Developmental prosopagnosia (DP)—or ‘face blindness’—refers to life-long problems with facial recognition in the absence of brain injury. We know that neurodevelopmental disorders tend to co-occur, and this study aims to explore if individuals with self-reported DP also report indications of other neurodevelopmental disorders, deficits, or conditions . In total, 115 individuals with self-reported DP participated in this online cross-sectional survey. Face recognition impairment was measured with a validated self-report instrument. Indications of difficulties with navigation, math, reading, or spelling were measured with a tailored questionnaire using items from published sources. Additional diagnoses were measured with direct questions. We also included open-ended questions about cognitive strengths and difficulties. Results: Overall, 57% reported at minimum one developmental comorbidity of interest, with most reflecting specific cognitive impairment  rather than diagnostic categories . Interestingly, many participants reported cognitive skills or strengths within the same domains that others reported impairment, indicating a diverse pattern of cognitive strengths and difficulties in this sample. The frequency and diversity of self-reported developmental comorbidity suggests that face recognition could be important to consider in future investigations of neurodevelopmental comorbidity patterns. Without the ability to recognize faces, one would live in a world of strangers. This is the reality of people suffering from developmental prosopagnosia (DP), a neurodevelopmental disorder of face recognition. The hallmark of this disorder is severely impaired face recognition in the absence of brain injury, intellectual impairment, or significantly impaired vision . ConsequIt is well-known that neurodevelopmental disorders tend to cluster and co-occur ,26,27,28The exception is the relation to autism spectrum disorder (ASD), where observations of face recognition deficits are common ,34,35. HOne reason why neurodevelopmental comorbidity in DP has not been described could be the lack of a gold standard to identify DP. Studies investigating DP have typically applied few and broad exclusion criteria, which also vary substantially between studies ,11. The In a first attempt to address the question of neurodevelopmental comorbidity in DP, we took an exploratory and broad approach to allow for potentially valuable unexpected findings , an apprself-reported developmental prosopagnosia (s-DP) is likely to co-occur with other neurodevelopmental disorders or conditions (comorbidities), and if so, to what degree. To this aim, we asked how people with s-DP rate their navigation, reading, spelling, and mathematical abilities, which all represent potentially related cognitive abilities/impairments [We asked whether airments ,41. In aairments . Becauseairments ,43. We dWhile we wanted to take a broad and open approach, we also used existing literature to guide the inclusion of relevant types of developmental disorders or deficits previously investigated in relation to face processing or DP as a starting point. These included navigation problems/developmental topographical disorientation ,44,45,46developmental comorbidity.In sum, and in alphabetical order, aphantasia, attention-deficit/hyperactivity disorder, dyscalculia, dyslexia, memory problems, navigation problems, object agnosia, and synesthesia were considered relevant conditions to investigate in DP. For practical reasons, they are collectively referred to here as n = 13); (2) reports of neurological disorder or brain injury (n = 4); (3) not reporting normal vision (n = 4); and (4) neurodevelopmental or psychiatric disorders that can cause impairment in intellectual or social functioning (n = 12), e.g., ASD [This cross-sectional survey study used convenience sampling. In total, 148 respondents filled out the Difficulties and Abilities in Developmental Prosopagnosia Questionnaire . The second item was assessing self-reports of other, perhaps less conventional conditions of interest: ‘Do you have any of the following conditions related to cognitive strengths or difficulties?’ with the response options aphantasia, synesthesia, object agnosia, memory problems, and other (free text). Finally, our questionnaire included two open-ended questions regarding cognitive strengths and difficulties, respectively, to allow participants to describe this in their own words . The maximum score is 100, and higher scores indicate more difficulty recognizing faces. Scores of 65–74, 75–84, and 85–100 can broadly indicate mild, moderate, and severe DP, respectively [To assess self-reported face recognition in the sample of s-DP, the full PI20 was included in the Difficulties and Abilities in Developmental Prosopagnosia Questionnaire. The PI20 is a widely used 20-item self-report measure of face recognition developed to identify and assess severity of prosopagnosia, . The PI2ectively .N = 356) [n = 78) [To investigate navigation abilities, the Difficulties and Abilities in Developmental Prosopagnosia Questionnaire included five items from the Wayfinding Questionnaire ,73, whicN = 356)  and stro[n = 78) . Four of[n = 78) , and the[n = 78) .r = 0.87 and 0.84), and construct validity (r = 0.57–70 between the Adult Reading History Questionnaire and reading measures) [The Adult Reading History Questionnaire (revised) is a 23-item self-report questionnaire, one of the few designed to identify a history of reading difficulties indicating dyslexia in adults . As menteasures) . Furthereasures) .Responses to the Adult Reading History Questionnaire are given on a 5-point Likert-scale, with higher scores corresponding to more difficulty. The original range is 0–4, but in the current study it was adapted to 1–5 to provide consistency amongst the majority of the scales . The fouThree items were constructed as no self-report measures of mathematical ability and dyscalculia for adults exist ,81. ScheAre there things that you are particularly good at, where you experience performing better than others?’ and ‘Are there things or situations, where you experience performing worse than others?’. The questions were provided with a guiding text, e.g., ‘Please consider and elaborate on any difficulties you might have, for example within the areas of math, memory, navigation, visualizing images or objects, literacy, sports or tone deafness’.The Difficulties and Abilities in Developmental Prosopagnosia Questionnaire also contains two guided open-ended questions aimed at a less constrained and suggestive assessment of the abilities and difficulties experienced by participants with s-DP in their own words. Aligned with the explorative nature of our questionnaire, this provides an opportunity for non-expected findings or responses . The quep ≤ 0.05.The statistical analyses were conducted using IBM SPSS, version 27.0  with a sA Chi-square test of independence was used to analyze whether the presence of any binary-measured developmental comorbidity  was independent of severity of self-reported face recognition impairment  within the sample of participants with s-DP ,89. The N = 115) to the PI20, the Wayfinding Questionnaire, the Adult Reading History Questionnaire, and the mathematical ability items. In other words, the interest is the underlying structure and relationship between self-reported face recognition ability and navigation, reading/spelling, and mathematical ability. A reasonable assumption could be that a four-factor structure would emerge. It has been demonstrated that the PI20 has one factor [An exploratory factor analysis was performed to investigate the latent variables underlying the responses of the sample of individuals with s-DP  was chosen to allow the factors to correlate . The numDirected content analysis, a deductive approach, was applied to the responses of the open-ended questions to investigate the frequency and variance in themes regarding abilities and difficulties, and thus provide a descriptive summary of what was reported . A mainlmathematical abilities, memory, navigation, visualizing images or objects, literacy, sports or musical talents’. When appropriate and reflected in the data, the first version codes were created in pairs reflecting a strength and a difficulty, e.g., Good Memory vs. Memory Problems. N.S. (first author) coded the first version codes and recorded meaningful information provided about experienced abilities and difficulties that was not captured by these first version codes. Secondly, new categories, e.g., Skills In Visual Arts, were created in an inductive fashion to fit the data that could not be coded with existing codes but still seemed to reflect meaningful themes in the data [Initial coding categories and operational definitions were developed for the statements concerning difficulties based on the developmental comorbidities  . First vthe data . Thus, wRecoding and revisiting the coding categories was repeated as a part of an iterative process. A final coding manual was written and discussed with a second independent coder  and revised accordingly , which is close to the suggested cutoff for severe DP, which is 85 . For theThe descriptive results for self-reported developmental comorbidity are reported in The Chi-square test of independence did not reveal a significant relationship between presence of developmental comorbidity  and severity of self-reported face recognition impairment  within the sample  studies . For theThis suggests that the presence of developmental comorbidity is independent of severity of self-reported face recognition impairment  in this An exploratory factor analysis extracting factors with principal axis factoring, using an oblique rotation, was applied to assess the underlying structure of the latent variables explaining the covariance amongst the responses to our questionnaire from the 115 included participants