Video games are popular and ubiquitous aspects of human culture, but their relationships to psychological and neurophysiological traits have yet to be analyzed in social-evolutionary frameworks. We examined the relationships of video game usage, motivations, and preferences with autistic and schizotypal traits and two aspects of neurophysiology, reaction time and targeting time. Participants completed the Autism Quotient, Schizotypal Personality Questionnaire, a Video Game Usage Questionnaire, and two neurophysiological tasks. We tested in particular the hypotheses, motivated by theory and previous work, that: (1) participants with higher autism scores would play video games more, and participants with higher schizotypy scores would play video games less; and (2) autism and positive schizotypy would be associated with opposite patterns of video game use, preferences and motivations. Females, but not males, with higher autism scores played more video games, and exhibited evidence of relatively male-typical video game genre preferences and motivations. By contrast, positive schizotypy was associated with reduced video game use in both genders, for several measures of game use frequency. In line with previous findings, males played video game more than females did overall, preferred action video games, and exhibited faster reaction and targeting times. Females preferred Puzzle and Social Simulation games. Faster reaction and targeting times were associated with gaming motives related to skill development and building behavior. These findings show that gaming use and patterns reflect aspects of psychology, and gender, related to social cognition and imagination, as well as aspects of neurophysiology. More generally, the results suggest that video game use is notably affected by levels of autistic and schizotypal traits, and that video games may provide an evolutionarily novel medium for imaginative play in which immersive play experiences can be decoupled from social interaction. Why do people play? Play is a nearly universal behavior among mammals , but onlHow, then, does the current digitalization of the social world affect how people play? Given increased virtualization of the social world, video games have come to increasingly predominate the “iGen”  play space . As of 2Despite the growing importance and popularity of video games in modern life, the relationships of video game culture with social and cognitive phenotypes remain little understood. To date, most research on video games had focused on specific aspects of neuropsychological traits to video game use, such as the relationship between aggression and violent video games , the useCurrent evidence suggests that video game usage patterns are consistent with psychological profiles and behaviors that mirror real life motivations and preferences . For exaHow, then, does the development of diverse social-psychological phenotypes correlate with general video usage? From the pattern described above, different typologies of video game players may be elucidated further, based on differential development in socio-cognitive traits and usage profiles.Emerging evidence indicates that video games usage may reflect not only users’ psychological traits, but also neurophysiological skills such as reaction time , spatialConsidered together, these results support the view that video game usage patterns are associated with variation in some psychological traits and neurophysiological phenotypes. However, most studies have focused on action games, and no previous work has analyzed subclinical autistic and schizotypal traits  together in relation to video game usage and preferences and their neurophysiological correlates. Such studies are important given the important roles of video games of diverse genres in human imaginative culture, and given that individuals with autism or schizotypy show some evidence of high rates of video game usage . This stTwo studies suggest that psychological variations related to the autism spectrum and the schizophrenia spectrum, including positive schizotypy, may mediate aspects of video game use. First, Second, according to the diametric model of social brain disorders , 2020, aMechanistic thought is characterized by a cognitive style specialized for recognizing patterns in rule-based systems  . In autiFurthermore, autistic traits have been associated with higher video game usage , and proIn contrast to autism, positive schizotypy can be characterized by hyper-mentalistic traits such as fantasy-proneness, ideas of reference , paranoia , and increased imagination . All of Positive schizotypal traits, in particular, have been associated with slower reaction time during conditions of high perceptual load  and defiGender differences in play have been well-documented in the literature, extending into video game usage and preferences. Male play is more physically aggressive  and “thiBased on the reasons outlined above, the following predictions can be made:Hypothesis 1: Gender differences in video game usage, genre preferences, and motivations will vary in the following ways: (1) Males will report greater video game usage than females, (2) Males will prefer mechanistic-oriented video games such as Action, Platformer, Strategy, Racing, Sports, RPG, and Construction and Management Simulation games while females will prefer Puzzle and Social Simulation video games, (3) Males will report greater motivation for Skill Development and Customization games and females will report greater motivations of Social Interaction, a Way to Fantasize, and a Way to Escape on the Video Game Usage Questionnaire used here.Hypothesis 2: Autistic traits will be associated with increased video game usage. Total and positive schizotypal traits, as quantified by total score on the SPQ-BR and scores on the SPQ Cognitive-Perceptual subscale, will be negatively associated with frequency of video game usage.Hypothesis 3: Autistic traits will be positively associated with preferences for relatively rule-based video game genres including Puzzle, Action, Platformer, Strategy, Racing, Sports, Idle, and Construction and Management Simulation games. Total and positive schizotypal traits will be positively associated with preferences for Fantasy, Role Playing, and Social Simulation video games.Hypothesis 4: Autistic traits will be positively associated with mechanistic motivations such as Skill Development and Customization on the Video Game Usage Questionnaire. Total and positive schizotypal traits will be positively associated with mentalistic motivations such as Social Interaction, Way to Fantasize, and Way to Escape on the Video Game Usage Questionnaire used here.Hypothesis 5: Autistic traits will be associated with increased neurophysiological skills, such as faster reaction time and hand-eye coordination time. Conversely, total and positive schizotypal traits will be associated with slower reaction and hand-eye coordination times.Hypothesis 6: Increased total video game usage will be predicted by higher reaction and hand-eye coordination time. In turn, slower reaction and hand-eye coordination time will predict lower video game usage.The predictions of these hypotheses were tested using data on measures of autism spectrum and schizotypy spectrum cognition in a non-clinical population, and data on reaction times and targeting times, two measures of neurophysiological performance that may be related to video game use and performance.nancy_yang_2@sfu.ca.” Participants were reimbursed with either a course credit or a $10 electronic gift card for their time. All participants provided informed consent before participating in this study. Data collection took place during the Spring 2021 semester (January–April 2021). The study was approved by the Simon Fraser University Research Ethics Board (Study Permit 2020s0503).A total of 351 participants  were included in the study. The participants were recruited from various electronic mailing lists  and the Simon Fraser University Undergraduate Psychology Research Pool. The following study description was circulated as the recruitment email: “Do you play video games? Or do you not play video games? Either way, we want to hear from you! We are doing an online study on the relationship between psychological traits and video game usage. You will receive a $10 gift card for participation. For more info please contact The Autism Spectrum Quotient (AQ) was used to assess individual variations in autistic traits . The AQ Schizotypal traits were quantified with Schizotypal Personality Questionnaire-Brief Revised (SPQ-BR) . The SPQA Video Game Usage Questionnaire was adapted from the Gaming Attitudes, Motives, and Experiences Scales (GAMES) . The queThe frequency of video game usage was quantified via participant self-evaluations on this questionnaire. There were five questions pertaining to video game usage. First, participants were asked on the following: (1) Self report usage: “What is your video game usage like?” on a 5-point Likert scale where 1 was “Very Often” and 5 was “Very rarely or not at all,” (2) Self report frequency: “How frequent do you play video games? Check one.” Participants had the option of selecting from “Daily,” “2–3 times a week,” “weekly,” “2–3 times a month,” “monthly,” “less than monthly,” and “never,” (3) Self report spare time: “What proportion of your spare time is spent on video games?” on a 5-point Likert scale where 1 was “Almost all of none of my spare time” and 5 “Almost all of my spare time.” For self-reported frequency, responses were scored as “1” if participants answered “Never” and “7” for “Daily.” Participants were also asked to enter the number of hours spent on video games for an average weekday and weekend day.https://www.psytoolkit.org/  Fitts Law Task to quantify targeting time, and (2) Simple Choice Task to quantify reaction time. Both computer tasks were administered via kit.org/ , 2017, aFitts’ Law Task  : There wSimple Choice Task  : For thiAnalyses were conducted in R (v4.0.5)  using fuEffects of reaction time and targeting scores on each of the five measures of video game use were analyzed with ANCOVAs using each of the game use variables as an outcome and either reaction time or targeting time score as the independent variable, and gender included as a covariate, and without an interaction term. To analyze the effects of the AQ and SPQ subscales, we performed backward stepwise regressions starting with each all of the AQ and SPQ subscales and gender as independent variables for each of the five use measure outcome variables. The least informative independent variable was iteratively dropped from the model until dropping a variable led to a less efficient model, as assessed using the Akaike information criterion.Tests for association between reaction time, and targeting scores, on the type of games played were conducted using logistic regressions. Each of the game types was modeled with a separate analysis, with type of game played as a Boolean outcome; the independent variables were either reaction time, or targeting score, each of which also included gender as a covariate, without interaction terms. Tests for the association between reaction time and targeting scores and each of the different types of motivation to play games were conducted in the same manner, with one logistic regression of the motivational type as a Boolean outcome variable against either reaction time or targeting with gender included as a covariate.t-tests, product-moment correlations) were conducted for some analyses, in addition to ANCOVAs and multiple regression analyses, for representation and depiction of the results for each relevant test, since these analyses make fewer assumptions.To test for associations of AQ and SPQ scales with the type of games played, logistic regressions were conducted using general linear models with binomial response families. Each of the game types was modeled with a separate analysis, with type of game played as a Boolean outcome, and all subscales were entered as independent variables along with gender. No interaction terms were entered. A backward stepwise method was used to successively drop the least informative independent variable, until dropping a variable led to a less efficient model, as assessed using the Akaike information criterion. Tests for association between the AQ and SPQ subscales and the motivations to play games were conducted in the same manner, with a separate stepwise elimination of subscales until reaching the most efficient model for each of the different motivation types. Simple bivariate analyses .In females only, higher SPQ-Magical Thinking was associated with decreased self-reported spare time, while SPQ-Social Anxiety and SPQ-Disorganization were associated with greater weekend time on video games. In females only, SPQ-Eccentric Behavior scores were also positively associated with greater weekend time and self-report spare time on video games, with the relationship marginally non-significant (p = 0.06), and significantly associated with greater self-reported usage, and self-report spare time on video games.In males only, higher SPQ-Magical Thinking was associated with greater self-reported usage and spare time spent on video games. Higher SPQ-Eccentric Behavior was associated with greater self-reported usage and spare time on video