Risk Of Illness Research Articles

Integrated Health Monitoring System using Fingerprint and Disease Risk Prediction

Recent developments in machine learning and biometric systems have had a big influence on healthcare applications. In order to provide a holistic approach to health monitoring, this research introduces a unique method that combines disease risk prediction with fingerprint-based blood group recognition. Based on user-provided health data, the system uses machine learning algorithms to determine the risk of common illnesses including diabetes, cardiovascular disease, and chronic kidney disease (CKD) and convolutional neural networks (CNNs) to identify blood type from fingerprint photos. Through the integration of fingerprint biometric data with health risk modelling, the suggested approach seeks to increase the precision and usability of health forecasts. The system's effectiveness is demonstrated by the evaluation's excellent classification accuracy for blood groups and trustworthy estimates of illness risk.This work demonstrates the possibility of integrating biometric data with predictive health models and offers a promising step toward customized healthcare solutions

Rapid on-site detection of viable Vibrio parahaemolyticus in seafood using cis-diamminedichloroplatinum and colorimetric loop-mediated isothermal amplification (CDDP-LAMP).

Vibrio parahaemolyticus in seafood and marine environments poses significant health risks, causing gastroenteritis worldwide. Current detection methods fail to differentiate live from dead cells, leading to inaccuracies in food safety assessments. This study introduces a novel method combining cis-diamminedichloroplatinum (CDDP) with direct colorimetric loop-mediated isothermal amplification (LAMP) for rapid and accurate detection of viable V. parahaemolyticus cells in seafood samples. CDDP treatment at 37°C for 30min selectively inhibits DNA from dead cells, enhancing the specificity of the assay by ensuring only live cell DNA is amplified. The optimized CDDP-LAMP procedure detects alive V. parahaemolyticus within 1h, with results observable through a color change. The CDDP-LAMP assay demonstrates excellent specificity, identifying live V. parahaemolyticus cells while excluding dead cells and other bacteria. It shows a detection limit of 2.348CFU per reaction and successfully detects V. parahaemolyticus in seafood samples across different food matrices. This study is the first to combine CDDP with colorimetric LAMP for direct detecting viable bacteria in food, enhancing specificity by eliminating signals from dead cells. The CDDP-LAMP assay provides a rapid, accurate process for detecting viable V. parahaemolyticus cells, especially in resource-limited settings. It also gives a model for screening different bacterial pathogens, speeding up and improving foodborne illness risk assessments.

Nirsevimab Effectiveness Against Medically Attended Respiratory Syncytial Virus Illness and Hospitalization Among Alaska Native Children - Yukon-Kuskokwim Delta Region, Alaska, October 2023-June 2024.

Respiratory syncytial virus (RSV) is a leading cause of hospitalization among young children. Historically, American Indian and Alaska Native (AI/AN) children have experienced high rates of RSV-associated hospitalization. In August 2023, a preventive monoclonal antibody (nirsevimab) was recommended for all infants aged <8 months (born during or entering their first RSV season) and for children aged 8-19 months (entering their second RSV season) who have increased risk for severe RSV illness, including all AI/AN children. This evaluation in Alaska's Yukon-Kuskokwim Delta region estimated nirsevimab effectiveness among AI/AN children in their first or second RSV seasons during 2023-2024. Among 472 children with medically attended acute respiratory illness (ARI), 48% overall had received nirsevimab ≥7 days earlier (median=91 days before the ARI-related visit). For children in their first RSV season (292), nirsevimab effectiveness was 76% (95% CI = 42%-90%) against medically attended RSV illness and 89% (95% CI = 32%-98%) against RSV hospitalization. For children in their second RSV season (180), effectiveness against medically attended RSV illness was 88% (95% CI=48%-97%). Nirsevimab is effective for preventing severe RSV illness among infants entering their first RSV season and children entering their second season with increased risk for severe RSV, including all AI/AN children.

Respiratory disease in people with bipolar disorder: a systematic review and meta-analysis.

