The aim of this study was to develop and validate a Romanian version of the Three-Factor Eating Questionnaire-R21 for children and adolescents CTFEQ-R21 and to assess its psychometrie properties and factor structure. Associations between the present version of the CTFEQ-R21 and anthropometric measures as well as body composition were also examined.2). The participants were fitst interviewed to ascertain their understanding of the CTFEQ-R21 and were then asked to self-complete the questionnaire. Height and weight were measured and body composition assessed using bio impedance analyzers (Tanita MC 780).153 children and adolescents  took part in this study (BMI of 17.7±3. 1kg/mThe CTFEQ-R21 showed satisfactory interna/ consistency (Cronbach's a=0.78). Cronbach's alpha coefficients were 0.55 for CR (cognitive restriction), 0.75 for UE (Uncontrolled Eating), and 0.76 for EE  separately. UE and EE were found to be significantly correlated . The three factors explained 43% of the toto/ variance. Correlation between CR, UE and EE with body weight, BMI and FFM were significant but low to moderate, with coefficients ranging from 0.20 to 0.37. The higher the CR, UE and EE tertiles, the higher the weight, fat mass (kg) and fat-free mass values.According to the psychometrie analysis of the questionnaire, the version of the CTFEQ-R21 proposed here is a satisfactory tool to assess eating behaviors in the Romanian child population that remains to be further developed. The continuous worldwide progression of overweight and obesity in pediatric populations is becoming one of the most critical global public health concerns ,2. WhileAlthough valid universal tools are available to objectively and properly measure physical activity , valid methods to assess the cognitive and behavioral dimensions of eating behaviors, as well as attitudes towards food, remain to be developed in Romania. The Three Factor Eating Questionnaire (TFEQ)  has beenSome studies have been interested in the relationship between weight status or body composition with eating behaviors in children and adolescents , 16, 17.While there is a growing interest in the prevention and treatment of pediatric overweight and obesity in Romania, there is also a need for adapted and validated tools to properly assess children and adolescents’ eating behaviors. The purpose of the present study was to validate a Romanian version of the TFEQ for children and adolescents and to analyze its psychometric properties and factor structure. A second aim was to explore the relationships between Romanian children’s and adolescents’ eating behaviors and their body composition.17.7±3.1 kg/m2. To be included in the study, children and adolescents had to be free of any history of psychological or eating disorders. None of the children and adolescents was following a diet, nor were they taking any medication that could interfere with the results. The participants were recruited among primary and secondary schools in Oradea, Romania. Both the participants and their legal representatives received information sheets and signed consent forms. The study was conducted in accordance with the Declaration of Helsinki of 1975 regarding the ethical principles for human research and after consideration by the appropriate local authorities .A total of 153 children and adolescents (68 boys and 95 girls) took part in this study, with a mean age of 10.8 ± 3.5 years (age ranged from 6 to 16 years) and a mean BMI of The Romanian version of the CTFEQ-R21 (see Appendix 1 ) was obtained after the following process (as described by : i) tranThe children and adolescents enrolled in the study were asked to join the university facilities where they received verbal and written instructions on how to properly complete the questionnaire. They answered the questions by themselves and a member of the investigation team was present to help them when necessary, especially the youngest participants. The questionnaire took about 10 to 15 minutes to complete. Anthropometric and body composition measurements were also taken using standardized procedures.A digital scale was used to measure body mass to the nearest 0.1 kg, and standing height was assessed barefoot, to the nearest 0.1 cm by using a wall-mounted stadiometer. BMI was calculated as body mass (kg) divided by height squared (m2). Body composition was assessed by bioelectrical impedance using a Anita MC-780 multi-frequency, segmental body composition analyzer. This consisted of a stand-alone unit which the participant had to step on barefoot (standard mode). Information about the participant  was entered by the experimenter. Once body mass had been assessed by the Tanita scale, the participant had to take grips in both hands  during the impedance measure (hand to foot). A full segmental analysis was performed in less than 20 s. Segmental fat mass and fat-free mass values were indicated at the end of the analysis on the digital screen ; as well as total body fat, fat-free mass and water. This newly developed technology has been recently validated in adults of various physical activity levels , showingexploratory factor analysis  was carried out to determine the scale structure. The number of factors was chosen according to usual recommendations: Kaiser criteria, plot of eigenvalues and part of variance expressed by principal components. The Kaiser-Meyer-Olkin test for sample adequacy was applied. Internal consistency was determined through Cron bach's alpha coefficient ; the item homogeneity coefficient , and the item-total correlation corrected for overlap . Regarding convergent validity, a high association  was hypothesized between the scale scores and other quantitative measures . Then, each dimension of the scale score was categorized in 3 modalities according to statistical distribution . The comparisons between groups for weight, BMI, fat-free mass and fat mass were performed by ANOVA or non-parametric Kruskal-Wallis test, followed by a post-hoc test for multiple comparisons . Relationships between quantitative variables were assessed using correlation coefficients and were represented graphically with a color-coded heatmap. Since we missed to observe any gender differences, the data were analyzed together and all the analyses were adjusted for age and gender.All statistical analyses were performed using Stata software  and the level of significance set at p<0.05. Analyses performed in this study were those usually used in studies aimed at validating scales. In addition to descriptive statistics, the following psychometric properties of the questionnaire were explored. Acceptability: Data quality was considered satisfactory if more than 95% of the scale data were fully computable. Score range, closeness of mean to median, floor and ceiling effects (accepted maximum for both: 15%), and skewness of score distributions (limits: -1 to +1) were also analyzed. An In this study, the Cronbach’s alpha coefficient for the whole questionnaire was 0.78. When analyzed separately, the Cronbach’s alpha coefficients were 0.55 for CR, 0.75 for UE, and 0.76 for EE. Only the correlation between UE and EE was found to be statistically significant, with a correlation coefficient of 0.54 (p<0.001). For the relation between CR and the other eating behaviors, the correlation coefficients were low .As illustrated in the color-coded heatmap, correlations between items assigned to a determined scale were moderate and correlations with items of the other two scales remained low, even if the relationships between UE and EE items were stronger , despite significant p-values (These results were confirmed by testing comparisons between body composition indicators by tertile of eating behavior scores (This study aimed to test the psychometric properties of a Romanian version of the CTFEQ-R21 to assess eating behaviors in children and adolescents (CTFEQ-R21). This Romanian version of the CTFEQ-21 provides a satisfactory assessment of childrens and adolescents’ eating behaviors, with an internal-consistency Cronbach’s alpha coefficient of 0.78. When analyzed separately, CR, EE and UE showed coefficients of 0.55, 0.76 and 0.75, respectively.These results are in line with those of Bryant et al. who proposed the adapted version of the TFEQ for children and adolescents showing an internal consistency coefficient of 0.81 . In theiThis Romanian version of the CTFEQ-R21 showed moderate correlations between each dimension of the questionnaire  and body weight, BMI and FFM. However, fat mass was not correlated with CR, UE, or EE. Although Bryant and colleagues also observed significant positive correlations between CR, body weight and BMI (particularly in girls) in a similar population, UE and EE were not related to anthropometric measures in their work . PreviouIn the present study, we also divided data according to tertiles of CTFEQ-R21 eating behavior traits that discriminate against children and adolescents showing the lowest, intermediate and highest values for each of the three dimensions. Accordingly, higher body weight, BMI, fat-free mass and fat mass (kg only) were observed with higher tertiles of eating behaviors. In their work, Martin-Garcia et al. also analyzed their results according to tertiles and found similar results for CR only . AccordiAlthough this work is the first to propose a version of the CTFEQ-R21 for Romanian children, its results must be interpreted in the light of some limitations. First, the composition of our sample must be considered. The present sample is mainly composed of normal-weight children and adolescents, so further investigations should be conducted among overweight and obese ones. Moreover, the sample presents quite a broad age range, which has to be considered when interpreting our results. The unequal proportion of boys and girls is certainly one of the main limitations of our sample. Indeed, we did not observe gender differences during our analysis, which is certainly due to this disproportionate number of boys and girls. This is of particular importance, since the literature clearly points out differences between boys and girls when it comes to eating behaviors, with girls usually showing significantly higher average results in each of such scale dimensions. Nevertheless, even if our analyses had been controlled for age and sex, it would have been more precise to also evaluate the participants’ biological maturation using Tanner stages. The use of an impedance analyzer to assess body composition might also be considered as a limitation, since more accurate methods, such as Dual-Energy X-ray absorptiometry (DXA) could be used, as in the study of Martin-Garcia et al. . HoweverThe proposed Romanian version of the CTFEQ-R21 for children and adolescents shows satisfactory psychometric properties and internal consistency, with anthropometric values, as well as FM and FFM, being correlated with the three eating behavior traits that compose the whole questionnaire. According to the present results, this first version of the Romanian CTFEQ-R21 proposes an interesting tool that needs to be further developed and improved. Further studies enrolling a larger sample should be conducted to specifically question the validity of this questionnaire among overweight and obese Romanian children and adolescents. Other international tools used to assess eating behaviors should be validated in developing countries that are today facing the progression of pediatric obesity which require effective public health strategies.