games. In males, higher SPQ-Disorganization was marginally non-significantly associated with greater weekend time . No other statistically significant relationships were detected in males or in both genders pooled together.By product-moment correlations, in females only, faster reaction times were associated with higher AQ-Total and SPQ-Total scores . There wFaster reaction times were associated with higher SPQ-Eccentric Behavior scores in both genders pooled together and in females. In females only, faster reaction times were associated with higher SPQ-Social Anxiety, SPQ-Disorganization AQ-Social Skills, and AQ-Attention to Detail. Higher SPQ-Magical Thinking scores were associated with slower reaction time in both genders pooled together and in males only .Higher AQ-Social Skills and SPQ-Social Anxiety scores were associated with faster targeting times in females. Higher SPQ-Magical Thinking scores were associated with slower targeting times in both genders pooled together, in males, and in females. Higher SPQ-Unusual Perception scores were associated with slower targeting times in both genders pooled together. Faster targeting time associated SPQ-Interpersonal in males. Higher SPQ-CogPer scores were associated with slower targeting time in both genders and in males.By multiple regression analyses, reaction times were significantly positively correlated with targeting times, with males being faster for both relative to females. No AQ or SPQ subscales were significantly associated with faster reaction times. Higher SPQ-Magical Thinking scores were associated with slower targeting times. These results are summarized in By product-moment correlations, faster targeting times were associated with increased self-reported spare time, weekend hours, weekday hours, greater self-reported video game usage and frequency in both genders pooled together, males only, and females only . Faster p = 0.058), SPQ-Odd Speech, faster targeting times, and being male. Higher weekend time was marginally associated with AQ-Communication, SPQ-Odd speech, faster targeting times, and being male. Higher self-report spare time was associated with higher SPQ-Eccentric Behaviors, lower SPQ-Magical Thinking, faster targeting time, and being male. No statistically significant relationships were detected for reaction times and any of the time use variables. Results are summarized in By stepwise regression analyses, higher self-reported video game usage was associated with higher AQ-Attention to Detail, higher SPQ-Eccentric, faster targeting times, and being male. Higher self-report frequency of video game usage was associated with faster targeting times, and being male. Higher weekday time was marginally associated with higher AQ-Attention to Detail  and the five video game usage variables. Gender was significantly associated with all usage variables . In the t-tests, faster reaction times were associated with preference for Action video games in both genders pooled together and marginally non-significantly in males (p = 0.07) (p = 0.06). Construction was associated with faster reaction times with both genders pooled together and in females. Idle game use was associated with faster reaction time in both genders and in males only.By  = 0.07) . Faster Preferences for Action and Idle game genres was associated with faster targeting time in both genders pooled together, and in females. Preferences for Role Playing Games (RPG), Strategy Games, and Construction Games were associated with faster targeting time in both genders, in females, and in males. Preferences for Social Simulation were associated with faster targeting time in females and males when they were analyzed separately.p = 0.066). Females reported greater preference for Puzzle and Social Simulation, but no significant relationships were found between reaction times and these two genres.ANCOVA was also conducted to analyze the separate relationships of reaction times, targeting times, to each of the 10 video game genres . Faster Faster targeting times were associated with preference for Action, RPG, Strategy, and Sports games in males. Faster targeting times were associated with preference for Construction and Idle, but no gender differences were detected. Females reported greater preference for Puzzle, but there were no significant differences in preference for Puzzle games and targeting times. Preference for Social Simulation were associated with faster targeting times in females. Results are presented in By both types of analyses, preference for Action, RPG, Strategy were associated with faster reaction and targeting times in males. Faster reaction and targeting times were associated with preference for Construction in both genders together. Preference for Social Simulation was associated with faster targeting times in females. Females reported greater preference for Puzzle but Puzzle was not associated with either faster reaction or targeting times.t-tests, faster reaction times were associated with the motivations Social Interaction, Skill Development, and Customization, in both genders pooled together and in males  associated with faster reaction times in males (p = 0.051). Males reported greater preference for Adrenaline Rush, but no relationship were detected between Adrenaline Rush and targeting times. Fantasy and Customization were associated with faster targeting times.By logistic regression analyses, Social Interaction was marginally non-significantly . Taken together, these patterns suggest that higher autistic traits may be related to greater video game usage via a decreased capacity for, or interest in, social and pretend play. In other words, because most video games environments involve pre-programmed characters, narratives, and behaviors, they may appeal to individuals with higher autistic traits who prefer predictable environments that can be navigated with pre-defined action patterns. In this light, video games may also function specifically for their self-contained immersive experiences that provide the illusion of sharing a social world without partaking in one. Furthermore, the relative anonymity and use of virtual avatars in video games offer an additional layer of interpersonal distance that can be conceptualized as the virtual extensions of parallel play behaviors commonly observed in children with autism . Users aWhy was there no evidence of a positive correlation of AQ score with video game use among males? One possibility is a “ceiling effect,” whereby males would exhibit too little variation in video game use scores for a positive relationship to be detected. However, males do exhibit comparable levels of variability (as measured by standard deviations) to females across the various measures of video game usage, and positive correlations restricted to females were found for multiple video game use frequency measures, which appears to render major influences from ceiling effects relatively unlikely. Alternatively, because most video games are designed with male-typical preferences such as competition  and physOur second hypothesis also predicted that patterns of video game usage would vary in opposite patterns along the autism-schizotypal axis, with autistic traits associated with greater video game usage and positive schizotypal traits  with lower video game usage.Evidence of negative relationships of SPQ-CogPer and SPQ-Magical Thinking with video game usage was detected from several analyses. These findings partially support predictions of the Why would individuals higher in positive schizotypal traits play video games less frequently? As outlined above, most video games appear to offer immersive but ultimately solitary play experiences that may not fulfill the mentalistic interests of many schizotypal individuals. Historically, most video games were developed as single-player ventures; lack of historical internet access meant that most games were developed to be enjoyed with only a limited number of players. For examples, the popularity of PC-based games in the 1990s meant that most games were designed to be self-contained, with clearly defined objectives, and catering to single players. In this light, given that the per se) would theoretically contain the following characteristics of high positive schizotypy: (1) rely on a short and fractured attention span on a wide variety of inter-changeable topics instead of one highly concentrated focus on a restricted set of clearly defined objectives, (2) verbally based, (3) high social connectivity, (4) virtual elements of high social monitoring in terms of detectable social feedback signals  that mimic in-person cues of joint attention and/or eye contact. In short, the logical equivalent of autism-video games appears to be schizotypy-Twitter or TikTok. Although we did not explicitly test for the relationship between schizotypy and social media platforms here, the association between positive schizotypy and Puzzle games suggest that such preferences could theoretically be extrapolated to social media platforms. Like most Puzzle games, most social media applications are designed to be used leisurely, with less cognitively taxing actions, and with no penalties if the user has less than accurate targeting movements.An opposite medium  . SurprisLastly, patterns of video game motivations described here partially support the Our study is constrained by several limitations. First, the data were collected during a school semester; thus, general video game usage patterns may have been under-reported due to greater time demands of the typical school semester. Future studies may account for potential differences in video game usage patterns due to classwork demands by incorporating a non-typical school semester in its time span of data collection for comparison. Second, given that we primarily recruited through a psychology student pool as well as university email lists, most of participants may have come from the undergraduate population; thus, the findings cannot be extrapolated to clinical populations, children, the elderly, or professional gamers who may demonstrate psychological traits atypical of our sample. Third, given that autistic and schizotypal traits were assessed via self-reports, results may be limited in that higher autistic and schizotypal traits may, paradoxically, be associated with lower cognitive insights and thus under-report of traits. Fourth, given the heterogeneous nature of most video games , findings from this study may be limited due to blending of mechanistic vs. mentalistic gameplay that characterize some video games. Future research could address such limitations by adding an open-feedback answer item as to better disentangle nuances in users’ motivations for gaming and gaming preferences. Finally, given that we administered reaction time and targeting time tasks online, variability in reaction and targeting time data may be confounded by participants’ choice of electronic device to complete the tasks . Although the computer tasks were designed to accommodate a wide variety of electronic devices, variability in reaction time and targeting time data may be influenced by participants’ use of a mouse vs. touchpad, which we did not control for. Some studies have shown that individuals were slower and tend to make more errors when using a touchpad than mouse to make pointing actions , and thaSince the COVID pandemic began, more and more recreational platforms have been moving to the virtual world. What will become of iGen 2030? The patterns described above suggest that the replacement of in-person play with virtual media may have important implications for the evolution of imaginative culture. First, the patterns in autistic play behaviors and video game usage described in this study suggest that video games may be a proverbial “new and reinvented” version of fantasy play. That is, unlike a traditional fantasy game where people must spontaneously imagine a shared mental space and participate accordingly, video games offer a pre-programmed imaginative space where anyone can join without having to spontaneously imagine entities into existence. Moreover, for the first time in human history, people are no longer bounded by the temporal-spatial limitations of other players to start and maintain a game. Almost everyone now can play a video game together—and alone.Finally, although we have found some evidence of decreased video game usage in association with positive schizotypy, we did not observe statistically significant patterns for greater mentalistic preferences in positive schizotypy as we did for mechanism and autism. Why would this be? One possibility is that video games only represent one end of the spectrum of virtual play behaviors that has now substituted for much of real-life play. The patterns of video game usage, preferences, and motivations described above suggest that imaginative and social aspects could be dissociated in video games; individuals with higher autistic traits appear to partake more in the former in lieu of the latter. In this light, as 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 Simon Fraser University Department of Research Ethics. The participants provided their written informed consent to participate in this study.All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.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.


