Dynamic Glass patterns (GPs) are visual stimuli commonly employed to study form–motion interactions. There is brain imaging evidence that non-directional motion induced by dynamic GPs and directional motion induced by random dot kinematograms (RDKs) depend on the activity of the human motion complex (hMT+). However, whether dynamic GPs and RDKs rely on the same processing mechanisms is still up for dispute. The current study uses a visual perceptual learning (VPL) paradigm to try to answer this question. Identical pre- and post-tests were given to two groups of participants, who had to discriminate random/noisy patterns from coherent form (dynamic GPs) and motion (RDKs). Subsequently, one group was trained on dynamic translational GPs, whereas the other group on RDKs. On the one hand, the generalization of learning to the non-trained stimulus would indicate that the same mechanisms are involved in the processing of both dynamic GPs and RDKs. On the other hand, learning specificity would indicate that the two stimuli are likely to be processed by separate mechanisms possibly in the same cortical network. The results showed that VPL is specific to the stimulus trained, suggesting that directional and non-directional motion may depend on different neural mechanisms. The human and non-human primate visual cortex is divided into two main streams called ventral and dorsal streams . The venmotion streaks  that influence motion perception [Cue invariance is the name given to this occurrence [Dynamic Glass patterns (GPs)  and randrception ,18,19,20rception . When thrception . This surception ,22. For rception  investigcurrence . Donato currence  assessedPsychophysical paradigms that looked at the individuals’ coherence thresholds were also used to study GPs and RDKs . Nankoo Most of the research into the neural underpinnings of dynamic GPs and RDKs has so far focused on complex configurations like circular and radial patterns. There have been no direct comparisons of the cortical visual regions involved in the processing of simple directional and non-directional motion elicited by dynamic translational GPs and RDKs. To bridge this gap and indirectly shed light on the neural mechanisms underlying dynamic translational GPs and RDKs, we employed visual perceptual learning (VPL). After persistent practice on the same activity, VPL refers to a considerably increased performance in a visual task ,29,30,31VPL has been used to improve visual functions, such as visual acuity, contrast sensitivity, and it can transfer to other untrained visual stimuli ,37,38. SThirty-one participants took part in the experiment. Specifically, fifteen participants  took part in the training with RDKs and sixteen  took part in the training with translational dynamic GPs. All participants were naïve except two of the authors (RD and LB) who participated in the experiment, one in the GPs training group (LB) and the other in the RDKs training group (RD). All participants had normal or corrected to normal vision. In the experiment, viewing was binocular. Participants have been randomly assigned to one of the two groups. Each observer was assigned by chance and in alternation to one of the two different learning groups . Participants performed the online experiment using their personal computers. The experiment was run in agreement with the World Medical Association Declaration of Helsinki . The stu2 and the length of the dipoles in GPs was 0.18°. Dynamic GPs were made of a set of independent frames where each frame contained a new dipoles’ spatial order, although dipoles’ orientation remained constant [We used translational dynamic GPs and RDKs. The spatial and temporal characteristics of dynamic GPs were the same as in Pavan et al. . GPs werconstant . Dynamicconstant .RDKs evoked directionally ambiguous motion. The lifetime of the dots was the same as the interval displayed to make a match with dynamic GPs. The temporal frequency of the stimuli was 20 Hz, with a single frame duration of ~0.05 s. In noise GPs, dipoles were randomly oriented. Instead, in noise RDKs, dots were placed in new random locations within the circular annulus on each successive frame . Both vihttps://zoom.us (10 January 2022); USA).The experiment has been programmed using the JavaScript library JsPsych  and carrThere were ten sessions in total: one pre-test, eight training sessions ,47, and To familiarize themselves with the task, each participant completed a series of trials with both stimuli . The coherent pattern was displayed in one interval, while the noise/random visual stimulus was delivered in the other. The participants had to report which temporal interval contained the coherent pattern by pressing the key ‘1′ on the keypad if the coherent pattern was contained in the first interval, and key ‘2′ if the coherent pattern was contained in the second interval. Each trial began with a 1-s black fixation point, followed by two 0.3-s intervals containing the visual stimuli and separated by a 0.2-s blank screen containing only the fixation point. The inter-trial interval was 2-s see .The pre- and post-tests were divided into four blocks, each with 300 trials. The first two blocks were performed with dynamic GPs, while the last two blocks were performed with RDKs. Except for the post-test, which was preserved in the same blocks order as the pre-test, the blocks order has been counterbalanced. As part of the familiarization with the task, participants completed a two-interval forced-choice task (2IFC) see . A modifThe training sessions differed from the pre- and post-tests for the number of blocks and the visual stimulus presented. The group that was trained with RDKs performed eight training sessions with RDKs, whereas the group that was trained with GPs performed eight training sessions with dynamic GPs. In addition, each training session consisted of three blocks of 300 trials each. A single training session lasted ~45′.lme4’ package [fitdist [log or inverse transform to the dependent variable as the manipulation we introduced  is supposed to directly affect the coherence thresholds rather than some function of them. Additionally, since all the coherence thresholds estimated are above zero and thus away from the negative boundary, it is unlikely for the model to produce negative values. The normality of residuals was assessed using a Shapiro–Wilk test. Outliers were identified using the median absolute deviation with a cut-off of 3 [The normality of residuals was assessed using the Shapiro–Wilk test. Data were analyzed using a Generalized Linear Mixed Model (GLMM) ,60,61,62 package ,64. A Ga package  and beca[fitdist . The lin[fitdist , a link off of 3 .W = 0.853, p < 0.001), with a high positive skewness of 1.45 (SE: 0.22). We also identified ten outliers that were included in the analysis. The GLMM included the learning group (learning GPs vs. learning RDKs), time (pre-training vs. post-training), and stimulus type (GP vs. RDK) and the interactions between all these terms as fixed effects. The subjects were the grouping variable. Fourteen models with different random effects (but the same fixed effects) were produced and compared. The best fitting model was selected using three different estimators of prediction error . The best fitting model from the three estimators of prediction error resulted in being a model with only random slope for time and stimulus type (no variation in intercept and correlation between random slopes for time and stimulus). The form of the best fitting model is as follows:χ2 = 11.627, df = 1, p < 0.001), time , stimulus , a significant interaction between group and stimulus , a significant interaction between time and stimulus , and a significant three-way interaction between group, time and stimulus type . The coefficients of the regression analysis are reported in R2 were 0.999 and 0.519, respectively.The regression analysis did report a significant effect of the group , coherence thresholds in the pre-test assessment were higher than in the post-test  and translational dynamic GPs had overall higher coherence thresholds than RDKs .The learning GP group exhibited a lower coherence threshold than the learning RDK group (adjp = 0.004), and between RDKs always for the two groups (adjp = 0.0119), suggesting a difference in coherence thresholds between GPs and RDKs for the two groups, and a significant difference between GPs and RDKs in the learning RDK group (adjp = 0.003).For the group x stimulus interaction, Holm-corrected post hoc comparisons reported a significant difference between GPs for the learning GP and learning RDK groups (adjp < 0.001) and RDKs (adjp < 0.001), between GPs and RDKs for the pre-training assessment (adjp = 0.0139), and between GPs and RDKs for the post-training assessment (adjp = 0.0314).For the time x stimulus interaction, Holm-corrected post hoc comparisons reported a significant difference between pre- and post-tests for GPs (adjp > 0.05). The same applies to the learning RDK group in which we found only a significant difference between pre- and post-test for the RDKs, but not for GPs (adjp > 0.05).For the three-way interaction, the most relevant Holm-corrected post hoc comparisons are reported in Given differences in the initial and final assessment sessions between the two groups, and to compare performance across conditions, the magnitude of learning was calculated for trained and untrained stimuli as follows :(1)MagniW = 0.755, p < 0.0001) and two outliers were identified. Data were analyzed using the Align Rank Transform (ART), a procedure for the factorial non-parametric analysis of variance [F1, 29 = 16.63, p < 0.001) . For the interaction between group and stimulus, Holm-corrected post hoc comparisons reported a significant difference only between GPs and RDKs in the learning GP group (adjp = 0.0089). For the learning RDK group, the high variability in coherence thresholds between the pre- and post-tests and the presence of an outlier (magnitude of learning = 2.03) might have biased the learning index by preventing a significant difference between GPs and RDKs for this group. In fact, uncorrected post hoc comparisons did report a significant difference between GPs and RDKs for