Post-COVID Neuropsychiatric Complications in Children and Adolescents: a Study Design for Early Diagnosis and Treatment Using Innovative Technologies.

BACKGROUND: The COVID-19 pandemic has had significant impacts on the child and adolescent population, with long-term consequences for physical health, socio-psychological well-being, and cognitive development, which require further investigation. We herein describe a study design protocol for recognizing neuropsychiatric complications associated with pediatric COVID-19, and for developing effective prevention and treatment strategies grounded on the evidence-based findings. METHODS: The study includes two cohorts, each with 163 participants, aged from 7 to 18 years old, and matched by gender. One cohort consisted of individuals with a history of COVID-19, while the other group presents those without such a history. We undertake comprehensive assessments, including neuropsychiatric evaluations, blood tests, and validated questionnaires completed by parents/guardians and by the children themselves. The data analysis is based on machine learning techniques to develop predictive models for COVID-19-associated neuropsychiatric complications in children and adolescents. RESULTS: The first model is focused on a binary classification to distinguish participants with and without a history of COVID-19. The second model clusters significant indicators of clinical dynamics during the follow-up observation period, including the persistence of COVID-19 related somatic and neuropsychiatric symptoms over time. The third model manages the predictors of discrete trajectories in the dynamics of post-COVID-19 states, tailored for personalized prediction modeling of affective, behavioral, cognitive, disturbances (academic/school performance), and somatic symptoms of the long COVID. CONCLUSIONS: The current protocol outlines a comprehensive study design aiming to bring a better understanding of COVID-19-associated neuropsychiatric complications in a population of children and adolescents, and to create a mobile phone-based applications for the diagnosis and treatment of affective, cognitive, and behavioral conditions. The study will inform about the improved management of preventive and personalized care strategies for pediatric COVID-19 patients. Study results support the development of engaging and age-appropriate mobile technologies addressing the needs of this vulnerable population group.

Non-Psychiatrist Healthcare Professionals? Attitudes Toward Patients with Mental Disorders: Lower Scores in Social Distance as a Fragile Facet of Public Stigma Against Depression.

BACKGROUND: The stigmatization by healthcare professionals (HP) of patients suffering from mental disorders is an important problem that interferes with the delivery of medical assistance. Social distancing by HP is an integral part of stigmatization, which differs between various mental disorders, as well as between psychiatrists (PSY) versus nonpsychiatrist healthcare professionals (NPHP). SUBJECTS AND METHODS: The study included 141 HP: PSY (n=20; 36.2±4.2 y.o.) and NPHP (n=121; 25.9±2.2 y.o.). The NPHP group included general practitioners (GP)/physicians (n=29; 20.6%), surgeons (n=19; 13.5%), obstetrician-gynecologists (n=26; 18.4%), neurologists (n=11; 7.8%), pediatricians (n=6; 4.3%), and other subspecialists (including urologists, tuberculosis specialists, ophthalmologists and dermatologists) (n=30; 21.3%). The modified Bogardus Social Distance Self-Assessment Scale (BSDS) was used to evaluate the indicators of social distance phenomena. The assessment was performed by HP for the following groups of patients with the following mental disorders: alcohol use disorder, bipolar disorder, depression, drug addiction, epilepsy, mental retardation, personality disorder, schizophrenia. All statistical calculations were performed using IBM SPSS-27 software (IBM Corp. 2021, licensed to Samara State Medical University). P-value ≤0.05 was determined as significant for the between-group (PSY vs NPHP) comparisons using a nonparametric Mann-Whitney U-test. RESULTS: Our data analysis showed that HP achieved varying social distance scores for patients depending on the type of mental disorder, but with common trends among PSY and NPHPs. The mean (SD) scores of social distance ranged from 3.65(1.50) for depression to 5.25 (1.74) for drug addiction in the PSY, versus 3.44 (1.69), 6.19 (1.37) in NPHP, respectively. As compared to PSY, mean BSDS total scores were greater in the NPHP group, notably in the obstetricians-gynecologist - 6.27(1.40), and GP - 6.62 (0.90) groups, with similar trends of differing attitudes appeared among pediatricians - 7.00 (0.01) - regarding drug addiction, whereas the neurologists demonstrated a tendency towards lower social distance in relation to patients with depression - 2.27 (1.68), and epilepsy - 2.82 (1.47). CONCLUSIONS: Social distance measures by PSY and NPHP groups in contemporary Russia were highest in relation to patients with drug addiction, and lowest scores for depression and epilepsy. Stigmatization among HPs seems to influence health care delivery to certain categories of patients, which calls for further investigation. Higher social distance scores for patients with drug addiction might be related to higher stigma and lack of compassion toward these patients. Conversely, lower scores of social distance and corresponding emotional acceptance of people with depression by HP might interfere in the timely diagnosis and availability of appropriate care at an early stage amenable to treatment. This might reflect the cultural context of depressive mentality in Russia, or elevated prevalence of depressive states among HP. We propose interventions aiming to destigmatize mental disorders by targeting particular subgroups of vulnerable patients and also certain representatives of HP community.