With the rapid development of the Internet, the wide circulation of disinformation has considerably disrupted the search and recognition of information. Despite intensive research devoted to fake text detection, studies on fake short videos that inundate the Internet are rare. Fake videos, because of their quick transmission and broad reach, can increase misunderstanding, impact decision-making, and lead to irrevocable losses. Therefore, it is important to detect fake videos that mislead users on the Internet. Since it is difficult to detect fake videos directly, we probed the detection of fake video uploaders in this study with a vision to provide a basis for the detection of fake videos. Specifically, a dataset consisting of 450 uploaders of videos on diabetes and traditional Chinese medicine was constructed, five features of the fake video uploaders were proposed, and a Naive Bayesian model was built. Through experiments, the optimal feature combination was identified, and the proposed model reached a maximum accuracy of 70.7%. These numbers provide a glimpse into the profound impact of the Internet on people’s daily lives and showcase the fact that short videos have already become an important channel for information acquisition.The wide adoption of computers, smartphones, and other electric terminals, which increase the number of channels and the speed of information transmission, has boosted the development of the Internet. Take China as an example. As of June 2020, China had 940 million Internet users and an Internet penetration rate of 67.0%; mobile phone users reached 932 million, 99.2% of whom used mobile phones to go online; users of online videos (including short videos) totaled 888 million, accounting for 94.5% of all Internet users, among which 818 million were short video users, accounting for 87.0% of all Internet users2 suggest that video chatting, video mails and video blogs provide novel ways for interactions among Internet users, and many Internet service providers are displacing text-based services by video-based alternatives, such as video reviews, video advertisements and video replies. Though legitimate and friendly short videos are convenient to watch, illegitimate and fake videos are misleading. Pantazi et al.3 found that explicitly false statements, if considered true, would impact users’ judgments. In particular, false videos intended to mislead the audience will affect the audience’s judgment and their subsequent decision-making.The Internet, boasting large volumes of multimedia materials and quick information transmission, has become the major channel for multimedia information transmission. Benevenuto et al.5. Although the detection of fake reviewer has been investigated by many prior studies7, the detection of fake video uploaders is still lacking. Detection of fake video uploaders is the key step to identify the bad intention of fake videos. Some fake videos are misleading because the uploaders are ignorant. That does not mean the uploaders are intentionally misleading the public to get some benefits. However, if a user is identified as a fake video uploader, we can make sure that the videos he/she uploaded have bad intentions. To address the important research gap, we explores the possibility of detecting fake-video uploaders in this study.Misinformation, disregarding the scope and speed of transmission, brings only limited trouble to users, but if the misinformation is delivered in the form of videos, it reaches a wider audience at a higher speed. Thus, it is necessary to detect fake videos. Fake videos can be detected based on its content or source. However, most extant studies on fake video detection focus on its contentThis paper is comprised of five sections. Section 2 is a review of related works, Sect. 3 presents the Naive Bayesian model and the dataset of fake video uploaders used in this work, Sect. 4 discusses the experimental results and analysis, and Sect. 5 presents the conclusions.Since the results of literature review suggest that researches on detection of fake video uploaders is lacking, we decide to review the following two parts: (1) Fake video content detection; (2) Spammer detection in social media.The detection of fake video content has attracted many researchers in recent years. Extant studies on fake video content detection mainly focus on fake portrait video , clickbait video or misleading video.4 proposed a deep fake source detection via interpreting residuals with biological signals. They found that spatiotemporal patterns in biological signals can be conceived as a representative projection of residuals. Yu et al.8 proposed a novel method to detect the fake high definition for high efficient video coding videos based on prediction mode feature. Choi et al.5 proposed a novel fake video detection method by adopting predictive uncertainty in detection. They devised the certainty-based attention network which guides to focus certainty-key frames in detecting fake videos.The first stream of researches focus on the detection of fake portrait videos. Fake portrait video generation techniques are now a threat to the society with photorealistic deep fakes for political propaganda, celebrity imitation, forged evidences, and other identity related manipulations. Therefore, it is relevant to separate deep fake portrait videos from real videos. Ciftci et al.9 developed a Clickbait Video Detector (CVD) which considers three latent features as user profiling, video-content and human consensus. Shang et al.10 developed a novel content-agnostic scheme with the video comments. Different from existing solutions, this approach does not depend on the video content and its meta-data such as title or thumbnail. Jain et al.11 proposed a novel model to detect visual clickbaits on Instagram and Twitter. The proposed model consists of a stacking classifier framework composed of six base models and a meta-classifier.The second stream of researches focus on the detection of clickbait videos. Clickbait is a sensationalized headline that encourages you to click a link to an article, image, or video. Instead of presenting objective facts, clickbait headlines often appeal to your emotions and curiosity. However, the clickbait strategy typically values getting clicks over producing quality information. That means clickbait videos may waste the reader’s time with mediocre content. Therefore, many scholars have investigated how to detect clickbait videos. Varshney and Vishwakarma12. As a result, the detection of misleading videos was less investigated. Among the limited studies, Boididou et al.13 proposed a system that could classify multimedia Twitter posts into credible or misleading. The system leverages the credibility-oriented information extracted from the tweet content and the user identification. In another study, Papadopoulou et al.14 presented an approach based on supervised learning to classify misleading Web video. The proposed approach considers both video metadata  and the video comments.The third stream of researches focus on the detection of misleading videos, which is most relevant to the purpose of our study. However, the detection of misleading videos is a challenging task compared with the other two tasks mentioned aboveThe detection of fake content uploaders has also attracted many researchers in recent years. Extant studies on fake content uploader detection mainly focus on spammer detection and fake reviewer detection.The first stream of researches focus on the detection of spammers. A spammer is a person or group that sends you email you don't want and didn't sign up for. The email a spammer sends is called spam. Spam is usually some kind of advertisement. Although spammers was first used to in the e-mail context, it is also soon applied to the social media context. Social spam is unwanted spam content appearing on social networking services, social bookmarking sites, and any website with user-generated content 15 investigated how to collectively use network and content information to perform effective social spammer detection in microblogging. Yu et al.16 presented a novel semi-supervised social media spammer detection approach, making full use of the message content and user behavior as well as the social relation information. Miller et al.17 proposed an approach to detect twitter spammers using data stream clustering. Different from previous studies that approached spam detection as a classification problem, they viewed it as an anomaly detection problem. Park et al.18 proposed an approach to detect adaptive spammers that dynamically change their spamming strategies or behaviors and attempt to pose as legitimate users. This approach introduces a new method of moving target defense wherein the concept of differential immunity of different classifiers is employed to detect the spammers.Many scholars have explored the detection of spammers in social media. For example, Hu et al.The second stream of research focuses on the detection of fake reviewers. Fake reviewers try to deliberately mislead readers by giving undeserving positive opinions to some target entities in order to promote the entities and/or by giving false negative opinions to some other entities in order to damage their reputation. As opinions on the Web are increasingly used in practice by consumers, organizations, and businesses for their decision making, detecting fake reviewers is now a critical task for many e-commerce and rating platforms.6 presented a fully unsupervised approach to detect anomalous behavior in online reviewers. They proposed a novel hierarchical approach in which they first derive distributions for key features that define reviewer behavior, and then combine these distributions into a finite mixture model. Zhang et al.7 proposed an improved label propagation algorithm with a propagation intensity and an