with s-DP. The data demonstrated good factorability: The Kaiser–Mayer–Olkin measure of sampling adequacy was 0.696 and above the accepted value of 0.6  (p. 668)ree plot  suggesteHowever, the theoretical a priori factor structure was assumed to have four factors or less if the factors were correlated, and the five-factor structure was not considered qualitatively meaningful and less stable than the four-factor structure when assessed (the five-factor solution is available at the OSF site associated with the project). Costello and Osborne  (p. 3) aThe first factor  consisted of 14 items loading above 0.32 on the factor, assessing different aspects of impaired face recognition, such as negative feelings associated with not recognizing someone , not recognizing familiar people , and coping strategies . All five navigation items had strong loadings on the second factor (Navigation and Orientation). The five items assessing reading and spelling ability, primarily in elementary school, collectively loaded on the third factor (History of Reading/Spelling Difficulty). The three items concerning mathematical ability in childhood  and current difficulties assessing quantity  loaded strongly on the fourth factor (History of Difficulties with Math).Additionally, Item 3 and 12 from the PI20 loaded on Factor 3, and Item 19 from the PI20 loaded on the fourth factor, which did not correspond with the content of the rest of the items within these factors. However, these loadings were quite small, e.g., just around −0.32. Items 2, 8, and 9 from the PI20 did not load above 0.32 or below −0.32 on any factor.All factors had at minimum three strong factor loadings (above 0.5 or below -0.5), and all factors consisted of more than three items, suggesting a stable solution . Factor ropriate . Additioropriate .Applying directed content analysis to the open-ended questions in the DAP-Q allowed for more detailed analysis of self-reports of the strengths and difficulties experienced by the participants. The coding categories representing the difficulties and strengths are presented in This study was designed to investigate which types of developmental comorbidity, as well as subjective difficulties and strengths, are reported by participants with s-DP. First, most participants in the study reported face recognition problems on the PI20 compatible with prosopagnosia, although we note again that we did not ascertain this in any other way. Two participants scored lower than the suggested range for DP, but we decided to keep their responses in the analysis as they did self-report significant problems with faces. Fifty-eight participants scored within the most severe group, as defined by Shah et al. .More than half of the sample reported the presence of at least one of the predefined conditions of interest . Relatively few participants reported dyslexia, dyscalculia, and ADHD. Synesthesia was reported by 10.4%. Aphantasia was reported by ~20%, and memory problems and object agnosia were reported by almost a fourth of the sample of individuals with s-DP. In total, 25% reported indications of clinically relevant navigation complaints on all of the selected Wayfinding Questionnaire items. In addition, the presence of developmental comorbidity was observed to be independent of severity of s-DP  when the participants were divided into a mild, moderate, or severe group.Finally, an exploratory factor analysis revealed a stable four-factor structure corresponding to the independent scales included, with a very weak correlation between the factors of Developmental Prosopagnosia Symptoms and History of Reading/Spelling Difficulty. The stability of the factor structure serves as an indication of validity of the composition of items, allowing for interpretation and analysis of the data from our questionnaire.When asked to describe their difficulties and strengths, e.g., in which domains they experience performing better or worse relative to others, a considerable number of participants report difficulties in the categories Navigation Problems, Difficulties with Math, Aphantasia, Memory Problems, and Difficulties with Sports. For strengths, the statements most frequently match the coding categories Good Memory, Reading and Spelling Abilities, Musicality, and Mathematical Abilities. For Aphantasia and Navigation Problems, more participants reported impairment, while comparatively fewer reported performing well in these domains. For Reading and Spelling and Memory, more participants with s-DP reported it as a strength rather than a difficulty, even though many also described memory problems. For skills within math, musicality, and sports, there were a number of reports of both strengths and difficulties.The exploratory factor analysis showed a clear and stable four-factor structure of the responses to our questionnaire, largely separating the different (dis)abilities in this sample of s-DP into self-reports of face recognition ability (PI20), navigation (the Wayfinding Questionnaire), reading (the Adult Reading History Questionnaire), and mathematical ability.However, the factor structure also revealed some interesting aspects of the PI20, where some items did not load on the factor of Developmental Prosopagnosia Symptoms (the first factor) , but instead on the third or the fourth factor, and some items did not load sufficiently on any factor  . Common r = −0.168), suggesting a slight association between reading and face recognition ability in this sample. On one hand, it could simply be due to the PI20 Items 3 and 12 which loaded weakly on the History of Reading/Spelling Difficulty factor. On the other hand, individuals with dyslexia can have impaired face processing, e.g., [Furthermore, Factor 1  and Factor 3 (History of Reading/Spelling Difficulty) correlated weakly , even though that there were only three items in total . These wBoth the quantitative and the qualitative analyses provided insights into the difficulties and developmental comorbidities that the participants experienced, and the qualitative data further allowed us to understand their self-reported strengths as well. Hence, we will discuss the quantitative and qualitative reports of difficulties and strengths in s-DP in relation to each other and the available literature. To provide a structure for this section, we divided it into cognitive domains/disorders which are presented in alphabetical order.Attention Deficit Hyperactivity Disorder. Seven (6.1%) s-DP participants reported ADHD as a comorbid disorder, which is within the range of self-report of ADHD in college students of between 2–8% [een 2–8% . Within een 2–8% ,45, and een 2–8% . There ieen 2–8% ,30, and een 2–8% , which mMathematical Abilities or Difficulties. Both mathematical ability and difficulties with math were reported at fairly high levels relative to the rest of the qualitative codes. However, only four (3.5%) participants reported dyscalculia in the close-ended questions  in both cases. Interestingly, Good Visual Mental Imagery was also reported, although not as frequently (n = 7).N = 2000) with self-reported aphantasia reported more difficulties with face recognition and autobiographical memory relative to 200 participants with vivid visual imagery [Given the suggested link between aphantasia and severely deficient autobiographical memory, memory deficits were also of interest ,101. Mem imagery .‘remembering things, details, or personal past events’. This was done with the aim of eliciting responses related to various forms of memory. It is notable in the qualitative data that both Good Memory and Memory Problems were amongst the most frequently used codes. The statements indicate that some participants, but not the majority, described problems related to autobiographic memory: ‘remembering names, holidays, places we have been, events I have been to, films I have seen’. At the same time, many also reported good semantic memory or good memory for pieces of music, e.g.: ‘I am good at remembering historical facts  and other random facts; taking multiple-choice tests’. Thus, the memory components the participants feel skilled at might not be the same ones that cause trouble to others.Memory problems can be considered a quite broad and non-specific term, and it was deliberately formulated in lay language in this survey study and guided with the description as Musicality. Both good Musical Ability (n = 26) and Lack of Musicality (n = 17) were reported by participants. For the former, ability to play an instrument and play by ear were often mentioned. For the latter, tone deafness and difficulty singing in tune were often reported, which seems to fit with reports of tone deafness in some cases of DP [es of DP  and impaes of DP . This coNavigation Problems or Abilities. Navigation problems (n = 41) was the most frequently represented category in the qualitative data. Not many reported good navigation abilities. Impaired navigation ability is not an official diagnosis, but is occasionally referred to as  topographical disorientation [entation . In the entation .N = 9) [N = 7) [A few studies have investigated topographical orientation and navigation ability in DP, and there are numerous anecdotal reports of co-occurrence . ExistinN = 9) . Another [N = 7) . As oppo [N = 7) . Interes [N = 7)  found de [N = 7)  did not Object Agnosia. The relationship between face and object recognition has perhaps been the most central debate in DP [te in DP , as it cte in DP . Twenty-te in DP ,111,112.te in DP ), as welte in DP ,114, stiReading and Spelling. The participants generally reported more instances of good reading and spelling ability, and few instances of the opposite. The abilities within reading/spelling are many, e.g., flair for languages, literacy, and learning to read from an early age. Few participants reported difficulties with reading or dyslexia on the direct question of 5–10% ,22,23,51of 