Tag: nevin manimala

Consort Psychiatr. 2022 Dec 28;3(4):28-37. doi: 10.17816/CP211. eCollection 2022.

ABSTRACT

BACKGROUND: There has been an increase in the prevalence of autism spectrum disorders (ASD) worldwide over the past decades. Studies have shown that the number of confirmed diagnoses correlates with the awareness of the disorder among the general public and the professional community, in particular, as well as the availability of formalized screening procedures and modern medical and educational tools for families raising children with ASD in regional population centers. Thus, comparing autism prevalence rates in regions of the same country helps identify regions with limited access to diagnostic services and adequate medical care.

AIM: To estimate the overall number of individuals meeting the diagnostic criteria for ASD in Russia and determine the differences in the number of registered individuals with established diagnosis in the constituent territories of the Russian Federation.

METHODS: We conducted a retrospective, observational study and analyzed data from official statistical reports (form 12 “Information on the Number of Diseases Registered in Patients Residing in the Service Area of a Healthcare Institution” for 2020-2021).

RESULTS: A steady upward trend in the number of individuals with autism has been observed since 2014 in the Russian Federation as a whole and in the federal districts, although the prevalence rates differ from the global median prevalence of ASD (all-Russian figure by almost 40 times). In addition, regional differences (by 104.5 times) in the frequency of the diagnosis have been revealed: from a minimum of 1.7 to a maximum of 177.7 per 100,000 population. The percentile distribution of the number of individuals with ASD that are followed-up at healthcare facilities in the constituent territories of the Russian Federation was in the interquartile range (25-75th percentile), below the 25th percentile, and above the 75th percentile in 38, 26 and 21 regions, respectively.

CONCLUSION: The study has shown significant differences in the ASD diagnosis rates by regions in the country against a backdrop of a low (compared to international data) number of registered cases of autism. The presented data suggest that, due to the lack of proper diagnosis, a significant number of individuals with ASD do not receive adequate medical care, nor do they receive social, psychological, or pedagogical support. Possible reasons for this probably include low awareness of new diagnostic approaches among psychiatrists; low level of involvement of pediatrics professionals in screening activities; and fear of stigmatization because of a psychiatric diagnosis in the absence of a developed medical care infrastructure that encompasses a social, psychological, and pedagogical support system for people with ASD.

PMID:39045584 | PMC:PMC11262083 | DOI:10.17816/CP211

Consort Psychiatr. 2022 Dec 28;3(4):8-17. doi: 10.17816/CP206. eCollection 2022.

ABSTRACT

BACKGROUND: The existing research has mainly focused on exploring how the duration of untreated psychosis effects the further course of the disease. By contrast, the duration of an untreated illness (DUI) in youth depression and its impact on the further course of the disease has remained scarcely investigated.

AIM: The current study aims to determine how the duration of untreated illness affects the severity of the symptoms during the first depressive episode and the degree to which the symptoms are reduced after treatment.

METHODS: Fifty-two young male patients (15-29 years old) were examined. First, they were hospitalized with a severe without psychotic symptoms (F32.2) and moderate (F32.1) depressive episode. The Hamilton Depression Rating Scale (HDRS), the Scale of Prodromal Symptoms (SOPS), and the Scale for Assessment of Negative Symptoms (SANS) were used to achieve the research goals. The examination was conducted twice at the time of patient admission to the hospital and before discharge. Our statistical analysis was carried out with the Statistica 12 software. The Mann-Whitney U test was used to compare the differences between two independent groups. The Spearman’s rank correlation coefficient was used to uncover any correlation between how long the illness has remained untreated and the severity of its clinical symptoms.

RESULTS: All patients were hospitalized at the first depressive episode. The average duration of an untreated illness was 35.8±17.0 months. The patients were divided into two groups: the first group (59.6%, n=31), with a duration of the untreated illness of more than 36 months, and the second group (40.4%, n=21), with a duration of the untreated illness of less than 36 months. A cross-group comparison between the participants showed that the reduction of HDRS scores was significantly higher in the second group (p=0.019) at the time of discharge, with no differences in the severity of depressive symptoms (p=0.544) at the time of admission. Comorbidity was detected in 83.9% of the patients in the first group and in 42.9% of the patients in the second group. A greater therapy effectiveness was found to exist in the second group, as the depressive symptoms score on the HDRS scale (p=0.016; U=196.0) and prodromal symptoms score on the SOPS disorganization subscale (p=0.046; U=218.0) were found to have been reduced significantly.

CONCLUSION: The study showed that DUI has an impact on the reduction of depressive, negative symptoms and symptoms of disorganization in youth patients at the first depressive episode. A high level of comorbidity has been uncovered, confirming that a variety of non-psychotic and psychotic disorders in youth manifest themselves in depression at a prodromal stage, causing difficulties in establishing diagnoses and requiring subsequent verification. Future research might need to focus on exploring depressive symptoms as predictors of mental disorders in youth patients.