Interactions between Anxiety Levels and Life Habits Changes in General Population during the Pandemic Lockdown: Decreased Physical Activity, Falling Asleep Late and Internet Browsing about COVID-19 Are Risk Factors for Anxiety, whereas Social Media Use Is not.

BACKGROUND: The COVID-19 pandemic has substantially contributed to increased anxiety rates among the general population worldwide. Pandemic-related health anxiety and worries about getting COVID-19 can lead to generalized anxiety and anxiety somatization, which, together with insalubrious daily life habits, are risk factors of worsening somatic health in people with SARS-Cov-2 infection. SUBJECTS AND METHODS: The current study is a part of the COMET-G project (40 countries, n=55589; approved by the Ethics Committee of the Aristotle University of Thessaloniki), which represents an intermediate analysis of data collected anonymously via online links from a national sample of the Russian general population (n=9936, 31.09±12.16 y.o., 58.7% females) to estimate anxiety using STAI-S and self-reported changes in anxiety and life habits (physical activity, nutrition and weight, internet use, sleep) during the lockdown. All statistical calculations (descriptive statistics, between group comparisons using chi-square test, MANOVA, ANOVA, significant at p<0.05) were performed with IBM SPSS 27. RESULTS: Overall STAI-S scores were 29±5.4, a subjective feeling of anxiety increase was reported in 40.3% of respondents (43.9% significantly > in females), worsening to clinical anxiety in 2.1% (2.4% > in females). 54.2% of respondents reported decreased physical activity, 33.1% gained weight, 72% used internet more often, 52.6% experienced worries related to the information about COVID-19 (56.8% > in females). 88% experienced worsened sleep quality, 69.2% stayed up until late, 23.2% took sleeping pills, and 31% had nightmares in which they felt trapped. To ANOVA, such life habits as reduced physical activity during the lockdown, increased time spent online, internet browsing about COVID-19, tendency to stay up late, use of sleeping pills and disturbing dreams with scenario of being trapped were significantly related to worsening of clinical anxiety. However, eating behaviour, weight changes, and social media use did not contribute to the clinical anxiety increase. CONCLUSIONS: Factors of decreased physical activity and sleep disturbances related to the lockdown, as well as excessive internet browsing for information about COVID-19, emerged as risk factors for increased anxiety, more notably in women than in men. Preventive measures should be targeted against relevant factors imparting anxiety in the vulnerable population.

Language in Mild Depression: How It Is Spoken, What It Is About, and Why It Is Important to Listen.

