The effects of behavioral addiction to video games has received increasing attention in the literature, given increased use intensity among subgroups of video game players.This study seeks to empirically determine the relationship between intensity of video gaming and hedonic experience of the player.We conducted a survey of 835 individuals who regularly play video games to determine the relationship between intensity of use and hedonic experience. We divided the sample into quartiles by self-reported video game addictive symptom level  and conducted polynomial regressions separately for each quartile.P=.005) and significantly positive (P=.004), respectively.We found that the higher video game addictive symptom level groups experienced a U-shaped (curvilinear) relationship between hedonic experience and intensity of play, whereas groups with lower video game addictive symptom levels exhibited no such relationship. The coefficients for the highest addictive symptom level group (quartile 4) for marginal effects for hours played per week and hours played per week squared were significantly negative (Our results are consistent with sensitization and tolerance theories, which suggest that high-symptom groups experience frustration and disappointment until they achieve excessive dopamine release, at which point their hedonic experience is expected to improve with additional play. Conversely, low-symptom groups experience no such fall-and-rise pattern. This result is consistent with the outcome that members of the latter group play the game for the direct experience, such that their hedonic experience is more directly related to events occurring in the game than to the increasingly elusive pursuit of excessive dopamine release. We also find that high-symptom groups spend substantially more time and money to support video game use and are much more likely to engage in video game use at the expense of other important activities, such as working, sleeping, and eating. In our current technological era, video games have become pervasive in the United States and many other developed countries. This form of gaming has high prevalence among people of different ages, socioeconomic levels, and cultural environments. The Entertainment Software Association (ESA) reports that “we are living in the golden age of video games, and video game players are thriving” . In 2020Video games are not only pervasive in many areas but also potent enough to provide hedonic experiences to some players. The pursuit of this hedonic experience has caused many players to make video games an essential routine in their lives. Video games have become a booming component of the entertainment industry; however, some health issues have been associated with them . StudiesMany studies have been conducted on the psychological components of video games; others have concentrated on the “emotional states of the game player”  and the The present study examines tolerance in the context of video games. Previous work has shown that excessive players of video games tend to be more reward dependent (for dopamine) . PreviouWithin the context of these prior research findings, we hypothesized that video game players who show addictive symptoms would experience a U-shaped relationship between hedonic experience in video games and video game hours played per week. If this relationship was present, then we would observe a significant negative association with video games and a significant positive association with video games squared, as in a standard polynomial regression analysis. Sensitization would increase the likelihood that such video game players would initiate play even when it does not improve quality of life . As these types of video game players play additional hours on average, we expect that an individual’s hedonic response to the game will decrease with play intensity up to the point of excessive release of target levels of dopamine. Once video game play is initiated, we expect such users to be increasingly frustrated until they attain excessive dopamine release, due primarily to tolerance. Upon attainment of this target, however, we expect hedonic response will increase in play intensity. For video game users not experiencing addictive symptoms, we hypothesized that there would be no such U-shaped relationship. Rather, we expected such users to derive hedonic experiences directly from features of the game rather than from chasing a dopamine response. As such, we hypothesized that there would be a comparatively flat relationship between hedonic experience and video game hours played per week for this latter group of video game players.To test this hypothesis, we divided the study subjects into quartiles based on self-reported addictive video game symptom levels using the Internet Gaming Disorder Scale (IGDS). Quartiles are commonly used in applied statistics to avoid arbitrary or convenient partition points. This method breaks the data into balanced subsamples by definition, because cutoffs are not arbitrarily determined by the researcher. Bennette and Vickers  state thIn our study, quartile 1 reported the lowest level of symptoms (mean symptom score 1.38) and quartile 4 reported the highest (mean symptom score 3.69). We used separate polynomial regression analyses for each quartile to test for significant nonlinear relationships between hedonic experience and video game hours played. Our use of polynomial regression to test for curvilinear relationships is a key contribution of this study, given that previous regression analyses of this topic have used linear regression. We studied this U-shaped relationship as a potential indicator of sensitization and tolerance in the addicted individuals. We specified a statistical model to explore this and, more specifically, estimated the “tipping point” at which the typical video game player exhibits addictive symptoms, such as attaining a target dopamine response and subsequently facing an increasing hedonic experience given additional video game play.This study aimed to examine how intensity of video game play  moderates the relationship between time spent on playing video games and hedonic experience. First, we hypothesized that subjects reporting higher behavioral addiction symptoms would show a U-shaped relationship between time spent on video games and hedonic experience. Second, we hypothesized that subjects reporting lower behavioral addiction symptoms would not show a U-shaped relationship between time spent on video game and hedonic experience, but instead would show a comparatively flat relationship.To test the hypotheses, an online survey-based study was conducted after acquiring approval from the institutional review board at Syracuse University (IRB number: 19-186). Based on several screening questions , subjects who played video games on a regular basis were identified and allowed to participate in the survey study. The target population were United States adults who played video games on a regular basis. Respondents were recruited and the survey was distributed via Amazon Mechanical Turk. The initial request asked them to participate in a survey about well-being. The survey was developed with Qualtrics software (SAP) and was a 6-screen survey. Interested subjects answered questions about their daily lives, including 2 screening questions: (1) Do you play video games on a regular basis? (responses were either yes or no) and (2) How often do you play video games? (multiple responses were available). Subjects who answered “no” to the first question and “not at all” to the second question were automatically excluded. Additionally, respondents who chose video game genres that they played in a multiple-choice question were also asked to list the game titles they had played in that genre. Respondents who listed titles that did not match the genre were excluded.Of 1072 attempts, 835 (77.8%) participants passed the screening and completed the survey. The average age of the participants was 32 years. More details on the respondents are presented in α of our data was .9. Time spent on video games was measured with a single item: “On average, how many hours per week do you play video games?” . The IGDS, defined by Lemmens et al [α was .91. Additional items to determine the level of