RATIONALE: Patients who experience seizures, including PNES, are usually advised to discontinue driving, or have their driving privileges revoked until a determined period of seizure-freedom is achieved. In this retrospective study, patients with PNES who requested driving privileges or reported having resumed driving were compared to those who did not on measures of depression, anxiety, PTSD, and cognitive flexibility/motor speed. METHODS: DiagnosisofPNESwasconfirmedwithvideo-EEG.Demographicand clinical dataand requests for reinstatement of driving privileges (requiring 6 or more months seizure freedom) and reports of decisions to resume driving were noted. Tests of motor speed and hand eye coordination and self-report questionnaires of depression, anxiety and PTSD administered as part of neuropsychological assessment were analyzed. RESULTS: A total of 403 patients with PNES evaluated in 2010-2020 were identified. Of those, 365 patients were eligible for inclusion, and of those, 60 applied for driving privileges or reported that they resumed driving. When the two groups were compared, the group that applied for driving privileges or decided to resume driving was significantly less depressed (p = 0.001) when tested than the group that did not. Furthermore, a significant difference was seen in measures of motor performance between those who requested to resume driving and those who did not (DKEFS T1, p = 0.006, DKEFS T2, p = 0.001, DKEFS T3, p = 0.002, DKEFS T4, p = 0.001; GPT dominant, p = 0.05, GPT non-dominant, p = 0.003). CONCLUSION: Driving a motor vehicle is a useful measure of improvement for PNES because patients with seizures are required to discontinue driving until seizure-freedom is achieved. This study revealed that lower levels of depression and better fine motor functioning were associated with reported seizure-freedom and driving resumption. Depression is commonly associated with diminished performance (slower motor response times and impaired fine motor movements) on tests of motor functioning, both of which may result in less interest in pursuing permission to resume driving. These findings suggest that mood symptoms (and associated performance on measures of motor speed and coordination) may have prognostic significance in patients diagnosed with PNES. This also suggests that timely treatment of depression in newly diagnosed patients with PNES may be indicated.

• Klíčová slova
• Depression, Disability, Driving, Functional dissociative seizures, Prognosis, Psychomotor speed,
• MeSH
• deprese psychologie   diagnóza   etiologie   MeSH
• dospělí MeSH
• elektroencefalografie MeSH
• konverzní poruchy psychologie   diagnóza   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• neuropsychologické testy MeSH
• posttraumatická stresová porucha psychologie   diagnóza   MeSH
• psychomotorický výkon fyziologie   MeSH
• psychosomatické poruchy diagnóza   psychologie   MeSH
• retrospektivní studie MeSH
• řízení motorových vozidel * psychologie   MeSH
• úzkost psychologie   etiologie   diagnóza   MeSH
• záchvaty * psychologie   diagnóza   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: There is a growing importance of loneliness measurement through valid and reliable instruments. However, to establish valid and reliable measures, there is a need to explore their psychometric properties in different research settings and language environments. For this reason, this study aimed to validate the Three Item Loneliness Scale (TILS) in the Czech Republic within a Slavonic language environment. METHODS: A sample of Czech adults (n = 3236) was used consisting primarily of university students. We utilized Classical Test Theory to assess TILS internal consistency, temporal stability, and factor structure. Item Response Theory (IRT) was used to estimate Differential Item Functioning (DIF), the discrimination and difficulty of the TILS items and to estimate the measurement precision of the whole scale. Construct validity was explored through the Spearman correlation coefficient using personality traits, depression, and anxiety. RESULTS: The results showed satisfactory reliability and validity of the TILS in the Czech Republic. The scale's internal consistency and temporal stability were found to be satisfactory (Cronbach's α = 0.81, McDonald's ω = 0.82, ICC = 0.71). The parallel analysis supported the unidimensionality of the TILS. The IRT results indicated that the highest measurement precision was reached in individuals with lower and above-average levels of loneliness. Significant correlations between the TILS scores, anxiety, depression, and personality traits supported the construct validity of the scale. Although the DIF analysis identified statistically significant differences in responses to items TILS_2 and TILS_3 based on education level and employment status (with no significant differences observed for TILS_1), the effect sizes of these differences were small. This indicates that, despite statistical significance, the practical impact on the scale's validity across these groups is minimal. CONCLUSIONS: The validated TILS provides a reliable and valid tool for assessing loneliness in the Czech Republic. Its brevity makes it a practical option for researchers and clinicians seeking to measure loneliness time-efficiently. Future studies should explore how adding new items could increase the measurement precision of the TILS.