In this study, we aimed to evaluate the relationship between tinnitus and a subsequent diagnosis of major depressive disorder (MDD) by studying the incidence of both entities.A retrospective cohort study.n = 375,272 controls) from the same dataset, with their index date being the date of their first health service claim in the year of diagnosis of their matched index case. We tracked each patient's claims records for 1 year from the index date to identify those who received a diagnosis of MDD. Cox proportional hazards regression was performed to calculate the MDD hazard ratio for cases vs. controls.Data for this observational follow-up study were retrieved from the Taiwan's National Health Insurance Dataset. A total of 375,272 patients with newly diagnosed tinnitus (study group) were retrieved. The date of first diagnosis of tinnitus was assigned as their index date. Comparison patients were selected by propensity score matching . Cox proportional hazards analysis showed that the patients in the study cohort had a higher hazard of developing MDD than the patients in the comparison cohort .We found that the overall incidence rate for MDD was 0.78 (95% CI = 0.76~0.80) per 100 person-years, being 1.17 (95% CI = 1.14~1.21) among the study cohorts and 0.38 (95% CI = 0.36~0.40) among the comparison cohorts. The log-rank test revealed that the patients in the study cohort had significantly lower one-year MDD-free survival when compared to the comparison cohort (In this study, we demonstrate that tinnitus is associated with an increased hazard of subsequent MDD in Taiwan. Tinnitus is defined as a non-observable, self-reported auditory phantom phenomenon with patients internally perceiving a sound without a corresponding external sound source , 2. TinnMajor depressive disorder (MDD) is a psychiatric illness with feelings of sadness, guilt, hopelessness, and worthlessness, followed by a high probability of suicide . It is rvice versa. Tinnitus and MDD may share common symptoms and risk factors, such as chronic health problems, lower socioeconomic status, and higher perceived stress levels , which is maintained and regulated by the Data Science Center of the Ministry of Health and Welfare of Taiwan. The NHIRD was established in 1995 and covers more than 99.6% of all 23 million-plus citizens. The NHIRD includes data on registries of contracted medical facilities and beneficiaries, and claims submitted for reimbursement. Taiwan's NHI program covers virtually everything, including preventive care, cancer screenings, mental health, general primary care, and in-hospital care. The NHIRD provides a unique opportunity for scientists in Taiwan to investigate the association between tinnitus and the subsequent occurrence of major depressive disorder. The study was approved by the Institutional Review Board of Taipei Medical University (TMU-JIRB N202109059). Since we used an administrative claim dataset to analyze data, patient informed consent was waived.We designed this study as an observational cohort study. We established the study cohort by identifying 393,761 patients aged ≥ 20 years who received their first diagnosis of tinnitus  at outpatient facilities  between January 1, 2014 and December 31, 2016. We defined the date of their first-time diagnosis of tinnitus as their index date. We excluded 18,489 patients who had received a diagnosis of major depressive disorder  or bipolar disorder within 3 years prior to the index date. Ultimately, the selected study cohort included 375,272 patients with tinnitus.We likewise retrieved patients of a comparison cohort from the registry of beneficiaries included in the NHIRD. After excluding patients aged <20 years of age and those with a history of tinnitus in the prior 3 years, we used propensity-score matching to select 375,272 comparison patients. The matching baseline characteristics were sex, age, monthly income, geographic region, urbanization level of the patient's residence , selected medical co-morbidities associated with tinnitus , and index year. The index year for the study cohort was the year when they received their first-time diagnosis of tinnitus. For comparison cohort patients, we defined their index year as the year of their matched tinnitus case after ensuring they had, at least, one episode of medical care utilization in the index year. Furthermore, we assigned their index date as the date of first utilization of medical care in the index year for the comparison cohort. We also ensured that comparison patients had not received a diagnosis of major depressive disorder within 3 years before their index date.All the patients were tracked for a one-year period, following their index date to identify any claim with a diagnosis of MDD, the outcome variable of interest in this study.Statistical analyses were performed using the SAS statistical package . We carried out Kaplan–Meier analysis with the log-rank test to test differences in 1-year, MDD-free survival between the study cohort and the comparison cohort. Kaplan–Meier estimator is one of the best methods to be used to estimate the survival function from lifetime data. We used Cox proportional hazards regression to estimate the 1-year adjusted hazard of MDD following tinnitus. The Cox proportional hazards model is employed for investigating the association between the survival time of patients and one or more predictor variables. We also verified that the proportional hazards assumption was satisfied based on survival curves of the two strata (study and comparison cohorts) showing proportional separation between the curves over time. We used an adjusted hazard ratio (HR) along with 95% confidence intervals (CI) to estimate the risk of MDD.p-values despite negligible differences in magnitude or composition. We, therefore, measured effect sizes to quantify these differences by calculating Cohen's d, Cohen's h, or Cohen's φ . There were statistically significant differences in sex composition , monthly income , geographic region , and urbanization level of the patients' residence  between the study cohort and the comparison cohort. There were no significant differences in the rates of hyperlipidemia , diabetes , and hypertension . However, there was a significant difference in the rate of coronary heart disease between the study and comparison cohorts . All effect sizes were all minuscule (≤ 0.02), and, therefore, the significant differences between the cohorts were negligible.p < 0.001).To our knowledge, this is the first population-based study, addressing the question of whether prior tinnitus may either trigger or be an initial symptom preceding MDD. We found that the overall incidence of MDD was 1.17 (95% CI = 1.14~1.21) and.38 (95% CI =0.36~0.40) in the study cohort and comparison cohorts, respectively. The adjusted HR of MDD during one-year follow-up was 3.08 (95% CI = 2.90~3.27) for the patients in the study cohort when compared to the comparison cohort. Previous literature has shown an association between tinnitus and depression, but these studies either had small samples or were not population-based samples, impeding generalization of findings to the population level , 21, 22,Persons with tinnitus had a 3-fold hazard of occurrence of MDD 1 year compared to those matched to them on demographic and co-morbidity status in this nationally representative Taiwan population sample. Previous studies showed that higher-order psychological/psychopathological aspects may drive effects of tinnitus distress and consequential depression , 25. Stuvia involvement of the nonauditory brain areas, including the anterior parietal area, the limbic system, which consists of the anterior cingulate cortex, anterior insula, amygdala, and the hippocampal and parahippocampal area , reducing the potential for diagnostic bias usually associated with socioeconomic status or residential location. Furthermore, because the NHIRD provides coverage for every type of medical care event for all Taiwanese residents with very low copayments, the NHI databases have claims records of ~23 million Taiwanese, including outpatient visits, emergency department visits, and inpatient admissions. Therefore, our study was able to capture data from any source if a diagnosis of tinnitus and MDD occurred. Troublesome tinnitus and MDD are alarming conditions, which usually result in patients seeking immediate medical help, which is facilitated by affordable and accessible health care facilitated by NHI. Therefore, identification of tinnitus and MDD may not vary by socioeconomic status. The use of claims data also avoids possible recall bias associated with self-reported data. Our cohort study design, selecting the comparison group by propensity score matching, strengthens the validity of findings, minimizing selection bias and misclassification bias. In most prior studies, self-reported questionnaires or scales were used to identify depression and tinnitus cases. The validity of disease definition in our study may be more precise.There are some study limitations. First, the NHIRD claims lack of certain critical items of data, such as lifestyle, dietary habits, body mass index, life events, chronic pain, stress, substance abuse, and family history and genetic factors. In addition, we did not take a sleep problem and medication into consideration. The relationship between tinnitus and MDD reported in this study may be partially explained by the residual confounding of the above factors. Second, some persons affected by tinnitus may not seek medical help because of the impression that treatment of this condition is not effective. The study findings might potentially result in underdiagnosis and undertreatment of tinnitus. However, the possibility of non-differential misclassification in tinnitus could have biased the results toward the null hypothesis. Third, we used medical claims data to investigate the association between tinnitus and MDD in this study. The diagnosis of MDD relied on administrative claims data reported by physicians, which may be less accurate than diagnoses made according to standardized criteria. However, we have assured all the patients with MDD in the present study had at least received one MDD diagnosis from a psychiatrist in which diagnoses were based on DSM-5 diagnostic criteria in Taiwan. Fourth, the NHIRD claims used in this study only included the data interval from years 2011 to 2017. This study was designed as a retrospective cohort study rather than a prospective cohort with a pre-designed protocol, so it should be cautious to draw a causal relationship between tinnitus and MDD. Furthermore, despite being a population-based study, our findings may not apply to other countries because of differences in ethnicity and living environment.In this study, we demonstrate that patients with tinnitus are at increased risk of developing MDD. Our findings call for greater awareness of the potential for patients with tinnitus to develop MDD. Careful history taking and timely follow-up to surveil for depressive symptoms are necessary for patients with tinnitus. Health care professionals, such as otolaryngologists, audiologists, and