neglect of other activities due to video games were also constructed. The first item was “Have you neglected school or work so that you could play games?” Additional items were phrased similarly, asking about neglect of sleeping, eating, socializing with others, and physical activity . Other items were used to examine money spent on video games ; health condition , physical condition  and alcohol consumption . Demographics were also assessed in the survey, including age, gender, race, education, marital status, and employment. These items are reported in In Lemmens et al’s study , video gns et al , was alsOn average, the highest addiction quartile individuals had markedly higher use intensity than any other group. However, some of these individuals exhibited low usage and low hedonic well-being from game play. Though less representative of the highest addiction quartile group, the presence of these individuals represents a potential paradox. Their presence in the sample might be attributable to access issues or the application of self-control, whereby individuals might accept a temporary loss of hedonic well-being in an attempt to break behavioral addictive symptoms. Indeed, at any point in time, a fraction of addicted individuals are motivated to quit . FurtherConversely, the lowest addiction quartile individuals, while exhibiting the lowest average use profile, did have some individuals who were high-intensity video game players. This also represents an apparent paradox. However, behavioral addiction involves dependence. That some low addiction quartile individuals reported high-intensity use does not necessarily indicate dependence. For example, it may be that these individuals enjoy gaming and have ample opportunity to game  but that they could self-regulate usage if life responsibilities dictated the need to do so. While correlated with each other, intense and problematic use of addictive activities are distinct processes .α) levels, as reported in t statistics for the regression coefficients.The key variables from the survey are summarized in P=.15, P=.17, P=.06, and P=.01; t216=1.46, t146=–1.365, t176=–1.872, and t155=–2.589) and hours played squared became larger and more significant  as we moved from quartile 1 to quartile 4. We found that the higher video game addictive symptom level groups experience a U-shaped  relationship between hedonic experience and intensity of play, whereas groups with lower video game addictive symptom levels exhibited no such relationship. The coefficients for the highest addictive symptom level group  representing marginal effects for hours played per week and hours played per week squared, respectively, were significantly negative (P=.005) and significantly positive (P=.004). The video game players exhibited a very different hedonic experience in weekly hours played across different addiction quartiles. As addictive quartile rose from quartile 1 to quartile 4, the hours played variables moved from an overall insignificant (not significantly different from flat) relationship with hedonic experience in the quartile 1 and quartile 2 regression results to the predicted U-shaped relationship for quartile 3 and quartile 4. In terms of coefficient value, hours played became smaller for quartiles 1 to 4 and more significant for quartiles 2 to 4  addiction quartile sample exhibited a trend curve with an inverted U shape. That is, sampled individuals in quartile 1 experienced first increasing, then decreasing hedonic experience with hours played. This trend curve shows that there were diminishing returns to video game play, a common result in microeconomic theory given standard utility functions. These sampled users reported increasing hedonic experience as they become involved in the challenges of a game but at a decreasing rate, until their hedonic experience reached a maximum and descended. The experience of diminishing returns tends to be associated with behavior moderation, as individuals experience negative reinforcement (declining hedonic experience) beyond a certain number of hours played. This observed negative reinforcement may be both a cause and symptom of low reported addiction levels. Moving to quartile 2, quartile 3, and quartile 4, the trend curve between hedonic experience and video game hours played per week became increasingly U shaped (in terms of both coefficient magnitude and coefficient significance level). For quartile 3 and quartile 4, this U-shaped relationship was significant, as reported previously.From the regression coefficient output related to hours played per week, we can compute the “tipping point” at which, according to prior findings discussed in the introduction, the typical video game player exhibiting addictive symptoms attains the target dopamine response and subsequently faces increasing hedonic experience given additional video play. For quartile 3 players, the estimated minimum hedonic experience value was 26.25 hours per week. For quartile 4 players, the estimated minimum hedonic experience value was 37 hours per week. These postregression estimates suggest that quartile 4 players experienced a longer period of declining hedonic experience, consistent with tolerance theory . The inIn general, there are two elements of addiction that represent theoretical constructs that are significantly consistent with the observed hedonic experience profiles: sensitization and tolerance. Sensitization indicates a hypersensitive reaction to video game exposure  and a heThe results confirm our two main hypotheses. Namely, for video game players reporting higher behavioral addiction symptoms, time spent on video game play has a significant U-shaped relationship with hedonic experience. For those reporting lower behavioral addiction symptoms, time spent on video game play does not have a significant U-shaped relationship with hedonic experience, but rather a comparatively flat relationship. Hedonic experience is a key motive and consequence for video gaming  that canThe first and second quartile respondents exhibited no substantial addictive symptoms. They are at low risk of developing video game addiction. They exhibited a more typical diminishing-returns response. They are social video gamers or experimental video gamers with limited video game addictive symptoms . Although they may exhibit some video game addictive symptoms, they do not meet the criteria for video game addictive disorder. However, King, Herd, and Delfabbro  state thNonetheless, results in the third and fourth quartiles show video gamers who display more addictive symptoms . They are frequent players, problematic players, or at-risk players. Their hedonic experience level drops at first , then rises (increasing returns to play). With high tolerance to video game exposure, they are frustrated due to their inability to attain the experience requirements of the game. This behavior is consistent with a study conducted by Kaptsis et al , in whicThe display of craving symptoms is consistent with a study conducted by Przybylski et al . In thisIn this study, we conducted a survey of 835 individuals who regularly play video games to determine the relationship between intensity of video game play and hedonic experience of the player. We divided the sample into quartiles by self-reported video game addictive symptom level (using the IGDS) and conducted polynomial regressions separately for each quartile. We found that the higher video game addictive symptom level groups experienced a U-shaped  relationship between hedonic experience and intensity of play, whereas groups with lower video game addictive symptom levels exhibited no such relationship. These results are consistent with sensitization and tolerance theories, which suggest that high-symptom groups are expected to experience frustration and disappointment until achieving excessive dopamine release, at which point their hedonic experience is expected to improve with additional play. Conversely, low-symptom groups experience no such fall-and-rise pattern. This result is consistent with the outcome that members of the latter group play the game for the direct experience, such that their hedonic experience is more directly related to events occurring in the game than to the increasingly elusive pursuit of excessive dopamine release. We also find that high-symptom groups spend substantially more time and money to support video gaming and are much more likely to engage in video gaming at the expense of other important activities, such as working, sleeping, and eating.Although this study shows a novel relationship across all genres of video game play, it does not study the relationship categorically by genre of play. Future research based on longitudinal data can provide information on players and their well-being at different points in time, shedding light on microlevel changes in this relationship. Further, this study does not address cognitive or behavioral consequences of video game play . Lastly,