5–10% ,48,49,50Social and Interpersonal Skills. Most descriptions of inadequacy in social and interpersonal skills were directly related to face recognition problems, and thus did not receive separate coding in the qualitative analysis. There were, however, some interesting descriptions of social strengths too, e.g.: ‘Knowing what other people feel, and why they feel it. ‘intuitive profiling’ so to say’. Some examples also refer to the ability to read emotions and show empathy. While we know that DP can be accompanied by anxiety and avoidance of social gatherings [therings , our resSports Difficulties/Skills and Motor Coordination and Body–Space Perception. There were a number of reports of Difficulties with Sport (n = 17), but also of good Sports Skills (n = 12). Sports Skills were often described with an example of excelling in one particular discipline. For Difficulties with Sport, the statements often reflected a broader lack of skill important for many sports. Some statements overlap with experiences coded as Motor Coordination and Body–Space Perception, and are coded with both categories e.g., ‘I have a hard time with things that require hand-eye coordination like playing sports or physical games’. Moreover, besides being clumsy, there are elements of having a hard time judging the distance between oneself and other objects in Motor Coordination and Body–Space Perception. One particularly interesting example is:‘(…) At work we have to make sure we do not walk within 5 m of an operational machine. I cannot imagine how far that is. I need to memorize the spots where the machines are often positioned, and memorise where I can walk based on where others have walked safely. I will not pass a machine in an unfamiliar spot without instruction from driver or my manager to do so because I can’t tell if I’m at a safe distance.’As far as we are aware, there is no existing literature on difficulties with motor coordination or body–space perception related to DP, and no investigations of the possible relationship between DP and developmental coordination disorder.Skills in Visual Arts. Some of the participants described talents within primarily drawing and painting. A few described themselves as established artists or/and receivers of awards for their work. For example:‘I am very artistic. I have shown my work and been featured in a variety of mediums throughout my whole life. Most specifically I paint faces and have since I was about 12 years old and was fascinated with faces.’To our knowledge, there are no studies regarding the artistic ability of participants with DP, although there are examples in popular media.Synesthesia. Twelve (10.4%) participants with s-DP reported synesthesia. There are few published estimates of synesthesia prevalence in the adult population, and these vary widely, but one well-controlled study reported a prevalence of 1.1–4.4%. [.1–4.4%. . Investi.1–4.4%.  measuresN = 3) [N = 16) [The quantitative reports do not align with the qualitative analysis, where only two descriptions of synesthesia are represented. This might be caused by the fact that synesthetic experiences might not instantly be categorized as difficulties or strengths, and thus are not reported in the open-ended questions. Interestingly, it has been shown that some individuals with grapheme-color synesthesia have abnormal face processing measured with, e.g., The Cambridge Face Perception Test (N = 3)  and CFMT[N = 16) . It has [N = 16)  or incom[N = 16) . Ulimoen[N = 16)  hypothesThe amount of developmental comorbidity reported by the sample was quite astonishing, as 65 participants (56.5%) reported suffering from at least one of the following: ADHD, aphantasia, dyscalculia, dyslexia, memory problems, object agnosia, or/and synesthesia. In addition, a large number of participants reported navigational problems on the questionnaire items. The qualitative data revealed that a large number of participants experienced problems in specific domains, in particular with imagery, math, memory, and navigation. However, for all these domains, there were also reports of good abilities—indicating that the link between any of these domains and DP might not be entirely systematic . To our knowledge, this study is the first to address the possible overlap between DP and other neurodevelopmental disorders and impairments on such a large scale. Our findings seem to suggest a curious link between at least some of the developmental comorbidities ,28,77. TAn additional explanation for the high rates of comorbidity observed could be that developmental comorbidity has not been in focus in the literature on DP, and it has not been customary to screen for or ask DP participants about other disorders besides ASD and brain injury ,11. ManyWhile the strength of the present study is in the exploratory and broad approach to the investigation of developmental comorbidity in self-reported DP in a fairly large sample, there are of course also limitations. The main limitation is the lack of a control group without s-DP, which leaves unknown what the frequencies of reports would be in the general population. In addition, all our results are based on self-reports, and while some of our questions are taken from published and validated instruments, we also included yes/no questions regarding the presence of a given condition without the use of validated self-reports or clinical judgement. Thus, our results should be viewed only as a first step in the investigation of possible developmental comorbidity ,122.While the PI20 can indicate whether people have trouble with face recognition, it cannot stand alone in determining whether someone is suffering from DP. It is debated within the field how valid self-report instruments like the PI20 are in measuring actual face recognition problems, and relatedly, how much insight people actually have into their facial recognition performance. It has been shown that people in general have only modest insight into their own performance on objective measures of face recognition abilities ,121,123,Thus, it is possible that not all participants included in our study would qualify for a diagnosis of DP. Bate and colleagues  found thRelatedly, recruiting from online fora might bias the sample towards people with particular interest in their suspected condition or in the research question, and perhaps also people with an interest in and experience of other diagnoses. We are not aware of any studies on bias in online recruitment in relation to prosopagnosia, but based on the general literature on self-selection and online recruitment ,130 thisIn addition, the current sample size of 115, and the additional metrics from the exploratory factor analysis, lies in the lower end to satisfy the criteria of Maccallum et al. . There a‘Memory, navigation, math’. As this was an online survey with unnamed participants, there was also no way we could ask clarifying questions in relation to statements that were arbitrary or lacked detail.For the qualitative data, the aim of applying the open-ended questions was to elicit more detailed descriptions that expanded our understanding of the phenomena under investigation, however, not all responses were detailed. For example, some participants would describe their difficulties or abilities by listing them very briefly like this: The observed high co-occurrence of developmental comorbidity in self-reported DP may have important implications for our understanding of neurodevelopmental disorders and conditions and their interplay. Particularly, high rates of self-reported synesthesia, navigational difficulties, aphantasia, and memory problems  and diversity within subjective difficulties and strengths, e.g., math skills and motor coordination, suggests that there is ample room for future research on this topic. Investigating the relationship of DP to other developmental conditions in more detail, and whether face recognition deficits may exist in other neurodevelopmental disorders, might prove fruitful in characterizing the neurodevelopmental co-morbidity space or overlap between disorders more fully. While we have taken diagnostic categories and pre-defined cognitive domains as our starting point here, further work might go beyond the ‘core-deficit’ approach , and our


Spasticity is considered a contributor to hypertonia, frequently presented in people with cerebral palsy (CP), affecting muscle function and motor activities. In CP football, the classification system determines that this impairment is eligible for competitive para-sports due to the impact on activity limitation and sports performance. However, the relationship between this feature  and performance determinants has not been explored yet. This study aimed to assess the association of clinical spasticity measurements with the performance of sport-specific tests used for classification purposes. Sixty-nine international footballers with CP voluntarily participated in this study. The Australian Spasticity Assessment Scale was used to measure spasticity in lower limbs muscle groups and activity limitation tests were conducted considering dynamic balance, coordination, vertical and horizontal jumps, acceleration, and change of direction ability. Low-to-moderate negative significant associations were found between the hip spasticity and measures of dynamic balance and dominant unipedal horizontal jump capacity. Additionally, moderate associations were reported between the knee spasticity and the non-dominant unipedal horizontal jump capacity and the change of direction actions with the ball. The ankle spasticity score reported small to moderate associations with the change of direction assessment without the ball and bipedal and dominant unipedal horizontal jump capability. Finally, the total spasticity score only presented a significant association with horizontal jump performance. This is a novel