People with bipolar disorder (BD) have an increased risk of premature mortality and the respiratory mortality rate is higher than those of the general population. To date, however, the evidence on respiratory disease in this population has not been meta-analyzed. We systematically review and meta-analyze the frequency of respiratory diseases in patients with BD and to compare prevalence and odds ratio (OR) with the general population. The systematic literature search was conducted in Pubmed, PsycINFO, Scielo and Scopus, with snowball search of reference and citation lists. Inclusion criteria were studies reporting diagnoses of respiratory diseases (asthma, chronic obstructive pulmonary disease (COPD), pneumonia, lung cancer and tuberculosis) in people with BD according to operationalized criteria and where possible, control group. Of the 2158 articles screened, 20 including 962,352 people with BD and 37,340,405 control group, met the inclusion criteria. In people with BD, the prevalence of COPD was 9.14% (95%CI: 6.61-12.5%), asthma 6.4% (95%CI: 4.56-8.91%), pneumonia 2.78% (95%CI: 2.51-3.08%) and lung cancer 0.44% (95%CI:0.23-0.84%). Compared to the general population, people with BD had significantly higher rates of COPD (OR: 1.73; 95% CI: 1.40-2.14), showing an increased rate in younger and female patients; asthma (OR: 1.91, 95% CI: 1.25-2.94), with a greater rate in younger patients; and pneumonia (OR: 2.82, 95% CI: 1.33-5.99). In the first meta-analysis on the topic, BD was associated with an increased risk of respiratory illness versus the general population. In COPD and asthma, young people and women are at particular risk. Prevention programs are urgently needed.

Trends in the Prevalence and Factors Associated with Undernutrition in Tunisian Children Aged 0–23 Months

Background: In recent years, undernutrition has remained a significant public health issue in Tunisia, increasing the risk of illness and mortality in young children. Therefore, this study aims to analyse the prevalence and factors contributing to undernutrition among Tunisian children aged 0–23 months. Methods: The study included 3265 children aged 0–23 months from the 2011–2023 Tunisia Multiple Indicator Cluster Surveys (MICS). Trends and logistic regression analyses were used to determine the prevalence and predictors of undernutrition. Results: The prevalence of stunting, wasting, and underweight in infants and children aged 0–23 months has increased by 3.3%, 0.5%, and 2.1%, respectively. Stunting and underweight were more common among infants aged 0–5 months (11.8% for stunting, 8.9% for underweight, p &lt; 0.01), and first-time mothers (8.3% for stunting, 4.1% for underweight, p &lt; 0.01). In 2023, compared to 2011, the odds of stunting, wasting, and being underweight had increased by 22%, 16%, and 70%, respectively. Infants aged 0–5 months had higher odds of undernutrition in all three indices. Children of obese or overweight mothers, and those who started breastfeeding late, were more likely to be stunted. Boys had significantly higher odds of wasting and underweight. Children with low birth weight, and duration of breastfeeding &gt; 12 months, had significantly higher odds of being underweight. Conclusions: This study shows that infants aged 0–5 months, first-time mothers, boys, and children from poor households in Tunisia are at a higher risk of undernutrition. To address the growing issue of undernutrition in Tunisian children, enhancing maternal and child health and nutrition services, improving parental education, and implementing community-based programs that provide breastfeeding and nutritional education to infants born to new mothers and mothers with high/low BMI is recommended.

Adverse childhood experiences, subsequent negative life events, and their impact on health in occupational rehabilitation patients: a mixed-methods study