The objective of the present study was to determine the morphologic features and measurements of the normal thymus on contrast-enhanced multi-detector computed tomography (MDCT) in subjects from the newborn period up to 18 years of age.The MDCT scans obtained from 464 children with a mean age ± SD of 8.43 ± 5.60 years were retrospectively re-evaluated. The shape, margins, side predominance, density, and measurements of the thymic gland were defined for each age group.A triangular thymic shape with a middle location and straight lateral contours were the most frequently seen morphologic features in children. The mean anteroposterior and transverse diameter of the thymus was 17.32 ± 4.58 and 29.99 ± 11.42 mm, respectively. The mean values for the width and thickness were 20.66 ± 5.36 and 15.15 ± 6.76 mm for the right thymic lobe, respectively; and 26.14 ± 7.85 and 14.91 ± 5.51 mm for the left, respectively. The transverse diameter of the thymus and thymic lobe dimensions decreased significantly with age, however, the anteroposterior diameter of the thymus was not significantly associated with age. Girls had higher mean thymic attenuation values compared to boys, however, this gender difference was not statistically significant .Our study provides a better understanding of the normal thymic appearances in children that can aid in accurate diagnosis and avoid unnecessary, costly, and invasive interventions. Computed tomography (CT) imaging evaluation of a normal thymus can be challenging since the morphologic features and the size of the thymus may differ even between children of the same age . This is2As no established guidelines are available, the CT interpretation of a normal thymus in children is mainly based on expert opinion. To the authors’ knowledge, the studies regarding morphologic appearance, dimensions, and CT attenuation values of the normal thymus were most recently conducted in 1982, 1987, and 2000, respectively using the earlier generations of CT scanners and a small number of children 56. Howev5The objective of the current study was to determine the morphologic features and measurements of the normal thymus on MDCT in subjects from the newborn period up to 18 years of age.The study protocol was approved by the Institutional Medical Research Ethics Committee following the guidelines of the Declaration of Helsinki (protocol number: 2022/688). A descriptive cross-sectional and retrospective study design was employed for this research.Over a period of five years from January 2016 to December 2021, 1,610 pediatric patients underwent thoracic MDCT examination in our University Hospital for various reasons including traumatic and nontraumatic thoracic emergencies and congenital or acquired pulmonary diseases. The exclusion criteria were defined as follows: subjects above 18 years of age [n = 28]; mediastinal or neck infection [n = 24]; lung infection  [n = 251]; mediastinal trauma  [n = 17]; mediastinal mass  [n = 146]; mediastinal distortion caused by thoracic or abdominal pathologies  [n = 84]; severe chest wall abnormalities [n = 14]; ectopic thymus [n = 5]; diseases associated with thymic enlargement  [n = 24]; conditions associated with thymic regression  [n = 142]; previous mediastinal or neck surgery [n = 9]; patients with hematologic and oncologic disorders [n = 375]; and CT investigations with poor image quality [n = 27].Following these exclusion criteria, a total of 464 patients remained in the study population.The thoracic contrast-enhanced MDCT examinations were obtained from the apex to the base of the chest using a 32-detector-row CT scanner  with the following parameters: matrix, 512 × 512; tube rotation time, 0.3–0.6 s; pitch, 1; section thickness, 3 mm; and intersection gap, 1 mm. A non-ionic iodinated contrast medium (300–320 mg I/mL), was administered intravenously at a dose of 1–2 ml/kg and an injection rate of 0.8–2.5 ml/s. Using the bolus tracking method and a region of interest, which was placed in the descending aorta, the arterial phase CT scan was initiated at a threshold of 140 Hounsfield units (HU). In order to keep the radiation as low as reasonably achievable (ALARA), acquisitions were performed at tube currents of 20–150 mA and a tube voltage of 80–120 kV depending on the patient’s weight. CT images were evaluated at window settings appropriate for mediastinum  on a Picture Archiving and Communication System (PACS) workstation .The assessment of the thymus was based on qualitative and quantitative approaches. In the first step, the shape, margins, and the side predominance of the thymus were described on three-dimensional CT images. The thymic shape was characterized as ‘round-oval’ , ‘quadriThe fat content in the thymic gland was scored using a four-point scale (0 to 3) scoring system as previously described by Ackman et al.  as folloThe mean thymic CT attenuation values in Hounsfield Units (HU) were measured on axial images using a manually delineated free-hand region of interest (ROI) covering the maximum area of the gland and avoiding the surrounding mediastinal fat, large blood vessels, motion artifacts, and partial volume effects  89].9.89].The measurements were performed, as previously described, on a single axial CT image showing the largest area of the thymic gland 710. The 7The image analysis was performed by a single European Board of Radiology – certified radiologist who was blinded to the age and gender of the patients.Distributions of continuous variables were assessed for normality using the Skewness-Kurtosis test and Kolmogorov-Smirnov test. Normally distributed data were presented as mean ± standard deviation (SD) and compared by one-way analysis of variance (ANOVA) test followed by post hoc analyses. Skewed distributed data were expressed as median [interquartile range (IQR) 25 – 75] and analyzed by the Wilcoxon rank-sum test and Kruskal-Wallice test. Categorical variables were compared by the Chi-square test and summarized using frequencies and percentages.After logarithmic transformation of non-normal distributed data, linear regression analyses adjusted for age and gender were performed to assess the relationship between thymic measurements and thymic CT attenuation values over time and age groups.Data were analyzed statistically using SPSS software, version 20.0 . P-values less than 0.05 were regarded as statistically significant.The study group included 266 (57.3%) boys and 198 (42.7%) girls with a mean age ± SD of 8.43 ± 5.60 years (age range 0 – 18 years). Children were stratified into six groups according to their age: Group 1 ; Group 2 ; Group 3 ; Group 4 ; Group 5 ; and Group 6 . The age groups were chosen according to the classification and definition of medical subject headings (MeSH) .A quadrilateral shaped thymus  was the most frequently seen morphologic feature on CT in children, followed by triangular  and round-oval . A round-oval thymus was more common in younger children with a mean age ± SD of 3.02 ± 3.23 years. A triangular thymus was more often seen in older children aged 11 years and above. These age-related differences in thymic shape proved to be statistically significant (p < 0.0001).The majority of children had straight , followed by biconvex , and mixed  thymic margins. The biconcave  borders were less commonly seen. Among the mixed thymic margins, 50% (53/106) of the study group had a combination of right straight-left convex and 33% (35/106) had right convex – left straight lateral contours. The thymus with biconvex margins was most commonly found in small children aged between 0 and 3 years. The thymus with