psychologists, should be alert to likely association between tinnitus and MDD and be prepared to address the psychological needs of patients with tinnitus.https://dep.mohw.gov.tw/DOS/cp-5119-59201-113.html).The data analyzed in this study was obtained from the National Health Insurance Research Database, which has been transferred to the Health and Welfare Data Science Center (HWDC). Interested researchers must obtain the data through formal application to the HWDC, Department of Statistics, Ministry of Health and Welfare, Taiwan . Written informed consent from the patients/ participants or patients/participants legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.H-CL, C-HW, and T-HY contributed to conception and design of the study. H-CL organized the database. Y-FC performed the statistical analysis. SX wrote the first draft of the manuscript. H-CL, C-HW, T-HY, and Y-FC wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Results show that hypnosis-practicing dentists score significantly higher in the intuitive/schizotypal ST personality style (p < 0.001) compared to non-hypnosis-practicing dentists. Female dentists scored significantly higher in intuitive/schizotypal ST and unselfish/self-sacrificing SL in the HYP DGZH sample but only in unselfish/self-sacrificing SL in the NONHYP DENT sample. The percentage of women was similar in both samples . Intuitive/schizotypal ST was found to be the predominant personality style of men who are interested in or use hypnosis, metaphorically so-called “homo hypnoticus.” Within the limitations of this cross-sectional non-interventional observational online-questionnaire study, results expand this notion to the so-called “homo hypnoticus dentalis.” However, further research on the subject is needed to investigate and confirm this personality type in other than the German-speaking DACH countries.Several publications with healthcare professionals, such as psychotherapists, have shown a significant difference in personality styles in practitioners using hypnosis compared to those not using hypnosis. To investigate differences in personality styles, dentists were contacted to participate in a personality-inventory [Personality Style and Disorder Inventory (PSDI)] online survey. Dentists using hypnosis (HYP DGZH) ( Since the first documented tooth extraction under hypnosis , there iThe aim of this study was to investigate whether there were differences (1) between NONHYP DENT and HYP DGZH in the five interesting personality styles intuitive/schizotypal ST, unselfish/self-sacrificing SL, charming/histrionic HI, optimistic/rhapsodic RH, and conscientious/compulsive ZW (hypothesis 1) as well as (2) between the sexes of the two samples. Furthermore, we were interested in personality style differences (hypothesis 2) that exist (3) between low, medium, and high hypnotizables (hypothesis 3).SD = 10.3). This hypnosis using a dentist sample (HYP DGZH) is identical to the sample of the 418 DGZH members examined in the study by The HYP DGZH sample: As a sample of HYP DGZH in the professional area, approximately 1,348 members of the German Society of Dental Hypnosis  were contacted. In addition, there were calls for participation in the survey during the congresses of the German and Austrian Dental Hypnosis Society  and also the Swiss Medical Society for Hypnosis (SMSH). A total of 418 subjects responded, 285 women (68.2%) and 133 men (31.8%) between 20 and 75 years of age .The NONHYP DENT sample: For the sample of dentists who were not practicing hypnosis, approximately 1,450 members of the universities of Bonn (Germany), Tübingen (Germany), Bern (Switzerland), Krems (Austria), and Vienna (Austria), as well as military dentists (Germany), were contacted. A total of 162 subjects responded, 109 women (67.3%) and 53 men (32.7%) between 21 and 69 years of age . No randomization or other group allocation was performed, and every participant was provided with written informed consent for research purposes. The data of the HYP DGZH sample were collected between August 1, 2017 and September 30, 2018, as well as between February 1, 2020 and June 30, 2020, and the data of the NONHYP DENT sample were collected between April 1, 2020 and April 30, 2021. The participation was entirely voluntary, and no advantage, financial or otherwise, was associated with participation. All procedures were performed in accordance with the 1964 Declaration of Helsinki and its subsequent amendments and the ethical standards of the local research commission. For this type of study, from the local ethics committee, no further formal approval was required. In accordance with the Swiss Human Research Act , the data from study participants were used under irreversibly anonymized conditions; all participants were adults.The study was designed as a cross-sectional non-interventional observational online-questionnaire study among dentists. All participants received an email that explained the study’s goals and asked for their participation in an investigation of personality styles t-values. The t-levels of 40–60 (one SD above/below the average mean of 50) describe personality styles, while those beyond this range band of 40–60 highlight the probability of a personality disorder. Of the 14 personality styles, only four interesting personality styles of the “homo hypnoticus,” namely, ST, SL, HI, and RH, and the ZW style for statistical calculations were analyzed. A short description of these five personality styles is found in Similarly in the studies by 1 The t-tests or one-way ANOVAs were used despite none of the PSDI scales showed normal distribution. Because, especially in large samples, both t-test and ANOVA are deemed to be quite robust against violations to the assumption of normality, we decided against the use of non-parametric tests, thus having more power detecting abnormalities and being able to calculate CIs for better assessment of the extent of these deviations. For evaluating the homogeneity of variances, Levene’s tests were used. Bonferroni tests of SPSS version 27 already adjusting for Type 1 Error were used for the post hoc analysis.The results from the PSDI were analyzed using the software package IBM SPSS, version 27 . The data were transferred from the questionnaire software SoSci Survey  directly in the data format for SPSS, respecting the currently applicable General Data Protection Regulation of the European Union .t-test revealed  significant results only in the personality style intuitive/schizotypal ST  (p = 0.51), the charming/histrionic HI style (p = 0.047), the optimistic/rhapsodic RH style (p = 0.028), and the conscientious/compulsive ZW style (p = 0.043).For the difference between HYP DGZH and NONHYP DENT samples, the unpaired 70/1.08] . After Bn = 162) consisting of 109 female and 53 male participants were compared in all fourteen styles. The analysis revealed that the female group scored higher in intuitive/schizotypal ST, unselfish/self-sacrificing SL, self-critical/avoidant SU, and passive/depressive DP traits compared to their male counterparts. However, after Bonferroni correction, only the difference in unselfish/self-sacrificing SL reaches statistical significance  (n = 418) consisted of 285 female and 133 male participants and showed significant differences only for the personality styles ST  and SL , not for HI, RH, and ZW  = 4.68, p < 0.001, η2 = 0.056, CI0.95 = 0.01/0.10], the unselfish/self-sacrificing SL style , the charming/histrionic HI style , and the optimistic/rhapsodic RH style . The Bonferroni-corrected post hoc analysis revealed significant differences for the intuitive ST style between the high and low hypnotizables , for the optimistic RH style between the high and low hypnotizables , and between the medium and low hypnotizables  , 76 attended more than two, and 303 attended more than 10 training seminars. Of these 303 who had attended more than 10 training seminars, 275 knew about their hypnotizability because they had been tested in the past. Notably, 126 were highly hypnotizable, 122 were medium hypnotizable, and 27 were low hypnotizable. Thus, for the hypnotizability of the HYP DGZH sample, there is no normal but an almost linear distribution with more high than medium and only a few low hypnotizables . The res3/12.23) .t-values higher than the norm mean of 50. Earlier in the study by This study aimed to investigate the personality profiles of HYP DGZH in their professional environment to relieve patients’ anxiety, make phobics treatable, or even reduce acute or chronic pain, and compare those profiles to the ones of NONHYP DENT. The general result confirms the previous findings of the intuitive/schizotypal ST personality style being the predominant signature of the “homo hypnoticus,” i.e., people interested in hypnosis . BecauseThere were three significant differences in personality styles when comparing female to male dentists , 3. NameBy previous data, we have indications that this intuitive/schizotypal ST signature not only applies to those interested in hypnosis but also correlates with hypnotizability, in the study by The intuitive/schizotypal ST style has been described as part of a continuum from the healthy population to extreme characteristics of schizophrenia with unusual perceptions and beliefs as one of its essential factors . Some auWe deliberately selected the two samples to find differences: The HYP DGZH group was contacted with clear references to hypnosis, whereas any reference to hypnosis was avoided in the NONHYP DENT group. However, we could not avoid the self-selection bias due to the principally voluntary participation in the study. This may have contributed, among other things, to the other major limitation of our study, i.e., the very small sample of the control group of the NONHYP DENT sample. Although there were many dentists contacted over 1 year, the willingness to participate in the online self-questionnaire was scarce. Reasons could be that dentists are not as accustomed as psychologists to spend time as test subjects. The time required to complete the questionnaire is approximately 20 min, which is rather in the upper third compared to common questionnaire studies in dentistry. This could mean that the 162 NONHYP dentists in our study have high unselfish/self-sacrificing SL scores for this very reason and therefore may not be representative of dentists in general. However, it is precisely for this reason that their significantly low intuitive/schizotypal ST values contribute to the difference to the significantly high intuitive/schizotypal ST values of their HYP DGZH dentists. A further limitation is that the selected target samples consisted only of dentists from the German-speaking DACH countries, such as Germany, Austria, and Switzerland. Other populations from other regions of the world, especially of other continents, should be investigated for this specific personality style both in dentists and in hypnosis using healthcare professionals in general.Several studies have shown that healthcare professionals of different disciplines, such as psychotherapists, using hypnosis within the context of their professional area