IntroductionAdverse childhood experiences (ACEs) are prevalent globally and can negatively impact an individual's lifespan by not only increasing the likelihood of encountering other negative life events (NLEs), but also escalating the risk of illness, absenteeism due to sickness, unemployment, and reliance on disability benefits in adulthood. Therefore, the objective of this study was to explore the prevalence of ACEs and NLEs, as well as their health impacts among patients undergoing occupational rehabilitation.Materials and methodsA total of 80 participants diagnosed with musculoskeletal disorders and/or common mental disorders who participated in two occupational rehabilitation programs in Norway were included. Data were collected by questionnaire and in-depth interviews (39 participants) at the start of the intervention. Comparative quantitative and qualitative analysis was conducted between individuals with a history of ACEs and those without these experiences. Thematic analysis was used to identify the impact of ACEs and NLEs on the health of the informants.ResultsHalf of the participants reported ACEs. Of these, 18% reported one ACE, 22% reported 2–3 ACEs and 9% reported 4 or more ACEs. Also, 25% were categorized as revictimized. The two groups with ACEs had more NLEs in adulthood compared to those without ACEs (p &amp;lt; 0.001), revictimized the most (mean numbers between groups 3.1, 4.5 and 5.9). Furthermore, a history of ACEs was associated with a higher number of reported mental health issues compared to those who had not experienced ACEs (p &amp;lt; 0.01). However, there were no significant differences between the two ACE groups. NLEs had a substantial impact on the participants’ current health status, whether they occurred in childhood or adulthood. In adult life, a high workload (psychologically or physically), interpersonal challenges, and financial struggles had an especially negative impact. Additionally, accidents and complications related to surgeries were also significant NLEs causing health problems. For most, there were complex interactions between NLEs and health.ConclusionsThe prevalence of ACEs and NLEs is high among occupational rehabilitation patients. ACEs are associated with subsequent victimization, interpersonal challenges, financial struggles, and increased mental health issues in adulthood. These findings highlight the need for systematic screening and a holistic, individualized approach in occupational rehabilitation programs to potentially mitigate the adverse effects of NLEs on health and work participation.

Possible rapid reduction of anti-RBD antibody titre after SARS-CoV-2 mRNA vaccination in pregnant women: Multicentre prospective study.

Pregnant women are at increased risk for severe illness associated with coronavirus disease 2019 (COVID-19) compared to nonpregnant women. The aim of this multicenter prospective study was to assess the current COVID-19 vaccination status of pregnant women in the southern Osaka district and to compare their antibody titers with those of nonpregnant women. Serum antibody titers of anti-NCP antibodies (antibodies against the SARS-CoV-2 nucleocapsid) and anti-RBD antibodies (the receptor binding domain of the S1 subunit of the spike protein) were evaluated in 753 pregnant women at 34-35 weeks of gestation from October 2021 to March 2022. Anti-RBD antibody titre was also investigated in 1003 health care workers at Kindai University hospital 3 and 6 months after a second dose of the vaccine from March 2021 to April 2021. 519 (68.9%) pregnant women were vaccinated during pregnancy, of whom 497 (95.8%) received two doses. The COVID-19 infection rate calculated from the number of pregnant women with a positive anti-NCP antibody titre or with confirmed diagnosis was 5.1% (12/234) in the unvaccinated and 3.5% (18/519) in the vaccinated. The estimated half-life calculated from anti-RBD antibody titers and the number of days between vaccination and antibody testing was 39.9 days. The antibody titre and half-life in pregnant women were significantly lower and shorter than in nonpregnant women aged 20-39 years (109.4 days). Our study showed that pregnant women may have lower vaccine-acquired COVID-19 immunity than nonpregnant women.

The influence of physical exercise on negative emotions in adolescents: a meta-analysis

BackgroundAdolescence is also accompanied by ongoing mood changes (relative to childhood and adulthood), which can trigger more extreme negative emotional responses. Physical exercise alleviates negative emotions and reduces the risk of mental illness. However, the effect of physical exercise on negative emotions in adolescents is unclear, so it is valuable to synthesize previous studies with meta-analysis.ObjectiveTo examine the influence of physical exercise (PE) intervention on negative emotions in adolescents aged 10 to 19 years.MethodsWe retrieved the articles from PubMed, Web of Science, EBSCO, Cochrane, and Embase up to April 11, 2024. The main search terms were physical exercise, negative emotions, adolescents, randomized controlled trials. The meta-analysis was conducted using Review Manager 5.3. A random-effects model was employed to calculate the standardized mean difference (SMD) and 95% confidence interval (CI). Subgroups were analysed as the type of negative emotions, type of control group, intervention type, duration, time, frequency.ResultsThe PE intervention group exhibited a significantly superior improvement in alleviating negative emotions compared to the control group (SMD = -0.59, 95% CI: -0.92 to -0.26, p &amp;lt; 0.01, Z = 3.50, I² = 95%). PE was particularly effective in mitigating adolescent depression (SMD = -0.67, 95% CI = -1.07 to -0.28, p &amp;lt; 0.01, I² = 96%) but did not yield significant results in reducing adolescent anxiety (SMD = -0.29, 95% CI = -0.63 to 0.05, p = 0.10, I² = 95%).ConclusionPE intervention can ameliorate negative emotions in adolescents.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024534375.