straight contours was observed in nearly all subjects aged 15 years and above. The differences in thymic margins among age groups were statistically significant (p = 0.001).The thymus was located at the midline in 266 (57.3%) and showed a predominance on the left side in 134 (28.9%), and on the right side in 64 (13.8%) children. The midline position of the thymus was more frequent among children older than 11 years of age. The right-sided thymus was common in infants aged 0–12 months. The age-related differences in the thymic side were statistically significant (p < 0.0001).The shape, margins, and the side predominance of the thymus did not show differences among gender .The morphologic features of the thymus according to age groups are summarized in The estimation of thymic attenuation was made via subjective and objective assessment. The majority of children in our study had a mainly soft-tissue attenuated thymus (Score 3) , followed by half fatty and half soft-tissue attenuated (Score 2)  and mainly fatty thymus (Score 1) . The complete fatty replacement of the thymus (Score 0) was observed in only 3 (0.6%) subjects. The thymic attenuation score did not show a significant gender difference (p = 0.271).2 = 0.590]. With increasing age, the fatty content of the thymus increased, while the thymic CT attenuation values diminished significantly (p = 0.002).The mean thymic CT attenuation values were 61.7 ± 24.2  HU. In general, girls had higher mean thymic attenuation values (63.8 ± 22.4 HU) compared to boys (60.1 ± 25.3 HU), and this gender difference was not statistically significant (p = 0.164). There was a good correlation between subjective thymic scoring and objective measurements of the CT attenuation values [F  = 665,179, p < 0.0001, RThe distribution of the thymic density according to age is described in The mean anteroposterior (AP) and transverse diameter of the thymus was 17.32 ± 4.58  and 29.99 ± 11.42  mm, respectively. The mean values for the width and thickness were 20.66 ± 5.36  and 15.15 ± 6.76  mm for the right thymic lobe, respectively; and 26.14 ± 7.85  and 14.91 ± 5.51  mm for the left, respectively.Although insignificant, the width of the left thymic lobe showed dominance over the right lobe in both males and females . The thymic gland was 1,5 mm wider in girls compared to boys; however, these changes did not reach the significant value . The transverse diameter of the thymus and thymic lobe dimensions decreased significantly with age . The AP diameter of the thymus did not decrease significantly with age (p = 0.750) .Numerous infectious, neoplastic, systemic inflammatory, and autoimmune diseases frequently involve the thymus in the form of an anterior mediastinal mass or diffuse enlargement 3. As the12The most recent studies describing the CT characteristics of the pediatric thymic gland were published in 1982, 1987, and 2000 and were performed using the earlier generation of CT scanners and small sample sizes 56. Howev5Amour et al.  have rep4Sklair-Levy et al.  have assTo date, only two studies including both children and adults have evaluated the thymic gland measurements 12. In th10The limitations of the present study need to be acknowledged. This study was performed retrospectively at a single center. Although the overall sample size was large, the number of infants in the Group 1 was relatively low (n = 24) compared to other groups. The inter-and intra-observer coefficient of variation was not investigated in this research. Finally, the interpretation of the results was restricted by the paucity of publications providing data on the subject, thus, future multicenter studies with a larger sample size are needed to validate our results.In conclusion, the present study demonstrates that a triangular thymic shape with a middle location and straight lateral contours are the most frequently seen morphologic features on CT in children. The transverse diameter of the thymus and thymic lobe dimensions decreased significantly with age, however, the anteroposterior diameter of the thymus was not significantly associated with age. There was a significant relationship between age and thymic CT attenuation values. Gender was not correlated with the thymic size and density. Our study provides a better knowledge of the normal spectrum of thymic appearances in the pediatric population which is important to prevent unnecessary invasive procedures and referrals to higher levels of healthcare.


We previously constructed a VGG-16-based artificial intelligence (AI) model (image classifier [IC]) to predict the invasion depth in early gastric cancer (EGC) using static images. However, images cannot capture the spatio-temporal information available during real-time endoscopy. Thus, we constructed a video classifier [VC] using videos by attaching sequential layers to the last convolutional layer of the IC. We computed the standard deviation (SD) of output probabilities for a video clip and the sensitivities in the manner of frame units to observe consistency. The sensitivity, specificity, and accuracy of the IC for video clips were 33.6%, 85.5%, and 56.6%, respectively. The VC performed better analysis of the videos . Furthermore, the mean SD was lower for the VC than the IC. The AI model developed utilizing videos can predict invasion depth in EGC more precisely and consistently than image-trained models, and is more appropriate for real-world situations.v2, using video clips. We computed the standard deviation (SD) of output probabilities for a video clip and the sensitivities in the manner of frame units to observe consistency. The sensitivity, specificity, and accuracy of IC v2 for static images were 82.5%, 82.9%, and 82.7%, respectively. However, for video clips, the sensitivity, specificity, and accuracy of IC v2 were 33.6%, 85.5%, and 56.6%, respectively. The VC performed better analysis of the videos, with a sensitivity of 82.3%, a specificity of 85.8%, and an accuracy of 83.7%. Furthermore, the mean SD was lower for the VC than IC v2 (0.096 vs. 0.289). The AI model developed utilizing videos can predict invasion depth in EGC more precisely and consistently than image-trained models, and is more appropriate for real-world situations.We previously constructed a VGG-16 based artificial intelligence (AI) model (image classifier [IC]) to predict the invasion depth in early gastric cancer (EGC) using endoscopic static images. However, images cannot capture the spatio-temporal information available during real-time endoscopy—the AI trained on static images could not estimate invasion depth accurately and reliably. Thus, we constructed a video classifier [VC] using videos for real-time depth prediction in EGC. We built a VC by attaching sequential layers to the last convolutional layer of IC  Several studies have reported the usefulness of artificial intelligence (AI) in diagnostic imaging, including endoscopic imaging, to detect or diagnose neoplastic lesions. However, the role of artificial intelligence in endoscopy is distinct from that of other imaging modalities, such as computed tomography or magnetic resonance imaging . In otheAll previous studies have used endoscopic static images to train AI models for detection and diagnosis of early gastric cancer (EGC) . PreviouThe differentiation between mucosal and submucosal invasion was used to predict the tumor invasion depth in EGC. It is essential to make a diagnosis from observing subtle differences between two invasion depths, compared with the detection of EGC from normal mucosa. In real-world situations, endoscopists can predict invasion depth more precisely and reliably when observing subtle changes in the EGC lesion during an endoscopic procedure rather than still images of the lesion. Furthermore, since fine-grained visual features which come from spatio-temporal information were not considered, CNN trained on static images cannot reliably estimate tumor invasion depth in EGC. The structure of a neural network is inspired by the human brain; hence, training a CNN model in the same way as the human brain is more effective. Therefore, we developed an AI model to estimate the depth of tumor invasion in EGC using endoscopic videos. This allowed us to investigate and prove training an AI using endoscopic videos was more