PMID:39045583 | PMC:PMC11262081 | DOI:10.17816/CP206

Front Psychiatry. 2024 Jul 9;15:1433316. doi: 10.3389/fpsyt.2024.1433316. eCollection 2024.

ABSTRACT

INTRODUCTION: Difficulty falling asleep place an increasing burden on society. EEG-based sleep staging is fundamental to the diagnosis of sleep disorder, and the selection of features for each sleep stage is a key step in the sleep analysis. However, the differences of sleep EEG features in gender and age are not clear enough.

METHODS: This study aimed to investigate the effects of age and gender on sleep EEG functional connectivity through statistical analysis of brain functional connectivity and machine learning validation. The two-overnight sleep EEG data of 78 subjects with mild difficulty falling asleep were categorized into five sleep stages using markers and segments from the “sleep-EDF” public database. First, the 78 subjects were finely grouped, and the mutual information of the six sleep EEG rhythms of δ, θ, α, β, spindle, and sawtooth wave was extracted as a functional connectivity measure. Then, one-way analysis of variance (ANOVA) was used to extract significant differences in functional connectivity of sleep rhythm waves across sleep stages with respect to age and gender. Finally, machine learning algorithms were used to investigate the effects of fine grouping of age and gender on sleep staging.

RESULTS AND DISCUSSION: The results showed that: (1) The functional connectivity of each sleep rhythm wave differed significantly across sleep stages, with delta and beta functional connectivity differing significantly across sleep stages. (2) Significant differences in functional connections among young and middle-aged groups, and among young and elderly groups, but no significant difference between middle-aged and elderly groups. (3) Female functional connectivity strength is generally higher than male at the high-frequency band of EEG, but no significant difference in the low-frequency. (4) Finer group divisions based on gender and age can indeed improve the accuracy of sleep staging, with an increase of about 3.58% by using the random forest algorithm. Our results further reveal the electrophysiological neural mechanisms of each sleep stage, and find that sleep functional connectivity differs significantly in both gender and age, providing valuable theoretical guidance for the establishment of automated sleep stage models.

PMID:39045546 | PMC:PMC11264056 | DOI:10.3389/fpsyt.2024.1433316

SAGE Open Med. 2024 Jun 24;12:20503121241260149. doi: 10.1177/20503121241260149. eCollection 2024.

ABSTRACT

INTRODUCTION: Imposter syndrome is common among health disciplinary students, leading to serious consequences. However, the impact of imposter syndrome on self-esteem and quitting intention among respiratory therapy students has not been well researched.

OBJECTIVE: To report on the prevalence of imposter syndrome and assess its impacts on self-esteem and quitting intention among respiratory therapy students in Saudi Arabia.

METHODS: A nonprobability cross-sectional questionnaire using the Clance Impostor Phenomenon Scale and the Rosenberg Self-Esteem Scale was self-administered and distributed among respiratory therapy students between October 2022 and April 2023. Data analysis was performed using Descriptive and inferential statistics.

RESULTS: Of the 1500 respiratory therapy students invited to participate in the study, 901 surveys were completed; and thus, included in the final analysis. Of whom, 92% were presented with imposter syndrome: 44% with moderate, 35% with frequent, and 13% with intense feelings. In addition, 60% of respiratory therapy students and interns experienced low self-esteem, while only 0.5% indicated high self-esteem. More than 50% of the study participants thought about quitting the respiratory therapy program, and 30% have been diagnosed with psychological disorders. Furthermore, there was a significant association between imposter syndrome and low self-esteem, p < 0.001. Factors associated with imposter syndrome and low self-esteem were family income (<0.005) and parents’ education (<0.005), quitting intention (<0.005), and having been diagnosed with psychological disorders (<0.005). Genders, academic levels, and grade point average were not associated with either imposter syndrome or self-esteem (>0.005).

CONCLUSION: Imposter syndrome and low self-esteem are prevalent among respiratory therapy students, both of which are associated with considering leaving the respiratory therapy program. Effective interventions should be implemented to ameliorate the symptoms imposter syndrome and low self-esteem; thus, improving the academic experience of respiratory therapy students.

PMID:39045543 | PMC:PMC11265236 | DOI:10.1177/20503121241260149

Front Hum Neurosci. 2024 Jul 9;18:1360218. doi: 10.3389/fnhum.2024.1360218. eCollection 2024.