The Impact of Residential Building Insulation Standards on Indoor Thermal Environments and Heat-Related Illness Risks During Heatwaves: A Case Study in Korea

This study investigates the impact of building insulation standards on indoor thermal environments and the risk of heat-related illnesses during heatwaves in South Korea. Indoor temperatures were measured in residential buildings located in Chuncheon and Gwangju during the 2022 heatwave, with outdoor temperature data sourced from the Korea Meteorological Administration. Probability distribution fitting was used to estimate the likelihood of indoor temperatures exceeding the critical threshold of 27 °C. Additionally, a linear regression analysis was conducted to examine the relationship between the probability of exceeding the threshold and heat-related illness data from 2017 to 2023 provided by the Korea Disease Control and Prevention Agency. The findings reveal significant variations in indoor thermal conditions during heatwaves, influenced by factors such as building type, year of construction, and climate region, which affect the thermal insulation performance. Buildings with a lower thermal insulation performance were associated with higher indoor temperatures, increasing the likelihood of exceeding the critical threshold and contributing to a higher incidence of heat-related illnesses, particularly in provincial non-metropolitan areas. These results underscore the need for region-specific building insulation standards that address both winter energy efficiency and summer heatwave resilience. Enhancing thermal insulation in vulnerable regions could significantly reduce the risk of heat-related illnesses and improve public health resilience to extreme heat events.

Risk Factors of the Severity of COVID-19 Infection in Infants

Background: The global COVID-19 crisis has profoundly affected populations worldwide. While it is widely accepted that older individuals are at greater risk of severe illness, data indicate that in newborns and infants, the disease is generally not fatal. Objectives: This cross-sectional study aimed to examine the roles of laboratory tests and clinical symptoms in determining the severity of COVID-19 infection in infants younger than three months. Methods: This study included all infants less than three months old with positive PCR tests for COVID-19 admitted to the Children's Medical Center between October 2020 and March 2022. We analyzed the association between disease severity and clinical symptoms, as well as laboratory findings. Results: Sixty-four neonates and infants under three months of age with COVID-19 participated in the study. Our findings suggest that lower birth weight and gestational age are associated with increased disease severity. Infants with underlying medical conditions were found to have a higher risk of reaching stage IIb or greater severity. Among laboratory and clinical findings, only white blood cell (WBC) count and cough symptoms showed a significant correlation with disease severity. Conclusions: Clinical evaluations, along with factors such as birth weight, gestational age, and underlying conditions, appear more effective in guiding decision-making for COVID-19 severity in infants. Further studies are necessary to explore the influence of these factors on COVID-19 severity in this age group.

Brain connectomes in youth at risk for serious mental illness: a longitudinal perspective.

Identifying biomarkers for serious mental illnesses (SMI) has significant implications for prevention and early intervention. In the current study, changes in whole brain structural and functional connectomes were investigated in youth at transdiagnostic risk over a one-year period. Based on clinical assessments, participants were assigned to one of 5 groups: healthy controls (HC; n = 33), familial risk for serious mental illness (stage 0; n = 31), mild symptoms (stage 1a; n = 37), attenuated syndromes (stage 1b; n = 61), or discrete disorder (transition; n = 9). Constrained spherical deconvolution was used to generate whole brain tractography maps, which were then used to calculate connectivity matrices for graph theory analysis. Graph theory was also used to analyze correlations of functional magnetic resonance imaging (fMRI) signal between pairs of brain regions. Linear mixed models revealed structural and functional abnormalities in global metrics of small world lambda, and resting state networks involving the fronto-parietal, default mode, and deep grey matter networks, along with the visual and dorsal attention networks. Machine learning analysis additionally identified changes in nodal metrics of betweenness centrality in the angular gyrus and bilateral temporal gyri as potential features which can discriminate between the groups. Our findings further support the view that abnormalities in large scale networks (particularly those involving fronto-parietal, temporal, default mode,and deep grey matter networks) may underlie transdiagnostic risk for SMIs.