effective for predicting the tumor invasion depth in EGC as compared to endoscopic static images.We trained our previous CNN model using more static images to improve the depth prediction performance. In addition, we developed the AI model using endoscopic videos and compared the performances of the two AI models using endoscopic videos.v2, by adding newer endoscopic static images  of the training image dataset to IC v1, which was developed in a previous study [v2 for depth prediction.The study design is summarized in us study . We usedIn addition, we built a CNN model called the video classifier (VC) to analyze the data from endoscopic white-light videos. The used video data were captured for 20 s at 30 frames per second (FPS) because a lesion has to be intactly placed on whole frames composing a video. A single EGC lesion was centered on each video. To use the video data before training the model, we organized video clips by setting up the exclusion criteria. Because extreme scene changes in a video can disrupt sequential continuity, we split the video into two video clips when a discontinuity was recognized. To avoid presenting endoscopy recordings to the VC that involved occlusion of the lesion, videos containing medical procedures and/or bleeding scenes were omitted. Finally, a consecutive frame section in which an EGC lesion was detected by the EGC detector developed in previous study [To reflect the diversity of the video data and thus minimize the overfitting, we employed some image data augmentation methods to the training video dataset. Random flipping, random rotation, random gaussian blur, random motion blur, and sequence reverses were used to generate augmented video clips. In general, there are many types of augmentation techniques including elastic transformation and random cropping. However, the continuity which is the basic nature of video data, makes it hard to apply image augmentation methods to videos because the augmentation process may disrupt sequential information.v2 and the VC are shown in All endoscopic static images and videos in the current study were retrospectively consecutively collected at the Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea. Baseline clinicopathological characteristics of EGC for IC v1 and IC v2. IC v1 was designed to mimic the architecture of VGG-16 [v2. The differences between the two classifiers are shown in v2. The GAP layer measures the average values of the output from the last convolutional layer in a two-dimensional manner. Although the number of the training parameters was dynamically decreased by using the GAP layer, there was a known result that the performance losses were insignificant [3 with an adaptive moment estimation (ADAM) optimizer.A 16-layer network of the Visual Geometry Group (VGG) was employed as the backbone architecture for both IC f VGG-16 , and somnificant . After fTo prove the effectiveness of utilizing endoscopic videos for training the deep learning models, we constructed and evaluated two representative sequential models. v2. The sequential layer and fully connected dense layer(s) were trained using an ADAM optimizer with an initial learning rate of 0.0001 on the gathered video clip dataset. To measure the training losses, we applied a cross-entropy loss. In this study, the VCs used seven consecutive frames as input frame segments. The performance differences by changing the number of input frames are shown in To train and test the deep learning models, we used TensorFlow (version 2.4) for Python (version 3.7.10) as a backend. The models were trained on dual NVIDIA GeForce RTX 3090 with 24 GB of CUDA memory for each, whereas an NVIDIA GeForce RTX 2080Ti with 11 GB of CUDA memory was used to evaluate the performance. The weights of the convolutional layers of each VC were initialized and fixed using the weights of the convolutional layers from IC A single inference procedure of ICs outputs the probabilities of an input frame, whereas the output of the VCs is the probability of the last frame among consecutive input frames. Therefore, the output of the VCs represents the predicted invasion depth of the seventh frame in this study.To evaluate the performance of invasion depth prediction, we derived three types of final decisions from the outputs of each classifier as follows: (1) frame-by-frame prediction, (2) video clip-based prediction by averaging outputs, and (3) video clip-based prediction by voting outputs. For frame-by-frame prediction, we assumed that the invasion depth in all frames was the same as in the source video clip. To evaluate the frame-by-frame prediction, we counted the frames that were classified to have the correct invasion depth. The prediction from the video clip was deduced using the outputs of all the frames that constituted a video clip. There are two methods for determining the video clip-based prediction by the classifiers—averaging (2) and voting (3). In the averaging method, all probabilities were averaged to determine the maximum argument, whereas the voting method was used to determine the most frequent invasion depth that was estimated from among the all-frame results, which was denoted as the estimated invasion depth of EGC.To prove that consistency increased with the video data, we also examined the probability distribution for the frame-by-frame predictions.The class activation maps (CAM) were designed to identify the discriminative image regions which are highly contributing to the final classification result of CNNs . To extrThe diagnostic performance of the CNN system per image and frame was measured in terms of accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of the receiver operating characteristic (ROC) graph. The standard deviation (SD) of the output probabilities was computed using a video clip, and the sensitivities in the manner of frame units to observe consistency.v1 and v2 in predicting invasion depth , we evaluated the diagnostic performance of IC on depth . The accv2 and the VC with GRU layers were compared in terms of frame-by-frame and video clip-based prediction when endoscopic videos  were used for testing. . That is, in many frames of IC v2, the invasion depth prediction showed values ranging between both extremes spanning the mucosa and submucosa. In contrast, the likelihood of depth prediction was more reliable with the VC. These findings indicate that the VC has higher diagnostic consistency than the IC. v2 and the VC in real-world situations.Many studies have reported the development of AI models to detect gastric cancer, including our previous study, which showed favorable results ,10,11,12v1) to predict the invasion depth by training it with more static images. However, the performance deteriorated when testing was performed using endoscopic videos. Furthermore, the diagnostic performance was very unreliable, and values representing both extremes between the mucosa and submucosa (v2), as observed in the unedited video (Several CNN models were developed to predict the invasion depth in EGC ,15,16,17ubmucosa  were deped video . The rolv2 for the front layers of the two video classifiers. Several sequential frames were independently fed into the convolutional layers to extract spatial features. Subsequently, the sequential layer analyzed the spatial-temporal relationship using sequentially stacked convolutional outputs as the input. Similar to our concept, the algorithms to detect anatomical landmark in the upper endoscopy have been proposed for temporal correlations [To observe the effectiveness of utilizing video data containing spatial and temporal information, we modeled two types of video classifiers using sequential layers. In this study, we attached an LSTM and GRU to the tail of the convolutional layers. The architectures of the convolutional layers and their trained weights were adopted from the pre-trained IC elations ,22,23,24Generally, the number of training datasets that are employed determines the efficiency of deep learning. That is, the performance of deep learning grows with increasing data ,26,27,28We developed an AI model utilizing endoscopic videos which can predict the invasion depth of EGC more precisely and consistently than an image-trained model. It is more appropriate for real-world endoscopic situations.