the learning RDK group (p = 0.0431).This procedure allows for the assessment of any changes in performance based on the original performance level. variance ,71,72. Wvariance . A lineap-values were corrected with the Holm method for two comparisons. The results showed that, for the learning GP group, the magnitude of learning index was significantly lower than zero only for GPs  (adjp < 0.0001), but not for the RDKs (adjp = 0.24). On the other hand, for the learning RDK group, the magnitude of learning index was significantly lower than zero only for RDKs  (adjp < 0.0001), but not for the GPs (adjp = 0.45). These results further suggest high specificity for the trained stimulus.A series of one-sided one-sample permutation tests (sampling permutation distribution 5k) were performed on the magnitude index of each learning group and stimulus type to assess whether the magnitude of learning was lower than zero. A magnitude of learning equal to zero would indicate no learning for the trained stimulus and no transfer of learning to the untrained stimulus. The resultant a is the scale parameter, indicates the value of the power function in x = 1  and expresses the difference between the initial and the asymptotic performance (c), b is the learning rate , c is the asymptotic coherence threshold after an arbitrarily large number of learning sessions, and x represents the amount of practice . The aim of this analysis was to assess for differences between the groups in terms of learning rate, whether the two groups differed from the outset , and asymptotic performance.a, b, and c parameter per learning group). The maximally restricted model, i.e., the model that postulated no change between learning groups, had only three parameters , and assumed that the three parameters were the same across the two learning groups . Between the fully saturated model and the maximally restricted model, a lattice of models having a different number of parameters was fitted (F-test (using the function ‘anova’ in R) to compare the models and assess which one provides the best parsimonious fit of the data. In the F-test, if the resulting p-value is higher than the significance level (0.05), then the simpler model is likely to be the preferred one. On the other hand, if the p-value is lower than the significance level, then the more complex model  is likely to be the preferred one. It should also be noted that the F-test can be used only with nested models . Comparisons between models with the same number of parameters  were performed using three estimators of prediction error . In this case, the model with lower AIC, AICc, and BIC is likely to be the preferred model. We created a lattice of models from a fully saturated model to a maximally restricted model ,75,76. Ts fitted . The besa and b across the two learning groups, but different asymptotic performance (parameter c) was the best fitting model. For the restricted model 4, parameters were: a = 18.34 (SE: 3.36), b = 0.482 (SE: 0.159), c1 = 13.298 (SE: 3.56), c2 = 20.45 (SE: 3.56) (quasi-R2 = 0.972). Restricted model 4 is the preferred model as it fits better than the fully saturated model (p = 0.339), than the maximally restricted model (p < 0.0001), and it has lower AIC, AICc, and BIC than the restricted models 5 and 6, having the same number of parameters. It also fits better than models with more parameters .We found that the restricted model 4, i.e., the model consisting of the same parameters These results suggest that learning curves can be described by an extended power function that has the same starting coherence threshold and learning rate for the two groups, but a different asymptotic performance. The best-fitting model is reported in Using a VPL paradigm, we investigated the mechanisms underlying directional motion and form–motion integration in translational RDKs and dynamic translational GPs. The aim was to assess whether VPL could be transferred to the non-trained visual stimulus. Before and after the training sessions, the coherence thresholds for dynamic translational GPs and translational RDKs were measured in both groups (learning GPs and learning RDKs). After the initial assessment, participants were given eight training sessions ,42,77. VThese results suggest that separate neural circuits control the processing of motion signals in translational RDKs and the processing of form–motion interaction in dynamic translational GPs. One possibility is that dynamic translational GPs are primarily led by the perception of global form, which necessitates the integration of local characteristics across space and time . SwettenIn terms of directional motion, evidence suggests that RDKs primarily engage higher-order extrastriate visual areas specialized in motion processing, such as the hMT+ ,84,85,86Despite the present study suggests that the perception of dynamic translational GPs and RDKs relies on different processing mechanisms, when training with RDKs, there is a small amount of transfer, although not significant, for untrained GPs . In thisIn this context, various research has found that task difficulty influences transfer ,42,94,95Moreover, we observed lower coherence thresholds for RDKs than dynamic GPs in both learning groups. Participants perceived translational RDKs easier than dynamic translational GPs . This prIn conclusion, though there is brain imaging evidence that both dynamic GPs and RDKs activate some overlapping cortical areas  ,22, the


Age was found to significantly correlate with total aggression (r = −0.133 p = 0.031), verbal aggression (r = −0.138 p = 0.025), and anger (r = −0.151 p = 0.014). The analysis demonstrated statistically significant relationships between gender and physical aggression (p = 0.017), anger (p = 0.032), and hostility (p = 0.002). A statistically significant positive correlation between the quality of sleep as per the PSQI and all subscales of the BPAQ was found (p < 0.001). (4) A considerable proportion of HCWs experienced sleep disturbances during the outbreak, stressing the need to establish ways to reduce long-term adverse outcomes associated with chronic insomnia and mental health problems and adjust interventions under pandemic conditions.(1) Healthcare workers are exposed to increased risks of insomnia and aggression during the COVID-19 pandemic. The aim of the study was to assess insomnia, sleep disturbances, and aggression and identify the associated risk factors among healthcare workers during the COVID-19 pandemic. (2) A total of 264 healthcare workers participated in the study. The study was conducted with the diagnostic survey method, using the Buss–Perry Aggression Questionnaire, the Athens Insomnia Scale, the Pittsburgh Sleep Quality Index, and a self-administered questionnaire. (3) The vast majority of the respondents (81.06%) suffered from insomnia and had poor sleep quality (78.03%). Education ( The Coronavirus-Disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been recognized as a public health emergency of international concern. The World Health Organization (WHO) expressed concern regarding the impact of COVID-19 on mental health along with psychosocial and socioeconomic considerations of the pandemic [Healthcare workers are exposed to increased risks of insomnia and aggression during the COVID-19 pandemic. In a pandemic situation, with an increased number of employees under heavy workloads, the exposure to negative psychological effects is even greater, and that, in turn, can increase the level of anxiety, depression, or stress . It is iAs a public health emergency of international concern, the COVID-19 pandemic is a traumatic event affecting both sleep and the mental health of the general population and healthcare providers ,6,7. PooJahrami et al.  demonstrFrontline healthcare workers (FHCW), understood as medical personnel  involved in the assessment, quarantine, isolation, and treatment of COVID-19 patients are particularly at risk of stressors .Hiong et al.  demonstrBarua et al.  report tWorkplace violence (WPV) against medical personnel is a complex issue., and rigorous research that would offer a solution is lacking .According to reports from the World Health Organization (WHO), approximately 8–38% of medical personnel had experienced physical violence before the COVID-19 pandemic . AdditioAggression in the workplace is a common phenomenon, but there are professional groups that are particularly exposed to it, for example, the medical profession, including the professional group of nurses. In these groups, the source of aggression can be patients as well as colleagues . AggressPhysical and verbal aggression from patients, their next of kin, and visitors is a widespread problem in healthcare facilities and has become a major public health issue. Nursing is one of the professions most exposed to aggression and violence ,26.During the COVID-19 pandemic, an increased frequency of violence towards healthcare workers was reported . This haThe pandemic is evolving rapidly, hence there is a need to gather data allowing a global review of the mental health of healthcare workers during the COVID-19 pandemic ,34,35,36There is a relationship between the occurrence of insomnia, sleep disturbance, and increased aggression among medical personnel during the COVID-19 pandemic.We hypothesized that:The research was conducted in 2021 on healthcare workers working directly with patients diagnosed with SARS-CoV-2 infection in the Independent Public Clinical Hospital No. 1 of the Pomeranian Medical University named after Prof. Tadeusz Sokołowski in Szczecin.The inclusion criteria were age >18 years, a current license to practice as a nurse, having worked a minimum of 3 months in wards admitting patients diagnosed with SARS-CoV-2, and informed consent to participate in the study.The size of the study sample was established by a statistician on the basis of statistical data concerning the number of healthcare workers working in the Independent Public Clinical Hospital No. 1 of the Pomeranian Medical University named after Prof. Tadeusz Sokołowski in Szczecin. The confidence level was set at 95%, the maximum error at 7%, and the estimated fraction size at 0.5. A total of 300 individuals