automatic filtering mechanism to find candidate spammer groups based on the constructed reviewer relationship graph.Many scholars have investigated the detection of individual fake reviewers. For example, Kumar et al.19 proposed a framework to detect spammer groups using graph-based algorithms with five group spamming features and also proposed a new group spamming feature, group rating similarity based on the review rating score. Wang et al.20 proposed a graph-based review spammer group detection method. They introduced a top-down computing framework, namely GGSpam, to detect review spammer groups by exploiting the topological structure of the underlying reviewer graph which reveals the co-review collusiveness.Many fake reviewers collaborate to cheat review readers in practice. Therefore, fake reviewer group detection has also be investigated in the literature. For example, Thahira and SabithaThe above literature review suggests that both fake video content detection and fake reviewer detection have received a lot attention. However, the work on their combination (the detection of fake video uploaders) is still lacking in the literature. Considering the explosive growth of short videos on social media, the detection of false video uploaders has become an important practical issue. To address the research gap, we proposed a Naive Bayesian model that extracts features of fake video uploaders for detection.In this section, the extraction of features of fake video uploaders and the Naive Bayesian model are introduced, and the dataset used in the study is described.As the extracted features have considerable impact on the accuracy of machine learning models, a set of effective features is necessary to detect fake video uploaders. In this work, features that can be directly collected are called observed features, such as user name, user signature, number of following accounts, number of followers, and number of likes, while the combinations of observed features are called high-dimensional features. All these features are extracted from video uploaders to differentiate legitimate users from fake video uploaders. The following five features were proposed and used in this study:1) Followers fans (FF), which measures the followed accounts and fans of the uploaders to be detected. FF is expressed as the ratio of fans of a user to the number of accounts the user follows:21 employed the ratio of fans of a user to the number of accounts that the user follows as a feature for the detection of spammers on Twitter. In this work, we consider this ratio an effective feature for the detection of spammers, and by analogy, the ratio of fans to the number of followed accounts of a user is used as an extraction feature.2) Average like (Al). People are more likely to believe what they think is correct. For example, eating leeks can reduce hyperglycemia. Although this is false, many people still believe it because it can satisfy people's expectations for good things. Compared with legitimate users, fake video uploaders are more likely to cater to people's expectations to mislead video watchers. Al refers to the average likes an uploader gets from the videos he/she uploads, expressed as:3) Search proportion (SP). A legitimate user, when seeing a video of interest, is very likely to click the like button, visit the main page of the uploader, and follow the uploader. Therefore, the number of fans should be less than the number of users who have watched the uploaded video. When the number of people who watch the uploaded video is much smaller than the number of fans, this is an abnormal phenomenon. A fake video uploader, however, directs the users to search his/her information and become fans. This can expand his/her influence and achieve the purpose of misleading more people. The SP is the ratio of the number of views to the number of fans:4) Signature similarity (SS), which refers to the similarity between the fake-video uploader’s user name and signature. Syafii et al.22 employed similarity criteria and the entropy interval in experiments to detect spammers. Likewise, we introduced the similarity method to the detection of fake video uploaders. Legitimate users often do not pay much attention to their signatures, but fake-video uploaders will try their best to make their signature in line with their user name to convince other users of their authenticity. The cosine similarity between the user name and the signature is employed to calculate SS:5) Time difference (TD) refers to the last time a video is uploaded. Mukerjee et al.23 detected spammers by account activeness, which was measured by the gap between the first time and the last time a review was posted and achieved sound results. In this work, we employed the interval between the last time the user uploads a video and the set time to detect fake-video uploaders because legitimate users release videos from time to time, while fake-video uploaders release a video only when necessary to mislead users. The equation for TD is:Figure In the modeling process in this work, the detection of fake-video uploaders was converted into a supervised classification problem, and the model simulated the differences between video uploaders. In the model, it was assumed that the fake- video uploaders to be tested were independent from the observed features, which is a premise of the Naive Bayesian model. Meanwhile, the observed features were processed into high-dimensional features, which were then compared with the labeled data by experts, to train the Bayesian classifier. Finally, the cross-validation method was employed to construct a test set and a training set to assess the model’s detection efficiency. The naive Bayesian model was employed here for the following three reasons. First, it is fast, has low complexity and requires no complicated procedures in the detection of the fake video uploaders. Second, the features used in this study are independent from each other, and the Bayesian classifier has good performance on independent features. Third, the sample size in this study is small. The Bayesian classifier, which does not require large quantities of samples, turns out a wise option. Figure When using the Naive Bayesian model to detect fake-video uploaders, we assume that a dataset As per the Bayesian principle, we obtained:In a Naive Bayesian model, it is assumed that all video uploaders are independent from the observed features, so 24, i.e., the prior probability has a large impact on the detection accuracy of the model, the prior knowledge matrix was employed to determine the hyperparameters in the prior distribution. We assume that the probability that a fixed attribute As the Naive Bayesian model is highly dependent on the estimation of the conditional probabilityLet the prior mean and prior variance be the mean and variance of the Beta distribution and we calculate estimates for the hyperparameters The Beta distribution We assume Thus, the logarithm of the likelihood function of the sample is:The Fisher information matrix is:Then, the prior density function of Meanwhile, as Then, we can solve https://www.bilibili.com/). We collected the information about all video-uploaders who uploaded more than 3 videos about diabetes or traditional Chinese medicine (TCM). The meta-data for each video include user name, signature, the number of following accounts, the number of fans, the number of likes, play counts and the number of views. Meanwhile, two experts in the medical field were invited to label the collected video uploaders. The medical experts judged the authenticity of videos posted by video uploaders. The number of legitimate video uploaders and fake-video uploaders was balanced without reducing the validity of the research results. We randomly selected 225 fake-video uploaders and 225 legitimate uploaders to constitute the research data. tenfold cross-validation was used to split the training data and test data. That is, the 450 samples are randomly and equally divided into 10 groups. One groups is randomly selected as the test data, and the remaining 9 group is used as the training data. The averaged performance on 10 test data was used as the final performance. All experimental protocols were approved by the Ethics Committee in the School of Business, East China University of Science and Technology. All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects or if subjects are under 18, from a parent and/or legal guardian. Table The data in this study was collected from a famous video websites in China Bilibili , we also compare it with other popular baselines. The baselines chosen in this study include decision tree, random forest and Support Vector Machine (SVM). The comparison of proposed approach and other baselines are shown in Table In this work, the Naive Bayesian model was employed to classify the dataset. Figure Figure Figure Table In this work, the detection of fake-video uploaders was discussed in detail. Specifically, a dataset consisting of 450 video uploaders and feature combinations was constructed, and experts were invited to label the uploaders; then, a Naive Bayesian model for the detection of fake video uploaders was built, and five detection features were proposed. Experiments were performed on different feature combinations, and the Naive Bayesian model reached a maximum detection accuracy of 70.7%.Future research efforts can be made in the following two aspects. First, the Naive Bayesian model proposed in this study can be optimized to improve its detection accuracy. For instance, it is feasible to assign weights to the detection features as per their impact on the results and calculate the weights of different feature combinations. Second, the fake-video uploader detection results achieved in this study can be used as a basis to explore more detection methods and construct new detection models.