ABSTRACT

Affect-biased attention is the phenomenon of prioritizing attention to emotionally salient stimuli and away from goal-directed stimuli. It is thought that affect-biased attention to emotional stimuli is a driving factor in the development of depression. This effect has been well-studied in adults, but research shows that this is also true during adolescence, when the severity of depressive symptoms are correlated with the magnitude of affect-biased attention to negative emotional stimuli. Prior studies have shown that trainings to modify affect-biased attention may ameliorate depression in adults, but this research has also been stymied by concerns about reliability and replicability. This study describes a clinical application of augmented reality-guided EEG-based attention modification (“AttentionCARE”) for adolescents who are at highest risk for future depressive disorders (i.e., daughters of depressed mothers). Our results (n = 10) indicated that the AttentionCARE protocol can reliably and accurately provide neurofeedback about adolescent attention to negative emotional distractors that detract from attention to a primary task. Through several within and cross-study replications, our work addresses concerns about the lack of reliability and reproducibility in brain-computer interface applications, offering insights for future interventions to modify affect-biased attention in high-risk adolescents.

PMID:39045509 | PMC:PMC11264899 | DOI:10.3389/fnhum.2024.1360218

Ecol Evol. 2024 Jul 23;14(7):e11569. doi: 10.1002/ece3.11569. eCollection 2024 Jul.

ABSTRACT

Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β-diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species-neutral dissimilarity (Bray-Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large-scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity.

PMID:39045499 | PMC:PMC11264350 | DOI:10.1002/ece3.11569

J Multidiscip Healthc. 2024 Jul 5;17:3121-3139. doi: 10.2147/JMDH.S468845. eCollection 2024.

ABSTRACT

BACKGROUND: The rapid growth of social media has profoundly transformed communication, community building, and information sharing worldwide. In Afghanistan, the proliferation of social media platforms has significantly impacted the social, cultural, and political landscape, particularly among the youth.

OBJECTIVE: This multi-disciplinary study aims to explore the diverse effects of social media on Afghan youth, focusing on usage patterns, mental health implications, entertainment-driven time allocation, financial expenditures, exposure to explicit content, and academic performance.

METHODS: A cross-sectional online survey was conducted between September and December 2023, gathering responses from 1556 participants (67% males, 33% females) through various social media platforms. Data were analyzed using SPSS version 26.0, employing statistical tests such as ANOVA and Chi-Square to examine relationships between social media usage and its impacts.

RESULTS: The study reveals significant links between social media usage and demographic, behavioral, and mental health factors. Key findings include Facebook as the most used platform (83.6%), with the majority of participants spending 1-3 hours daily on social media. Age differences in time spent were significant (F=15.64, p<0.001). Entertainment was the primary use (45.5%), with gender differences in engagement levels. High anxiety (78.5%) and moderate depression (38.3%) were reported. Significant associations between social media use and mental health were found (eg, χ2=591.87, p<0.001 for nervousness). Excessive use negatively impacted study habits, with 25.7% feeling it hindered their academic performance.

CONCLUSION: This study highlights the multifaceted impacts of social media on Afghan youth, including both positive aspects like enhanced communication and empowerment and negative aspects such as mental health issues and academic challenges. The significant relationships between social media usage and various life aspects underscore the need for targeted interventions to promote healthy digital habits and mitigate adverse effects. Further research is recommended to explore long-term impacts and effective strategies for managing social media use among Afghan youth.

PMID:39045489 | PMC:PMC11264374 | DOI:10.2147/JMDH.S468845

Environ Epidemiol. 2024 Jun 25;8(4):e314. doi: 10.1097/EE9.0000000000000314. eCollection 2024 Aug.

ABSTRACT

BACKGROUND: Air pollution health risk assessment (HRA) has been typically conducted for all causes and cause-specific mortality based on concentration-response functions (CRFs) from meta-analyses that synthesize the evidence on air pollution health effects. There is a need for a similar systematic approach for HRA for morbidity outcomes, which have often been omitted from HRA of air pollution, thus underestimating the full air pollution burden. We aimed to compile from the existing systematic reviews and meta-analyses CRFs for the incidence of several diseases that could be applied in HRA. To achieve this goal, we have developed a comprehensive strategy for the appraisal of the systematic reviews and meta-analyses that examine the relationship between long-term exposure to particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM_2.5), nitrogen dioxide (NO₂), or ozone (O₃) and incidence of various diseases.