were invited to participate in the study; however, due to staff shortages and workload, 264 individuals were enrolled in the study.The study was carried out using a traditional method of distributing paper questionnaires by an interviewer among healthcare workers employed in the hospital. At every stage of the research, the respondents had the opportunity to obtain assistance if needed, as well as withdraw from the study.The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethical Committee of the Pomeranian Medical University in Szczecin by Resolution No. KB-0012/25/04/2020/Z. The study was conducted taking into account ethical considerations. Informed consent was required, and participation in the study was voluntary. Moreover, the participants were assured of anonymity and confidentiality and were free to withdraw from the study at any stage.The Buss–Perry Aggression Questionnaire (BPAQ) is a measure of aggression in adults. It consists of 29 items, subdivided into four factors: Physical aggression (9 items), verbal aggression (5 items), anger (8 items), and hostility (8 items) . The BPAAthens Insomnia Scale (AIS) includes 8 questions and is a common and easily interpretable screening tool used to measure insomnia, with a total score ranging from 0 to 24 points. The first five items relate to sleep-related symptoms and correspond to criterion A of the ICD-10 diagnosis of inorganic insomnia. If a given symptom occurred at least three times a week during a one-month period, it is to be marked –, which is consistent with the duration and frequency of symptoms required for the ICD-10 diagnosis of insomnia (criterion B). The remaining three items refer to daytime functioning  and correspond to criterion C of the ICD-10 diagnosis of insomnia, which includes complaints about insomnia consequences experienced during the day. Cronbach’s alpha for the AIS is 0.90 .The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire used for the assessment of the quality of sleep and sleep disturbances over a 1-month time interval. Nineteen individual items generate seven “component” scores, namely, subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for the seven components yields one global score. The PSQI has a sensitivity of 89.6% and specificity of 86.5% for identifying cases with a sleep disorder, using a cut-off score of 5. Cronbach’s alpha for the PSQI is 0.83 .Self-administered questionnaire—includes questions about sociodemographic data , employment , history of exposure to COVID-19, and additional information required in relation to COVID-19 collected using the authors’ questionnaire.The following standardized survey instruments were used:The analysis of quantitative variables was performed by calculating the mean, standard deviation, median, quartiles, minimum, and maximum values. The comparison of quantitative variables in two groups was performed with the use of the Mann–Whitney U test. The correlations between quantitative variables were analyzed with the Spearman correlation coefficient. The Kruskal–Wallis test and Dunn test were used in this study.p < 0.05 [All calculations were performed using R version 4.1.2. . The level of statistical significance was set at p < 0.05 .The study sample consisted of 264 healthcare workers. The mean age of the respondents was 43.42 years (SD = 11.05). The vast majority of the respondents were female (82.58%), in a formal relationship (54.92%), with higher education attainment (68.56%), and were living in a city of more than 100,000 residents (43.56%) and working at a hospital (46.97). More than half of the respondents had children (72.35%), and 84.85% of healthcare workers were in close contact with a person with a confirmed COVID-19 infection.The analysis was performed regarding sleep disorders (according to the AIS and PSQI) and aggression (according to the BPAQ) among healthcare workers during the SARS-CoV-2 Pandemic.The vast majority of the respondents (81.06%) suffered from sleep disorders and had poor sleep quality (78.03%) .The analysis of the results obtained with the BPAQ showed that the mean score for total aggression amounted to 70.18 points, while physical aggression had 18.96 points, verbal aggression had 13.77 points, anger had 18.78 points, and hostility had 18.67 points .This study analyzed the influence of selected sociodemographic variables  on sleep disorder and aggression among healthcare workers during the SARS-CoV-2 Pandemic.p = 0.043). Moreover, the study determined that insomnia was significantly less pronounced in childless respondents in comparison with other respondents (p = 0.004). Insomnia and trouble sleeping were found to be significantly more common in respondents who had completed Higher education (Bachelor) as compared with other respondents .It was found that insomnia was significantly more pronounced in respondents who were in a formal relationship rather than those that were single , verbal aggression (r = −0.138 p = 0.025), and anger (r = −0.151 p = 0.014). There were no statistically significant correlations between age and physical aggression or hostility (p = 0.017), anger (p = 0.032), and hostility (p = 0.002). It was found that in women, anger and hostility were more pronounced, and in men, we observed physical aggression. The analysis of the data did not demonstrate the influence of gender on total aggression and verbal aggression (p = 0.032). Physical aggression was significantly more pronounced in respondents in a formal relationship rather than single participants and in respondents with underage children rather than childless respondents. In turn, all types of aggressive tendencies were found to be significantly more pronounced in employees who completed Higher education (Bachelor) in comparison with other groups  on sleep disorder and aggression among healthcare workers during the SARS-CoV-2 Pandemic.p = 0.025), verbal aggression (r = −0.139 p = 0.023), and anger (r = −0.165 p = 0.007). Moreover, the analysis showed a statistically significant positive correlation between work time and physical aggression (r = 0.168 p = 0.006) and anger (r = 0.121 p = 0.05). Additionally, there was a statistically significant negative correlation between work time and verbal aggression (r = −0.132 p = 0.032)  .p = 0.044). The analysis showed a statistically significant relationship between the place of work (p = 0.002) and insomnia, according to AIS. Insomnia was markedly more pronounced in healthcare workers in non-invasive treatment wards, surgical wards, or highly specialized hospital wards in comparison with those working in other wards. Work experience and employment types were not statistically significant contributors to insomnia according to the AIS (Work time was found to significantly correlate with insomnia (r = 0.124  the AIS .p <0.001). Verbal aggression was significantly more intensified in healthcare workers of surgical and highly specialized wards rather than in those working in non-invasive treatment wards (p = 0.037). Anger was found to be significantly more pronounced in respondents working in surgical wards than in those working in highly specialized wards who, in turn, showed a markedly higher level of anger in comparison with the employees of the remaining types of wards under study (p < 0.001). Hostility was significantly more intensified among surgical-ward employees compared to the remaining groups (p < 0.001)  .p < 0.001)  .p < 0.001).Moreover, a statistically significant positive correlation between the quality of sleep as per PSQI and all subscales of BPAQ was found. This can be interpreted as the greater the intensity of sleep problems, the greater the intensity of all types of aggressive tendencies  has increased since the start of the pandemic (compared to 6–10% for pre-pandemic chronic insomnia). These data are consistent with other research that has also shown greater insomnia prevalence rates during the post-pandemic period, though some studies have shown even larger increases in moderate-to-severe insomnia symptoms ,43,44,45The meta-analysis by Pappa et al.  demonstrp < 0.001), thus suggesting that the decrease in quality may be a psychosomatic consequence of the COVID-19 infection.Fu et al.  report tOur own studies have demonstrated that it is important to conduct further research assessing the prevalence of aggression among medical personnel. The review of the literature on the subject shows that during the COVID-19 pandemic, there were reports of violence, bullying, or stigmatization against healthcare workers and patients . There iAccording to our own research, education, marital, and parental status were statistically significant contributors to insomnia according to the AIS. The studies demonstrated that insomnia was markedly more pronounced in respondents in a formal relationship as compared with single respondents, and it was also found to be higher in respondents who had completed Higher education (Bachelor) in comparison with other respondents. Furthermore, it was determined that insomnia was significantly less pronounced in childless respondents as compared with the rest of the group. Education was a statistically significant contributor to sleep quality according to PSQI. Sleep disturbances were markedly more pronounced among respondents who completed Higher education (Bachelor) as compared with other respondents.The review of the literature shows that there are numerous factors affecting the occurrence of sleep disturbances among healthcare workers, for example, providing care to patients diagnosed with COVID-19 , being aAge was found to significantly correlate with total aggression, verbal aggression, and anger. There were no statistically significant correlations between age and physical aggression or hostility. The analysis demonstrated statistically significant relationships between gender and physical aggression, anger, and hostility. It was found that in women, anger and hostility were more pronounced, whereas, in men, we observed physical aggression. Marital status, parental status, and education were found to significantly correlate with physical aggression. Physical aggression was markedly more pronounced in respondents in a formal relationship, as