The video-based commonsense captioning task aims to add multiple commonsense descriptions to video captions to understand video content better. This paper aims to consider the importance of cross-modal mapping. We propose a combined framework called Class-dependent and Cross-modal Memory Network considering SENtimental features (CCMN-SEN) for Video-based Captioning to enhance commonsense caption generation. Firstly, we develop class-dependent memory for recording the alignment between video features and text. It only allows cross-modal interactions and generation on cross-modal matrices that share the same labels. Then, to understand the sentiments conveyed in the videos and generate accurate captions, we add sentiment features to facilitate commonsense caption generation. Experiment results demonstrate that our proposed CCMN-SEN significantly outperforms the state-of-the-art methods. These results have practical significance for understanding video content better. However, most research  efforts Video-based commonsense captioning is a cutting-edge research topic, and Video2Commonsense  executesFurthermore, compared with image captions, video captions usually show more complex semantic patterns that contain more sentimental features. Previous studies only focused on the characters’ behavior in the video and ignored their sentimental attributes. Sentiment is a critical component of user-generated videos. Sentimental factors are present in human activities in videos. The sentimental content of videos can be used to help create commonsense descriptions. When a video’s sentiment is positive, we can easily infer that the generated description should also be positive. However, the current study does not consider sentimental features, instead relying solely on motion features. The recent research may result in the predicted words being biased or taking longer to correct.To address the abovementioned issues, we implement sentiment control in For sentiment control, we use bipolar sentiment and the sentimental content in the video to facilitate text generation corresponding to sentiment. As a control variable (a given condition), sentiment encourages the model to generate text that matches the control variable. Our model uses sentiment control to go from positive to negative. For example, if the given control variable is positive in sentiment, the model will make generating text that reflects positive sentiments easier. The sentiment feature we introduced represents the SENtimental Dimension (SD). Furthermore, we use multi-modal fusion to combine 1D audio features, 2D appearance features, 3D motion features, and SD sentiment features, allowing our model to learn to generate commonsense captions from different sources of information.To consider the interaction between different modalities and the importance of video type, we propose a class-dependent cross-modal memory network to record the alignment of video and text to facilitate interaction between modalities. Specifically, we use prior information to initialize a shared memory network matrix and use it to perform memory queries and memory responses on video and text features. For memory queries, we measure the similarity of cross-modal features and memory vectors under the same label and select the vectors with the highest similarity to interact with cross-modal features, and calculate their weights. The memory responses are generated by weighting the memory vector of the query and then feeding the responses corresponding to the input video and text features to the encoder and decoder to generate commonsense captions from learned interactions of cross-modal information.Our contributions are summarized below:We propose a combined framework called Class-dependent and Cross-modal Memory Network considering SENtimental features (CCMN-SEN) to generate relevant commonsense captions.A class-dependent cross-modal memory network is proposed to record the alignment of video and text to facilitate interaction between modalities.Sentimental Dimension (SD) is introduced, making generating text corresponding to video sentiment easier.Extensive experiments and analyses demonstrate the effectiveness and superiority of our proposed model.2.2.1.In recent years, commonsense knowledge has increasingly become a research hotspot in the field of NLP and even multi-modal  and inte2.2.Captioning is essential for understanding visual effects. The task of video captioning  is to im3.This section describes the architecture and design of our proposed CCMN-SEN. It records the alignment between video features and text, allowing cross-modal interactions and generation to take place on cross-modal matrices that share the same labels, facilitates cross-modal interactions, and leverages sentiment to facilitate commonsense captioning generation. As illustrated in V consisting of what is described in sentence S. Our framework can be used for generating commonsense descriptions C in the setting. In the setting (Completion task), we use ground-truth captions to guide the generation of commonsense captions. This task can be seen as a complement to captions. The setting can be formulated as:Consider a video V is the video and S is the ground truth caption.where The following subsections detail and discuss our contributions, which primarily focus on the design of class-dependent cross-modal memory networks.3.1.Given a video, we use pre-trained models, including ResNet152 , SoundNewhere 3.2.The video encoding is fed into two transformer language decoder networks (a robust architecture that achieves state-of-the-art on many tasks). Our commonsense decoder network uses multi-commonsense learning similar to 3.3.Video provides humans with an emerging channel to express sentiments, which play a crucial role in human life. These sentiments can be defined as complex psychological states such as anger, disgust, amusement, awe, etc. Sentiments can be positive or negative, and they belong to different sentiment categories (positive or negative). In this paper, we introduce Sentiment Dimension (SD) in the preprocessing stage, aiming to help create commonsense descriptions. The SD represents the SEN in our proposed model. Specifically, we use the pre-trained model Bert to get each video’s sentiment category (positive or negative) and then convert the sentiment category into a 768-dimensional sentiment representation. The resulting representation is used as the source input for all subsequent modules.3.4.There could be correlations between different modalities of video and text for the video-to-commonsense captioning task. These associations can be an excellent reference to aid in the generation process. It is also possible to record the alignment of cross-modal representations such as video and text. At the same time, there may be noise in the interaction between different types of video and text, and it can be more accurate only to allow interaction between the same type of video and text. To take advantage of this relationship, we use CCMN to improve the mapping relationship, make cross-modal video and text interaction more effortless, and make commonsense caption generation easier.As shown in Instead of randomly initializing matrices, as in previous studies, which may hinder subsequent matrix learning, we utilize prior information. Specifically, for the same type of video, we utilize pre-trained models to extract video and text features separately and combine them, then employ K-Means to cluster each feature set into 3.4.1.Our cross-modal matrix query first measures the similarity between its feature representation and the cross-modal model memory vector under the same label as the video and selects the top vector with the highest similarity to interact with the feature representation. We apply multi-thread querying to perform this operation, wherein each thread of the querying process follows the same procedure. We linearly transform each memory vector in M and the input features to ensure the input video and text features are in the same representation space. Taking audio features and caption text features as examples, the linear transform process is formalized as:where where the number of extracted memory vectors can be controlled by a hyper-parameter 3.4.2.via:The responding process is also conducted in a multi-thread manner corresponding to the query process. For each thread, we first perform a linear transformation on the queried memory vector where where Considering possible noise responses, we first concatenate single-modal features with their associated responses. A linear layer is then applied to fuse unimodal features and cross-modal vectors. This research makes it possible to focus on essential differences and filter out noisy signals. The process is defined as:where 4.4.1.n = 1–4; We evaluate our proposed CCMN-SEN and compare it to other methods on the Hybrid Network , respectively; in the Intention section, our CCMN-SEN increased by 6.5%, 1.9%, 2.2%, 2.3%, 1.5%, and 2%. Because CCMN-SEN and HybridNet both use similar structures and multi-commonsense learning, we can attribute our improved performance to multi-modal interaction and the addition of sentimental factors. We introduce sentimental features in a novel way to aid in generating commonsense captions, and we can unify cross-modality features by aligning features using a shared memory matrix. This improvement demonstrates that our CCMN-SEN is a robust baseline model for the V2C task.An example visualization is shown in 4.4.We conduct a detailed ablation study by examining the effectiveness of each proposed component in BASE: We use the HybridNet model as the baseline for comparison, i.e., including the memory module but only considering inter-text interactions.BASE + CCMN: Based on the BASE model, we replace the standard memory module with a Class-dependent Cross-modal Memory Network module (CCMN), which considers the interaction between different modalities.BASE + SEN: Based on the BASE model, we only input sentimental features without changing the memory module and explore the impact of sentimental features on commonsense learning.CCMN-SEN: Integrates a Class-dependent and Cross-modal Memory Network considering SENtimental features (CCMN-SEN) model for sentimental control.4.4.1.The introduction of sentimental features increases BLEU-1 by 0.4% in terms of intention, 0.9% in effect, and 0.3% in the attribute. At the same time, we find that introducing sentimental features achieves better results on effect completion. As shown in 4.4.2.We observe that CCMN can significantly improve all completion task metrics. For example, compared with the baseline model, the advantage of our CCMN can significantly increase the attention by 1.4% (69.4% vs. 70.8%), increase the effect by 2.1% (49.0% vs. 51.1%), and increase the attribute by 0.5% (58.7% vs. 59.2%) on the BLEU-1 indicator. This enhancement can be attributed to the well-learned CCMN better capturing the cross-modal information flow and embedding the information into the feature learning process. These significant improvements demonstrate the feasibility and effectiveness of our CCMN on video-based commonsense completion tasks. It is worth mentioning that the interaction between the same category of video and text will reduce noise. However, when a category always appears with other categories, other categories may scatter the matrix of related categories.5.In this paper, we propose a Class-dependent and Cross-modal Memory Network considering SENtimental features (CCMN-SEN) framework to improve video-based commonsense caption generation by incorporating sentimental features and a class-dependent cross-modal memory network. Its sentimental features can help the model generate texts that match the video’s sentiments in less time. Then, the class-dependent cross-modal memory network applies the memory network to both the encoder and the decoder simultaneously and stores the features of different modalities through a matrix to form a video and map between texts, better-aligned features. On the V2C dataset, our CCMN-SEN achieves state-of-the-art performance, demonstrating the effectiveness and superiority of our model.https://drive.google.com/file/d/1qt0JsOAqBsdCTlDUw0gw7c_IosShysoW/view.Publicly available datasets were analyzed in this study. This data can be found at: V2C dataset HX, YZ, JL, and YC took part in the discussion of the work described in this paper. HX wrote the first version of the paper and did part of the experiments of the paper. YZ performed the data processing and analysis. JL and YC revised the paper in different versions of the paper. All authors contributed to the article and approved the submitted version.This work was supported by the Humanities and Social Science Project of Ministry of Education of China (grant no. 21YJCZH186) and the National Natural Science Foundation of China (grant nos. 72171004 and 71901014).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.