study that provides evidence of the associations between an eligible neural impairment and relevant specific measures of activity limitation tests. These results suggest that the amount of spasticity according to each evaluated joint muscle group of the lower limbs presents a low-to-moderate significant relationship with determined measures of dynamic balance, coordination, horizontal jump, acceleration, and change of direction ability with and without the ball in international-level CP footballers. Further studies are necessary to elucidate the real contribution of neural and non-neural impairments related to hypertonia on fundamental sport-specific motor skills of para-footballers with CP. In para-sport, evidence-based grading is mandatory to develop a competition system that ensures that outcomes are based on a causal relationship between eligibility and the impact of the eligible impairment on sports performance . CurrentAmong the three eligible impairments, hypertonia, or related impairments  are the most common type of CP, resulting from the injury of the upper motor neurons and possibly the loss of descending inhibitory input, thereby altering muscle tone, which intensifies with movement velocity . The uppSpecifically, spasticity is a clinical phenomenon thought to be the result of a hyper-excitable position and velocity-dependent stretch reflexes, resulting in a relevant contributor to muscle hypertonia with neural-physiological adaptations that shapes motor function over time . AdditioAt present, classification methods for assessing spastic hypertonia in para-sport are based, principally, on manual testing of overreacting muscle resistance to rapid stretch generated due to increased reflex activity, where it is not possible to differentiate between neural  and non-neural  contributors to joint resistance . Conside–2) from 12 national teams of competitors at the World Championships Qualification Tournament  voluntarily participated in this study. The impairment profile of the participants was 66.7% (n = 46) congenital and 33.3% (n = 23) with acquired brain injuries. All the participants reported training on average 4.2 ± 1.5 times a week and had 10.1 ± 5.5 years of playing experience. Only para-footballers with a valid license from the International Federation of Cerebral Palsy Football (IFCPF) were involved in this study. Additionally, the inclusion criteria were to have an eligible impairment of spasticity and to be categorized according to their impairment profile of bilateral spasticity (n = 15), unilateral spasticity (n = 47), and mixed CP profiles (n = 7). All participants were classified as level 1 profiles of the Gross Motor Function Classification System (GMFCS)  . As an eD) and non-dominant legs (RHTND)], vertical and horizontal jump , acceleration , and change of direction ability  tests ] tests . Leg dom)] tests .Spasticity rating measurements were conducted with the Australian Spasticity Assessment Scale (ASAS). This is a simple and standardized testing procedure that combines aspects of the Tardieu Scale and the practical scoring framework of the Modified Ashworth Scale, allowing comparison between muscle groups and categorizing the muscles tested in one category, avoiding ambiguous assessments . In thisParticipants walked barefoot in a straight line with the front foot placed such that its heel touched the toe of the standing foot to complete a 5 m line as fast as possible and with the best accuracy . The triD and RHTND), starting first with the dominant side and heel contact with 1 min rest between attempts. When the participant makes an erroneous contact, the attempt is not considered, and the time (in s) to complete the fastest two trials were registered . The player was requested to perform 25 cycles at the command, considering that one cycle is the sum of two hits of alternate contacts with the heel and toes separately on a tapping platform (35 cm × 20 cm). The test was performed twice with each leg . Those players who presented spastic hemiplegia and difficulty maintaining their hands on their hips were allowed to keep their hands alongside their body .D and THND) with 1 min rest between them, and the best trial with each leg was considered for data analysis . Two attempts with 1 min of rest were permitted, and the best trial was considered for statistical analysis . In the analysis .The participants were instructed to accelerate as quickly as possible through a 20 m sprint in a straight line from a standing start with the recording time of 5, 10, and 20 m using infrared photocells . Two attempts were permitted with 90 s of rest between attempts, and the fastest trial was used for data analysis .In the MAT, the participants began behind a starting line in a standing position and performed sprint forward (5-m), following 2.5-m side-stepping toward right, 5-m toward left, 2.5-m toward right again, and completing the course with 5-m backward . The 505t-test and, the effect size was given by Cohen’s d-values, which were interpreted as follows: above 0.8, between 0.8 and 0.5, between 0.5 and 0.2, and lower than 0.2 were considered large, moderate, small, and trivial, respectively  and standard error measurement (SEM). ICC 0.90–1.00 were considered excellent, 0.70–0.89 high, 0.50–0.69 moderate, and < 0.50 as low (SEM = r) analysis was used to examine the relationship between the spasticity scores and the performance in the activity limitation tests. This strength of associations was interpreted as trivial (r < 0.1), small (r = 0.1–0.3), moderate (r = 0.3–0.5), large (r = 0.5–0.7), very large (r = 0.7–0.9) and nearly perfect (r = >0.9) (p < 0.05.This study presents the data as means ± standard deviations (SD) and the mean 95% confidence interval (CI). The normality of the data distribution and homogeneity of variance were assessed using Kolmogorov-Smirnov and Levene’s tests, respectively. The differences between the two trials in each activity limitation tests were determined using Student’s paired ectively . The rel0 as low . The SEMinjuries , 2020. P = >0.9) . The stap > 0.05, d = 0.00 to 0.35). The reliability of THD, THND, and S10-20m was categorized as excellent . A high ICC was obtained for tandem walk, countermovement jump, standing broad jump, sprint 0–5 m, modified agility test, 505 with ball, and rapid heel-toe contacts with dominant and non-dominant legs . However, S5-10m presented low reliability scores .Descriptive results and within-session reliability for each physical test  in all footballers with CP are presented in D . Moreover, players with higher knee spasticity scores demonstrated lower performance in the THND and 505 with ball test . Similarly, a significant relationship was obtained between ankle spasticity scores and performance in the standing broad jump , THD , and modified agility test . Considering the total spasticity scores, players with better horizontal performance apparently presented a lower presence of spasticity, considering the assessments of standing broad jump, THD, and THND .The associations between the spasticity scores and the activity limitation variables are shown in The aim of this study was to examine the association between spasticity and sports-specific performance measurements in international footballers with CP. This research found small-to-moderate associations between the level of spasticity in the lower limbs and the measures of coordination, horizontal jumps, and change of direction ability performance, where performance may decrease as the muscle spasticity score increases. In the context of Paralympic classification, identifying the relative strength of association between impairment measures and sport-specific determinants of performance is a mandatory step to develop evidence-based classification systems . To the ad hoc measurements of impaired coordination in different Paralympic sports. In this line, Previous investigations have attempted to examine the predictive value of impairment measures in para-sport performance but using Hip adductor spasticity has been described as a negative component that impacts body motion and could induce pathological characteristics reflected in a limited range of movement of joints and motor dysfunctions  and the change of direction ability in the 505 with ball test. Likewise, Regarding the spasticity affecting the muscle groups involved in the motion of the knees, higher scores in flexors were found compared to knee extensors, in line with other clinical studies with CP participants with similar GMFCS profiles . The ASAD) and change of direction ability , showing the negative impact of impairment on jumping and change of direction performance, respectively. Although no significant associations were found with sprint performance in this study, the soleus and gastrocnemius muscles have been described as the principal contributors to forward propulsion and support during running performance  should be considered in further analyses that include all those tests . However, this study provides specific reliability scores for CP footballers with unique eligible impairments of hypertonia  because recent research suggested a potential impairment-specific relationship between eligible impairment and para-sports performance . All the participants provided their written informed consent to participate in this study. The patients/participants provided their written informed consent to participate in this study.AR and RR: conceptualization, methodology, and visualization. RR and DC: formal analysis. AI, DC, and MH: investigation. RR and JY: resources and supervision. RR and MH: data curation. AR, RR, MH, and JY: writing—original draft preparation. RR, AR, DC, AI, JY, and MH: writing—review and editing. RR: project administration and funding acquisition. All authors have read and agreed to the published version of the 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.