compared with single respondents, and in those who had underage children in comparison with childless respondents. In turn, all types of aggressive tendencies were significantly greater among respondents who completed Higher education (Bachelor) in comparison with the other groups. The literature review demonstrates that older age , female Our own studies demonstrated that work time significantly correlated with insomnia. Moreover, there was a statistically significant relationship between insomnia and working with COVID-19 patients and between sleep quality measured with the PSQI and working with patients diagnosed with COVID-19. The studies did not reveal any statistically significant relationships between sleep quality and work-related variables among healthcare workers during the SARS-CoV-2 pandemic. On the basis of the collected data, a statistically significant relationship between work experience, total aggression, verbal aggression, and anger was shown. Additionally, a statistically significant correlation between work time, physical aggression, and anger was found, as well as a statistically significant negative correlation between work time and verbal aggression. The studies show a statistically significant relationship between total aggression, verbal aggression, anger, hostility, and the place of work. Moreover, a statistically significant relationship between verbal aggression and working with COVID-19 patients was identified. On the basis of the obtained results, a statistically significant positive correlation between insomnia according to AIS with all aspects of aggression according to BPAQ was found. Moreover, a statistically significant positive correlation between the quality of sleep according to PSQI and all subscales of aggression according to BPAQ was demonstrated. This means that more pronounced sleep disorders translate into a higher intensity of all types of aggressive tendencies.The review of the literature on the subject shows that during the COVID-19 pandemic, violence in the workplace was found to increase, which presumably contributes to the increased prevalence rate of sleep disorders among healthcare workers ,73,74. NMeaklim et al.  demonstrThe study by Demichelis et al.  points tKillgore et al.  found thThe meta-analysis by Yosep et al.  determinPagnucci et al.  demonstrIn conclusion, problems with sleep or aggression seem to be widespread during the COVID-19 pandemic. The vast majority of respondents experienced sleep disturbances during the pandemic. Therefore, more longitudinal and randomized controlled studies are needed to examine how insomnia and the expression of aggression change over time and determine the causal link between problems sleeping and mental distress.It is necessary to establish and implement screening programs and preventive measures concerning sleep disorders to help healthcare workers identify and overcome sleep disturbances. They must be encouraged to apply evidence-based strategies, e.g., cognitive-behavioral therapy, meditation, sports, and healthcare interventions. Moreover, medical personnel should be trained in identifying and treating sleep problems in various populations.Studies should be conducted with the aim of determining the extent of insomnia by its severity; it is necessary to conduct longitudinal studies to determine whether insomnia is short-term or long-term.To ensure the wellbeing of healthcare workers and quality of care during a pandemic, it is vital to provide targeted preventive measures and psychological support to the group. Additionally, effective programs for fighting aggression may have a positive effect on the sleep of healthcare workers.Good-quality sleep is of fundamental importance to safety in the workplace and the health of healthcare workers. By means of assessing sleep quality during times of crisis, medical personnel can identify possible means of promoting health and safety through education on sleep hygiene, monitoring sleepiness or fatigue, and the assessment of the possibility of changing organizational policy.The COVID-19 pandemic has had a drastic effect on the functioning of healthcare in Poland. The physical and emotional load on healthcare workers is substantial and constitutes an additional risk to providing patient care and the productivity of a hospital. It is necessary to conduct further research on the relationship between workplace violence in medical facilities and pandemic-related factors. Aggression from patients is indeed an obstacle to ensuring the best practices and providing efficient care. It is a challenge that may delay treatment and allocation and inhibit the best possible result of hospital treatment. Therefore, it is vital to implement more safety precautions, reduce workplace violence, improve communication and problem-solving methods with respect to patient care, and introduce training courses with respect to the means of coping with aggression.The present study has some limitations.The study was conducted in one medical facility in Szczecin during the second wave of the pandemic, therefore the possibility of generalization of the obtained results may be limited.The data were collected with self-report questionnaires and not with clinical interviews.Objective sleep measurement data were not collected to confirm the subjective reports of sleep.One of the disadvantages of adopting a convenient sample was the small sample size. A larger study group would provide greater statistical power.A considerable proportion of HCWs have experienced sleep disturbances during the outbreak, stressing the need to establish ways to reduce long-term adverse outcomes associated with chronic insomnia and mental health problems and adjust interventions under pandemic conditions.Our study demonstrates a significant association between sociodemographic variables  and work-related variables  and the prevalence of insomnia or aggression among healthcare workers during the COVID-19 outbreak.Insomnia and sleep disturbance were found to be connected to aggression. It transpires that sleep plays a significant role in aggressive behavior. Further studies are necessary to demonstrate the relationship between sleep disturbance and aggression, and to investigate the moderating and intervening variables that would explain when and in what way aggression affects sleep. Since nurses are subject to different types of aggression and experience sleep disturbance, it is vital to implement appropriate interventions to protect the mental health of nurses, not only during the pandemic, characterized by an increase in aggressive behavior and sleep disturbance but also on a regular basis. Positive attitudes towards work and well-rested personnel may provide better patient care and superior quality of service.


Adherence to the exercise intervention and demographic or clinical characteristics of patients with breast cancer undergoing adjuvant treatment may moderate the exercise intervention effect on VO2peak. In this study, the objective was to investigate whether baseline values of VO2peak, body mass index (BMI), time spent in moderate- to vigorous-intensity physical activity (MVPA), physical fatigue, age, chemotherapy treatment, and the adherence to the endurance training moderated the effect of HI vs. LMI exercise on VO2peak.The results from the physical training and cancer randomized controlled trial (Phys-Can RCT) indicate that high intensity (HI) strength and endurance training during (neo-)adjuvant cancer treatment is more beneficial for cardiorespiratory fitness . The exercise interventions from the RCT included strength and endurance training at either LMI, which was continuous endurance training at 40–50% of heart rate reserve (HRR), or at HI, which was interval training at 80–90% of HRR, with similar exercise volume in the two groups. Linear regression analyses were used to investigate moderating effects using a significance level of p < 0.10. Statistically significant interactions were examined further using the Johnson–Neyman (J-N) technique and regions of significance (for continuous variables) or box plots with adjusted means of post-intervention VO2peak (for binary variables).We used data collected from a subsample from the Phys-Can RCT; women who were diagnosed with breast cancer and had a valid baseline and post-intervention VOB = −0.08, 95% CI , pinteraction = 0.06, and B = 1.63, 95% CI , pinteraction = 0.07, respectively). The J-N technique and regions of significance indicated that the intervention effect (HI vs. LMI) was positive and statistically significant in participants aged 61 years or older. Baseline measurement of CRF, MVPA, BMI, physical fatigue, and chemotherapy treatment did not significantly moderate the intervention effect on CRF.Age, as a continuous variable, and adherence, dichotomized into < or > 58% based on median, moderated the effect of HI vs. LMI on CRF (Women with breast cancer who are older and who have higher adherence to the exercise regimen may have larger effects of HI exercise during (neo-)adjuvant cancer treatment on CRF. LMI exercise during breast cancer treatment on VO2peak.The objective of this study was to investigate whether baseline values of VOwith or without additional behavioral change support. Exclusion criteria were stage IIIb–IV breast cancer, inability to perform basic activities of daily living, cognitive disorders, severe psychiatric disease, or other disabling conditions that might contraindicate HI exercise, treatment for an additional ongoing malignant disease, and BMI < 18.5 kg/m2 or pregnancy.The study protocol , a tri-axial monitor previously validated in cancer survivors .SD) for continuous variables and proportions as number (n) and percentage (%) for categorical variables.Baseline descriptive including demographic, clinical, or behavioral characteristics is presented as mean and standard deviation (2peak was regressed on the intervention (HI vs. LMI exercise) while adjusting for baseline VO2peak. Study site was included as a covariate in the models, due to the possibility that patients from the three sites may have been receiving some variations regarding treatment regimes, test-personnel, and coaches. Moderating effects