Short and animated story-based (SAS) videos can be an effective strategy for promoting health messages. However, health promotion strategies often motivate the rejection of health messages, a phenomenon known as reactance. In this study, we examine whether the child narrator of a SAS video  minimizes reactance to a health message about the consumption of added sugars.This study aims to determine whether our SAS intervention video attenuates reactance to the sugar message when compared with a content placebo video  and a placebo video  and determine if the child narrator is more effective at reducing reactance to the sugar message when compared with the mother narrator  or family physician narrator  of the same SAS video.This is a web-based randomized controlled trial comparing an intervention video about sugar reduction narrated by a child, the child’s mother, or the family physician with a content placebo video about sunscreen use and a placebo video about earthquakes. The primary end points are differences in the antecedents to reactance , its components (anger and negative cognition), and outcomes . We performed analysis of variance on data collected (N=4013) from participants aged 18 to 59 years who speak English and reside in the United Kingdom.P<.001). We found no evidence that the child narrator  attenuated reactance to the sugar reduction message when compared with the physician  and mother . In addition, the physician was perceived as more qualified, reliable, and having more expertise than the child (P<.001) and mother (P<.001) narrators.Between December 9 and December 11, 2020, we recruited 38.62% (1550/4013) men, 60.85% (2442/4013) women, and 0.52% (21/4013) others for our study. We found a strong causal relationship between the persuasiveness of the content promoted by the videos and the components of reactance. Compared with the placebo  and content placebo  videos, the intervention videos  aroused higher levels of reactance to the message content (Although children may be perceived as nonthreatening messengers, we found no evidence that a child narrator attenuated reactance to a SAS video about sugar consumption when compared with a physician. Furthermore, our intervention videos, with well-intended goals toward audience health awareness, aroused higher levels of reactance when compared with the placebo videos. Our results highlight the challenges in developing effective interventions to promote persuasive health messages.German Clinical Trials Registry DRKS00022340; https://tinyurl.com/mr8dfenaRR2-10.2196/25343 Comparisons of digital behavior change interventions with traditional face-to-face interventions indicate that web-based health promotion is generally at least as effective as conventional approaches and has several advantages, such as low cost, feasibility, and scalability ,2. Existrequired ,6, and crequired . To furtrequired . Howeverrequired .The theory of reactance consists of 4 elements: (1) perceived freedom, which individuals possess insofar as they are aware of it and can enact it; (2) threat to freedom, when pressure is exerted that makes it difficult to enact that freedom; (3) reactance, which refers to the motivation to reestablish the threatened freedom; and (4) direct restoration, which involves the freedom of the individual to perform the forbidden behavior . ReactanIn this study, we produced a SAS video with a message about reducing the consumption of added sugars. Designed for a diverse and global audience, the animated video uses a narrative based structure to minimize reactance to the sugar message. For our first hypothesis, we assess if our narrative-based, animated video is effective at attenuating reactance to a persuasive health message.We hypothesize that there is a causal pathway between exposure to a SAS video about sugar intake reduction and reactance, its antecedents, and outcomes.Hypothesis 1While designing the video, we considered the degree of social authority that should be assigned to the narrator. First, we selected the traditional role of a physician who has high social authority. Although health experts and physicians are often used to promote health messages -19, prevWe hypothesize that a SAS video about sugar consumption narrated by a child  will arouse less reactance when compared with a video narrated by the child’s mother  or the family doctor .Hypothesis 2We used a randomized controlled trial (RCT) to measure the causal effect of social authority on reactance to a short, animated video about sugar intake reduction. The randomization ensures that there are no systematic differences introduced at the enrollment stage, which may lead to potential bias. In addition, an innovative feature of our study is the use of 2 placebo groups, which enabled us to isolate the health awareness and content effects of the intervention video.arms 1-3), a content placebo arm (arm 4), and a placebo arm (arm 5). The participants in each intervention arm watched the same sugar video narrated by a child , the child’s mother , or the physician . Arm 4 watched a content placebo video with a health message about tanning and sunscreen (no sugar message), and arm 5 watched a placebo video about earthquakes .This study is a web-based RCT with 3 intervention arms (We used the Prolific platform (Prolific Academic Ltd)  to recruParticipants were asked basic demographic questions about their age, sex, and highest education level. The Gorilla algorithm then randomly assigned participants at a 1:1:1:1:1 ratio to the trial arms. The participants watched 1 video from start to finish.arms 1-3) is a SAS video about sugar intake reduction developed by our coauthor (MA) at the Stanford School of Medicine [The intervention video  affective (anger) and (2) cognitive (negative cognition) . TherefoThis message makes me feel irritated.This message makes me feel annoyed.This message makes me feel aggravated.This message makes me feel angry.Negative cognition was measured using the scale from Quick et al  with theThe thoughts I had while watching this video were mostly unfavorable.The thoughts I had while watching this video were mostly negative.The thoughts I had while watching this video were mostly bad.Source appraisal, also called source derogation , refers Attitude toward message advocacy was measured using the following 4 items from Shen :I agree with what the message recommends.I support what the message advocates.I am in favor of the position in the message.I endorse the claims made in the message.We calculated the sample size needed for pairwise comparisons among the 5 groups using the analysis of variance. Our calculations resulted in a sample size of n=769 per group . For a 5Descriptive statistics were used to obtain means and SDs of the demographic data of the sample, which included age, sex, and education status. We used analysis of variance to estimate the difference in the means of the outcome measures between the sugar intervention videos, the content placebo video, and the placebo video. The significance level α was set at .05. Post hoc tests with Tukey range method were used to create CIs for all pairwise differences between the means while controlling for family error rate. The placebo arm was chosen as the reference group, as the placebo video did not include any content related to sugar or health and, therefore, did not have any persuasive intent. All statistical analyses were performed using the statistical software R .The data were collected and stored on the Gorilla platform. The study investigators own and have complete control of the research data, which can be accessed at any time. For statistical analysis, the data were downloaded and stored safely in a computing system maintained by the Heidelberg University.Ethical approval was obtained from the Heidelberg University’s ethics committee (Universität Heidelberg Ethikkommission der Medizinische Fakultät) on March 18, 2020, protocol: S-088/2020.Between December 9, 2020, and December 11, 2020, a total of 4159 participants from the United Kingdom were recruited for the trial. After recruitment, 0.26% (11/4159) participants were lost and another 3.24% (135/4159) participants were dropped, as they did not complete the study for either technical reasons  or other unknown reasons. Of the recruited sample, 96.48% (4013/4159) completed the trial and were included in the final analysis . Table 1P=.92, which did not vary significantly between the 5 arms. When comparing the means scores for threat to freedom, the analysis revealed a significant difference between the 5 groups (P<.001). Furthermore, the pairwise comparisons for the threat level, using a Bonferroni correction, indicated that participants in the content placebo and intervention arms reported higher threat to freedom when compared with the placebo arm  but not in the child arm (P=.52). Although the threat level in the child arm  was slightly higher than in the doctor arm , the difference was not found to be significant (P=.21).Trait reactance proneness and threat to freedom are antecedents to reactance. Higher scores on trait proneness and threat to freedom scales indicate higher proneness to reactance and greater perceived threat, respectively. As shown in  P<.001; . When coP<.001). P<.001). However, there was no statistically significant difference between intervention arms, suggesting that participants experienced the same amount of reactance when watching the video narrated by either the child, mother, or physician. When considering anger and negative cognition scales separately, the analysis revealed similar outcomes, where all arms were significantly different when compared with the placebo arm . As seen in P<.001) as well as placebo and intervention arms (<.001), suggesting that participants in the placebo arm had a more favorable evaluation of the video narrator than the participants in other study arms. However, there was no significant difference in the appraisal of the source between the content placebo and intervention arms (P=.25). When comparing intervention arms separately, participants who watched the video narrated by the physician had higher scores, that is, a more positive evaluation of the source, than the participants who watched videos narrated by the child (P<.001) or the mother  and physician (P=.03). In addition, unlike the narrators in the content placebo (P<.001), mother (P<.001), and doctor (P<.001) arms, the narrator in the child arm was found to be as smart as the narrator in the placebo arm (P=.89). However, all 3 intervention arms (P<.001) and the content placebo arm (P=.003) scored significantly lower on the unknowledgeable or knowledgeable item in comparison with the placebo arm. There were no significant differences between intervention arms on this item. The placebo arm narrator was also seen to be more informed than the narrators in the content placebo (P=.04) and intervention arms . When comparing the intervention arms with each other, all narrators were considered to be equally informed and intelligent. However, the participants in the doctor arm rated the message source to be more qualified (P<.001), reliable (P<.001 and P=.02), and expert (P<.001) than those in the child and mother arms, respectively. Furthermore, the mother narrator was also seen as more qualified (P<.001) and expert (P<.001) than the child narrator, although the same difference was not found for the unreliable or reliable item  is the major component of our research question. As seen in  P<.001; . The narm P=.25; .P<.001), pairwise comparisons confirmed that participants in the content placebo and intervention arms had significantly more positive attitudes toward the message when compared with participants in the placebo arm . As the message in all 3 intervention videos was the same, there were no statistically significant differences between the child, mother, and doctor arms  and a placebo video about earthquakes . With