Background: Among antiepileptic drugs (AEDs), sodium valproate alone or in the combination of topiramate (TPM) for treating refractory epilepsy was controversial. This meta-analysis aimed to systematically evaluate the clinical effects of these two regimens in this population.Methods: Relevant studies up to August 2021 were identified through systematic searches of CNKI, Wanfang, PubMed, and Embase databases. We assessed the effectiveness and the frequency of absence seizures, atonic seizures, and tonic–clonic seizures. The included literature's risk of bias was evaluated using the Cochrane Collaboration's Risk of Bias tool. Sensitivity analysis was conducted to confirm the results' stability. STATA 15.0 was utilized for all pooled analyses in the included studies.Results: Totally 10 articles were determined for our meta-analysis, involving 976 patients with epilepsy in total . The results of this meta-analysis indicated that the total effective rate of sodium valproate combined with TPM was higher than that of sodium valproate alone . The frequency of absence seizures in the combined group was lower  than that in the monotherapy group, with a statistical difference (p < 0.05). The combined group had lower frequency of atonic seizures  and lower frequency of tonic–clonic seizures . In addition, the distinct difference of adverse events was non-existent between two groups.Conclusions: Sodium valproate combined with TPM was more effective than sodium valproate alone for epilepsy therapy. This meta-analysis provides feasibility data for a larger-scale study on AED therapy of refractory epilepsy and may contribute to better therapy strategies for epilepsy clinically. Epilepsy is a chronic brain disorder characterized by long-term prone epileptic seizures , 2. It iPharmacotherapy paradigms in epilepsy are constantly evolving. The monotherapy or multitherapy for AEDs has been a controversial topic over the last few decades. Monotherapy with AEDs is the primary initial cure for epilepsy . GloballTopiramate (TPM) is a promising new AED as monotherapy or adjunctive therapy for generalized tonic–clonic seizures or partial seizures in adults and children , 14. ThiHowever, there may be safety issues during combination therapy, such as unwanted drug interactions. For example, Cheung et al. described a case report that valproate combined with TPM-induced hyperammonemic encephalopathy syndrome for a 15-year-old boy . Moreovevia discussion, and if necessary, arbitrated by the third reviewer. Two authors independently assessed the searched studies based on the selection criteria, manually checking the retrieved articles' reference lists to determine additional relevant studies. Differences were resolved through discussion until the consensus was reached.For this meta-analysis, two researchers independently, comprehensively, and systematically searched the literature in CNKI, Wanfang, PubMed,and also Embase databases. The literature search was limited to full-length articles published up to August 2021 in Chinese and in English. The keywords used in the search were “Topiramate OR Topamax OR TPM” and “Sodium Valproate” and “epilepsy” and “Refractory epilepsy OR Intractable epilepsy.” Two reviewers independently evaluated the qualified articles, and divergence was resolved Studies included in our meta-analysis were required to satisfy the following criteria: (1) be related to AED therapy for refractory epilepsy (no restriction to the type of refractory epilepsy); (2) the intervention of the experimental group was sodium valproate combined with TPM, and the intervention of the control group was sodium valproate; (3) the main outcomes in the study included effectiveness, absence seizures, atonic seizures, tonic–clonic seizures, and adverse events.Studies were excluded from this analysis if they were (1) repeated articles; (2) summary of the meeting, comments, letters, existing systematic reviews, and meta-analysis; (3) study on TPM combined with other drugs.The information from all qualified articles that met the inclusion criteria was extracted by two reviewers independently. Meanwhile, the risk of bias of the selected studies was evaluated to ensure the data's reliability. Any difference in the extracted data was resolved through discussion. If a disagreement still existed after the discussion, a third investigator was invited to evaluate these articles. The data extracted by the two researchers independently reading the full text of each eligible article, including the following information: the author's name, publication date, sample size, age, intervention measures, and also outcome measures.The included studies' risk of bias was assessed using the Cochrane Collaboration's Risk of Bias tool, categorizing the study as “low risk” of bias, “high risk” of bias, or “unclear risk” of bias . The quaWe assessed the rate of effectiveness and the frequency of absence seizures, atonic seizures, tonic–clonic seizures, and also adverse events. The main outcome for measuring efficacy was the total effective rate. The total effectiveness was defined as the improvement of symptoms and signs, mainly including sudden, recurrent loss of consciousness, body convulsing, and frothing at the mouth, and also a decrease of ≥50% in seizure frequency from baseline to posttreatment. The other outcome was the condition of patients who suffered from treatment-emergent adverse events (TEAEs). TEAE is an adverse event that occurred or became worse in the treatment phase . TEAEs eQ-test and I2-test were applied to assess the heterogeneity between studies. The fixed-effect model was used in case of p > 0.1, I2 ≤ 50%; Otherwise, the random-effect model was used. Sensitivity analysis was used for estimating the results' stability. A funnel plot combined with Egger's test was used to assess publication bias  and 95% CI or odds ratios (OR) value and 95% CI. The frequency of seizures was described by mean and standard deviation, and the pooled effect analysis in this meta-analysis was performed on the mean of seizures in each study. Statistical methods for combining the results of studies generally weight the influence of each study by the inverse of the variance for the estimated measure of effect. Based on the heterogeneity test results, the total effects were evaluated through random-effect or fixed-effect models , 35. Q-tion bias , 37. TheOverall, 152 articles were searched by the systematic search in total, of which 32 duplicates were excluded. After independently screening the title and abstract by two review authors, 72 irrelevant articles were removed, and 48 studies were selected for detailed full-text review. In the light of selection criteria, 38 articles were eliminated, and 10 were eventually included in our meta-analysis. The flow chart  describeThe literature's risk bias estimation results were presented in OR = 2.17, 95% CI 1.47-8.47), and the difference was statistically significant (p < 0.05). By removing each qualified study in turn, we conducted the sensitivity analysis to evaluate the impact of each individual study on the pooled OR  than that of sodium valproate alone, with statistically significant difference . In addition, the results of subgroup analysis indicated that there were no differences in the incidence of headache (p = 0.710), anorexia (p = 0.410), and nausea (p = 0.527) between the two groups.We pooled data on adverse events mainly including headache, loss of appetite, and nausea. Five studies reported these adverse events with the two treatments, which were presented in Epilepsy is one of the most common neurological disorders, leading to a considerable incidence rate . In clinTo date, many researchers have compared the efficacy of sodium valproate combined with TPM vs. sodium valproate alone for refractory epilepsy. Nevertheless, there is still a lack of systematic collection, classification, and assessment of these research data. In our study, 10 articles were screened strictly based on the selection criteria, and 976 patients with refractory epilepsy were included, with the age range of 10-70 years. The results fully indicated that sodium valproate combined with TPM has significant curative effect on refractory epilepsy compared with sodium valproate alone, which can reduce epilepsy attack frequency. Here, we conducted the meta-analysis to provide the comprehensive and explicit evidence-based evaluation of relative efficacy of the two therapeutic strategies. To our knowledge, this meta-analysis was the first evaluation in regard to clinical effect of sodium valproate combined with TPM vs. sodium valproate alone for refractory epilepsy.There were similar design features among included studies, and the low heterogeneity between trials enhances the estimates' accuracy . The res+ current can account for decline of seizure frequency. Moreover, one study reported that TPM-induced reduction in tonic–clonic seizures corresponded well with the decrease of glutamate levels in SER  project of Shantou Science and Technology Bureau (2021010206).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.