show significant differences in certain personality styles compared to their peers not practicing hypnosis. This led to the formulation of the “homo hypnoticus” hypothesis . The stuburkhard-peter@t-online.de.The raw data analyzed in this study are subject to the following licenses/restrictions: General European Data Protection Regulation (GDPR) of 25 May 2018. Requests to access these datasets should be directed to PB, Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.BP and TW designed and planned the study. EB and TW were in charge of the experiment. BP was in charge of the statistical conduction of the investigation. EB prepared the first draft of the manuscript. TW and BP revised the first draft of the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Acute systemic diseases, such as severe infections, can lead to electrolyte and acid-base alterations. To study the presence of electrolyte imbalance in severe COVID-19, we investigated the frequency and consequences of changes in electrolyte and acid-base patterns over time. We performed a retrospective cohort study including 406 patients with severe COVID-19. Levels of electrolytes, base excess, pH, serum osmolality, and hematocrit, the first 2 weeks of hospitalization, were collected daily from the laboratory database and clinical data from patients’ medical records. We found that hyponatremia was present in 57% of the patients at admission and 2% in hypernatremia. However, within 2 weeks of hospitalization 42% of the patients developed hypernatremia, more frequently in critically ill patients. Lower levels of sodium and potassium during admission were associated with the need for mechanical ventilation. Decreased pH at admission was associated with both death and the need for mechanical ventilation. Hypernatremia in the ICU was combined with rising base excess and a higher pH. In the group without intensive care, potassium levels were significantly lower in the patients with severe hypernatremia. Presence of hypernatremia during the first 2 weeks of hospitalization was associated with 3.942 (95% CI 2.269–6.851) times higher odds of death. In summary, hypernatremia was common and associated with longer hospital stay and a higher risk of death, suggesting that the dynamics of sodium are an important indicator of severity in COVID-19. Electrolyte and acid-base imbalance are common in many types of severe diseases. In the SARS-Cov-2 pandemic, the combination of respiratory failure and metabolic changes due to organ failure results in unpredictable electrolyte and acid-base patterns.Hyponatremia in severely ill patients in the intensive care unit (ICU) is a known complication of somatic diseases such as pneumonia and heart failure . SeveralHypernatremia is not uncommon in the ICU, and previous studies have reported a frequency of 4.3–15.8% depending on the type of ICU  and the definition of hypernatremia as above 145 or 150 mmol/L) , 17, 18.A publication of a small cohort of patients, from the first phase of the pandemic, with severe COVID-19, indicates the importance of therapy-resistant hypernatremia which prolonged the total hospital stay . In a reRegarding other electrolytes and acid-base biomarkers, there are only a few studies published. Low levels of potassium during admission have been associated with poor prognosis and severe disease, but little is known of the dynamics over time in COVID-19 , 24. IncThe reported deviations in electrolytes during COVID-19 can affect treatment, length of hospital stay, and mortality. Patients with severe COVID-19 are often hospitalized over long periods, and further characterization of electrolyte and acid-base levels over time are, therefore, of great interest.The aim of this study was to examine the dynamics of routine plasma electrolytes and acid-base biomarkers in patients with severe COVID-19 and if they were associated with the need for mechanical ventilation and mortality. Electrolyte levels together with base excess, pH, and hematocrit were also evaluated.The study was a retrospective observational cohort study of 428 consecutive patients with severe COVID-19 admitted to Karolinska University Hospitals (Karolinska) Solna and Huddinge, between March 5 and April 20, 2020. The study was approved by The Swedish Ethical Review Authority (SERA), Regional Board of Linköping (N 2020-01752). Due to the retrospective nature of this project, the need for informed consent was waived in accordance with the approval from SERA. The study was conducted in accordance with all the relevant guidelines and regulations.Inclusion criteria were positive RT-PCR for SARS-Cov2, admission to a hospital connected to the Karolinska laboratory, and being assessed as having severe disease defined by SaO2 < 94% on room air at sea level , 29. PatPatients transferred to a hospital in another region, before they recovered, were excluded.Descriptive data on age, gender, BMI, weight, comorbidities , hypertension, and obstructive pulmonary disease (OPD)) were retrieved together with information on the day of hospitalization and admittance to ICU, need for intubation and length of mechanical ventilation, presence of acute kidney injury (AKI) and continuous renal replacement therapy (CRRT), death and total hospital stay.Patients were defined as discharged when dismissed from inpatient care to their homes or a rehabilitation facility. Information on mortality was retrieved from the medical records from admittance to the hospital until the last day of follow-up. A critically ill patient, including in the ICU group, was assessed by a specialist in anesthesiology to be in need of intensive care. Patients included in the ward group were never admitted to the ICU. AKI was classified as present when noted in the medical records or by ICD code. Three groups were defined according to the patients’ peak level of sodium; non-hypernatremia (<145 mmol/L), moderate hypernatremia (145–149 mmol/L), and severe hypernatremia (>149 mmol/L). Presence of hyponatremia, defined as plasma sodium < 137 mmol/L, was also recorded.Laboratory parameters were collected from the Karolinska laboratory database. Information on levels of plasma sodium, potassium, and serum osmolality as well as blood gas analysis of arterial chloride, base excess (BE), and pH was recorded from the day of admittance and onwards daily, when measured, until 2 weeks had passed. If there were several measurements of a parameter the same day, the result closest to 8.00 AM was recorded. Information on hematocrit and plasma creatinine levels at admission and at the day of peak sodium level was retrieved. For the non-hypernatremia group, the median day of peak sodium in the hypernatremia group was used for extraction of the second hematocrit and plasma creatinine values. For more information on laboratory equipment and methods, see Supplementary Table 1  and SPSS . Normality of data was assessed using Shapiro–Wilk test. Pearson’s In our total cohort of 406 patients with severe COVID-19, hyponatremia during admission was seen in 219 (57%) patients, and during 2-week study period, 299 (74%) patients had at least one sodium result below 137 mmol/L. Over time, sodium in plasma increased to the level of hypernatremia in 170 patients (42%) and 61  of these patients had peak levels of 150 mmol/L or above.2, and the most common comorbidities were hypertension (39%) and diabetes mellitus type 2 (30%), see Median age of the total cohort was 59 years, the majority were males (75%), median BMI was 29 kg/mP = 0.171 and P = 0.064, respectively.The cohort was further divided into three groups, depending on the development of hypernatremia and its severity, and the descriptive variables are presented in each group. No differences in the distribution of descriptive variables were found between the groups with moderate hypernatremia, severe hypernatremia, or normonatremia . There wP = 0.032), and a higher proportion of patients with DM II was seen in the hypernatremia groups in the ward group (P < 0.001). There were no other significant differences found in the subgroup analysis regarding the descriptive variables of Another subgroup analysis was performed dividing the total cohort into two groups depending on whether the patient was stable enough to only be treated at standard level of care (the ward group) or if the patient was in need of intensive care (the ICU group) during the time in hospital. The two groups were further divided into three groups depending on the development of hypernatremia, as described above. Less patients with treated hypertension were found in the hypernatremia groups in the ICU group compared to the non-hypernatremia group , and 21% did not survive . When diP = 0.001), using binary logistic regression and controlling for age, gender, and presence of diabetes mellitus type 2, hypertension, and OPD. There was no association with death found for admission levels of sodium, potassium, and chloride, (P = 0.626), (P = 0.820), and (P = 0.866), respectively.A decrease in pH levels during admission by 0.1 did significantly increase the odds of death by 2.374 (95% CI 1.398–4.033) (P = 0.007 for both). A decrease in pH level during admission by 0.1 increased the odds of need for mechanical ventilation with 2.864 (95% CI 1.440–5.697) (P = 0.003). There was no association with mechanical ventilation found for admission levels of chloride (P = 0.343).A decrease in sodium or potassium level during admission, by 1 mmol/L, increased the odds of need for mechanical ventilation by 1.153 (95% CI 1.040–1.280) and 2.752 (95% CI 1.315–5.763), respectively . For more information on group differences and P-values see Supplementary Table 4. Regarding serum osmolality, increasing levels during the course of hospitalization occurred with a median of 315 mOsmol/kg a week after admission.The different patterns of laboratory parameters of the ICU group, containing critically ill patients, divided into groups by peak sodium are presented in Fig. 2, and information about the number of patients contributing to each median is shown in Supplementary Table 3. On day 0, no differences between the groups were seen in any of the five parameters investigated . On day 4, only differences between sodium levels could be shown. On day 8, in additional to differences in sodium levels, there was a significant difference in chloride levels between the moderate hypernatremia group and the severe hypernatremia group as well as significant differences in base excess between the patients with no hypernatremia and the other two groups. On day 12, group ANOVA showed significant differences in all parameters except potassium. The non-hypernatremia group was different from all the other groups, and there were significant differences between moderate and severe regarding sodium and chloride. Potassium levels showed significant differences between the non-hypernatremia and moderate hypernatremia groups, but the group ANOVA was not significant . Pairwise comparison showed lower potassium in the group with severe hypernatremia compared to the group with non-hypernatremia (P = 0.024) (potassium at day of peak sodium).For the patients in