were examined by adding the moderator variable and its interaction term with the intervention variable into the regression model. Because the interaction effects were exploratory and intended to generate hypotheses for future research, we used an alpha level of 0.10 for the interaction terms  and 95% CI.Continuous moderators were kept as continuous if the variables were normally distributed  and dichotomized if not. Linear regression analyses were used to investigate potential moderators of the effect of HI vs. LMI exercise on CRF refer to . In the  Durand, . The res2peak after the intervention by indicating a “region of significance,” which is the case if the upper and lower CIs are completely below or above zero. A J-N plot was made by using the coefficients of the regression model in Microsoft® Excel® for Microsoft 365, version 2202 to visualize the moderated effect of the intervention (HI vs. LMI exercise) on VO2peak.Models with continuous moderators were estimated using the PROCESS macro-version 4.0 for SPSS Hayes, . PROCESS2peak post-intervention with adjustment for baseline VO2peak and study site was reported within subgroups of the moderator. Dichotomization of continuous variables was carried out using median-split or by cut points derived through J-N plots, which were made as the preferable choice. These figures related to the binary variables were made using GraphPad Prism, version 7.00 for Windows .For visualizations of statistically significant binary moderators such as chemotherapy treatment, the estimated margin of means of VO2peak test, reported for the LMI and the HI group, are presented in Baseline characteristics of the participant with breast cancer with a valid pre- and post-intervention VOB = −0.08, 95% CI , pinteraction = 0.06). The J–N plot illustrated that the intervention effect (HI vs. LMI exercise) was positive, in favor of HI, and statistically significant in patients aged 61 years or older, n = 68, as visualized in the colored area in the plot  and 52% (SD 32) for the LMI and HI exercise groups, respectively. For patients aged ≥62, the mean exercise adherence was 66% (SD 31) and 42% (SD 30) for the LMI and HI exercise groups, respectively  are presented in the plot , whereasectively . ChemothB = 1.63, 95% CI , pinteraction = 0.07), with larger effects in patients who adhered above 58%  compared to the LMI exercise group (66%). The same trend was observed for women under the age of 61 years, but adherence to HI was higher in the younger group: 52% in the HI exercise group and 65% in the LMI exercise group .2peak. There were no differences between the young and old groups, with the young group (mean age 49 years) averaging 84% of predicted VO2peak, and the old group (mean age 68 years) averaging 85% of predicted VO2peak, when using data from the Norwegian HUNT study as a reference for healthy women in different age groups  to be a moderator of the intervention effect in this study. Although others have found more intense treatment such as chemotherapy in addition to radiotherapy, to moderate the intervention effect when compared to a control group  that the lower limit of the CI is just above zero, the finding of age as a moderator should be interpreted with caution. In summary, there is a strong indication that age may moderate the effect of the intervention on VO2peak after being randomized to HI or LMI exercise for 6 months during breast cancer treatment. However, we suspect this finding to be somewhat disturbed by variations in chemotherapy treatment across the age span.Another aspect to acknowledge relating to the finding of age as a moderator is the wide CIs, especially for the youngest and oldest participants, due to the few participants (in the oldest and youngest age) and the large variations in VO2peak, where women who adhered above the median level had a significantly higher VO2peak if they had been performing HI exercise, compared to LMI exercise.Adherence to the endurance training was found to moderate the intervention effect on VOIn the Phys-Can RCT  on CRF in women undergoing (neo-)adjuvant breast cancer treatment. By investigating these potential moderators, we were able to identify possible subgroups of patients with breast cancer who could benefit most from exercising at HI vs. LMI. Our findings that many of the investigated variables do not moderate the intervention effect, according to being randomized to HI or LMI exercise, suggest that most women may choose their preferable exercise intensity. The difference in CRF is not large between the LMI and HI exercise groups, although the HI group seems to benefit more than the LMI group adjuvant cancer treatment. Adherence to the endurance training is important for achieving a beneficial change in CRF of exercising at HI, compared to LMI. Therefore, strategies to improve exercise adherence in the population of women undergoing (neo-)adjuvant breast cancer treatment are important.Baseline levels of BMI, MVPA, CRF, and physical fatigue, in addition to chemotherapy treatment, do not seem to moderate the intervention effect on CRF by exercising for 6 months at LMI levels vs. HI levels during (neo-)adjuvant breast cancer treatment. Therefore, if women have variations within these variables, we cannot advise either of the exercise intensities over the other; consequently, women may choose either LMI or HI exercise according to their own preferences.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Regional Ethical Review Board in Uppsala (Dnr 2014/249). The patients/participants provided their written informed consent to participate in this study.AB: responsible for the writing process and statistical analyses throughout the whole process. LB, TR, and ID: planning, writing, discussing findings and part of the writing process, and editing the final manuscript. AS: advising regarding statistical matters and editing the final manuscript. KN: editing and feedbacks on the manuscript. SB: conceptualization, feedbacks and discussions throughout the whole writing process, and editing the final manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the Swedish Cancer Society (Grant Nos. 150841 and 160483), the Swedish Research Council (Grant No. KDB/9514), the Nordic Cancer Union (2015), and the Oncology Department Foundations Research Fund in Uppsala .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.


The associations with cancer and cardiovascular diseases (CVD) had inconsistent results. The study aimed to investigate the risk of cardiovascular diseases (CVD) between populations with and without cancer.Patients with common cancers in Taiwan were enrolled in the study between 2007 and 2018 using the Taiwan Cancer Registry. We focused on colorectal cancer, women’s breast cancer, lung cancer, liver cancer, oral cancer, prostate cancer, and thyroid cancers. The study endpoint was fatal and non-fatal CVD, which was defined as ischemic heart disease and ischemic stroke according to the National Health Insurance Research Database. We compared the risk of CVD between patients with cancer and age- and sex-matched (1:1 ratio) participants who did not have cancer or CVD. Multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were obtained from Cox regression analysis. To evaluate the chronological trend, we estimated the HRs and 95% CI yearly since the diagnosis.Among the 552,485 cancer patients  during the median follow-up period of 4.1 years, 32,634 cases of fatal and non-fatal CVD were identified. Compared with that noted in the non-cancer population, the overall fully adjusted HR with 95% CI was 1.28  in the cancer population. The CVD risk was the highest in the first year, the adjusted HR with 95% CI was 2.31 , and this risk decreased yearly.Patients with cancer had a significantly higher risk of fatal or non-fatal CVD. The risk was the highest in the first year since diagnosis and decreased yearly.The online version contains supplementary material available at 10.1186/s12885-022-10314-y. Cardiovascular disease (CVD) is the leading cause of death worldwide. Approximately 85% of CVD cases are due to ischemic heart disease (IHD) and stroke . The traAsia accounted for the highest number of newly diagnosed cases of cancer in 2020 in both the sexes for all cancers ; the mosThis study aimed to investigate the risk of CVD in patients with common cancers in Taiwan, compare the risk of CVD over time, and perform subgroup analysis across sex and age to explore a potential effect modification.This was a nationwide cohort study conducted between 2007 and 2019 in Taiwan. The target cancers were the seven most common cancers in Taiwan : colorecThe primary composite outcome, CVD, was defined as fatal or non-fatal IHD or ischemic stroke. IHD was defined as hospitalization with an ICD code or intervention with a procedure code of revascularization percutaneous coronary or coronary artery bypass graft Tables S and S2. For each cancer patient, an age- and sex-matched, cancer-free, and CVD-free individual was selected from the NHIRD at a 1:1 ratio. The same index date with the corresponding cancer patient was assigned. Details on covariates of age, sex, cancer stage, and grade were obtained from the TCR database. The socio-economic status of urbanization, occupation, income, medical information of comorbidities, medication, and numbers of medical service used were retrieved from the NHIRD Table S. Our expCategorical variables are presented as numbers and percentages and were analyzed using the chi-square test. Continuous variables are presented as mean and standard deviation and were analyzed using the t-test. Incidence rate was calculated as the number of event divided by 1000 person-year at risk. Person-years for each participant was calculated from the index date of initial cancer diagnosis until the date of occurrence of a CVD event, death, or on December 31, 2019, whichever came first. The risk of CVD in patients with or without cancer over time was demonstrated by Kaplan–Meier survival curves and was compared using the log-rank test.Multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression analysis. Proportional hazards assumption was not violated through the visual inspection of the log ) versus log