• Klíčová slova
• Item response theory, Loneliness, Measurement, Psychometric Properties, TILS, Validation,
• MeSH
• deprese psychologie   diagnóza   MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• osamocení * psychologie   MeSH
• průzkumy a dotazníky normy   MeSH
• psychometrie * MeSH
• reprodukovatelnost výsledků MeSH
• úzkost psychologie   diagnóza   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Česká republika MeSH

OBJECTIVE: To compare persons with epilepsy (PWE) to those with psychogenic non-epileptic seizures (PNES) on measures of depression, anxiety, and alexithymia subscales (i.e., difficulty identifying emotions, difficulty describing emotions, and external-oriented thinking). MATERIAL AND METHODS: In this retrospective study, 235 epilepsy patients and 90 patients with PNES were evaluated between 2012 and 2020 at the Northeast Regional Epilepsy Group. These patients had completed the Toronto Alexithymia Scale (TAS-20), The Center for Epidemiologic Studies - Depression Scale (CES-D) and The State-Trait Anxiety Inventory (STAI). Background information was collected regarding work/student/disability status at the time of the evaluation history of psychiatric diagnosis; psychological trauma; and involvement in psychotherapy either at the time of the evaluation or prior. RESULTS: Significant differences between PWEs and those with PNES were found not only in historical data (e.g., Psychiatric History, History of Trauma, and History of Therapy) (p < .001) but also on measures of Depression (p = .002) and Anxiety (p < .001). ANOVA analysis also revealed significant differences in the distribution of the TAS-Total score, TAS-Describing emotions, and TAS-Identifying emotions. Using logistic regression (stepwise model) the optimal set of predictors for a differential diagnosis of epilepsy and PNES was combination of TAS-Identifying emotions score, history of psychological trauma, and history of therapy. The accuracy of the prediction was determined to be 80.2 %. CONCLUSIONS: Although higher alexithymia rates are present in PNES and PWEs, clinicians may find a combination of TAS-Identifying Emotion score, history of trauma, and history of psychotherapy useful in supporting a differential diagnosis. Also, a subgroup may exist among those with PNES with high levels of alexithymia, depression, and anxiety that may require a different treatment approach focused on addressing difficulties in identifying and describing their emotions and their other symptomatology.

• Klíčová slova
• Alexithymia, Anxiety, Depression, Epileptic seizures, Functional dissociative seizures, Functional neurological disorders,
• MeSH
• afekt fyziologie   MeSH
• afektivní symptomy * diagnóza   etiologie   MeSH
• deprese diagnóza   etiologie   MeSH
• dospělí MeSH
• epilepsie * psychologie   komplikace   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• psychiatrické posuzovací škály MeSH
• retrospektivní studie MeSH
• úzkost * diagnóza   etiologie   MeSH
• záchvaty * psychologie   diagnóza   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• srovnávací studie MeSH