Drowning and near-drowning are the consequences of recreational activities and natural disasters. The purpose of this study was to review the microbiology literature on drowning and near-drowning and to understand its applications in the diagnosis and treatment of these injuries and diseases.This study is the result of a short review on publications extracted by searching in scientific databases including Google Scholar, PubMed and Semantic Scholar in the period from 1961 to 2021, using the keywords "Microbiology" and "Drowning" or "Near-Drowning".A search in scientific databases revealed 184 articles related to "drowning" and "microbiology" and 84 articles related to "near-drowning" and "microbiology", of which 65 and 28 articles have been published in the last twenty years, respectively. Of these, 43 articles were used for this study. Regarding the microbiology of drowning and near-drowning, no study was conducted in the Islamic Republic of Iran in this field. The findings of the present study showed that:• Near-drowning in its victims causes physical and mental injuries, and invasive polymicrobial and fungal pneumonia, brain abscesses, and sepsis.• They are mainly associated with numerous bacterial agents e.g. Aeromonas spp., Nocardia spp., Vibrio spp., Photobacterium spp., Burkholderiapseudomallei, Pseudomonas spp., Plesiomonas shigelloides, and Shewanella spp. and Fungal and Protozoan pathogens are limited to Aspergillus spp., Scedosporium apiospermum, and Rhizopus spp., and Cryptosporidium parvum (rare), respectively.• If bacterial, fungal, and protozoa infections are not properly diagnosed and treated in drowning victims, they can lead to death in intensive care units and even long after discharge from the hospital.• Deaths from drowning and near-drowning are candidates for organ transplants, especially lung, bone, liver, and heart.• Clinical, environmental, forensic, and eco-microbio-epidemilogy studies in pre-and post-mortem drowning victims are being developed using cultured-based and molecular methods such as PCR, LAMP, NGS, and Metagenomics, etc. to determine the drowning microbiome pattern.Several cases of infections and diseases caused by drowning and near-drowning have been reported among the victims of recreational activities and natural disasters in different countries. Therefore, eco-microbio-epidemiological study of drownings in our country, where there is an average of 1,200 annual drownings on the north and south coasts and inland waters is essential. Even predicting tsunami and destructive storms on the shores of the Caspian Sea and the Oman Sea are very important in determining the microbiome pattern of natural aquatic areas and the role of microbes in diseases and complications caused by drowning. Finally, a national protocol should be developed for microbial monitoring of drowning victims from the scene of water accidents to the hospital bed and on the autopsy table.Microbiology, Microbiome, Drowning, Near-Drowning, Natural Disasters


To carry out a quasi-systematic review of the use of serious video games for health as a cognitive rehabilitative tool in patients diagnosed with attention-deficit hyperactivity disorder.A quasi-systematic review of serious video games used as an evaluative and rehabilitative tool in patients with ADHD was conducted. It included behavioral patterns in the use of video games and addiction problems in this population. For its elaboration the PRISMA GUIDES were followed. The search was carried out in three PubMed databases, MEDLINE, and PsycInfo using the keywords: [game OR serious game OR computer game) AND  AND (adhd)], [(adhd) AND (Video game addiction)]. All articles written in English, Spanish, or Portuguese from January 1970 to June 2021 were included: those in which reference was made to the use of video games and/or new technologies as a therapeutic and evaluative tool in children and adults diagnosed with ADHD, as well as those that referred to behavioral and clinical patterns in the use of video games.We found 605 articles of which 128 were reviewed . Serious video games can be used to ameliorate ADHD symptoms while improving adherence to treatment. Some serious video games show high accuracy properties assessing ADHD features.Serious video games for health are increasingly being used as a cognitive rehabilitation tool in patients with attention-deficit hyperactivity disorder (ADHD).www.crd.york.ac.uk/prospero], identifier [CRD42021247784].[ The use of video games, particularly by children, is increasingly a matter of concern worldwide. Indeed, “Internet gaming disorder” (IGD) is considered a behavioral addiction . IGD is Children with ADHD are particularly vulnerable to developing a severe addiction to gaming . Indeed,Serious video games may also be used to evaluate cognitive functions related to ADHD. Instances of this are Cyber Cruise  and CogMIn particular, several video game versions of the CPT are available, such as MOXO-CPT , Kinect-The aim of the present study is to systematically review all sound scientific literature published to date about the relationship between video games and ADHD considering three prisms: (1) the problematic (addictive) use of video games, (2) the potential use of video games to improve the diagnosing of ADHD, and (3) the potential therapeutic role of video games in patients with ADHD. We think that a holistic, comprehensive view of this interesting relationship will assist developers and health staff in the development of serious video games with diagnostic and therapeutic properties, as well as the inclusion of some ethics into the development of such tools .1 with the aim of providing the scientific community with an overview of the potential use of serious video games for health as a therapeutic tool for cognitive rehabilitation in patients diagnosed with ADHD. For this, we have taken into consideration all the scientific literature written about cognitive rehabilitation through video games in ADHD, behavioral patterns during their use, and the growing problem of addiction to new technologies in said subpopulation.We have developed a quasi-systematic review following the PRISMA guidelinesOur systematic review has been prospectively registered in the PROSPERO register of systematic reviews, where it is provisionally published as it was submitted (CRD42021247784).We proceeded to perform in June 2021 a first search in PubMed, PsycInfo, and Medline databases, in keeping with other recent systematic reviews in the field , 36, 37,2 (10 first pages). All those articles with scientific rigor published in English, Spanish, or Portuguese were selected from January 1970 to June 2021: those that referred to the use of video games and/or new technologies as a therapeutic and evaluative tool in children and adults diagnosed with ADHD, as well as those that alluded to behavioral and clinical patterns in the use of video games.Finally, we conducted a new search with the same terms by using the search engine in Google ScholarExcluded were those in which the game was used only as an evaluation method without providing further relevant data, those lacking scientific rigor, and all those in which there was no explicit reference to the existence of a relationship between the use of video games and clinical patterns of ADHD.In total, 605 articles were selected, of which 339 were eliminated because they were not related to the purpose of our study and 70 because they were repeated. Of the remaining 196, 4 were discarded because they were in a language in which none of the authors were competent, 9 were eliminated for not focusing on the relationship between ADHD and video games, 47 were eliminated for not providing knowledge relevant to the subject of study, in 5 we could not access the full article because of lack of library funds, and 6 were discarded for other reasons. Finally, to the 125 articles reviewed, 3 new articles found in the reading of other articles were added.A total of 128 articles were reviewed, of which 44 were observational studies, 26 were quasi-experimental studies, 26 were experimental studies, 9 were narrative texts, 8 were systematic reviews, 7 were pilot studies, 6 were case reports, and 2 were meta-analyses. 