Background: The use of social media daily could nurture a fragmented reading habit. However, little is known whether fragmented reading (FR) affects cognition and what are the underlying electroencephalogram (EEG) alterations it may lead to.Purpose: This study aimed to identify whether individuals have FR habits based on the single-trial EEG spectral features using machine learning (ML), as well as to find out the potential cognitive impairment induced by FR.Methods: Subjects were recruited through a questionnaire and divided into FR and noFR groups according to the time they spent on FR per day. Moreover, 64-channel EEG was acquired in Continuous Performance Task (CPT) and segmented into 0.5–1.5 s post-stimulus epochs under cue and background conditions. The sample sizes were as follows: FR in cue condition, 692 trials; noFR in cue condition, 688 trials; FR in background condition, 561 trials; noFR in background condition, 585 trials. For these single-trials, the relative power (RP) of six frequency bands  were extracted as features. After feature selection, the most important feature sets were fed into three ML models, namely Support-Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes to perform the identification of FR. RP of six frequency bands was also used as feature sets to conduct classification tasks.Results: The classification accuracy reached up to 96.52% in the SVM model under cue conditions. Specifically, among six frequency bands, the most important features were found in alpha and gamma bands. Gamma achieved the highest classification accuracy . In both conditions, alpha RP in central sites of FR was stronger than noFR (p < 0.001). Gamma RP in the frontal site of FR was weaker than noFR in the background condition (p < 0.001), while alpha RP in parieto-occipital sites of FR was stronger than noFR in the cue condition (p < 0.001).Conclusion: Fragmented reading can be identified based on single-trial EEG evoked by CPT using ML, and the RP of alpha and gamma may reflect the impairment on attention and working memory by FR. FR might lead to cognitive impairment and is worth further exploration. Given the prevalence of fragmented information from various social media , people As the most commonly used neuroimaging tools, functional MRI (fMRI) and electroencephalogram (EEG) have been widely applied to find out sensitive biomarkers and explain the underlying cognitive neural mechanism. Due to the high spatial resolution of fMRI, it is widely used to study cognition and has made fruitful achievements . HoweverElectroencephalogram collected in CPT has been widely used to study cognitive impairment . Many ofManually identifying FR is inefficient and could not take full advantage of the whole EEG spectrum information. Group-level statistics analysis has difficulty in identifying FR at the individual level. ML is currently a popular tool to conduct individual-level accurate identification . TherefoWe acquired EEG data through CPT, extracted 0.5–1.5 s post-stimulus epochs, and calculated the relative power (RP) of six frequency bands as features. Then, these features of six frequency bands, alone or collectively, were fed into ML models to conduct FR identification. Furthermore, in order to find out how FR impairs cognition, frequency bands that showed superior performances in classification were further analyzed by statistical comparison at the group level.All the subjects were college students from Fourth Military Medical University, Xi’an, China. They were required to complete a self-reported questionnaire on demographic information and habits of social media apps usage. Demographic information included age, sex, height, weight, family structure, urbanization, ethical group, smoking habits, alcohol consumption, color blindness, handedness, history of brain trauma, and family history of mental illness. To prevent biases and fit with the theme of this study, only three social media apps most commonly used in China were included. The main contents of one app  were short text and pictures, and of the other two software (TikTok and Kwai) were short videos, which contained a lot of fragmented information.First, the subjects were excluded according to the following criteria: BMI > 30 or <18.5, smoking, alcohol consumption, color blindness, left-handedness, history of brain trauma, or family history of mental illness. Afterward, from the questionnaire results of the habits of social media apps usage, the time that subjects spend on social media apps per day was considered as the time they spend on FR per day and defined as FR-time in this study (measured in hours). In order to investigate whether FR has an influence on cognition, this study extracted two groups of extreme cases for comparison according to the FR-time: (i) FR group, subjects who spend a lot of time on FR, i.e., at the top of the FR-time list; (ii) noFR group, subjects who spend little time on FR, i.e., at the bottom of the FR-time list. Therefore, after removing the subjects with questionable data quality, the top 12 subjects were selected as FR group (age 20.75 ± 0.75), while the bottom 12 subjects were selected as noFR group (age 20.67 ± 0.98) . This stt-test. There were no significant differences between them on the behavior level.A numeral version of AX-CPT was carried out according to the study by Continuous EEG data was recorded by a 64-channel electrode cap of GSN-Hydrocel64 , sampling rate equaled to 500 Hz. During recording, the impedance of electrodes was kept below 30 kΩ. EEG was acquired simultaneously with fMRI in this study, so it was firstly preprocessed through the software NetStation  to reducing the artifacts caused by fMRI (mainly including gradient artifacts and ECG artifacts). In order to get pure EEG, EEGLAB  was usedThe original power spectrum was calculated by multitaper methods , in whic∗ 64 channels) were used for the classification of FR and noFR under each condition, and the classification of cue and background conditions in each group. Moreover, RP of each frequency band on 64 channels was also used separately for the classification of FR and noFR. Before classification, to ensure the balance of sample size, trials in other cases were randomly down-sampled according to the case with the least number of trials. Finally, all the trials were randomly divided into train sets and test set with the ratio of 4 to 1, and the test set was not involved in model training.For two groups (FR and noFR) under two conditions (cue and background), all the RP of six frequency bands in 64 channels were considered as features. First, a total of 384 features .In this study, three common classifiers were selected, including Support-Vector Machine , K-Nearest Neighbor , and Naive Bayes. These models were from MATLAB  machine learning toolbox and trained to carry out classification in 10-fold cross-validation (CV). For the 10-fold CV, samples of the train set were randomly divided into 10 equal sets, a classifier was then trained on nine of the 10 sets and tested on the left-out one. The final test set was also input into the classifier of each fold. This process was repeated 15 times. All the reported results were the average value from 10-folds in 15 rounds , true negatives , false positives , and false negatives . Classification accuracy was computed as a ratio of the sum of TP and TN divided by the sum of all classified subjects. The precision was calculated as the number of true positives divided by the number of true positives plus the number of false positives and the recall was calculated as the number of true positives divided by the number of true positives plus the number of false negatives. Besides, Area under the curve (AUC)  and F1-st-test was used to compare the accuracies of 10-fold CV between two models.For comparisons between classification cases, a t-tests were conducted between two groups (FR and noFR) or two conditions (cue and background) to achieve statistical comparisons at the group level. False discovery rate (FDR) correction based on