Radiofrequency ablation guided by real-time cardiovascular magnetic resonance.

Cardiovascular magnetic resonance (CMR) is gaining ground in guiding electrophysiology (EP)-based ablation procedures of typical atrial flutter and atrial fibrillation, allowing for the avoidance of radiation exposure for patients and operators and reducing the risk of occupational illnesses. CMR allows comprehensive assessment of cardiac anatomy and provides tissue characterization by identifying pathological substrates, such as myocardial scars and edema, identified with the implementation of late gadolinium enhancement and T2-weighted short-tau inversion recovery sequences. Intraprocedural imaging is useful for real-time catheter tracking during the ablation procedure while simultaneously providing visualization of cardiac anatomy. Additionally, CMR facilitates the evaluation of the ablation procedure accuracy by acquiring edema-sensitive sequences, thereby aiding in preventing early complications. This report serves as a primer for radiologists and illustrates the value of CMR in planning and performing the ablation procedure, as well as its role in post-procedural imaging.

Enhanced predictability and interpretability of COVID-19 severity based on SARS-CoV-2 genomic diversity: a comprehensive study encompassing four years of data.

Despite the end of the global Coronavirus Disease 2019 (COVID-19) pandemic, the risk factors for COVID-19 severity continue to be a pivotal area of research. Specifically, studying the impact of the genomic diversity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on COVID-19 severity is crucial for predicting severe outcomes. Therefore, this study aimed to investigate the impact of the SARS-CoV-2 genome sequence, genotype, patient age, gender, and vaccination status on the severity of COVID-19, and to develop accurate and robust prediction models. The training set (n = 12,038), primary testing set (n = 4,006), and secondary testing set (n = 2,845) consist of SARS-CoV-2 genome sequences with patient information, which were obtained from Global Initiative on Sharing all Individual Data (GISAID) spanning over four years. Four machine learning methods were employed to construct prediction models. By extracting SARS-CoV-2 genomic features, optimizing model parameters, and integrating models, this study improved the prediction accuracy. Furthermore, Shapley Additive exPlanes (SHAP) was applied to analyze the interpretability of the model and to identify risk factors, providing insights for the management of severe cases. The proposed ensemble model achieved an F-score of 88.842% and an Area Under the Curve (AUC) of 0.956 on the global testing dataset. In addition to factors such as patient age, gender, and vaccination status, over 40 amino acid site mutation characteristics were identified to have a significant impact on the severity of COVID-19. This work has the potential to facilitate the early identification of COVID-19 patients with high risks of severe illness, thus effectively reducing the rates of severe cases and mortality.

Understanding occupational therapy perinatal mental health practice in mothers from ethnic minorities: A qualitative study of practitioner perceived barriers and enablers

Introduction: In the United Kingdom, ethnic minority mothers experience increased risk of mental illness compared to white women of British heritage. However, there is insufficient research to guide perinatal mental health occupational therapists to develop services that are accessible and meet the diverse needs of service users. This study explored perinatal mental health occupational therapists’ perceptions of the barriers and enablers to an inclusive service provision for ethnic minority mothers. Methods: A qualitative study was undertaken. Recruitment via social media used non-probability sampling. Semi-structured interviews collected data which were then analysed thematically. Results: Eight occupational therapist participated in the study. Three main themes were identified: observation of caseloads; experience of providing occupational therapy; influence of the therapist’s culture. Participants perceived stigma, fear, language and cultural perceptions created barriers for ethnic minority mothers. Discussion: Limited workforce diversity, ineffective mandatory training and insufficient referral to occupational therapy by other healthcare professionals were believed to negatively impact service delivery. Cultural experience and reflective practice were felt to enable inclusive practice. Recommendations to inform perinatal mental health occupational therapy practice in the United Kingdom and internationally include collaborations to gain a more diverse workforce, improved mandatory training and strategies to increase cultural sensitivity and competence.