METHODS: To establish the basis for our evaluation, we considered the causality determinations provided by the US Environmental Protection Agency Integrated Science Assessment for PM_2.5, NO₂, and O₃. We developed a list of pollutant/outcome pairs based on these assessments and the evidence of a causal relationship between air pollutants and specific health outcomes. We conducted a comprehensive literature search using two databases and identified 75 relevant systematic reviews and meta-analyses for PM_2.5 and NO₂. We found no relevant reviews for long-term exposure to ozone. We evaluated the reliability of these studies using an adaptation of the AMSTAR 2 tool, which assesses various characteristics of the reviews, such as literature search, data extraction, statistical analysis, and bias evaluation. The tool’s adaptation focused on issues relevant to studies on the health effects of air pollution. Based on our assessment, we selected reviews that could be credible sources of CRF for HRA. We also assessed the confidence in the findings of the selected systematic reviews and meta-analyses as the sources of CRF for HRA. We developed specific criteria for the evaluation, considering factors such as the number of included studies, their geographical distribution, heterogeneity of study results, the statistical significance and precision of the pooled risk estimate in the meta-analysis, and consistency with more recent studies. Based on our assessment, we classified the outcomes into three lists: list A (a reliable quantification of health effects is possible in an HRA), list B+ (HRA is possible, but there is greater uncertainty around the reliability of the CRF compared to those included on list A), and list B- (HRA is not recommended because of the substantial uncertainty of the CRF).

RESULTS: In our final evaluation, list A includes six CRFs for PM_2.5 (asthma in children, chronic obstructive pulmonary disease, ischemic heart disease events, stroke, hypertension, and lung cancer) and three outcomes for NO₂ (asthma in children and in adults, and acute lower respiratory infections in children). Three additional outcomes (diabetes, dementia, and autism spectrum disorders) for PM_2.5 were included in list B+. Recommended CRFs are related to the incidence (onset) of the diseases. The International Classification of Diseases, 10th revision codes, age ranges, and suggested concentration ranges are also specified to ensure consistency and applicability in an HRA. No specific suggestions were given for ozone because of the lack of relevant systematic reviews.

CONCLUSION: The suggestions formulated in this study, including CRFs selected from the available systematic reviews, can assist in conducting reliable HRAs and contribute to evidence-based decision-making in public health and environmental policy. Future research should continue to update and refine these suggestions as new evidence becomes available and methodologies evolve.

PMID:39045486 | PMC:PMC11265782 | DOI:10.1097/EE9.0000000000000314

Paediatr Child Health. 2023 Jul 19;29(4):216-223. doi: 10.1093/pch/pxad040. eCollection 2024 Jul.

ABSTRACT

OBJECTIVES: Due to their medical and technology dependence, families of children with medical complexity (CMC) have significant costs associated with care. Financial impact on families in general have been described, but detailed exploration of expenses in specific categories has not been systematically explored. Our objective was to describe out-of-pocket (OOP) expenses incurred by caregivers of CMC and to determine factors associated with increased expenditures.

METHODS: This is a secondary observational analysis of data primary caregiver-reported OOP expenses as part of a randomized control trial conducted in Ontario, Canada. Caregivers completed questionnaires reporting OOP costs. Descriptive statistics were utilized to report OOP expenses and a linear regression model was conducted.

RESULTS: 107 primary caregivers of CMC were included. The median (IQR) age of participants was 34.5 years (30.5 to 40.5) and 83.2% identified as the mother. The majority were married or common-law (86.9%) and 50.5% were employed. The participant’s children [median (IQR) age 4.5 (2.2 to 9.7); 57.9% male] most commonly had a neurological/neuromuscular primary diagnosis (46.1%) and 88% utilized medical technology. Total OOP expenses were $8,639 CDN annually (IQR = $4,661 to $31,326) with substantial expenses related to childcare/homemaking, travel to appointments, hospitalizations, and device costs. No factors associated with greater likelihood of OOP expenses were identified. A P-value of <0.05 was considered significant.

CONCLUSION: Caregivers of CMC incur significant OOP expenses related to the care of their children resulting in financial burden. Future exploration of the financial impact on caregiver productivity, employment, and identification of resources to mitigate OOP expenses will be important for this patient population.

PMID:39045474 | PMC:PMC11261824 | DOI:10.1093/pch/pxad040

J Am Stat Assoc. 2024;119(546):904-914. doi: 10.1080/01621459.2022.2147531. Epub 2023 Jan 5.

ABSTRACT

Predicting the response at an unobserved location is a fundamental problem in spatial statistics. Given the difficulty in modeling spatial dependence, especially in non-stationary cases, model-based prediction intervals are at risk of misspecification bias that can negatively affect their validity. Here we present a new approach for model-free nonparametric spatial prediction based on the conformal prediction machinery. Our key observation is that spatial data can be treated as exactly or approximately exchangeable in a wide range of settings. In particular, under an infill asymptotic regime, we prove that the response values are, in a certain sense, locally approximately exchangeable for a broad class of spatial processes, and we develop a local spatial conformal prediction algorithm that yields valid prediction intervals without strong model assumptions like stationarity. Numerical examples with both real and simulated data confirm that the proposed conformal prediction intervals are valid and generally more efficient than existing model-based procedures for large datasets across a range of non-stationary and non-Gaussian settings.

PMID:39045463 | PMC:PMC11262549 | DOI:10.1080/01621459.2022.2147531