Benjamini and Hochberg method  were selected out, including frontal site (Fp1 and Fp2), central site , and parieto-occipital site . For each ROI, the RP of the frequency bands of interest was calculated by averaging the RP on all the channels in ROI. Then, one-sided g method  was usedThree models were trained and tested by all six frequency bands  in cue and background conditions. Features were arranged in descending order according to their importance scores calculated by the MRMR feature selection method. In this order, the number of features used for model training and testing was gradually increased one by one. Finally, the best results were selected to be reported in Before model training, feature selection based on MRMR provided the importance scores of 384 features. We defined a feature whose importance score > 0 as the effective feature (EF). As a result, the distributions of importance scores of EFs are shown in To further explore the performance of each frequency band in the classification of FR and noFR, we chose the SVM classifier, which has the best classification performance, and respectively input the RP of each frequency band as features without feature selection. Results are shown in In cue condition, theta , alpha , and gamma  showed top three classification ability for FR. Delta was the worst to classifying FR (Accuracy = 73.79%). In background condition, beta1 , beta2 , and gamma  showed top three classification ability for FR. At the same time, delta still showed the worst ability for FR classification (Accuracy = 75.23%). In general, among six frequency bands, gamma had the most significant classification ability for FR (Accuracy greater than 85% under both conditions).t-test, alpha showed a highly significant difference in the classification accuracies between cue and background conditions .Meanwhile, for each frequency band, comparing the accuracies of 10-fold CV in 15 times training and test between two different conditions by t-test are shown in Feature selections showed that theta, alpha, and gamma contribute more EFs to the classification of FR and noFR, especially alpha see . Meanwhip = 0.089; significant for background, p < 0.001). For RP of alpha in the central site, FR had a significantly higher RP of alpha than noFR in both conditions (p < 0.001 for both cue and background). In the parieto-occipital site, FR also had a higher RP of alpha than noFR . This was in line with the result in the classification of FR and noFR based on features of alpha that there was a significant difference between the classification accuracies in cue and background conditions , while there was no significant difference for noFR (p = 0.053). Central site alpha activity was significantly weaker in cue condition than in background for both FR and noFR (p < 0.001), while parieto-occipital site alpha activity was significantly weaker in cue condition than in background condition only for noFR (p = 0.002).Besides, frontal site gamma activity was significantly stronger in the cue condition than in the background condition for FR . The highest classification accuracy of cue condition was up to 90.4% in the noFR group.Furthermore, we also classified cue and background conditions in FR and noFR groups respectively to compare the performance of the two groups in distinguishing the two conditions. Again, three models  were trained based on the whole 384 features data set. Features were also arranged in descending order according to their importance scores calculated by MRMR. In this order, the number of features used for model training and testing was gradually increased one by one. The best results were selected to be reported in Fragmented reading can be accurately identified based on single-trial EEG spectral features of all the six frequency bands. All the three classifiers  used in this study demonstrated high classification performance, and the highest test accuracy reached 96.52% achieved by SVM under background conditions. Through (1) feature selection algorithm and (2) comparisons of models trained by features of each frequency band, alpha (8–13 Hz) and lower gamma (30–40 Hz) were found to make more important contributions to the classification between FR and noFR. Considering the statistical analysis together, it suggests that RP of alpha and gamma might reflect the differences of the multiple types of cognitive abilities between FR and noFR, which could help to understand how FR impacts cognition.The relative power of alpha might reveal the impairment on attention caused by FR. FR was found to have significantly stronger alpha activity than noFR in the central site under both conditions and the parieto-occipital site under cue conditions. Besides, parieto-occipital site alpha was significantly suppressed from background to cue in the noFR group, but not in the FR group. It suggests that the difference between cue and background conditions in the FR group might be smaller than those in the noFR group. This was consistent with the ML result that cue and background conditions were harder to be classified in the FR group than noFR. Take previous findings into consideration stating that a decrease in alpha represents an increase in the attentional resources allocated , our resThe relative power of gamma might reveal the impairment on working memory (WM) caused by FR. In both cue and background conditions, gamma was found to have the best ability for the classification between FR and noFR, and FR showed a significantly weaker gamma activity in the frontal site than noFR in the background conditions. Previous studies have found an association between gamma activity and various cognitive functions in healthy humans , among wFinding out which EEG segments are used to analyze in CPT is critical since different cognitive processes happen in different time windows . Most prThere were some limitations to this study. First, since EEG data were acquired in sync with the fMRI, it would be better to carry out a fusion analysis of EEG and fMRI. Besides, while collecting the task state data, it would be better to also collect the resting-state data to compare these two to clarify the brain activity of the subjects in each state more clearly. Finally, more longitudinal studies are needed to further demonstrate the cognitive impact of fragmented reading habits.Fragmented reading is the most common way we obtain information today. It provides great convenience for our daily life, and at the same time, might also impair our cognitive abilities. Based on RP of single-trial EEG evoked by AX-CPT, for the first time we successfully identified FR with accuracy up to 96.52% (SVM model). Alpha and lower gamma were found to make larger contributions to the classification of FR and noFR and might indicate the cognitive impairment caused by FR. Alpha, which was hard to suppress in central and parieto-occipital sites for FR, might reflect the impairment on attention caused by FR. Gamma, which was hard to activate in the frontal site for FR, might reflect the impairment on working memory caused by FR.The present study helped to reveal the neural mechanism of the cognitive impairment caused by FR, which is worth further exploration. Consequently, we suggest that, for social media apps, relevant regulations should be introduced to limit the fragmented way of the content presented, and for the users, especially children and adolescence, they should be aware of the impairment of FR and not addicted to the fragmented content in the online world.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 Tangdu hospital. The patients/participants provided their written informed consent to participate in this study.JZ, WW, and GC: conceptualization, funding acquisition, and supervision. BH and JS: data curation and investigation. JF: formal analysis, methodology, software, and roles/writing – original draft. BH and WW: project administration. BH: resources. JF and BH: visualization. JZ and WW: writing – review and editing. 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.