History of Concussion and Risk of Severe Maternal Mental Illness: A Population-Based Cohort Study.

History of Concussion and Risk of Severe Maternal Mental Illness: A Population-Based Cohort Study.

Health outcomes reported by healthcare providers and clients of a community-based medically tailored meal program

BackgroundMedically tailored meal (MTM) programs provide home-delivered meals to people living with serious illness and poor nutritional status. Client outcome studies have found evidence of decreased healthcare utilization and cost savings associated with MTM program participation, and inconclusive evidence of change in health measures. The purpose of this study was to use a novel observational framework to describe the client profile and change in health outcomes using routinely collected health and program data from a community-based MTM program at MANNA (Philadelphia, PA).MethodsClients reported their self-rated health and experiences of food insecurity and malnutrition. Healthcare providers reported clients’ body mass index, systolic blood pressure, and hemoglobin A1C. These health outcomes, measured at program intake and 3–6 months later, were linked with administrative data for 1,959 clients who completed at least two months of MTM services in 2020, 2021, and 2022.ResultsClients exhibited substantial heterogeneity in demographics and health status at intake. Self-reported malnutrition risk decreased significantly over program duration (p < .001). Nearly one-third of clients with poor health reported improvement over time. Over 60% of clients with obesity experienced stable BMI. Clients with hypertension experienced significant improvements in systolic blood pressure (p < .001). Clients with diabetes and available data (n = 45) demonstrated significant reduction in hemoglobin A1C (p = .005).ConclusionWe found evidence that participation in MANNA’s MTM program was associated with favorable health outcomes for clients with serious illness and nutritional risk. Community-based organizations can maximize the completeness of their data by focusing on routinely collected internal data like validated health screeners and surveys.

Textile Fabric Defect Detection Using Enhanced Deep Convolutional Neural Network with Safe Human–Robot Collaborative Interaction

The emergence of modern robotic technology and artificial intelligence (AI) enables a transformation in the textile sector. Manual fabric defect inspection is time-consuming, error-prone, and labor-intensive. This offers a great possibility for applying more AI-trained automated processes with safe human–robot interaction (HRI) to reduce risks of work accidents and occupational illnesses and enhance the environmental sustainability of the processes. In this experimental study, we developed, implemented, and tested a novel algorithm that detects fabric defects by utilizing enhanced deep convolutional neural networks (DCNNs). The proposed method integrates advanced DCNN architectures to automatically classify and detect 13 different types of fabric defects, such as double-ends, holes, broken ends, etc., ensuring high accuracy and efficiency in the inspection process. The dataset is created through augmentation techniques and a model is fine-tuned on a large dataset of annotated images using transfer learning approaches. The experiment was performed using an anthropomorphic robot that was programmed to move above the fabric. The camera attached to the robot detected defects in the fabric and triggered an alarm. A photoelectric sensor was installed on the conveyor belt and linked to the robot to notify it about an impending fabric. The CNN model architecture was enhanced to increase performance. Experimental findings show that the presented system can detect fabric defects with a 97.49% mean Average Precision (mAP).

Impact of Age and Comorbid Conditions on Incidence Rates of COVID‐19‐Associated Hospitalizations, 2020–2021