respect to our first hypothesis, we therefore demonstrate a causal relationship between exposure to a SAS video and the antecedents and components of reactance. In particular, our results show that compared with the placebo video, the content placebo video was perceived as more threatening, while the intervention videos were seen as the most threatening. In addition, participants who watched the intervention videos experienced significantly higher levels of anger and negative cognition than those in the placebo and content placebo arms. Although psychological reactance has not been fully tested in the context of digital health promotion, this study contributes evidence to the existing literature on persuasion and reactance .One plausible explanation for the higher levels of reactance to the intervention videos may be rooted in the part that describes the death of the child’s father, which is attributed to the regular consumption of soda drinks. Some scholars have argued that health promotion messages can be effective when they increase people’s fear or concern about risky behaviors that can threaten their health ,41. In oIn this study, we focused on 1 modifiable component—the social authority of the narrator—and its effect on reactance to a message about reducing sugar intake. Initially, we assumed that a child narrator would be a more persuasive messenger and would be less likely to arouse reactance when compared with the adult narrators (mother and physician), as the audience may view the child as nonthreatening and lacking vested interest. Contrary to our expectations, we found no evidence that the child narrator attenuated reactance when compared with the same intervention videos narrated by the mother and the family physician. Therefore, we fail to reject the null hypothesis of H2 in that there were no significant differences between the child and the mother and the child and the physician with respect to the threat to freedom, anger, negative cognition, and the combination of the last 2 components (state reactance).However, one of the few significant differences that we observed was in the source appraisal component, which plays a critical role in this context. Our results show that the physician narrator was perceived to be more qualified and reliable and has more expertise than the child and the mother narrators. This is an expected finding as doctors are generally seen as experts in the health field and reliable sources of accurate and valid information. Earlier studies have shown that message recipients tend to be more motivated to change and persuaded by an expert rather than a non–expert message source ,46. HoweAnother minor yet interesting finding was that the participants evaluated the child source as smarter than the mother and the physician. A possible explanation for this difference might lie in the fact that participants, who were exclusively adults, were not willing to call the child narrator stupid owing to potential social desirability bias, which is described as the tendency of research participants to give socially desirable responses instead of honest responses . As we cthreat to freedom and trait proneness to reactance. This means that design differences such as animation style, background shapes or colors, and target audience are not hypothesized to arouse reactance and hence are unlikely to account for differences in reactance. Nevertheless, we acknowledge that the sugar intervention video was narrated by a female voice, and the placebo videos were narrated by male voices. There is evidence that men are perceived as more credible than women, and women are perceived as more trustworthy than men [We do not believe that design differences between the intervention and placebo videos can account for differences in reactance across the trial arms. This is because we were careful to select placebo videos that were similar to the sugar intervention video, such that all videos were short (3.42 minutes), animated, story-based, and in English. The only systematic difference among the videos was the content of the narrated messages , which were the trial arms. Importantly, as we explain in than men . To the The findings of this study make an important contribution to the literature on digital health promotion. Several studies that focused on added sugar reduction have used nonanimated, web-based videos, such as a puppet show , expert This study had several strengths. First, we used an RCT design, which allowed us to eliminate any potential sources of bias by randomization. Randomization ensures that there are no systematic differences introduced at the enrollment stage. Second, the web-based nature of our experiment enabled us to reach a large sample size, which ensured the quality and reliability of the sample. The use of content placebo and placebo videos is also an innovative feature of our study, which enabled us to isolate the health awareness effect and content effect of the intervention video. We are not aware of any previous study that had such a large sample size and used a similar experimental approach to examine the social authority of the health message source. Once the design of the SAS video that we created is further examined and modified, it can be used for larger audiences on social media and other educational sources, as it is short, simple, and quickly scalable.Our study has several limitations. First, Prolific uses convenience sampling to recruit participants, so that study places are filled on a first-come, first-serve basis. Thus, a considerable portion of responses could come from participants who are on the web at the time a study is launched or immediately afterward. Rapid-responder bias may be an issue if the required sample is very small or very specific. However, our study was general  and ran continuously for 3 consecutive days. In addition, Prolific has several mechanisms to reduce rapid-responder bias and equally distribute study places among active participants. For example, when a study is launched, Prolific sends an email to a random subset of all eligible participants every 48 hours until the sample size is reached. Therefore, it is unlikely that rapid-responder bias will have significantly affected our results. Second, our study had a sampling bias toward women  and participants with higher education  had a bachelor’s degree or higher). Similar sample distributions have been reported in several web-based studies . It has A third limitation is that the Prolific participants may have chosen to participate in our study because of the sugar-related topic. However, it is unlikely that this type of selection bias would have considerably affected our results for one important reason: randomization. For our RCT, we randomized participants to either the sugar intervention video, the content placebo video, or the placebo video, so that any topic-specific selection bias would have been uniformly distributed across the trial arms. Fourth, it is possible that participants may have been motivated by financial rewards, which could introduce a selection bias. Again, this form of bias would have been equally distributed across the trial arms because of our randomized design. In addition, financial rewards are standard for web-based studies and are acceptable when the research is not focused on a specific disease or treatment and does not involve potential risks . The stuTaken together, the findings of this study demonstrate that the content of health messages may have a greater impact on reactance than the source of the message and its authority. Moreover, the use of SAS videos on social media can facilitate public health efforts to promote healthy behaviors to a larger audience. The experimental design and the use of multiple placebo groups in this study present novel approaches for further investigation in this area. It is essential to gain a better understanding of the unique ways in which messages about healthy behaviors are processed and the resulting emotions and intentions to advance health communication strategies worldwide.


Background: Elevated intrapartum temperature has been widely proven to be associated with adverse clinical outcomes in both mothers and neonates. Histological chorioamnionitis (HCA), the inflammation of chorion and amniotic membranes, is commonly observed in those with elevated intrapartum temperature. Thus, we aimed to explore whether the combination of HCA would further affect the pregnancy outcomes in those with intrapartum temperature ≥ 37.5°C.Methods: This retrospective cohort study was conducted at the International Peace Maternity and Child Health Hospital (IPMCH), including all full-term women with intrapartum temperature ≥ 37.5°C from Jan 2017 to Jan 2019. Patients were divided in to HCA group or control group according to placental pathology results, and we used 1:1 propensity score matching (PSM) to reduce the effects of potential confounding factors between the two groups. Univariate and multivariable logistic regression were used to identify the association between HCA and different adverse maternal and neonatal outcomes.Results: We formed a propensity-score matched cohort containing 464 women in each group. Higher positive rate of mycoplasma  was found in the vaginal secretion culture of women in the HCA group. After adjusting for various baseline clinical characteristics, women with HCA were more likely to end their delivery by cesarean section , and puerperal morbidity  as well as prolonged hospitalization  were more likely to be observed in the HCA group. The existence of HCA might also be associated with neonatal sepsis  and NICU admission  in newborns. In the study on the impact of different stages of HCA, we found that both maternal and neonatal outcomes would not be affected by mild HCA (stage I), while HCA of stage III was associated with increased need for neonatal respiratory support and elevated likelihood of prolonged hospitalization in neonates.Conclusions: Elevated intrapartum temperature complicated by HCA might be related to the elevated occurrence of several adverse maternal and neonatal outcomes, except those with HCA of stage I. Advanced HCA stage correlated with a worse prognosis. Elevation of body temperature is a common phenomenon during labor, which can be caused by both infectious and noninfectious factors  , 2. Most9/L)  . HCA, al9/L) , 12. It 9/L) , and cou9/L) –17.Due to the strong association between HCA and preterm birth, most of the current studies on the effect of HCA on pregnancy outcomes were carried out in a preterm population, while there are limited studies focusing on pregnancy outcomes at term. At the same time, although the separate effects of elevated intrapartum temperature and HCA on maternal and neonatal outcomes have been widely confirmed, few studies have compared the differences between elevated intrapartum temperature alone and those complicated by HCA. Therefore, we designed this retrospective cohort study to explore whether the combination of HCA will further worsen the prognosis of mothers and newborns in full-term women with elevated intrapartum temperature, in order to provide scientific support for their clinical management and treatment.This single-center, retrospective, 1:1 matched cohort study was conducted from Jan 2017 to Jan 2019, at the International Peace Maternity and Child Health Hospital (IPMCH), which is a tertiary specialized hospital of obstetrics and gynecology and accounts for 10–20% of births in Shanghai, China. We included all women with a record of elevated temperature (at least one temperature record of ≥37.5°C) after entering active labor . Exclusion criteria included preterm birth (<37 weeks), multiple pregnancy, confirmed infection outside the uterine cavity, trial of labor after cesarean section (TOLAC), fetal structural or chromosomal abnormalities, and missing or untraceable clinical data.www.medresman.org), and the registration