BACKGROUND: Frailty is one of the key syndromes in geriatric medicine and an important factor for post-transplant outcomes. We aimed to describe the prevalence of frailty and examine the correlates of frailty and depressive symptoms in older kidney transplant recipients (KTRs). METHODS: This cross-sectional study involved 112 kidney transplant recipients (KTRs) aged 70 and above. Frailty syndrome was assessed using the Fried frailty criteria, and patients were categorized as frail, pre-frail, or non-frail based on five frailty components: muscle weakness, slow walking speed, low physical activity, self-reported exhaustion, and unintentional weight loss. Depressive symptoms were measured using the 15-item Geriatric Depression Scale (GDS). The relationship between frailty and depressive symptoms was evaluated using multinomial logistic regression, with the three frailty categories as the dependent variable and the severity of depressive symptoms as the independent variable, while controlling for age, gender, renal graft function, and time since transplant surgery. RESULTS: The participants had a mean age of 73.3 ± 3.3 years, and 49% were female. The prevalence of frailty syndrome was 25% (n = 28), pre-frailty was 46% (n = 52), and 29% (n = 32) of the KTRs were non-frail. The mean score for depressive symptoms was 3.1 ± 2.4 points, with 18% scoring above the clinical depression cutoff. Depressive symptoms were positively correlated with frailty (r = .46, p < .001). Among the frailty components, self-reported exhaustion (r = .43, p < .001), slow walking speed (r = .26, p < .01), and low physical activity (r = .44, p < .001) were significantly positively correlated with depressive symptoms, while muscle strength (p = .068) and unintentional weight loss (p = .050) were not. A multinomial logistic regression adjusted for covariates indicated that, compared to being non-frail, each additional point on the GDS increased the odds of being pre-frail by 39% (odds ratio [OR] = 1.39, 95% confidence interval [CI] 1.01-1.96) and roughly doubled the odds of being frail (OR = 2.01, 95% CI 1.39-2.89). CONCLUSION: There is a strong association between frailty and depression in KTRs aged 70 years and older. Targeted detection has opened up a new avenue for collaboration between geriatricians and transplant nephrologists.

• Klíčová slova
• Depression, Frailty, Geriatrics, Kidney transplantation, Posttransplant,
• MeSH
• deprese * epidemiologie   psychologie   diagnóza   MeSH
• geriatrické hodnocení metody   MeSH
• geriatrie metody   trendy   MeSH
• křehkost * epidemiologie   diagnóza   psychologie   MeSH
• křehký senior psychologie   MeSH
• lidé MeSH
• nefrologové trendy   MeSH
• prevalence MeSH
• příjemce transplantátu psychologie   MeSH
• průřezové studie MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• transplantace ledvin * psychologie   MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Depression and anxiety are among the most prevalent mental health issues experienced worldwide. However, whereas cross-cultural studies utilize psychometrically valid and reliable scales, fewer can meaningfully compare these conditions across different groups. To address this gap, the current study aimed to psychometrically assess the Brief Symptomatology Index (BSI) in 42 countries. METHODS: Using data from the International Sex Survey (N = 82,243; Mage = 32.39; SDage = 12.52; women: n = 46,874; 57 %), we examined the reliability of depression and anxiety symptom scores of the BSI-18, as well as evaluated evidence of construct, invariance, and criterion-related validity in predicting clinically relevant variables across countries, languages, genders, and sexual orientations. RESULTS: Results corroborated an invariant, two-factor structure across all groups tested, exhibiting excellent reliability estimates for both subscales. The 'caseness' criterion effectively discriminated among those at low and high risk of depression and anxiety, yielding differential effects on the clinical criteria examined. LIMITATIONS: The predictive validation was not made against a clinical diagnosis, and the full BSI-18 scale was not examined (excluding the somatization sub-dimension), limiting the validation scope of the BSI-18. Finally, the study was conducted online, mainly by advertisements through social media, ultimately skewing our sample towards women, younger, and highly educated populations. CONCLUSIONS: The results support that the BSI-12 is a valid and reliable assessment tool for assessing depression and anxiety symptoms across countries, languages, genders, and sexual orientations. Further, its caseness criterion can discriminate well between participants at high and low risk of depression and anxiety.