As the third most common type of cancer in the United States, colorectal cancer (CRC) was previously thought to be rare in young populations. Despite a decrease in the overall incidence of CRC, the rate of new cases under 50 years old has been continuously increasing.  The purpose of our study was to analyze risk factors of young-onset CRC.  Commercially available software platform, Explorys, was used to extract data from a collective healthcare database electronically.  In this database, 13,800 young adults (age 20–50) were diagnosed with primary colorectal malignancy. Compared to subjects with a previous family history of CRC who had an odds ratio of 17.78, those diagnosed with primary malignant neoplasm of breast and inflammatory bowel disease (ulcerative colitis and Crohn's) had odds ratios of 16.94, 4.4, and 3.7 for young-onset CRC, respectively. Patients with a history of alcohol abuse, smoking, obesity, diabetes mellitus, and hyperlipidemia had higher chances of developing young-onset CRC. In addition, the odds of CRC were lower in Hispanic ethnicity in comparison to Caucasians (OR: 0.54), with no statically significant differences between Caucasian, African American, and Asian populations.  Currently, this is an expansive study investigating the risk factors for early-onset CRC. The analysis showed factors such as family and individual history of IBD to have high association with early onset. Notably, an individual history of breast malignancy was strongly associated with early-onset CRC. Colorectal cancer (CRC) is ranked as the third most common malignancy and cause of mortality in men and women. CRC was responsible for 145,600 of newly diagnosed cases of malignancy, and 51,020 deaths in 2019 .Following this marked increase in CRC, particularly in young individuals, American Cancer Society (ACS) proposed to decrease the age threshold of CRC screening to 45 years for the average-risk population [Considering the multifactorial nature of this neoplasia, the occurrence of CRC is noted to be irregular in the general population and showed considerable variation with several risk factors including genetic susceptibility, obesity, vitamin D deficiency, diabetes, smoking, and other dietary factors . In younThe aim of our study is to shed more light on potential classic and/or unconventional risk factors that could be contributing to this increased incidence of CRC in the young adult population.We performed a retrospective large population-based analysis of a commercially available database , from the year 1999 to 2019. Explorys is a culmination of Electronic Health Record (EHR) information. Data was collected from 26 reputable healthcare systems of US which were closely integrated .2), smoking, alcohol intake, diabetes mellitus, hyperlipidemia, Crohn's disease (CD), ulcerative colitis (UC), primary malignant neoplasm of breast, and family history of colorectal cancer were collected.Patient cohorts were created with Explorys software, and mining of the database was performed on September 1, 2019. The created cohort from this database consisted of every individual who had a diagnosis of primary malignant neoplasm of colon and rectum, between the ages of 20 to 50 years. Furthermore, a control group with patients without the diagnosis of primary malignant neoplasm of colon and rectum within the same age group was established. Demographic data including age, gender, race, and medical comorbidities and social habits including obesity (body mass index (BMI) >30 kg/m2), tobacco use, alcohol intake, diabetes mellitus, hyperlipidemia, Crohn's disease, ulcerative colitis, primary malignant neoplasm of the breast, and family history of CRC. A multivariate regression model was developed and used to minimize the confounding effects of the previously mentioned covariates. This was attempted with the use of binary logistic regression with colorectal cancer being the outcome. Statistical Package for the Social Sciences  was the package of choice. In all evaluations, a 2-tailed P value of <0.05 was considered statistically significant.The overall prevalence of CRC among the study group was calculated by dividing the number of CRC cases by the number of all young adults included in the study. We compared prevalence of CRC in subgroups based on age, gender, and race. The prevalence rates of CRC were calculated for each group by dividing the total number of individuals with CRC by the total number of individuals in the group. The odds ratio, with 95% confidence intervals, was calculated for age, gender, race, obesity  in the age group of 45–49 years when compared to 20–25 age group as the reference group .In terms of ethnicity, CRC was more common among Caucasian and African American young adults, and the prevalence of CRC was lower in the Hispanic and Latino populations compared to other races included in our study, in all age groups .Risk of colorectal cancer was lower in the Hispanic/Latino group in comparison with Caucasians , and there was no statistically significant difference between Caucasian, African American, and Asian populations .The prevalence of CRC trended upward with increasing age among patients with family history of GI malignancies and personal history of CD or UC, in comparison to their counterparts in the control group. On the contrary, CRC prevalence declined with age among patients with history of breast cancer, although it slightly increased among patients without breast cancer .A multivariate analysis of our data revealed that the risk of having young adult-onset colorectal cancer was higher in males with an odds ratio of 1.35 (95% CI: 1.31–1.39).Family history of colorectal malignancy had the strongest association with young adult colorectal cancer with an odds ratio of 17.78 (95% CI: 16.97–18.62) proceeding with primary malignant neoplasm of breast with odds ratio of 16.94 (95% CI: 15.74–18.24). There was a statistically significant association between UC/CD and young-onset CRC with an odds ratio of 4.42 (95% CI: 4.04–4.84) and 3.7 (95% CI: 3.44–4.07), respectively. In addition, CRC was more common in patients with BMI >30, diabetes mellitus, or hyperlipidemia . Among patients with alcohol abuse and nicotine dependence, the odds ratios of developing early-onset colorectal cancer were 1.89 (95% CI: 1.77–2.02) and 1.59 (95% CI: 1.53–1.64), respectively .The definition of “early-onset CRC” or “young adult-onset CRC” remains debatable in literature. The common consensus among the major gastroenterology and oncology societies is that CRC can be considered early onset if the patient's age falls below the screening guidelines . The dirStudies have shown that gender plays a role in the development of colorectal cancer. The CRC incidence and mortality rate are higher in men compared to women. Furthermore, colorectal neoplasia is found at an earlier age in men than in women , 13. In In the United States, the incidence and mortality rates for CRC are higher among African Americans . ReasonsThe strength of family history as a risk factor of colorectal malignancy declines as a person ages and is no longer seen after 70 years of age . A EuropP = 0.001) [Literature has indicated a potential risk of CRC among patients with history of breast cancer. Two review articles, which both were published in 1994, estimated colorectal cancer relative risks of 1.1 and 1.15, respectively, regarding breast cancer history. These articles concluded that the risk increase was not significant enough to alter colorectal screening protocol in women with history of breast cancer , 21. In = 0.001) . It suggOur study showed a higher prevalence of CRC among patients with history of breast cancer in comparison to individuals without such history. Furthermore, prevalence of CRC decreased with age among patients with history of breast cancer in our study population. This trend may indicate that an association exists between breast cancer and development of CRC, which declines with age. Similarly, Newschaffer et al. reported a reduced risk of CRC in women diagnosed with breast cancer after the age of 65 . This trOur data was consistent with previous studies that showed that patients with inflammatory bowel disease have a greater probability to develop CRC in a younger age, in comparison to sporadic CRC –32. AlthThe association between colorectal cancer and other intestinal diseases such as irritable bowel disease (IBS) and microscopic colitis has been investigated before. In a European study, including 968 IBS patients, only 2 individuals were found to have CRC at the age of 56 and 58 years old . A largeα and IL-6. Chronic inflammation is the possible mechanism of CRC in obese patients [2 has been established. Our data in conjunction with previous studies indicate that the rise of young-onset CRC can be partially attributed to the increased incidence and prevalence of MS, in particular within the developed countries and this age group [Multiple studies supported the idea that metabolic syndrome (MS) may be a risk factor for CRC and certain other types of cancers , 38. Eacpatients . Data repatients . In contpatients . The carpatients . Among tpatients –47. In tge group .Direct dose-related correlation between smoking, alcohol use, and CRC incidence has been shown in previous studies –51. AlthAllium vegetables such as garlic reduces the crypt foci and adenomatous polyp as the precursor lesions for colon cancer [Allium extract also showed promising therapeutic results in patients with CRC.The association between diet and CRC has been investigated before. A European case-control study showed that the diet centered on high levels of processed meat was associated with increased risk of early-onset CRC . The samn cancer . The AllAlthough Explorys provides information from 26 major health systems across the nation, it has several limitations that should be noted in our study. This cohort study shows the validity and comprehensiveness of the results to be directly related to the EMR in use at each institution. Furthermore, in converting ICD-9 or CPT codes to equivalent Explorys descriptors, possibilities for redundancy and ambiguity are introduced. Additionally, data regarding family history was limited. It did not specifically determine if it was first- or second-degree relation and how many family members had been affected. Explorys also broadly reports family history of GI malignancy not specifically CRC. In addition, we also did not have the data of BRCA mutation carriers in the database. Lastly, other potential risk factors such as medications, activity level, and diet could not be reliably tracked in this database.This study is one of the most current yet comprehensive papers in the analysis of risk factors for early-onset CRC. As expected, previously known risk factors such as family history of CRC and individual history of IBD showed a strong correlation with early-onset CRC. Additionally, the individual history of breast cancer in our study has shown a noteworthy association between breast cancer and CRC, which has the potential to warrant an early screening protocol in this subset as well. To a lesser extent, other risks such as obesity, diabetes mellitus, hyperlipidemia, alcohol abuse, and smoking have shown an association with early-onset CRC. This study once again emphasizes the importance and merits of early screening and identification following identification of high-risk individuals. Our findings also emphasize the importance of lifestyle modification that may help overcome multiple risk factors in the prevention of CRC. Follow-up studies may provide further clarification on this aspect.