ABSTRACTBackgroundCOVID‐19‐associated hospitalization rates by age and comorbid conditions can more precisely assess risk for severe illness and target prevention and treatment strategies.MethodsWe performed a retrospective study to estimate population‐based COVID‐19‐associated hospitalization among patients by age and selected comorbid conditions in three hospital systems in Rochester and New York City (NYC), NY. Incidence rate ratios (IRR) comparing incidence rates for patients with and without these comorbidities were determined.ResultsFrom March 2020 to December 2021, 7779 patients were hospitalized with COVID‐19 of whom 43.8% had ≥3 comorbid conditions. Overall annual incidence ranged from 325.3 to 965.8 per 100,000 persons. Age group‐specific incidence was lowest in children 10–14 years (range 4.4–58.9) and highest in adults ≥85 years (range 2790.5–5889.6). Incidence rates for comorbid conditions generally increased with increasing age while IRR decreased with increasing age. Children in NYC 5–17 years with asthma or obesity had 3.4 and 53.3 times higher hospitalization rates, respectively, than children without these conditions. Adults in all age groups with obesity, diabetes, coronary artery disease, or congestive heart failure CHF had 1.6–4.7 times, 1.7–7.2 times, 2.0–10.1 times, or 1.7–20.2 times higher hospitalization rates, respectively, than those without these conditions. Adults ≥50 years with asthma had 1.5 to 1.8 times higher hospitalization rates than those without asthma.ConclusionsThe burden of hospitalization with COVID‐19 was high, particularly among adults ≥85 years and adults with obesity, diabetes, CAD, or CHF. However, the impact of comorbidities was less in older adults. Population‐based incidence rates by age and comorbidities provide more precise estimates of the benefits of vaccines and antiviral medications.

“There's a lot of factors”: Researcher reflections on using I-Poetry to empathetically understand vaccine hesitant individuals

Background: Despite higher vaccination rates compared to other age groups, many US older adults remain under-vaccinated against preventable diseases leading to increased risk of serious illness, hospitalization, or death posed from disease. This study investigates the underlying reasons for older adults not getting vaccinated. Methods: From a larger interview study conducted in North Dakota, eight older adults (Mean Age = 73) were identified as being vaccine hesitant. Participants were asked, “How do you decide about whether or not to get a specific vaccine?” Then, participants' responses were analyzed using the I-poetry qualitative methodology, which involves creating a poem from interview transcripts to capture the essence of participants' experiences. Results: Poetic findings clarify interacting sources of immunization unease and highlight potential intervention avenues for medical professionals. Specifically, the poetic analysis revealed themes of mistrust in the healthcare system, preference for natural immunity, and concerns about vaccine side effects. The study suggests that healthcare professionals should consider using empathetic communication strategies to address vaccine hesitancy in older adults. Conclusions: Understanding vaccine hesitancy as a tapestry instead of individual factors may be more useful for older adults who culminate their hesitant beliefs from prior life experiences. Additionally, to improve trust in healthcare providers, it is suggested that more first-person narratives of older adult experiences are used and solicited by healthcare providers. Possible interventions are discussed.

Two-year trajectories of anhedonia in adolescents at transdiagnostic risk for severe mental illness: Association with clinical symptoms and brain-symptom links.

Anhedonia emerges during adolescence and is characteristic of severe mental illness (SMI). To understand how anhedonia emerges, changes with time, and relates with other symptoms, there is a need to understand patterns of this symptom's course reflecting change or stability-and associations with clinical symptoms and neural reward circuitry in adolescents at risk of SMI. In total, 113 adolescents at low or high familial risk of developing SMI completed clinical measures at up to five time points across 2 years and functional magnetic resonance imaging scanning during a guessing reward task at baseline. Growth curve analysis was used to determine the trajectory of anhedonia across 2 years, including different phases (consummatory and anticipatory) and their association with clinical features (risk status, average suicidal ideation, and average depression across time) and neural activation in response to rewards (ventral striatum and dorsal medial prefrontal cortex). The findings revealed anhedonia decreased across 2 years. Furthermore, lower depression severity was associated with decreases in anhedonia across 2 years. There were no interactions between neural reward activation and anhedonia slopes in predicting clinical features. Exploratory analyses examining latent classes revealed three trajectory classes of anhedonia across phases. While preliminary, in the low and decreasing consummatory anhedonia trajectory class, there was a positive association between neural activation of the right ventral striatum in response to rewards and depression. Certain patterns of anhedonia development could confer risk or resilience for specific types of psychopathologies. The results are preliminary but do highlight the complexity and heterogeneity in anhedonia development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).