• Klíčová slova
• Anxiety, Brief Symptom Inventory, Cross-cultural, Depression, Measurement invariance, Psychometric,
• MeSH
• deprese * diagnóza   MeSH
• dítě MeSH
• dospělí MeSH
• lidé MeSH
• průzkumy a dotazníky MeSH
• psychometrie MeSH
• reprodukovatelnost výsledků MeSH
• srovnání kultur * MeSH
• úzkost diagnóza   MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely and precise recognition of depression is vital for appropriate mediation and effective treatment. Electroencephalography (EEG) has surfaced as a promising tool for inspecting the neural correlates of depression and therefore, has the potential to contribute to the diagnosis of depression effectively. This study presents an EEG-based mental depressive disorder detection mechanism using a publicly available EEG dataset called Multi-modal Open Dataset for Mental-disorder Analysis (MODMA). This study uses EEG data acquired from 55 participants using 3 electrodes in the resting-state condition. Twelve temporal domain features are extracted from the EEG data by creating a non-overlapping window of 10 seconds, which is presented to a novel feature selection mechanism. The feature selection algorithm selects the optimum chunk of attributes with the highest discriminative power to classify the mental depressive disorders patients and healthy controls. The selected EEG attributes are classified using three different classification algorithms i.e., Best- First (BF) Tree, k-nearest neighbor (KNN), and AdaBoost. The highest classification accuracy of 96.36% is achieved using BF-Tree using a feature vector length of 12. The proposed mental depressive classification scheme outperforms the existing state-of-the-art depression classification schemes in terms of the number of electrodes used for EEG recording, feature vector length, and the achieved classification accuracy. The proposed framework could be used in psychiatric settings, providing valuable support to psychiatrists.

• MeSH
• algoritmy MeSH
• deprese * diagnóza   MeSH
• elektroencefalografie MeSH
• lidé MeSH
• strojové učení MeSH
• support vector machine * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

PURPOSE OF THE STUDY: Cognitive disorders are common in geriatric surgical patients We conducted a study to evaluate depression and cognitive behavior in geriatric patients undergoing orthopedic surgery. MATERIAL AND METHODS: This descriptive cross-sectional study was conducted at a university hospital in Turkey, involving 262 elderly patients who underwent orthopedic surgeries. Data were collected using The Patient Information Form, Standardized Mini-Mental Test, and Geriatric Depression Scale. RESULTS: The mean score of the Standardized Mini-Mental Test scale of the patients after surgery was 17.97±4.99, mean score of the Geriatric Depression Scale was 6.20±2.78. The study revealed that 85.1% (n=223) of the participants had cognitive impairment and 69.1% (n=181) depressive symptoms. Additionally, cognitive impairment and depressive symptoms increased as age, pain scores, and length of hospital stay increased. Our research also showed that individuals with a history of falls, visual/hearing impairment, malnutrition, use of assistive devices, dependence on others for daily activities, non-educated or single, individuals are more likely to experience geriatric depression and have a higher of cognitive impairment. Additionally, patients who have had hip arthroplasty, have low hemoglobin levels, or have high ASA scores are more prone to cognitive impairment. Cognitive impairment was more common in patients with higher depression scores. CONCLUSIONS: Considering these findings, it is crucial to identify the cognitive disorders and depressive symptoms during their initial hospitalization to prevent or treat them in geriatric patients. Regular monitoring of geriatric patients in orthopedic clinics for symptoms of cognitive status and depression is recommended, and caregivers should be made aware of this issue. KEY WORDS: geriatric patients, orthopedic procedures, cognitive status, depression.

• MeSH
• délka pobytu MeSH
• deprese * diagnóza   etiologie   psychologie   MeSH
• geriatrické hodnocení metody   MeSH
• kognitivní dysfunkce * etiologie   diagnóza   psychologie   MeSH
• lidé MeSH
• ortopedické výkony * škodlivé účinky   psychologie   metody   MeSH
• průřezové studie MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Turecko epidemiologie   MeSH

INTRODUCTION: Our study (part of multicentric "MindCOVID") investigates risk factors for anxiety and depression among pregnant women during the COVID-19 pandemic in the Czech Republic. MATERIAL AND METHODS: The study used a prospective cross-sectional design. Data was collected using an online self-administered questionnaire. Standardized scales, general anxiety disorder (GAD)-7 and patient health questionnaire (PHQ)-9 were administered online. Multivariate regression analysis was employed to evaluate the relationship between sociodemographic, medical and psychological variables. RESULTS: The Czech sample included 1830 pregnant women. An increase of depressive and anxiety symptoms measured by PHQ-9 and GAD-7 in pregnant women during the COVID-19 pandemic was associated with unfavorable financial situation, low social and family support, psychological and medical problems before and during pregnancy and infertility treatment. Fear of being infected and adverse effect of COVID-19, feeling of burden related to restrictions during delivery and organization of delivery and feeling of burden related to finances were associated with worse anxiety and depressive symptoms. CONCLUSIONS: Social and emotional support and lack of financial worries are protective factors against mood disorders in pregnant women in relation to COVID-19 pandemic. In addition, adequate information about organization of delivery and additional support from healthcare professionals during the delivery are needed. Our findings can be used for preventive interventions, given that repeated pandemics in the future are anticipated.