need of intensive care, potassium substitution was very common, stated in the patient medical records. Therefore, a subgroup analysis  of potassium levels in the ward group was performed and found significant , with a median hospital stay of 22 days in the hypernatremia group and 10 days in the non-hypernatremia group. The need for ventilatory support was seen in a larger proportion  of the hypernatremia group  compared to the non-hypernatremia group .The presence of hypernatremia was associated with a long time stay in the hospital (χ2(6) = 80.737, P < 0.001). Three of the individual variables were statistically significant; age (P < 0.001), gender (P = 0.017), and the presence of hypernatremia. An increase in age by 1 year was associated with 1.075 (95% CI 1.048–1.104) times higher odds of death, and males had 2.336 (95% CI 1.162–4.696) times higher odds of death compared to females. Presence of hypernatremia was associated with 3.942 (95% CI 2.269–6.851) times higher odds of death. To further investigate possible contribution or association with volemic status, an additional model was run with the added covariate hematocrit on the day of the sodium peak. For the non-hypernatremia group, the day of median sodium peak in the hypernatremia group, day 9, was used. This model did not show any association between hematocrit (P = 0.488) and risk of death, but still a significant association between hypernatremia and death (P < 0.001). Higher sodium was also associated with a higher likelihood of death, as an increase by 1 mmol/L was associated with 1.087 (95% CI 1.034–1.143) times higher odds of death.To investigate the effect of hypernatremia on the likelihood of death, a binary logistic regression was conducted. Age, gender, peak sodium level, and presence of diabetes mellitus type 2, hypertension, and OPD were entered into the model. The logistic regression model was statistically significant (P = 0.764). There was a significant difference in hematocrit between the groups on the day of sodium peak (P = 0.002 using one-way ANOVA). The median hematocrit levels decreased in the groups with higher sodium levels. We found a median value of 0.37 in the non-hypernatremia group, 0.35 in the moderate hypernatremia group, and 0.33 in the severe hypernatremia group. The hematocrit values in the moderate and severe hypernatremia groups are thus below reference levels on the day of peak sodium levels, consistent with hypervolemia or dilution , as assessed by Wilcoxon signed ranks tests, between admission and the day of the sodium peak.There was no difference between the three groups in hematocrit on admission  of in-hospital hypernatremia found in our cohort could be an viral effect on endocrine functions, physiological reactions to severe disease, and/or increased fluid loss compared to intake from iatrogenic dehydration caused by a negative fluid balance. Dehydration following treatment according to the acute respiratory distress syndrome (ARDS) protocol together with the virus disturbing endocrine functions, like the Renin-angiotensin-aldosterone system (RAAS), would be expected to shift the electrolyte pattern from hyponatremia to hypernatremia. It is notable that more ICU patients were receiving treatment for hypertension before the onset of COVID-19 in the group that did not develop hypernatremia, and it can be speculated that if the development of hypernatremia was inhibited by the anti-hypertensive drugs, possibly by modulation of the RAAS. Other possible contributing factors could be osmotic diuresis due to the severe catabolism seen in critically ill ICU patients .In the present cohort, almost all patients with sodium levels above 149 mmol/L received active sodium-lowering treatment, according to the patient medical record. There was also a significant decrease in hematocrit in both groups with hypernatremia between admission and day of sodium peak, speaking against dehydration as a main contributor to the hypernatremia. Therefore, we believe that the very high sodium levels were unintended and likely caused by the disease.In addition, there was an increased length of hospital stay, need for mechanical ventilation, and mortality in the hypernatremia group compared to the non-hypernatremia group. Altogether, these clinical observations suggest that hypernatremia is an indicator of severe illness.et al. reported a case series of six ICU patients with severe COVID-19 and hypernatremia . This may be explained by an over-activation of the RAAS, but to further understand the pathophysiology behind the variations in sodium levels in severe COVID-19, prospective studies with structured measurements of serum levels of angiotensin II, aldosterone, AVP, copeptin, urinary sodium, potassium, and osmolality, together with clinical information of fluid and sodium input and output, would be of great value.The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.A S designed the study, collected, analyzed and interpreted the data, wrote the first draft, and revised the manuscript. S R has interpreted the data and revised the manuscript. H S analyzed and interpreted the data, and revised the manuscript. C H has supervised the course of the study, interpreted the data, and revised the manuscript. All authors read and approved the final manuscript.


Machine learning modeling can provide valuable support in different areas of mental health, because it enables to make rapid predictions and therefore support the decision making, based on valuable data. However, few studies have applied this method to predict symptoms’ worsening, based on sociodemographic, contextual, and clinical data. Thus, we applied machine learning techniques to identify predictors of symptomatologic changes in a Spanish cohort of OCD patients during the initial phase of the COVID-19 pandemic.127 OCD patients were assessed using the Yale–Brown Obsessive-Compulsive Scale (Y-BOCS) and a structured clinical interview during the COVID-19 pandemic. Machine learning models for classification (LDA and SVM) and regression (linear regression and SVR) were constructed to predict each symptom based on patient’s sociodemographic, clinical and contextual information.A Y-BOCS score prediction model was generated with 100% reliability at a score threshold of ± 6. Reliability of 100% was reached for obsessions and/or compulsions related to COVID-19. Symptoms of anxiety and depression were predicted with less reliability . The suicidal thoughts are predicted with a sensitivity of 79% and specificity of 88%. The best results are achieved by SVM and SVR.Our findings reveal that sociodemographic and clinical data can be used to predict changes in OCD symptomatology. Machine learning may be valuable tool for helping clinicians to rapidly identify patients at higher risk and therefore provide optimized care, especially in future pandemics. However, further validation of these models is required to ensure greater reliability of the algorithms for clinical implementation to specific objectives of interest. The COVID-19 outbreak, declared on March 11, 2020 by the World Health Organization (WHO), caused an increase in symptoms of anxiety, distress and depression in the general population, due to the uncertainty of the situation. People with mental disorders experienced worsening of symptoms and, in particular, OCD patients were affected by the general measures implemented to prevent the spread of COVID-19 infections  .Obsessive-Compulsive Disorder (OCD) is a psychiatric condition affecting 2–4% of the population and it is characterized by frequent, intrusive and threatening thoughts, images and ideas (obsessions) which the individual tries to control through repetitive behaviors and thoughts (compulsions) .Evidence suggests that people with OCD suffered a substantial impact with the current pandemic , especiaThe risk of worsening symptomatology can be predicted by using machine learning models, which have proved valuable in the field of psychiatry  for predFor several years, the world has been alerted to the possibility of the occurrence of global pandemics. Since 2014, when the Ebola epidemic emerged in West Africa, there has been talk of the possibility of a SARS pandemic that would entail devastating economic losses worldwide . ScientiIt is important have tools to predict how the severity of psychiatric patients’ symptoms might change with the onset of a new pandemic.The main objective of this study was to predict clinical changes in a cohort of OCD patients during the initial stages of the COVID-19 pandemic, based on contextual, sociodemographic and clinical variables, by using advanced machine learning models. Being able to predict worsening symptoms in conditions similar to the COVID-19 pandemic will guide the development of more effective treatments for such patients in future pandemics.SD = 11.87; 59 males; mean = 42.34, SD = 10.91) participated in this study. Sociodemographic and clinical characteristics of the sample can be consulted in A total of 127 adults with OCD with ages between 18 and 65 years old . These variables will be referred to hereafter as the 1.Sociodemographic data: age, gender, high-risk occupation and economic income during the pandemic.2.Social context during the pandemic: cohabitants, relatives with mental illness, dependents, changes in family cohabitation and environment, perception of family support, and leaving home.3.Contact with COVID-19: diagnosis of COVID-19 in a friend, relative or the participant themselves and daily time spent obtaining information about COVID-19 during the pandemic.4.Previous psychiatric conditions: age of onset of OCD and duration in years, OCD subtype, current therapy and type of response, Y-BOCS and HDRS scores and daily hours dedicated to rituals.5.Emotional regulation and coping strategies for stress: fears related to or caused by the COVID-19 pandemic and engagement in distracting activities.Machine learning has been successfully applied to a wide variety of fields in the modeling of many real problems. A machine learning model learns to predict the output data as a function of the input data in a process called training, that uses a collection of examples that include input variables  and output variables . Once the model is trained, it can generalize its prediction to new data not used during training. When the output data takes a limited number of unordered values, they are considered as class labels and the models are called classifiers. When the output takes continuous values, the model is a regressor.The classification was performed using the Linear Discriminant Analysis (LDA), implemented in the R statistical computing language, included as a simple linear classifier with a baseline performance. The Support Vector Machine (SVM) with radial basis function (RBF) kernel was also selected because it achieved a good performance in our previous generic comparative study . SpecifiWith the aim of anticipating the situation of patients diagnosed with OCD in a pandemic context, several output variables that are useful for clinicians were predicted:1.Patients’ scores on the Y-BOCS during pandemic, that anticipate the