of survival time plot Fig. S. The folP for interaction was obtained through the likelihood ratio test between a fully adjusted model with the interaction term and a nested model without the interaction term. To observe the differences in the sex-specific effect estimates, all the analyses in this study were stratified by sex. To test the robustness of our results, we performed two sensitivity analyses. We reported the risk of CVD, IHD, and stroke separately. Considering the competing risk of non-CVD deaths, cause-specific hazards competing risk model was performed [To evaluate the chronological trend, we estimated the HRs and 95% CI yearly since the diagnosis. Aging is the shared risk factor of cancer and CVD, we set the cutoff age at 65 years as most of the older adults were defined . Potentierformed .P value of 0.05 was considered statistically significant. Analyses were performed using SAS software  and Stata version 16.1 .All statistical tests were two-tailed with a type I error of 0.05, and a n = 78,465), double cancer , carcinoma in situ , unreasonable or missing data (n = 169), men with breast cancer (n = 461), not in our eligible age group (n = 1380), and established CVD . The most common cancer was colorectal cancer , followed by women’s breast cancer , lung cancer , liver cancer , oral cancer , prostate cancer , and thyroid cancer . The flow diagram is shown in Fig. SA total of 552,485 cancer patients were included after excluding patients with duplicated data (Table P < 0.001). A total of 32,634 incident cases of fatal and non-fatal CVD in 2,154,515.8 person-years were documented in the overall cancer patients during a median (interquartile range) follow-up time of 4.1 (range 1.7–7.6) years. Table We used the first event to calculate the person-years if a person had several events. The Kaplan–Meier survival curves of cancer are shown in Fig. Figure P < .001 for interaction). Overall, the risk of CVD was not significantly different in terms of sex (P = .058 for interaction). The fully adjusted HR with 95% CI was 1.33  in women with cancer and 1.36  in men with cancer. The interaction effect of sex and age was different for each cancer. The results of all the analyses in the study stratified by sex are shown in Table SSubgroup analysis Table S revealedThe risks of CVD, IHD, and stroke mortality and morbidity for the overall cancer patients are shown in Table SOur study showed that patients with cancer had a significantly higher risk of CVD than their non-cancer counterparts. The risk of CVD was highest in lung cancer patients and was lowest in thyroid and breast cancer patients. The risk was the highest in the first year since cancer diagnosis, and this risk decreased yearly. Sex and age showed significant interactions with the risk of CVD with cancer. Based on the main findings, the risk of CVD was significantly higher in cancer patients, and this risk remained robust considering the competing risk.Our findings were compatible with those of previous studies, in that cancer patients had a higher risk of stroke , 24, 25 Age, obesity, smoking, and others were reported to be shared risk factors of cancer and CVD . Cancer Our study provided evidence from real-world analysis to elucidate the risk of cancer-related CVD. The epidemiological evidence bridged basic and clinical research to improve patient care . ClinicaTo the best of our knowledge, we report the first study of CVD risk in multiple cancers in Taiwan with a complete Cox model of years since cancer diagnosis and subgroup analyses. Our study has some limitations. First, residual confounders such as smoking, family history, and obesity existed. We made best efforts to collect the most relevant covariates in our database. Second, we focused only on the seven most common cancers. Further studies on more cancer types are warranted. Third, the level of evidence was limited in our retrospective cohort study. However, we ascertained these covariates and outcomes by medical records. Finally, considering the matched pairs in our methodology, frailty models should be used. However, due to large sample size and limited computing power of the hardware, we performed Cox model. The final results may be more conservative, but the basic trend toward protective or harmful will not change.In conclusion, our study demonstrated that cancer patients had a higher risk of CVD, especially lung cancer patients and in the first few years. Age was a significant effect modifier of overall cancer. Our study provided epidemiological evidence to elucidate the risk of cancer-related CVD, bridged basic and clinical research to improve patient care.Additional file 1.


Most university students do not follow recommendations for fruit and vegetable intake, with a consequent increase in the prevalence of cardiovascular disease (CVD) risk factors. The aim of this study was to compare obesity prevalence and biomarkers of metabolic status between Italian and Spanish university students, in relation with the consumption of fruits and vegetables. Food consumption, adherence to a Mediterranean diet (MD), level of physical activity (PA), blood glucose, total cholesterol, triglycerides and ketones, blood pressure, and body composition were evaluated. Among CVD risk factors, only glucose was significantly higher in Spaniards (SP), and only 3.1% of SP presented ketosis. SP had a higher percentage of energy from fat. Although adherence to MD and fruit and vegetable consumption did not differ between Italians and SP, students who consumed at least four servings of fruit and vegetables (FV group) showed better values for pressure and metabolic parameters than the no FV group. We observed an association between consumption of fruit and PA. Students who consumed more vegetables than fruit reported a better body composition profile and lower glucose concentrations. As previously suggested, in addition to PA, two servings of fruit and three servings of vegetables per day should be recommended. Over the years, several studies have highlighted the beneficial effect exerted by the Mediterranean diet (MD) on different diseases, among which is metabolic syndrome (MetS). Additionally, adherence to this dietary regime has been associated with a lower incidence of metabolic risk factors such as cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), and cancer . NotablyOver the last 20 years, there has been an increase in obesity rates among college students ,4,5. MorCompliance with the recommendations of the MD pyramid has been evaluated among Italians (IT), and the regular consumption of fruits and vegetables was significantly more common in females, and it increased with age and education (84.7% of those with a university degree) . A studyIn a recent systematic review, it has been reported that alcohol consumption and low consumption of fruits and vegetables were among the main behaviors associated with weight gain . We prevIn this context, the present study was aimed at comparing the obesity prevalence and biomarkers of metabolic status between Italian and Spanish university students, in relation to the consumption of fruits and vegetables , in ordehttps://www.clinicaltrials.gov/ct2/show/NCT04099420 (accessed on 23 May 2022). Online questionnaires were administered to collect information about dietary habits, level of physical activity (PA), and lifestyle of the subjects. Moreover, students were evaluated with clinical parameters of metabolic status , and underwent anthropometric, impedance, and blood pressure measurements. The presence of risk factors for MetS was assessed: waist circumference , elevated TG (≥150 mg/dL) or drug treatment for hypertriglyceridemia, high blood pressure  or hypertensive drug treatment, and high fasting glucose (>100 mg/dL) or drug treatment for hyperglycemia [This study was carried out on a sub-group of participants from a previous study about the lifestyle and dietary habits of university students . Non-worglycemia ,20,21. PAs described in the previous study , to eval2 kg−1 min−1 in adults. According to the Italian Society of Endocrinology (SIE), IPAQ allows population to be classified into three PA levels: low , moderate  and high .The International Physical Activity Questionnaire (IPAQ)  was usedHeight was measured with the SECA 217 portable stadiometer, with the measure approximated to the nearest 0.1 cm , whereasTo evaluate body composition, in particular body fat and muscle mass (MM), bioelectrical impedance analysis (BIA) has been used. Body weight, BMI, MM, and fat mass (FM) percentages were measured by the impedance balance OMRON BF511 with the subject in fasting conditions . BMI claIn addition to BIA, body skinfold thickness was measured to the nearest 0.1 cm by the Harpenden caliper at biceps, triceps, subscapular, and supra-iliac areas on the right side of the body with the subject standing in a relaxed condition . Then, FBP was measured with Omron X3 Comfort Upper Arm Blood Pressure Monitor.