Category: Nevin Manimala

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

Consort Psychiatr. 2021 Dec 31;2(4):2-12. doi: 10.17816/CP112. eCollection 2021.

ABSTRACT

INTRODUCTION: Common mental disorders – anxiety and depression – are prevalent among patients with cardiovascular disease (CVD) and diabetes mellitus type 2 (DM) and can negatively influence treatment outcomes and healthcare expenses. Despite the importance of management of depression and anxiety in primary care facilities, the diagnostics and treatment of these disorders remain insufficient in the Russian Federation.

AIM: To explore whether the rates of referrals to psychiatrists and indicated pharmacological treatment received due to depression or anxiety among patients with CVD and DM will significantly change in primary healthcare facilities after the training of primary care physicians (PCPhs) to deal with comorbid depression and anxiety (including the algorithm for referral to a psychiatrist).

METHODS: Patients in primary care outpatient settings with diagnoses of CVD and DM passed screening on anxiety and depression using the Hospital Anxiety and Depression Scale (HADS), and information about the indicated treatment for anxiety or depression was collected when present (Sample 1: n=400). The educational programme for PCPhs on the diagnostics of anxiety and depression was then performed, and PCPhs were instructed to refer patients with HADS >7 to a psychiatrist. After the training, the second sample was collected (Sample 2: n=178) using the same assessments as for Sample 1. The independent expert (psychiatrist) evaluated whether the patients had received the indicated pharmacological treatment according to the screening criteria used in the study for anxiety and depression for both samples.

RESULTS: The proportions of patients with borderline abnormal and abnormal HADS scores (>7) were 365 (91.2%) and 164 (92.1%) in Sample 1 and Sample 2, respectively. In Sample 1, among patients with HADS >7, 119 (29.8%) received psychopharmacological treatment, but in only 46 (38.7%) cases was it indicated in compliance with the screening criteria. In Sample 2, among patients with HADS >7, 59 (33.1%) received psychopharmacological treatment, and in only 14 (23.7%) cases was it indicated in compliance with the screening criteria. The differences in the indicated pharmacological treatment were not statistically significant, and no one from Sample 2 with HADS >7 met a psychiatrist through PCPh referral.

CONCLUSIONS: Anxiety and depression are prevalent in patients with CVD and DM treated in primary care facilities, but these patients may not be receiving the indicated pharmacological treatment. Barriers to referral and the use of psychiatric consultation exist despite the focused training of PCPhs and the straightforward referral protocol provided.

PMID:39045451 | PMC:PMC11262072 | DOI:10.17816/CP112

Front Psychol. 2024 Jul 9;15:1400695. doi: 10.3389/fpsyg.2024.1400695. eCollection 2024.

ABSTRACT

INTRODUCTION: Fear of disease progression (FoP) has been identified as one of the most prevalent unmet needs among breast cancer patients in recent years. The aim of this study was to examine FoP in patients with breast cancer and explore its associations with demographic and clinical characteristics, self-management efficacy, and family functioning. We also aimed to create a clinically-relevant prediction model based off of these factors (i.e., a “nomogram”) to help identify patients’ probability of experiencing high FoP.

METHODS: A cross-sectional survey of breast cancer in patients at the Affiliated Hospital of Jiangnan University was conducted from June 2023 to February 2024. The study included the Demographic and Clinical Characteristics Questionnaire, the Fear of Disease Progression Scale (FoP-Q-SF), the Chinese Self-Management Efficacy Scale for Cancer Patients (C-SUPPH), and the Family Care Index Questionnaire (APGAR). Data analysis included descriptive statistics, independent-samples t-test, one-way ANOVA, Pearson correlation analysis, and multiple regression analysis. A nomogram was constructed based on multiple regression results and the model performance was evaluated.

RESULTS: A total of 151 breast cancer patients were enrolled in the study. The mean (standard deviation) FoP score of the patients was 35.87 ± 9.24. The average score of C-SUPPH was 96.97 ± 17.29, and the average score of APGAR was 6.74 ± 2.98. Pearson correlation analysis showed that FoP was negatively correlated with self-management efficacy (r = -0.544, p < 0.01) and family functioning (r = -0.730, p < 0.01). Multiple regression analysis showed that age (B = -4.038), self-management efficacy (B = -0.085) and family functioning (B = -1.972) were significantly related to FoP, and together explained 36% of FoP variation (R ² = 0.360, F = 20.50, p < 0.001). The nomogram of these variables showed satisfactory prediction performance [the Bootstrap Correction Consistency Index (C-index) = 0.872]. According to previous studies, a C-index of >0.70 indicates that the model is acceptable.

CONCLUSION: We found that greater fear of cancer progression (FoP) was associated with younger age, lower self-management efficacy and poorer family functioning in breast cancer patients. Based on these variables, our exploratory prediction model should be further investigated in order to help identify breast cancer patients who may be at highest risk of experiencing high FoP.

PMID:39045441 | PMC:PMC11264380 | DOI:10.3389/fpsyg.2024.1400695