number is ChiCTR2000038345. Ethical approval was given by the Institutional Review Board of the IMPCH (No. GKLW 2013-51).All the cohort data are available at the Res Man Manager of Chinese Clinical Trial Registry , infiltration of the chorionic membrane (stage II), and infiltration of both the chorionic and amniotic membranes (stage III) .For all women, complete blood count and C-reactive protein (CRP) levels were measured after the detection of an elevated temperature. Sampling of vaginal secretions should also be completed at that time, and samples should be sent for routine culture and anaerobic culture as soon as possible. For their newborns, complete blood count, CRP levels and procalcitonin (PCT) levels were routinely tested on the first day after delivery, and for those admitted to NICU, blood culture is routinely performed.All data were collected from the electronic medical record System. The information collected for each woman included socio-demographic characteristics, reproductive history, antepartum and intrapartum factors, the results of laboratory tests performed at the time of elevated temperature, and pregnancy outcomes. Data collected for each newborn included birth records, the results of laboratory tests performed on the first day after delivery and neonatal complications.Adverse maternal outcomes were as follows: assisted vaginal delivery (forceps or vacuum), cesarean section, placental adhesion, cervix or vagina laceration, postpartum hemorrhage, puerperal morbidity, late postpartum hemorrhage, admittance to intensive care unit (ICU), and hospitalization time (from entering active labor to discharge) ≥7 days. Puerperal morbidity means after 24 h and within 10 days after childbirth, the oral temperature reached 38°C for at least twice with an intervals of 4 h, which is mostly caused by puerperal infection.Adverse neonatal outcomes included 5-min Apgar score <7, small for gestational age (SGA), birth trauma , neonatal jaundice , neurolop-values before and after PSM of each variable were calculated, and a SMD of <10% along with a p-value more than 0.05 indicated a relatively small imbalance.To reduce the effects of potential confounding factors between the two groups, we first screened out those who met the diagnosis of CCA according to the Gibbs criteria. Secondly, a 1:1 propensity score matching (PSM) was used to identify the rest non-CCA women with similar baseline clinical characteristics, including maternal age, pre-pregnancy BMI, educational levels, parity, gestational age, mode of conception, gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, hypothyroidism, premature rupture of membranes (PROM), duration from rupture of membranes (ROM) to delivery, presence of meconium-stained amniotic fluid, maximal intrapartum temperature, duration of fever, intrapartum antibiotic use, and fetal sex. All the above variables were entered into a multivariate logistic regression model to estimate propensity scores, and matching was performed by using a 1:1 nearest neighbor matching algorithm with a caliper width equal to 0.1 without replacement. Standardized mean differences (SMDs) and t-tests or Mann-Whitney U tests, and categorical data were compared by using either chi-Squared tests or Fisher's exact test. To identify the association between HCA and different adverse outcomes, univariate and multivariable logistic regression analyses were used, and odds ratios (ORs) were adjusted for all variables involved in PSM. Sensitivity analysis and subgroup analysis were used to assess the difference in certain maternal and neonatal outcomes in each subgroup between the matched two groups to identify potential bias. P for interaction <0.1 was considered to indicate significant interactions in the subgroups. A two-sided p-value of <0.05 was considered statistically significant. All statistical analyses were performed by using SPSS  and R statistical software version 4.0.2 .The Kolmogorov–Smirnov test was used to assess the normal distribution. Normally distributed variables are expressed as mean ± standard deviation (SD), and non-normally distributed variables are expressed as median . Continuous data were compared by using either Student's n = 503) or without HCA (n = 614). Finally, we constructed a propensity-score-matched population of 464 women in each group , PROM , and intrapartum temperature <38°C  in the HCA group was higher than that in the control group. After matching, the p-values of all variables were > 0.05, and the SMD of all variables were <10%, indicating no significant differences between the two groups.The comparisons of the clinical features between the two groups before and after PSM were shown in Univariate and multivariable logistic regression analyses were used to assess adverse maternal outcomes . CompareAdverse neonatal outcomes were also assessed by using univariate and multivariable logistic regression analyses. After adjusting for all baseline clinical characteristics mentioned in PSM, we found that HCA seemed to be associated with admittance to NICU  and neonatal sepsis . No differences were found between the two groups in the remaining adverse outcomes .9/L, p = 0.019). Neutrophil count, CRP level and PCT level showed no significant differences between the two groups (Neonates of women with HCA had higher level of WBC count (28.10 vs. 26.80 × 10o groups .p for interaction = 0.054] in comparison to those under 35 years old.p for interaction = 0.096].p = 0.007) in mothers and higher propotion of neonatal sepsis  in newborns.Since the standard for intrapartum hyperthermia is temperature ≥38°C, we further analyzed that in the subgroup of intrapartum temperature ≥38°C, whether HCA would lead to adverse pregnancy outcomes. The results are shown in p = 0.027) and cervix or vagina laceration . And the probability of neonatal sepsis was elevated in the CCA group .Meanwhile, there were another 180 women who met the diagnostic criteria of CCA in our study population, thus, we compared the differences in pregnancy outcomes between the CCA group and the control group (without PSM). The results are shown in According to the results of placental pathology, 139, 209 and 116 women were evaluated as HCA stage I, stage II and stage III, respectively. After adjusting for all baseline clinical characteristics (those used for PSM), we did not find an association between adverse maternal outcomes and HCA stage I. Women of HCA stage II were more likely to develop puerperal morbidity . Those with HCA stage III showed higher likelihood of cesarean section  and prolonged hospitalization  .Compared with those in the control group, neonates of women with HCA stage I were less likely to develop neonatal jaundice  and showed a lower likelihood of prolonged hospitalization . As for neonates in the HCA stage II group, higher likelihood of neonatal sepsis  and admittance to NICU  were observed. And those in the HCA stage III group showed increased need for respiratory support , and elevated proportion of neonatal sepsis , admittance to NICU  and prolonged hospitalization  .The incidence of elevated intrapartum temperature was 4.1%  in our study, and the total presence of HCA was 44.5%  among them. In this study, we not only evaluated the differences in the pregnancy outcomes of women with elevated intrapartum temperature complicated by HCA and those with intrapartum temperature ≥37.5°C alone, but also the impacts of different HCA stages.After PSM and adjusting for various baseline clinical characteristics, we found that women with elevated intrapartum temperature complicated by HCA were more likely to end up with cesarean section, and seemed to have a longer hospitalization time. At the same time, this group of women seemed to have a higher proportion of puerperal morbidity. But further study failed to find an association between HCA stage I and adverse maternal outcomes. We also found an elevated proportion of neonatal sepsis and NICU admission in those with intrapartum temperature ≥37.5°C complicated by HCA. Further analysis suggested that HCA stage II was associated with neonatal sepsis and NICU admission. And for newborns in the HCA stage III group, in addition to the above two outcomes, prolonged hospitalization was observed and the need for respiratory support also increased.The results of our study were generally in agreement with previous studies of similar design , 20. In p for interaction = 0.096]. But at the same time, we cannot ignore the fact that there might be differences in the NICU admission standards between different countries and even between different hospitals. Moreover, since it is a retrospective observational study, we are unable to conclude that the use of antibiotics during labor could improve pregnancy outcomes, and a prospective study is necessary to confirm this result.Both the overall analysis and the subgroup analysis indicated that HCA was associated with neonatal sepsis, especially in those with HCA of advanced stage (II-III), which is consistent with the results of many previous studies carried out in preterm infants . AugmentAt the same time, choosing the right type of antibiotic is very important for the prevention of maternal postpartum infection and neonatal infection. As the drug susceptibility test is relatively time-consuming, clinicians usually use antibiotics empirically, and adjust the type of antibiotics according to its effect and the results of the drug susceptibility test later. Our study found that women with HCA had a higher positive rate of mycoplasma in vaginal secretion culture, suggesting that this microorganism might be associated with HCA. This is consistent with previous studies on pathogenic bacteria of chorioamnionitis , 24. HowOur study has several strengths. First, to our knowledge, this is one of the few studies that compared the maternal and neonatal outcomes between elevated intrapartum temperature alone and those complicated by HCA. Second, this is a single-center cohort study, so all women and newborns received unified diagnostic criteria and clinical management strategies, and almost all those with hyperthermia underwent placental pathology examination, which ensured the integrity of the retrospective cohort. Meanwhile, we included all full-term single pregnancy women with intrapartum temperature ≥37.5°C after entering active labor during the study period, and only a very small number of women were excluded from our study, which mainly because of incomplete data. Therefore, our study population was almost unselected, which might increase the universality of the results to a certain extent. Additionally, previous study of Haddad et al.  found thThere are still some limitations in this study. First, although we included as many confounding factors that might affect pregnancy outcomes as possible, other unmeasured confounding factors might exist and cause bias in the propensity-score matched population. Second, we did not carry out neonate follow-up after hospital discharge, so the long-term neonatal outcomes cannot be traced.In conclusion, the presence of HCA can further worsen the maternal and neonatal outcomes of full-term women with elevated intrapartum temperature. But women with HCA of stage I shared similar pregnancy outcomes with the control group.The original contributions generated in the study are included in the article/The studies involving human participants were reviewed and approved by The Ethic Committee of International Peace Maternity and Child Health Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.YG collected the data, performed the statistical analysis and drafted the manuscript. CZ assisted with the statistical analyses. YC conceptualized and designed the study and was responsible for data collection. HH conceptualized and designed the study, revised the manuscript and gave the final approval of the version to be submitted. 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.