changes in symptomatology. This variable takes continuous values ranging from 0 to 40 and gives a regression problem.2.Appearance of obsessions and/or compulsions related to COVID-19, with values “yes” or “not,” that gives a classification problem.3.Scores of self-perceived anxiety symptoms, taking continuous values between 0 and 10 and giving a regression problem.4.Self-perceived depression symptoms, also taking continuous values between 0 and 10 and giving a regression problem.5.Suicidal thoughts take three possible values “no suicidal thoughts,” “thoughts about death” or “thoughts about suicide,” that gives a classification problem.6.Need for urgent psychiatric care, with values “yes” or “not,” that gives a classification problem.Prediction of each of these outputs requires the construction of a specific machine learning classifier or regressor, depending on the output. Both models for classification (LDA and SVM) and regression (LR and SVR) use the whole set of variables including continuous and discrete ones.K), that evaluates the agreement between the true and predicted categories labels excluding the agreement by chance , let the true positive (TP) be the number of sick people correctly identified as sick, the false positive (FP) be the number of healthy people incorrectly identified as sick, the true negative (TN) be the number of healthy people correctly identified as healthy, and false negative (FN) be the number of sick people incorrectly identified as healthy. The confusion matrix  refers to the classifier’s ability to correctly detect sick patients while the specificity (Sp) relates the classifier’s ability to correctly reject healthy patients, according to these definitions:RMSE), defined as:Finally, another performance measure for classification with two-classes is the area under the ROC curve (AUC), also in %. The ROC curve is defined by the sensitivity plotted against 100-specificity when the classifier behavior changes from assigning all the patterns to one class to assign all the patterns to the other class. In regression problems, the most popular measures are the Fisher correlation coefficient (R) and the root mean squared error  the model. Since most of the models have one or several hyper-parameters whose values must be tuned in order to get the best available performance, two of these threefold are used to train the model using a given combination of hyper-parameter values, while the remaining fold is used as the so called “validation set” to evaluate the performance of this trained model. The process is repeated for the different combinations of hyper-parameter values, and the combination with the highest performance on the validation set is selected. Finally, the model trained with the training and validation set using the best combination of hyper-parameter values is tested on the i-th fold, which was devoted to the test. This process is repeated for i = 1,…,4 and the test performance is averaged over the fourfold.In our study, we use a fourfold cross-validation to estimate the model performance. In the SD = 11.3 years). The mean age of onset of the disorder was at age 17.5 years (SD = 6.2). The mean severity of OCD prior to the pandemic was 17.9 points, and the mean score for symptoms of depression was 10.83 points. Of the 127 participants, 17 lived alone (13%), 40 lived with their birth family (32%), 67 lived with their own family (53%), and 3 lived with friends (2%). In addition, 54 participants were employed (42%), 16 were unemployed (13%), 53 were pensioners (42%), and 4 were students (3%). Finally, 14 participants (11%) were living with other people with psychiatric disorders.The sample used in this study comprised 127 participants (53.5% women). The participants ranged in age from 18 to 64 years . Following the Colton criterion (Y-BOCS during the pandemic is represented in Y-BOCS during the pandemic predicted by the model. The red dots lying within green lines represent patients for whom the prediction of Y-BOCS during the pandemic was wrong in less than 3 of the true scores (indicating that 76.47% of the patients were correctly classified within this tolerance threshold). This tolerance threshold is related to MAE. Correct classifications for different tolerances (t) were as follows: 15.44% of the patients were classified within t = 0, where true and predicted values were equal. In the case of t = 1 (Y-BOCS during the pandemic was predicted within a tolerance threshold of ± 1), 44.85% of the patients fit within this threshold, while 65.44% of the patients were correctly classified with t = 2, and 76.47% of the patients were correctly classified within t = 3. The percentage of patients correctly classified within different tolerances in Y-BOCS during pandemic is represented in Regarding the regression analysis, the correlation (R) and Mean Absolute Error (MAE) for the outputs riterion , the preself-perceived depression, the prediction was improved by using the SVR regressor and including gender (MAE = 1.51 and R = 0.68). Prediction of self-perceived anxiety was improved by using the SVR regressor but only considering the inputs taking MAE as criterion (MAE = 1.76 and R = 0.53). When R was used as a criterion, the prediction was improved by including gender (MAE = 1.85 and R = 0.58). Following the Colton criterion, the prediction varied from moderate to good for self-perceived depression and self-perceived anxiety. All of the results for prediction of each variable are presented in self-perceived depression and self-perceived anxiety) with four different thresholds: t = 0, t = 1, t = 2, and t = 3.For new obsessions and/or compulsions related to COVID-19 infection (2 classes), suicidal thoughts , and are reported in obsessions and/or compulsions related to COVID-19 was perfect (kappa = AUC = 100%) with the SVM classifier including inputs and gender. For the remaining outputs, the results were adequate, with kappa values of between 21 and 40%: suicidal thoughts (kappa = 38.9% using LDA without gender information), and need for urgent psychiatric care (kappa = 32.3% using SVM including gender information). In this case, both classes are very unbalanced (only 6.3% of patients required urgent care). Thus, the AUC (80.9%), that does not consider the class unbalance, is much higher than kappa.classes) and suicidal thoughts with the inputs and the classifier LDA (kappa = 38.9%) in With the aim of explaining the meaning of a specific kappa value, we present the confusion matrix for fss function of the nan package of the Octave software, that uses the Feature Subset Selection and Feature Ranking method . In Sexual Subtype), the SVM predicted Obsessions and compulsions with the same kappa (100%) as using the whole set (28 variables). Considering regression, the SVR using only the most relevant variable Ritual hours achieved R = 0.90, very near to the maximum value R = 0.94 achieved with all the variables, in the prediction of Y-BOCS during the pandemic, even excluding the Previous Y-BOCS variable.The expectable behavior is that performance gradually degrades as the number of variables reduces. This degradation should be slow at the beginning, where the less relevant variables are discarded, and fast when more relevant variables are removed. This behavior was observed in the majority of the outputs, such as thoughts  raised fThis validity study aimed to demonstrate the reliability and usefulness of using machine learning models to predict symptomatology changes in a cohort of OCD patients during the COVID-19 pandemic based on pre-pandemic sociodemographic and clinical data. Worsening of OCD symptoms prediction or the emergence of new symptomatology is important in situations such as pandemics, as it could help clinicians to prescribe individually tailored interventions to patients at risk. The results of our predictive analysis based on the full set of input variables was useful for a reliable prediction of the outputs. Specifically, the interview provided very good reliability regarding prediction of changes in general OCD symptomatology and in COVID-19 related symptoms, as well as prediction of OCD comorbid symptoms such as depression or anxiety.Y-BOCS during the pandemic, almost 100% correct classification was achieved in a ± 6 threshold. The model may fail to classify the patient’s severity range especially if the score difference is very small. However, if the difference falls above or below 6, the model shows very good prediction, wish can be crucial to detect changes in the severity level of OCD, especially in the cases in which subjects have scores in the YBOCS that are in the cutting edge to change to a different severity level .Regarding the reliability prediction of Prediction of changes in symptoms during the initial stages of the pandemic was important to enable provision of appropriate and timely support to high-risk patients. Evidence of worsening of OCD symptoms during the pandemic has been reported, especially in symptoms, such as compulsive hand-washing, related to the measures implemented to prevent COVID-19 infections , in bothAnxiety and depression were by far the most commonly reported psychological symptoms in OCD patients  during tneed for urgent psychiatric care and suicidal thoughts), the models yielded a low level of agreement between the true and the predicted value. For need for urgent psychiatric care, the reliability was improved by including gender. Predicting comorbid symptomatology is very important for the prognosis of OCD patients. Recent studies have reported sleep problems  were generally very small. Thus, gender information may be implicitly included in some of the other input variables, providing the information needed in those cases.This study has the following limitations: generality of the results to the OCD population needs to be considerate with caution, and the since the sample size used in this preliminary study is small. In addition, due to pandemic-related restrictions, the evaluations were performed by phone, which may have been less effective that face-to-face clinical evaluation in detecting clinical changes in the symptomatology. Also, we did not include the type of pharmacological treatment in the model, nor the comorbid disorders that patients presented. We did not consider variations in pharmacological treatment (type and dosage) over the examined period due to patients’ worsening that could be interesting to predict.We constructed relatively reliable and accurate predictive models for OCD symptoms during the COVID-19 pandemic, providing useful information about the most relevant variables for predicting worsening of symptomatology among OCD patients during a pandemic situation. The present results should be taken into account in developing preventive measures for the OCD population at risk of worsening symptoms. Prediction of other symptoms such as emotional traits could prevent suffering in OCD patients, who would otherwise have to seek urgent care in mental health units in a pandemic situation. Prediction of symptoms during a pandemic may not require an extensive battery of clinical measures in order to distinguish between patients at higher risk of worsening of symptoms from those at lower risk and, therefore, to ensure provision of timely and appropriate clinical support.Prediction of symptoms also has important benefits to the general population. The maintenance of scheduled consultations by telephone as opposed to unnecessary constant monitoring of OCD patients could help decongest mental health services, enabling more efficient distribution of human resources to attend to people who develop new comorbidities and new mental health problems caused by the pandemic , such asMachine learning models are important techniques for identifying sets of predictors in OCD patients, with implications for clinicians and researchers. Our study may serve as proof of viability for future applications of the machine learning models developed. This method could be used to develop a software application that could be used in psychiatric services, acting as an alarm system to predict changes or new symptomatology to be developed by patients under a future pandemic situation, and clinicians should be aware of this information.In conclusion, our study provides evidence that artificial intelligence can be used efficiently to predict the psychological impact of a pandemic in OCD patients. Some of the most important symptoms in this context can be predicted by using a machine learning model in changes in Y-BOCS scores and the appearance of OCD symptomatology related to COVID-19. These models may be of great support for clinicians to provide optimized and personalized care to people with a high risk of suffering mental health problems during situations such as a pandemic. When prediction of symptoms is not reliable, clinicians should consider other symptoms that patients may display. Further validation of the models is required in order to enable clinical implementation of the current findings.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of Hospital de Bellvitge. The patients/participants provided their written informed consent to participate in this study.MT-F: conceptualization, methodology, investigation, writing—original draft, writing—review and editing, and visualization. EC: conceptualization, methodology, software, validation, formal analysis, writing—original draft, and writing—review and editing. ÓG: resources, writing—original draft, writing—review and editing, and supervision. CS, SB, LM-B, and ER: investigation, resources, and writing—review and editing. MF-D: methodology, software, validation, formal analysis, and writing—review and editing. JM and AC: resources, writing—review and editing, and supervision. SC: conceptualization, methodology, resources, writing—original draft, and writing—review and editing. PA: conceptualization, methodology, investigation, resources, writing—original draft, and writing—review and editing. MF-P: conceptualization, methodology, investigation, writing—original draft, writing—review and editing, visualization, and project administration. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


We designed four learning conditions: Handwriting Chinese (HC), Viewing Chinese (VC), Drawing followed by Character Recognition in Chinese (D-C), and Drawing followed by Word Recognition in English (D-E). In both handwriting and drawing conditions, we also designed curved vs. straight-line stimuli. Both behavioral and EEG results showed that handwriting straight line strokes facilitated visual word recognition in Chinese compared to handwriting curved lines. Handwriting conditions resulted in a lateralization of the N170 in typical readers, but not the dyslexic readers. Interestingly, drawing curved lines facilitate word recognition in English among dyslexic readers. Taken together, the results of the study suggest benefits of handwriting on the neural processing and behavioral performance in response to Chinese character recognition and curved-line drawing effects on English word recognition among dyslexic readers. But the lack of handwriting effects in dyslexic readers suggest that students who have deficits in reading may also be missing the link between multisensory integration and word recognition in the visual word form areas. The current study results have implications for maintaining handwriting practices to promote perception and motor integration for visual word form area development for normal readers and suggest that drawing practices might benefit Chinese dyslexic readers in reading English.Handwriting serves to link auditory and motor routines with visual word processing, which is a hallmark of successful reading. The current study aims to explore the effect of multisensory integration as a pathway to neural specialization for print among typical and dyslexic readers across writing systems. We identified 9–10-year-old dyslexic Chinese children ( Writing meaningful symbols is a major landmark in the evolution of human culture. Handwriting connects visual word processing, a milestone for successful reading, with motor and auditory routines  that promotes behavioral performance and connects brain systems to functional networks  and readers , and others of which consist of straight lines . English words consist of letter strings in a sequential order. The word recognition process takes place The N170 is an event-related potential (ERP) functioning as a neurophysiological indicator of early visual word recognition. The typography of N170 ERP responses demonstrates visual specialization for reading development , and viewing Chinese (VC) as a control; and the difference between drawing followed by Chinese recognition (DC) and drawing followed by English recognition (DE). Second, the current study also focuses on the stimuli effect of either curved or straight lines. Specifically, we focus on the early visual ERPs indicator of N170, and aims to explore the effect of four learning conditions on the underlying different neural mechanism word recognition. The following research questions guide the present investigation:Whether and to what extent does the handwriting effect exist in word recognition in typical and dyslexic readers in terms of behavioral and ERP responses;Whether and to what extent does the drawing effect exist in word recognition in typical and dyslexic readers in terms of behavioral and ERP responses;Whether and to what extent does the stimuli effect (curved line vs. straight line strokes) exist in Chinese character recognition in handwriting in terms of behavioral and ERP responses;Whether and to what extent does the stimuli effect (curved vs. straight-line shape) exist in English word recognition in drawing in terms of behavioral and ERP responses;How different is it in the laterality effect of the handwriting and drawing on word recognition across languages  between typical and dyslexic readers?Mage = 9.5 years, SD = 0.86) in grades three and four, in which handwriting instruction has just been introduced and is thus considered as the critical period of handwriting development, participated in the experiment. Dyslexic readers were also diagnosed from a pool of nearly 450 grade 4, 5, and 6 students from elementary school. After screening, 21 children  in grades three and four participated in the experiment.The University of Science and Technology Beijing (USTB) ethics committee approved the study. The consent forms were signed first, and a background language experience survey were also completed by individual parents of the participants. The survey also included questions about children's developmental disorders and learning disabilities. After screening, 21 children . All the participants were right-handed, with normal or corrected-to-normal vision, and no history of neurological disorders based on screening tests. The intelligence quotients of our selected participants were all above 80, as assessed by Wechsler Intelligence Scale for Children (WISC)-IV Chinese Version. There was no variability in participants' English proficiency as they were English beginners. At the point of the experiments, they had been taught all 26 letters at school and were familiar with all of the stimuli. We offered the stipends for both traveling to the from the experimental sites and their accommodation fees. Each individual participants were also paid with 80 yuan (approximately $11 USD) per hour.To be diagnosed as having dyslexia, children's checklist composite score and at least three sets of cognitive-linguistic composite performance needed to be at least 1 SD below the means of their respective age groups on the parent-report scale of Dyslexia Checklist for Chinese Children . Thirty-two target 1 contained all 26 capital letters. The word length of the 32 target 2 words contained no more than 6 letters in caps. Before training, we made sure that all participants were familiar with the forms of these words. Therefore, the words chosen were known by all participants, which controlled for the effect of familiarity. Because participants were familiar with all of the stimuli, learning should not be affected by priming as all four conditions  shared experimental stimuli with similar features and the only differences lied in the learning procedure. Even if a priming effect were present, comparison between conditions should cancel it out. The judgment task was the same for both Chinese and English: to decide whether target 1 was embedded in target 2. The sample stimuli are shown in For two drawing condition, the stimuli containing 4 curved-line drawing images , and 4 straight-line drawing images . Pleases refer to A within-subject design was carried out. Four conditions were treated as independent variable; behavioral performance (accuracy and response time) and the magnitudes of N170 ERP component were treated as the dependent variables for different research questions.There were four learning conditions. The first learning condition was viewing-Chinese (VC), under which participants viewed Chinese word stimuli and then responded to the judgment target task by making a binary decision on whether target 2 contained target 1. The second condition was handwriting-Chinese (HC), in which participants wrote simple Chinese character stimuli on a writing pad and then responded to the same Chinese judgment target task. The drawing condition followed by Chinese recognition (DC) required the participants to draw the prompt  on the writing pad first and then respond to the embedment judgment task in Chinese. The drawing followed by English recognition (DE) asked the participants to draw the same prompts as those in the DC condition and the responded to the judgement task in English. The order of the four conditions in this experiment was counterbalanced.Each participant participated in an electroencephalogram (EEG) test with a total duration of 350 s. The data was collected in the EEG laboratory of the National Institute of Education Science, and all materials appeared in the center of the computer screen. Before the formal experiment, participants participated in a training activity designed to familiarize them with the experimental procedures in all four conditions. See Response time and accuracy were recorded during EEG data acquisition. EEG data was collected using NeuroScan's ESI-64 system. Electrode position in this study approximated locations of the international 10–20 system. The study used the left mastoid as the reference electrode. The vertical electrooculogram (VEOG) was recorded by using two electrodes placed above and below the midline of the right eye, and the recording electrodes of the horizontal electrooculogram (HEOG) were placed beside the left and right eyes in horizontal alignment with the eyeball.All electrodes were placed on the scalp using conductive paste to ensure that the impedance of each electrode was kept below 5 KΩ. The EEG data acquisition software was NEUROSCAN. The amplifier was SYNAMPS2, and AC continuous sampling was adopted. Scalp potentials were recorded with a sampling rate of 1,000 Hz, and the bandpass filter is 0.05~100 Hz.Offline analysis of EEG data was performed using Curry 7.0. During the recording, the left mastoid was used; later, the data was referenced offline using a reference averaged across left and right mastoids. First, a constant baseline correction was performed. Second, the data was digitally filtered with a 30-Hz lowpass. Then, the components related to eye movement were removed. In addition, amplitudes exceeding ±100 μV were also excluded as artifacts. The continuous EEG data was segmented, with the duration of the segmentation starting 200 ms before the onset of target 1 and extending 800 ms after target 1. Finally, the ERP components were superimposed and averaged, and the baseline correction was performed using the baseline of 200 ms before the stimulus.For behavioral data, we conducted 4  × 2  repeated measures ANOVAs on response time and accuracy.via PO7 and PO8 electrodes, and a lateralization effect has been reported, with the left negative wave larger than the right negative wave  × 2 (electrode position: left PO7 and right PO8) repeated measures analyses of variance (ANOVAs) were performed to analyze the amplitude and latency of the N170 of both normal and dyslexic readers. After demonstrating a significant main effect of group and learning condition, as well as their interaction, we broke the analyses down into two groups . To answer the first two research questions, we compared three pairs of learning conditions  in the normal and dyslexic readers groups respectively.For ERP data, according to prior literature  × Laterality (PO7 vs. PO8) analyses on both behavioral data and hemispheric differences in the N170. A Bonferroni correction was used to correct for multiple comparison as the data violated the assumption of sphericity  and response time (RT) for target 2. Accuracy analyses were based on the aggregated means per subject per condition. We recorded the response time (RTs) at the onset of target 2 button press. The analyses also excluded the outliers in RTs in the extreme 5% on either end of the Z-normalized distribution of RTs . At last, 7.5% of trials being excluded as outliers, following the criteria (from 5 to 10%) suggested by Ratcliff . The desF = 24.71, p = 0.04, η2 = 0.029] and condition × group interaction ; for accuracy, there was a significant effect of learning condition  and a significant condition × group interaction . Therefore, three sets of post-hoc analyses were carried out below in normal and dyslexic readers, respectively.Four repeated-measures analyses of variance (ANOVAs) were performed using a single factor , by submitting response time and accuracy for each condition across normal and dyslexic readers. The group  factor was used as the between-participant factor. Response time and accuracy of normal and dyslexic readers demonstrated significant effects of learning condition. For response time, there was a significant effect of learning condition , and the accuracy rate in HC  was significantly higher than in VC , . For dyslexic readers, the patterns were the same. Their response time in HC  was shorter than VC , , and accuracy of HC  was lower than VC , .Among normal readers, the response time in HC  was shorter than DC , , and the accuracy in HC  was significantly higher than DC , . For dyslexic readers, there was a longer response time of HC  compared with DC ,  and accuracy in HC  was lower than DC , .For normal readers, the response time in HC  was not significantly different from English recognition in the DE condition , , but the accuracy of DC  was significantly lower than the DE condition , . This pattern of results might not be affected by the condition effect between DC and DE, but by the fact that the normal readers felt more familiar with the English stimuli than the Chinese stimuli. For dyslexic readers, there was no difference in response time (p = 0.28), and no significant difference between accuracy with DE higher than DC either (p = 0.17).For normal readers, the response time of Chinese recognition in the DC condition  was higher than for straight-line characters , , and the accuracy for curved-line characters  was lower than straight-line characters  .For normal readers, the response time for curved-line characters  compared with straight-line drawing ,  and accuracy for curved line drawing  was significantly higher than straight-line drawing , .For dyslexic readers, there was a longer response time for curved-line drawing  = 4.72, p = 0.005, η2 = 0.02] and hemisphere , and a significant condition × hemisphere × group interaction . Moreover, we found a significant condition × hemisphere 2-way interaction , and significant group × condition two-way interaction . This indicates a different pattern across hemispheres between conditions and between the two groups, and also a significant group × hemisphere × stimuli three-way interaction .Therefore, the ERP analyses on the N170 amplitude were conducted to test comparison between normal and dyslexic groups separately in each of all four conditions. The descriptive statistics of ERP data are shown in To better show the handwriting effect, F = 0.72, p = 0.035, η2 = 0.03, showing that handwriting facilitates recognition of Chinese characters. For dyslexic readers, this pattern was the same. The amplitude of the N170 was significantly greater for HC than for VC, F = 1.879, p = 0.03, η2 = 0.06.For normal readers, there was a greater N170 amplitude during HC than VC, F = 2.191, p > 0.05, η2 = 0.068 for normal readers; F = 0.473, p > 0.05, η2 = 0.02 for dyslexic readers].For both normal and dyslexic readers, there was no difference in N170 amplitude for HC vs. DC, , VC , but laterality effects were not significant in the two drawing conditions .For normal readers, the peak value of N170 in the left hemisphere (PO7) was significantly higher than that in the right hemisphere (PO8) for HC  and for DE . The other two conditions showed no significant laterality effect .For dyslexic readers, the peak value of N170 in the left hemisphere (PO7) was significantly higher than that in the right hemisphere (PO8) for VC . Laterality effects were not significant for the curved line condition  or the control condition .For normal readers, the peak value of N170 in the left hemisphere (PO7) was significantly higher than that in the right hemisphere (PO8) for straight-line handwriting , but laterality effects were not significant in the straight-line drawing condition and control condition (p < 0.01).For dyslexic readers, the peak value of N170 in the left hemisphere (PO7) was significantly higher than that in the right hemisphere (PO8) for curved-line drawing followed by English recognition [We investigated handwriting in comparison to drawing on word recognition between typical and dyslexic readers. We first compared handwriting-Chinese (HC) with viewing-Chinese (VC) characters and with two other drawing conditions, i.e., drawing followed by Chinese recognition (DC) and drawing followed by English recognition (DE). Moreover, stimuli to be handwritten and drawn included both curved-line vs. straight-line strokes and curved-line vs. straight-line shapes. Five main findings were revealed. First, we found a Chinese handwriting facilitating effect in normal readers on behavior and the N170 compared to viewing in Chinese. Second, we found a drawing facilitating effect on English word recognition compared to Chinese character recognition for dyslexic readers, represented by behavioral and N170 indicators. Third, we revealed a laterality effect of handwriting in comparison to viewing Chinese among normal but not dyslexic readers, suggesting greater specialization in reading development in normal readers. Fourth, for normal readers, the left lateralization of the handwriting effects was supported by straight-line stimuli trials only but not for curved-line stroke handwriting. Finally, for dyslexic readers, the drawing effect on English word recognition was supported by curved-line shape drawing but not straight-line shape drawing.The handwriting-Chinese condition (HC) has a facilitative effect on the Chinese word recognition when compared to the viewing-Chinese condition (VC), with longer reaction time and higher accuracy in VC than in HC. The peak N170 amplitude for HC in microvolts was likewise significantly larger than that of VC. Both the behavioral and ERP results show that HC facilitated the Chinese character processes, and when compared to the results for VC, HC facilitated the Chinese characters processing for typically developing but not dyslexic readers. The fact that the HC condition elicited a greater N170 than the VC condition indicates the N170 reflects efficient orthographic recognition due to handwriting experience, consistent with Liu and Perfetti's  study reThe handwriting effect, on the other hand, did not persist in the response patterns for the dyslexic readers in our study. For typically developing readers, handwriting practice, which focuses on the intricate visual-orthographic components of stroke construction, is expected to enhance motor-sensory integration to aid visual recognition  did not have such an effect.More importantly, our findings are consistent previous studies that demonstrated laterality effect in Chinese word recognition. Cao et al.  claimed The absence of handwriting effects in dyslexic readers might be due to the following three reasons. First, the priming strokes of the basic symbols in the handwriting condition included only curved vs. straight-line strokes. These simple straight-line or curved-line handwriting experiences might not elicit dyslexic readers' sensitivity to the positional hierarchy and internal structure of the constituent parts of the Chinese characters  on dyslexic children's handwriting in relation to orthographic features of linguistic writing units. It is speculated that the visual-form areas in the brain might be less activated by curved letters in comparison to straight-line letters in English as the visual-motor integrative processing of curved and smooth shapes requires less cognitive effort than straight but sharp-angled shapes , Beijing Social Science Key-level Grant (18YYA001), and China National Science Foundations (62077011) awarded to the CG.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.