® areo β-Keton Sensor kit [Clinical parameters of metabolic status were assessed from capillary blood samples. In particular, TC, TG, and glucose (Glu) blood levels were evaluated with the MultiCare In System . To perfnsor kit  was usedFood consumption was evaluated using a 7-day food diary. Participants were asked to write day-by-day quality and quantity of food consumed and to report how they felt before and after eating. A short training session was provided giving instructions in order to fill in the diary correctly. Furthermore, a photographic food atlas  was provt-test and Mann–Whitney test for continuous variables, and chi-square test and Fisher′s exact test for categorical variables. Furthermore, results were analyzed using the Kruskal–Wallis one-way analysis of variance on ranks. Statistical analysis was performed using the Graph Pad software , and variables with a p-value < 0.05 were considered statistically significant. Principal Component Analysis (PCA) was performed using PAST .A descriptive statistical analysis  was first performed. Normal distribution of variables has been checked using the Shapiro–Wilk test. Categorical variables have been expressed as percentages, while continuous variables as means with standard deviation (SD) or medians with interquartile interval. Spearman correlations were used to evaluate relationships between variables. Bivariate analysis was conducted using an unpaired Participants were university and doctoral students from both scientific (98.5%) and humanistic (1.5%) areas, with 87.9% and 12.1% living in the city and in a rural area, respectively. The two groups were comparable for gender distribution and smoking habit. Regarding BMI, WC, WHR, and waist-to-height ratio (WHtR), no significant differences have emerged between IT and Spaniards (SP), as well as in the prevalence of OW/OB and in mean values of BP.Characteristics of participants and differences between Italy and Spain are reported in Concerning lifestyle (PA and dietary habits), no significant differences were found in IPAQ a, but thAs regards adherence to MD , assesseThe average daily energy intake was significantly higher in SP than IT. As regards macronutrients, the daily energy intake of lipids, expressed as a percentage, was suitable for the Italian group, in line with the indications from the national guidance that recommends between 20% and 35% in adults, whereas the Spanish counterparts showed a significantly different consumption above recommendations . CarbohyThe biochemical markers were evaluated by capillary sampling to determine Glu, TC, TG, and Ket plasma concentrations .Among the sample, 20.6% of IT and 50.0% of SP reported a prediabetes condition, manifested by glucose levels > 100 mg/dL and worthy of long-term monitoring, whereas 11.8% of IT and 18.8% of SP showed TC values ≥ 200 mg/dL, related to a moderate risk of experiencing CVD. As regards Ket concentrations, only 3.1% of Spanish students reported a ketosis condition.In order to evaluate differences in body composition and metabolic status in relation to fruit and vegetable intake, the sample was divided into four groups  on the basis of the subscores F-QueMD and V-QueMD . It emerSpearman correlations  have beeIn order to better evaluate the influence of fruit and vegetable intake on metabolic risk factors in IT and SP, a PCA was performed . Based oThis study aimed to compare body composition and metabolic status in Italian and Spanish university students in relation to fruit and vegetable consumption. In line with preceding studies ,45,46,47It has been found that the risk for excess body weight in the university students who reported not consuming fruits/vegetables daily was two to three times higher than in their peers who showed an adequate intake . The autPA has been suggested as a means to reduce and control body fatness. In China, vegetable and fruit intake had a positive association with physical exercise and a negative association with fat mass index/free fat mass index (FMI/FFMI) ratio . OverallFrom the analysis of the nutritional profile, a higher intake of lipids and a lower consumption of carbohydrates has been observed among SP than IT, with an adequate intake of protein for both groups.According to the criteria of the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III), in a previous study carried out in Yemeni students (11.7% OW), the overall prevalence of hypercholesterolemia and hypertriglyceridemia was 21.7% and 23.8%, respectively . In ChinThe study has some limitations, and our results should be interpreted carefully. The major limitation is the limited sample size. Moreover, since respondents were from central Italy and southern Spain because of the university locations, the results of this study may not be generalizable to all Italian and Spanish university students. Furthermore, the COVID-19 pandemic has represented a limitation to this study since it limited recruitment, and it has induced strong changes in the lifestyle and eating habits of university students, that could explain the differences that emerged with American students, in particular regarding alcohol consumption. However, a higher calorie consumption has emerged among SP that influenced metabolic parameters, in addition to a higher intake of fruit that mostly affects body composition.The different relationship of fruit and vegetable intake with obesity was in line with the previous finding that the daily intake of three servings of vegetables and two servings of fruit was associated with lower mortality, and a higher intake was not associated with additional risk reduction . Further


Orphan oncology drugs used in this article were defined by the type of disease treated by drugs, as drugs used to treat rare diseases with a prevalence of ≤ 500 per million people per year. In this article, our concern was to explore focus on the economic evaluation of the National Institute for Health and Care Excellence (NICE), when orphan oncology drugs were appraised for reimbursement, and provide advice and suggestions to decision-makers.A retrospective study was used in this study. Thirty guidance were gathered as our subject by NICE from 2016 to 2020, excluded drugs were not identified as orphan by European Medicines Agency (EMA) and orphan drugs were not used for cancer, and orphan oncology drugs were terminated at the time of data collection at NICE. Qualitative analysis, descriptive statistics, and Fisher's exact test were conducted.Of all guidance, the partitioned survival model was used most to appraise orphan oncology drugs, and every drug had a kind of commercial arrangement such as patient access scheme (PAS), managed access arrangements (MAAs), and commercial access agreement (CAAs). End of life is an important indicator that had been defined by NICE in the methods of technology appraisal in 2013, and drugs that met the criterion would be given a higher threshold of ICER. In addition, we found that potential health benefits were increasingly concerned such as drug delivery.In the setting of uncertain clinical and cost efficacy, orphan oncology drugs are comprehensively evaluated in multiple additional dimensions, which include life-extending benefits, and innovation. NICE uses a combination of special considerations for incomplete data, appropriate economic models, and appropriate health technology assessment (HTA) methods during the assessment process, besides, orphan oncology drugs with insufficiency evidence were recommended Cancer Drugs fund (CDF) to afford for patients, which would obtain more availability and accessibility, based on which, high-quality drugs for treating rare cancers can fall within the scope of affordable healthcare provided by the English medical insurance fund. Rare diseases are also known as Orphan diseases, which were used to refer to some uncommon, low incidence, and often life-threatening diseases. Drugs that treat orphan diseases are called orphan drugs. Orphan drugs, or Orphan Medicinal Products (OMPs), exist for <3% of rare diseases . It is sThere were two definitions of orphan drugs used in oncology. Take the European Union as an example, one is defined by the type of disease treated by drugs, such as orphan drugs in oncology, oncology drugs with orphan designation, medicines for orphan indications in oncology, oncology Orphan drugs (ODs), which were defined as drugs used to treat rare diseases with a prevalence ≤ 500 per million people per year. They are usually referred to by the following terms: orphan drugs in oncology, oncology drugs with an orphan designation, medicines for orphan indications in oncology, and oncology ODs. This article focuses on this definition, using “orphan oncology drugs.” An alternative definition defines orphan drugs as those used to treat cancers with an incidence of ≤ 60 per million people/year, and refers to them as rare tumor drugs. There are about 200 rare tumors in Europe, which account for 20–24% of all tumor diagnoses  was chosen for four reasons: (i) it is well-established, (ii) its guidance had been publicly available, (iii) it made a very important role in the final reimbursement decision in the UK, (iv) and its guidance had been reported in a language understood.We conducted a retrospective study on guidance published on the website of the National Institute for Health and Care Excellence/NICE from 2016 to 2020  and technology appraisal guidance (TAG)  on the wWe paid attention to the economic analysis of guidance and formulated a framework with the method of thematic analysis . IndicatThere were 30 orphan oncology drug guidance between 2016 to 2020 on the NICE website were chosen in this study. And among the 30 orphan oncology drugs, 21 were recommended to NHS, and 9 were recommended to CDF. The content of guidance of 30 orphan oncology drugs would be described in four sections as the framework.From 2016 to 2020, all orphan oncology drugs were appraised by Single Technology Appraisal (STA), except in 2018. There was a growing trend in the usage of partition survival models , but no via Single Technology Appraisal (STA) and 3 (10%) were appraised via Multiple Technology Appraisal (MTA). A single technology appraisal (STA) covers a single technology for a single indication. A multiple technology appraisal (MTA) normally covers more than one technology or one technology for more than one indication. The three orphan oncology drugs appraised by MTA were lutetium (177Lu) oxodotreotide for treating unresectable or metastatic neuroendocrine tumors, cabozantinib for treating medullary thyroid cancer, and lenvatinib and sorafenib for treating differentiated thyroid cancer after radioactive iodine, all of whose guidance was published in 2018  were appraised  in 2018 .Of the guidance that presented a specific and clear perspective, 8 (26.7%) analyses were conducted from the perspective of the NHS and Personal Social Services (PSS), and 5 (16.7%) from the perspective of the NHS without PSS. A total of 16 drugs did not formulate a perspective in their guidance . The scoQualitative analysis was used in the first stage of the research. On the basis of the framework, all the relevant information at each step of the decision process was identified. Then, the data collected was exported into excel for analysis. Descriptive statistics were conducted to determine the types and frequencies of indicators. A Fisher's exact test was used to measure associations between recommendation and ICER/end