Chronic obstructive pulmonary disease (COPD) is a recognized risk factor for malnutrition. The European Respiratory Society (ERS) statement included nutritional status assessment and dietary intervention as essential components of comprehensive management in subjects with COPD. According to the GLIM algorithm, the first step in diagnosing malnutrition is risk screening with a validated tool. Our study aimed to assess the diagnostic performance of three screening tools  used in the GLIM algorithm in older patients with COPD. Additionally, we evaluated the agreement between these tools in the diagnostics of malnutrition. We performed a cross-sectional study of 124 patients aged at least 60 years with COPD diagnosed, based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We assessed the participants’ nutritional status with the three examined screening questionnaires . Regardless of their results, we performed full malnutrition diagnostics following the GLIM algorithm in all subjects. The proportion of malnourished participants varied from 18.5% for the MUST questionnaire to 27.4% for the MNA-SF and 57.3% for the NRS-2002 score. Based on the GLIM criteria, malnutrition was diagnosed in 48 subjects (38.7%). All assessed questionnaires had an unsatisfactory sensitivity against the GLIM criteria for malnutrition: it was fair (58.3%) for the MNA-SF tool and poor for the MUST and NRS-2002 questionnaires (47.9% for both questionnaires). Considering the negative health consequences of malnutrition, a full diagnostic including GLIM etiologic and phenotypic criteria should be recommended in all elderly patients with COPD, regardless of the screening results. Disease-related malnutrition is found in 20–50% of hospitalized subjects. Chronic obstructive pulmonary disease (COPD) is a recognized risk factor for malnutrition ,2. The EIn 2018, experts from the Global Leadership Initiative on Malnutrition (GLIM) launched new diagnostic criteria for malnutrition, including two etiologic and three phenotypic criteria. The etiologic criteria were (1) reduced food intake or assimilation and (2) disease burden/inflammatory condition. The phenotypic criteria included not only low body mass index (BMI) and non-volitional weight loss but also reduced muscle mass reflecting changes in body composition .According to the GLIM algorithm, the first step in diagnosing malnutrition is risk screening with a validated tool. The Mini Nutritional Assessment—Short Form (MNA-SF) is among the most commonly used screening tools in older adults ,6,7. OthOur study aimed to assess the diagnostic performance of three screening tools  used in the GLIM algorithm in older patients with COPD. Additionally, we evaluated the agreement between these tools in the diagnostics of malnutrition. Our study is the first such analysis in subjects with COPD to the best of our knowledge.We performed a cross-sectional study in patients aged at least 60 years (age range: 60–86 years) with a COPD diagnosis based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD)  criteriaThe study was conducted under the Declaration of Helsinki. Its protocol was approved by the Bioethical Committee of the Poznan University Medical Sciences, Poland .We took the results of the respiratory functional tests for our analysis from the hospital database. We assessed participants’ nutritional status with the three examined screening questionnaires . Regardless of their results, we performed full malnutrition diagnostics following the GLIM algorithm in all subjects. Additionally, we performed diagnostics for sarcopenia according to the European Working Group on Sarcopenia in Older People (EWGSOP2) recommendations . Data onGOLD 1 (mild obturation) FEV1 ≥ 80%GOLD 2 (moderate obturation) FEV1 ≥ 50%GOLD 3 (severe obturation) FEV1 ≥ 30%GOLD 4 (very severe obturation) FEV1 < 30%All subjects underwent spirometry . Based on the GOLD recommendations, subjects with FEV1/FVC  below 70 were diagnosed with COPD . The sevAs there were few subjects in group GOLD 1 and GOLD 4, pooled categories GOLD1+GOLD2 (GOLD1+2) and GOLD3+GOLD4 (GOLD3+4) were used in further analysis.Patients’ cognitive performance was assessed with the Abbreviated Mental Test Score (AMTS). It consists of ten items scoring one point each. Subjects who scored <7 (indicating significant cognitive dysfunction) were excluded from our analysis .The assessment of nutritional status  was performed by one person (a certified dietician).The anthropometric assessment  was performed with the dual frequency InBody 120 analyzer . The device uses 8 adhesive electrodes to measure segmental impedance . Subjects were asked to take off clothing and jewellery, stand barefoot on electrodes and grasp the hand electrodes. The measurements were taken after at least 2 h fasting.The Mini Nutritional Assessment—Short Form questionnaire contains six items: decrease in food intake, weight loss during the preceding three months, mobility, psychological stress or acute disease during the preceding three months, neuropsychological problems, and BMI. The maximum score is 14, and a score of fewer than 12 points indicates a risk of malnutrition .The MUST questionnaire contains BMI, percentage unplanned weight loss in the preceding 3–6 months, and no nutritional intake for more than five days owing to an acute illness. The maximum score is 6, and a score of 1 or more indicates a risk of malnutrition .The NRS-2002 questionnaire refers to two aspects of malnutrition: deterioration of nutritional status  and increased requirements due to acute and chronic illnesses. Subjects aged 70 and more are given an additional 1 point. The maximum score is 7, and a score ≥3 indicates a risk of malnutrition and the necessity for nutritional intervention .The following phenotypic GLIM criteria were used:2 in persons aged below 70 years and <22 kg/m2 in subjects aged 70 or more years1. Low BMI: <20 kg/m2)). Low muscle mass (LMM) was diagnosed in subjects with an ALM index below the previously estimated Polish cut-off points (5.6 kg/m2 in women and 7.4 kg/m2 in men) [2. Low muscle mass was diagnosed based on the bioimpedance analysis of the body composition. We used appendicular lean mass (ALM) to calculate the ALM index (a ratio of ALM (in kg) to squared body height (in m in men) .3. Unintended weight loss >5% body mass in the past six months, or >10% in a period longer than six months.We assumed that COPD fulfils the etiologic criterion of chronic disease with severe systemic inflammation. Consequently, we diagnosed malnutrition in all participants with at least one phenotypic criterion.We measured upper limb muscle strength with a hand dynamometer  in all participants. We assumed the values <16 kg in women and <27 kg in men indicate low upper limb muscle strength. Additionally, we assessed lower limb strength with the chair stand test (CST). Low lower limb muscle strength was diagnosed in subjects with the CST time >15 s. Participants with low upper and/or lower limb strength were classified as at risk of sarcopenia .The diagnosis of sarcopenia in patients at risk was confirmed based on the ALM index.n) and percentage (%).Continuous data were described with mean and standard deviation, and categorical variables with numbers —for samples with normal distribution and homogeneity of variance;-Kruskal–Wallis test—for samples not fulfilling the homogeneity of variance criterion.The differences between the four subgroups were assessed with the following tests:-t-test—for samples with normal distribution and homogeneity of variance;Student -Mann–Whitney U test—for samples not following a normal distribution.The differences between the two subgroups were assessed with:Categorical data were evaluated with Pearson’s chi-squared test.In order to assess diagnostic performance of the MNA-SF, MUST, and NRS-2002 questionnaires against the GLIM criteria, we calculated sensitivity and specificity , positive predictive value (PPV), negative predictive value (NPV), area under the ROC curve  and kappa coefficient  .p-value < 0.05 was considered statistically significant. Statistical analyses were performed with STATISTICA 10 PL .We included 124 subjects aged 60 years or more (mean age: 69.4 ± 6.1 years) admitted to the Pulmonary Rehabilitation Ward (Great Poland Centre of Pulmonology and Thoracic Surgery). The length of stay on the ward was 21 days in all patients. Men constituted 59.7% of the study sample. All participants were of Polish nationality. They were taking from 1 to 20 prescribed medications (mean 8.3). Seventy-nine percent of subjects had vocational or secondary education. Nearly two-thirds of the patients (64.3%) were living in urban areas, and 78.6% of them had households consisting of at least two persons. In addition to COPD, most participants had other medical conditions. The most frequent comorbidities were hypertension (62.9%), diabetes (30.6%), cardiovascular disease (29.0%) and dyslipidemia (22.6%).p = 0.0047) than individuals with mild to moderate obstruction. They also had lower weight (p = 0.0048), BMI (p = 0.0046), skeletal muscle mass (p = 0.0071), and free fat mass (p = 0.0117) as compared to the GOLD1+2 group.p = 0.0318) and BMI (p = 0.0249). Other anthropometric parameters and functional test results did not differ between the individuals with malnutrition diagnosed with various questionnaires. The prevalence of sarcopenia was similar in all four groups, and all subjects with sarcopenia fulfilled the GLIM criteria for malnutrition.Volkert et al.  have recDespite the general acceptance of the GLIM diagnostic criteria for malnutrition published in 2018, the use of screening tools in the first step of diagnostics is the subject of much controversy ,32,33. ODávalos-Yerovi et al.  have sugn = 42) had a negative screening result with the MNA-SF [The screening questionnaires assessed in our study have been previously examined in other populations. Sanchez-Rodriguez et al.  observede MNA-SF .n = 152, mean age 78.3 ± 7.6 years). Similarly to our results, the MUST questionnaire had a higher diagnostic performance with an accuracy of 73.7% (MUST accuracy in our study was 79.8%) as compared to NRS-2002 with the accuracy of 62.5% (41.1% in our study); of note, none of the tools had good diagnostic performance [These findings ,32 questformance . It shouOverlooking malnutrition, particularly in elderly individuals, may lead to sarcopenia. The concomitance of these conditions is defined as malnutrition-sarcopenia syndrome (MSS). Hu et al. , in a stThere are some limitations to our study. As an objective assessment of weight changes within the past 12 months was impossible, we based on patients’ declarations. Similarly, information about the reduction in dietary intake was not derived on calculations of nutritional demand and assessment with a diary but was declarative only. This limitation did not influence the prevalence of malnutrition according to the GLIM criteria, as COPD in all subjects fulfilled the other etiologic criterion (any disease burden or inflammatory condition). As our study has a cross-sectional design, any causal conclusion cannot be drawn. The trial was conducted in one district, so its findings could not be generalized.To the best of our knowledge, our study was the first attempt to assess the relationship between malnutrition diagnosed with various screening tools and the severity of COPD in elderly subjects. It fills a gap in the literature and emphasizes the importance of a full diagnostic of malnutrition in these patients.Our study demonstrates unsatisfactory sensitivity against the GLIM criteria of the MNA-SF, MUST and NRS-2002 questionnaires. The use of various screening questionnaires in the first step of the GLIM algorithm in elderly subjects with COPD yielded conflicting results. These findings have important clinical implications. Considering the negative health consequences of malnutrition, a full diagnostic including GLIM etiologic and phenotypic criteria should be recommended in all elderly patients with COPD, regardless of the screening results.