• Klíčová slova
• anxiety, covid-19, depression, mental health, pregnant women, risk factors, socioeconomic status,
• MeSH
• COVID-19 * epidemiologie   psychologie   MeSH
• deprese diagnóza   MeSH
• lidé MeSH
• pandemie prevence a kontrola   MeSH
• prospektivní studie MeSH
• průřezové studie MeSH
• SARS-CoV-2 MeSH
• těhotenství MeSH
• těhotné ženy psychologie   MeSH
• úzkost diagnóza   MeSH
• Check Tag
• lidé MeSH
• těhotenství MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Česká republika epidemiologie   MeSH

BACKGROUND: In time, we may be able to detect the early onset of symptoms of depression and even predict relapse using behavioural data gathered through mobile technologies. However, barriers to adoption exist and understanding the importance of these factors to users is vital to ensure maximum adoption. METHOD: In a discrete choice experiment, people with a history of depression (N = 171) were asked to select their preferred technology from a series of vignettes containing four characteristics: privacy, clinical support, established benefit and device accuracy (i.e., ability to detect symptoms), with different levels. Mixed logit models were used to establish what was most likely to affect adoption. Sub-group analyses explored effects of age, gender, education, technology acceptance and familiarity, and nationality. RESULTS: Higher level of privacy, greater clinical support, increased perceived benefit and better device accuracy were important. Accuracy was the most important, with only modest compromises willing to be made to increase other factors such as privacy. Established benefit was the least valued of the attributes with participants happy with technology that had possible but unknown benefits. Preferences were moderated by technology acceptance, age, nationality, and educational background. CONCLUSION: For people with a history of depression, adoption of technology may be driven by the desire for accurate detection of symptoms. However, people with lower technology acceptance and educational attainment, those who were younger, and specific nationalities may be willing to compromise on some accuracy for more privacy and clinical support. These preferences should help shape design of mHealth tools.

• Klíčová slova
• Depression, Discrete choice experiment, Mobile technology,
• MeSH
• deprese * diagnóza   terapie   MeSH
• lidé MeSH
• pacientova volba MeSH
• stupeň vzdělání MeSH
• telemedicína * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Depression is a major depressive disorder characterized by persistent sadness and a sense of worthlessness, as well as a loss of interest in pleasurable activities, which leads to a variety of physical and emotional problems. It is a worldwide illness that affects millions of people and should be detected at an early stage to prevent negative effects on an individual's life. Electroencephalogram (EEG) is a non-invasive technique for detecting depression that analyses brain signals to determine the current mental state of depressed subjects. In this study, we propose a method for automatic feature extraction to detect depression by first constructing a graph from the dataset where the nodes represent the subjects in the dataset and where the edge weights obtained using the Euclidean distance reflect the relationship between them. The Node2vec algorithmic framework is then used to compute feature representations for nodes in a graph in the form of node embeddings ensuring that similar nodes in the graph remain near in the embedding. These node embeddings act as useful features which can be directly used by classification algorithms to determine whether a subject is depressed thus reducing the effort required for manual handcrafted feature extraction. To combine the features collected from the multiple channels of the EEG data, the method proposes three types of fusion methods: graph-level fusion, feature-level fusion, and decision-level fusion. The proposed method is tested on three publicly available datasets with 3, 20, and 128 channels, respectively, and compared to five state-of-the-art methods. The results show that the proposed method detects depression effectively with a peak accuracy of 0.933 in decision-level fusion, which is the highest among the state-of-the-art methods.

• Klíčová slova
• Decision-level fusion, Electroencephalography, Feature-level fusion, Graph-level fusion, Node2vec,
• MeSH
• algoritmy MeSH
• deprese diagnóza   MeSH
• depresivní porucha unipolární * diagnóza   MeSH
• elektroencefalografie MeSH
• lidé MeSH
• rozhraní mozek-počítač * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH