers’ preferences can lead to an ill-posed bilevel problem due to the possible existence of multiple optima to the lower-level problem. As the commonly employed optimistic and pessimistic strategies are inadequate for this problem, a specific approach is proposed bearing in mind the customers’ rational behavior. In this work, we propose a novel formulation of the problem as a bilevel model in which each customer faces a lexicographic biobjective problem in which the preference is maximized and the total cost of accessing the selected facility is minimized. This allows for a more accurate representation of customer preferences and the resulting decisions regarding facility location and pricing. To address the complexities of this model, we apply duality theory to the lower-level problems and, ultimately, reformulate the bilevel problem as a single-level mixed-integer optimization problem. This reformulation incorporates big-M constants, for which we provide valid bounds to ensure computational tractability and solution quality. The computational study conducted allows us to assess, on the one hand, the effectiveness of the proposed reformulation to address the bilevel model and, on the other hand, the impact of the length of the customer preference lists and fixed opening cost for facilities on the computational time and the optimal solution. Full article

Despite the revolutionary impact of new media, television remains a socially shared reference point for media functions, e.g., information, entertainment, and hybridized genres. Through its simplified knowledge and scripts, television reduces cognitive asymmetry between experts and the public on general and specific topics, thus having a critical role in constructing social representations. This work examines two (apparently) distant realities, i.e., mental health as a fundamental aspect of public health and popular and “light” entertainment formats like reality shows. In the past, researchers investigated media representation of mental illness in general terms alongside other types of programs, e.g., coming-of-age, dramedy television series, and children’s television programs. This study examines how depression is discursively constructed and socially represented in a case that shook the Italian public opinion, i.e., a Big Brother VIP cast member with depression symptoms. The critical discourse analysis, focusing on positioning and representations about depression, enabled us to emphasize that (1) knowledge about depression is poorly defined and participants’ reactions are mostly immature and clumsy, and (2) mass media can play an essential role in creating more mindful and complete knowledge about mental health. Full article

Background/objectives: The way in which topics like suicide, mental health concerns and alcohol and other drug use are communicated matters. It has the potential to have either a positive or negative impact on people and communities, particularly those with a lived experience of these concerns. This article draws on the findings of a qualitative study designed to explore the experiences and perceptions of stakeholders on the imagery and language used to depict suicide, mental health concerns or alcohol and other drug use. Methods: The focus group method was used as a form of participatory action research to gain an in-depth understanding of the experiences and views of those who use or are impacted by language and imagery about suicide, mental ill-health and AOD use, including those with lived experiences of these topics. Results: A series of 10 focus groups were created in February and March 2022 with media and other professional communicators; people identifying as having a lived experience of suicide, mental ill-health or alcohol and other drug use; mental health and suicide prevention sector professionals; and people from priority populations (n = 49). From these focus groups, principles were developed as well as exemplars of helpful and less helpful depictions. Rather than prescriptive or static rules, the participants indicated that safe representations require an ongoing engagement with the principle of “do no harm”. Conclusions: A positive conclusion arose—that words and images have the potential to promote help-seeking, challenge stigma or stereotypes and create change. Full article

Aim: Older age is not a homogenous or stereotypical experience. Age-stereotypical representations can often be disconnected from older people’s own experiences. Challenging the status quo is relevant for aging well. The aim of this study is to analyze older adults’ perspectives on stereotypical versus their own age representations. Method: This qualitative study included a sample of 433 older adults who were 65 to 74, 75 to 84, and 85+ years of age. Content analysis was carried out. Results: Findings from this study indicated that the great majority of the participants (88%) did not identify with stereotypical age representations. This was so among participants in the 65–74 age group in relation to Showing a sense of agency (81.1%); Feeling spiritual (73.4%); Having meaningful goals (72.2%); Holding a significant social network (70.9%); Staying tuned to the world (67.1%); and feeling physically attractive (59.8%). Participants who were 75–84 years of age clarified what physical health (81.0%) and surviving chronic illnesses (78.9%), autonomy (75.5%), being socially active (74.9%), and staying mentally active (70.1%) represent at that age. The +85 years age group drew attention to No pain or physical limitations (95.6%), Physical health (93.1%), Cognitive autonomy (87.1%), Staying tuned to society and the world (76.3%); and Mobility (72.2%). Conclusions: Participants’ favoring their own over stereotypical thinking about people their age represents inner resourcefulness and a penchant for aging well. Collaborative partnerships for sharing such wisdom around could enrich policy programs and interventions that favor inclusivity and fight ageism, fostering a more accurate perspective of what it means to be a certain ‘age’ versus simply being ‘old’. Full article