BACKGROUND: Our previous research demonstrated that mild depression (MD) is characterized by patterns of atypical language use such as inverted word order, greater repetition, increased use of reflexive/personal (e.g. myself) or negative/ indefinite (e.g. nobody) pronouns, verbs in past tense, and other lexico-grammatical, stylistic and syntactic indicators (how the patient speaks). We now investigate the role of semantic features (what the patient speaks about) in diagnosing (why it is important to listen) affective states. SUBJECTS AND METHODS: 201 written narratives from 124 patients with MD and 77 healthy controls (HC), including 35 cases of normal sadness (NS), were studied using principle component lexis analysis. Statistical data evaluation was performed with SPSS-25 (p<0.05, significant) and included the Cohen's kappa for inter-rater reliability, nonparametric methods to measure between-group differences (Mann-Whitney U-test, Pearson Chi-square test, Kruskal-Wallis, one-way ANOVA), and discriminant analysis for modeling of semantic variables related to affective diagnostic types. RESULTS: Component lexis analysis revealed an exaggerated usage of semantic categories describing existential and family values in the texts of MD patients compared to HC. However, there were fewer cognitive and altruistic categories presented in patients' self-reports. The most substantial between-group difference was the lesser semantics of self-realization in MD patients, as well as their significantly lower ranking of social status' priorities. Communicative and hedonic values in MD speech displaced and predominated in ranking over the values of social status, versus the opposite relationship in HC speech. The discriminant model revealed a set of semantic indicators significantly distinguishing the MD, HC and NS groups (96.3%; Wilks' λ=0.001, p<0.001, r=0.996). CONCLUSIONS: Linguistic structure and content of patients' verbalizations may serve as diagnostic markers of MD. Evaluation of psychosocial themes within the content of narratives should enable a better understanding of MD pathogenesis and emphasize the importance of monitoring social difficulties during treatment.

Language Patterns Discriminate Mild Depression From Normal Sadness and Euthymic State.

OBJECTIVES: Deviations from typical word use have been previously reported in clinical depression, but language patterns of mild depression (MD), as distinct from normal sadness (NS) and euthymic state, are unknown. In this study, we aimed to apply the linguistic approach as an additional diagnostic key for understanding clinical variability along the continuum of affective states. METHODS: We studied 402 written reports from 124 Russian-speaking patients and 77 healthy controls (HC), including 35 cases of NS, using hand-coding procedures. The focus of our psycholinguistic methods was on lexico-semantic [e.g., rhetorical figures (metaphors, similes)], syntactic [e.g., predominant sentence type (single-clause and multi-clause)], and lexico-grammatical [e.g., pronouns (indefinite, personal)] variables. Statistical evaluations included Cohen's kappa for inter-rater reliability measures, a non-parametric approach (Mann-Whitney U-test and Pearson chi-square test), one-way ANOVA for between-group differences, Spearman's and point-biserial correlations to analyze relationships between linguistic and gender variables, discriminant analysis (Wilks' λ) of linguistic variables in relation to the affective diagnostic types, all using SPSS-22 (significant, p < 0.05). RESULTS: In MD, as compared with healthy individuals, written responses were longer, demonstrated descriptive rather than analytic style, showed signs of spoken and figurative language, single-clause sentences domination over multi-clause, atypical word order, increased use of personal and indefinite pronouns, and verb use in continuous/imperfective and past tenses. In NS, as compared with HC, we found greater use of lexical repetitions, omission of words, and verbs in continuous and present tenses. MD was significantly differentiated from NS and euthymic state by linguistic variables [98.6%; Wilks' λ(40) = 0.009; p < 0.001; r = 0.992]. The highest predictors in discrimination between MD, NS, and euthymic state groups were the variables of word order (typical/atypical) (r = -0.405), ellipses (omission of words) (r = 0.583), colloquialisms (informal words/phrases) (r = 0.534), verb tense (past/present/future) (r = -0.460), verbs form (continuous/perfect) (r = 0.345), amount of reflexive (e.g., myself)/personal (r = 0.344), and negative (e.g., nobody)/indefinite (r = 0.451) pronouns. The most significant between-group differences were observed in MD as compared with both NS and euthymic state. CONCLUSION: MD is characterized by patterns of atypical language use distinguishing depression from NS and euthymic state, which points to a potential role of linguistic indicators in diagnosing affective states.