of life/drug delivery/drug combination.From 2016 to 2020, a partitioned survival model was used to perform a cost-effectiveness analysis for 22 orphan oncology drugs (73.3%), a Markov model for 5 (16.7%), and a decision tree model for 3 (10%). Four orphan oncology drugs did not document the type of economic model used in their guidance .Several economic models were combined for the cost-effectiveness analysis of four drugs. The economic model for Pomalidomide, a treatment for multiple myeloma that was previously combined with lenalidomide and bortezomib, in 2017 was a semi-Markov partitioned survival structure. In 2018, Tisagenlecleucel was evaluated using a partitioned-survival model, semi-Markov, and decision tree model. Blinatumomab, which was appraised in 2019 for treating acute lymphoblastic leukemia in remission with minimal residual disease activity, was analyzed using a partitioned-survival model and a semi-Markov model. Gilteritinib, which was appraised in 2020 as a treatment for relapsed or refractory acute myeloid leukemia, was assessed using a decision-tree structure followed by partitioned survival models.via a simple discount, 7 (23.3%) had a managed access arrangement (MAA), and 2 (6.7%) had a commercial access agreement (CAA)  had a patient access scheme (PAS) nt (CAA) .p = 0.238)  was below £20,000, 11 orphan oncology drugs (36.7%) were between £20,000 and £30,000, while that of 16 orphan oncology drugs (53.3%) was above £30,000. One drug's ICER/QALY value was not published. And there was no significant difference between ICER/QALY value and recommendations (= 0.238) .The discount rate of pharmaceuticals is generally between 3 and 5% . The disThe most common clinical indicator was overall survival (OS), which was included in the economic models of 29 of the 30 recommended orphan oncology drugs. The second most frequent was progression-free survival (PFS), which was included in 83.3%. Other indicators included complete response , response rates , and event-free survival . Less common indicators included objective response rate , disease-free survival , time to next treatment (10%), relapse-free survival , overall remission rate , minimal residual disease , and duration of response . The clinical outcome indicator of response time was used only once in 2016 for Panobinostat .The majority of the published guidance on drugs in our study  included a separate paragraph to discuss evidence regarding end-of-life and orphan oncology drugs. A total of 10 orphan oncology drugs met NICE's criteria for being considered a life-extending treatment and had sufficient evidence, 12 orphan oncology drugs did not meet NICE's criteria, and 6 orphan oncology drugs were considered a life-extending treatment but had uncertain cost-effectiveness estimates. 2 orphan oncology drugs had unspecified end-of-life guidance .It is shown that 80% of indications of disease were blood and bone marrow cancers, including multiple myeloma, large cell lymphoma, Philadelphia chromosome-negative acute lymphoblastic leukemia, acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), CD30-positive Hodgkin lymphoma, follicular lymphoma, large B-cell lymphoma, and chronic lymphocytic leukemia (CLL), followed by thyroid cancer (6.7%), which included medullary thyroid cancer. liver cancers, metastases, head and neck cancers, and ovarian cancer were the target for 3.3% of treatment each .Of all the 30 drugs, 4 (13.3%) were used for treating diseases at least 2 previous treatments, 8 (26.7%) were used for relapsed or refractory disease, 9 (30%) were used for treating acute disease, and 4 (13.3%) were used for treating untreated disease. Most drugs were used for adults, except Kymriah (Tisagenlecleucel), which was used to treat relapsed or refractory B-cell acute lymphoblastic leukemia in people aged up to 25 years.p = 0.675)  were administered by intravenous infusion. And the difference between drug delivery and recommendation found has no significance (= 0.675) .p = 0.675)  .Orphan oncology drugs can be recommended to the NHS or CDF. The guidance of the drugs that were recommended to the NHS will be reviewed after 2 or 3 years. Drugs were usually recommended for use as an option for the Cancer Drugs Fund because of uncertain cost-effectiveness estimates, immature survival data, an uncertain impact of the treatment on patient life expectancy, and in incomplete compliance with end-of-life standards. Drugs recommended to the CDF would not impede patient use while more evidence is collected for a final NICE review and a final recommendation regarding NHS use. To some degree, orphan oncology drugs recommended to CDF may obtain more availability and accessibility, a study showed that there is greater availability and accessibility of orphan medicines in England where most of the 68 OMPs were reimbursed because they were included in the NHS England specialized commissioning list [32] or the Cancer Drugs Fund [13], compared with Scotland and Wales . This kiThe most useful economic model for orphan oncology drugs in all the guidance was the partitioned survival model, and there was an increasing trend from 2016 to 2020 , which iEvery orphan oncology drug has at least one commercial arrangement. Drugs recommended to the NHS usually have PAS, which entails a simple discount. However, it is a pity that we cannot ascertain the amount that was discounted due to commercial confidentiality.Managed access arrangements (MAAs) are an agreement between NHS England and a company. Some drugs cannot be recommended due to uncertainty about their value for money, MAAs were used by the time to collect more evidence to address the uncertainties. Usually, without managed access, NICE might not be able to recommend patients have access to these promising new drugs at that time. Managed access provides a vital alternative route for patients to access these treatments. In our study, MAAs were all used for drugs recommended to the CDF, which include a Data Collection Agreement (DCA), and Commercial Access Agreement (CAA), with a simple discount PAS. However, CAAs were also unpublished because of commercial confidentiality. Drugs were funded through the CDF for a limited period of time (up to 2 years), during which MAAs will be maintained in accordance with (1) the results that need to be collected to address uncertainty in key clinical areas, and (2) the cost of the drug regulatory access agreement. The drug will then undergo rapid reconsideration to decide if it is recommended for use in the NHS .In conclusion, PAS are pricing agreements proposed by pharmaceutical companies to enable patients to access high-value drugs. MAAs are data collection protocols added to CAAs . In 2016Except for overall survival/OS and progression-free survival/PFS, some other indicators such as progression-free survival/PFS, objective response rate/ORR, complete response/CR, relapse-free survival/RFS, disease-free survival/DFS, event-free survival /EFS, overall remission rate/ORR, minimal residual disease/MRD, response rates/RR, duration of response/DoR, time to next treatment, time to response were also used to evaluate the clinical outcome of drugs. Even though overall survival remains/OS  and progNational Institute for Health and Care Excellence (NICE) typically defines a price of £20,000 to £30,000 per unit of QALY as cost-effective . In our The guide to the methods of technology appraisal had been published in 2013, and the purpose of the guide is to ensure that all interests should be considered when evaluating a treatment designed to prolong life. The guidance details that a “life-extending treatment at the end of life” treatment should satisfy two criteria (i) the treatment is indicated for patients with a short life expectancy, normally < 24 months, and (ii) there is sufficient evidence to indicate that the treatment has the prospect of offering an extension to life, normally of a mean value of at least an additional 3 months, compared with current NHS treatment. Besides, they should satisfy the two criteria and the evidence should be sufficient, and the assumptions used in the reference case economic modeling should be plausible, objective, and robust , if it hBesides, we explored the association between recommendation, ICER/QALY value, and end-of-life . Resultsvia intravenous infusion. NICE takes into account not only the economics and effectiveness of the medication, but also the characteristics of the drug itself such as its delivery to patients, and it proved that some hidden factors had been given increasing attention, which would give more convenience for patients and their family, reduce non-medical costs and enhance the quality of life.Of all the 10 oral medications, 8 drugs (80%) were recommended to the NHS. This rate of recommendation was higher than that of drugs that needed to be administered The selection and appraisal process of NICE for orphan oncology drugs is important and also provides a good reference for other decision-makers. Attribute to the high treatment cost, small population, insufficient evidence of orphan oncology drugs, in order to solve the problem of a small number of subjects for validated trials and the uncertainty of clinical outcomes related to drug treatment, alternative indicators, special treatment of incomplete data, and appropriate economic models and HTA methods were used to estimate cost-effectiveness. Clinical evidence and cost-effectiveness are the basis of NICE's appraisal of orphan oncology drugs, but they also take into account factors such as the potential health-related benefits, its life-extending effects, and the impact of the medication on patient quality of life. Within the limits of affordable national medical insurance, how to improve the availability and accessibility of orphan oncology drugs became a global problem instead of a matter for any individual country, researchers should do their best to maximize the usage of orphan oncology drugs within limited resources.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.DS, LZ, and ZN were responsible for data collection and analysis. ZW, YY, LJ, and YN were responsible for data collection. 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.