3 ranging from level I  to level V (expert opinion).All studies were classified according to their level of evidence for primary research questions,n = 49), video games as an evaluation tool (n = 11), and behavioral and clinical patterns in the use of video games (n = 23).In order to address the main theme of our research from a general framework that encompasses the beneficial study of the use of video games in patients with ADHD, but also behavioral and clinical patterns that may become maladaptive in their use, we decided to distribute the 128 articles among three tables: the use of video games as a cognitive rehabilitation tool .Adherence to treatment is improved, taking special care on a series of features of serious video games . A motivating general theme for the game  can greatly improve adherence, as well as the use of frequent and immediate rewards and novelty in challenges  (see text footnote 4). About serious video games features with an effective impact on ADHD improvements, two caveat should be considered. First, serious video games tend to get important inspiration from cognitive treatment tasks already validated , and second, in general terms, immediate feedback and rewards improve not only adherence but also performance, particularly in ADHD patients  (see text footnote 4). Nevertheless, scientific literature on the specific topic of video game components and its influence on clinical improvements is scarce and falls beyond the scope of the present review, so our discussion on the matter should be taken with caution.Finally, we must pay attention to the problems that derive from an excessive use of new technologies in the general population, and in particular in ADHD. Several investigations show how patients with ADHD are more prone to addiction to video games , 25, 108Males seem to be more affected by video game addiction , 113. ThIn this systematic review we wanted to provide the scientific community with a holistic view of video games and attention-deficit hyperactivity disorder with the main objective of creating new cognitive rehabilitation tools based on video games that are more efficient and motivating for patients. The scope of this review is broader than other recent reviews, covering the appearance of ADHD symptoms and related psychological deficits, as well as their assessment and treatment through serious video games and the benefits of ADHD therapy though video games.Despite the fact that favorable evidence has grown exponentially in recent years, there are several limitations in published studies such as the lack of replication of studies, the low systematization of research, and low master size, among others.Serious video games are a tool for the diagnosis and treatment of ADHD symptoms and other related issues. A therapist should maintain a comprehensive view of video games, including both their problematic use (IGD) but also their potential use as either diagnostic or therapeutic tools. However, the present conclusion is reached after reviewing predominantly male samples, so generalizations to female patients should be made carefully. In the creation and design of a therapeutic video game for patients with ADHD, some relevant aspects should be taken into account: it is necessarily a diagnostic evaluation in order to offer personalized training in those areas and sub-areas more severely affected. The training must be constant over time, the difficulty level must be adjusted to the patient’s competence and in which his progression becomes visible, receiving a positive reinforcement in the first immediate moment and progressively increasing the delay time. In addition, other factors to consider are time management, inhibitory control, reasoning, competitive nature, and transference to situations of daily life, as well as the virtual world in which the game is developed.The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.MR-Y and HB-F conceived the original idea and formulated the problem, applied the inclusion and exlusion criteria, and selected the articles for revision. MR-Y designed the search syntaxes. MR-Y and MB-F performed the searches. MR-Y and HB-F wrote the drafts for the manuscript. CG-T and MB-F critically reviewed the manuscript. All authors reviewed and accepted the final version of the manuscript.www.fipse.es) in 2018. CG-T and HB-F were employed by Consulting Asistencial Sociosanitario SL. The remaining 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.In the last two years, HB-F has received lecture fees from AB-Biotics, Rovi, Praxis, and Shire. He has been paid by Praxis for the design and writing of an article. He was the recipient of a FIPSE Grant (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.


A key component of the joint source-channel coding (JSCC) scheme based on double low-density parity-check (D-LDPC) codes is the introduction of a linking matrix between the source LDPC code and channel LDPC code, by which the decoding information including the source redundancy and channel state information can be transferred iteratively. However, the linking matrix is a fixed one-to-one mapping, i.e., an identity matrix in a conventional D-LDPC code system, which may not take full advantage of the decoding information. Therefore, this paper introduces a general linking matrix, i.e., a non-identity linking matrix, connecting the check nodes (CNs) of the source LDPC code and the variable nodes (VNs) of the channel LDPC code. Further, the encoding and decoding algorithms of the proposed D-LDPC coding system are generalized. A joint extrinsic information transfer (JEXIT) algorithm is derived for calculating the decoding threshold of the proposed system with a general linking matrix. In addition, several general linking matrices are optimized with the aid of the JEXIT algorithm. Finally, the simulation results demonstrate the superiority of the proposed D-LDPC coding system with general linking matrices. Compared with classical separate source and channel coding schemes, a common objective of joint source-channel coding (JSCC) schemes is to make full use of the source and channel information in order to boost the performance of the overall system. As a promising coding structure, a JSCC scheme consisting of two low-density parity-check (LDPC) codes was proposed in , where aIn the D-LDPC coding system, a core idea is the introduction of a linking matrix setting up the connections between the check nodes (CNs) of the source LDPC code and the variable nodes (VNs) of the channel LDPC code, and we name it as the source check–channel variable (SC-CV) linking matrix. Using the SC-CV linking matrix, the joint belief propagation (BP) decoding can iteratively exchange the source redundancy and channel state information to improve the system performance. To achieve a better performance, the non-zero column vectors in the linking matrix should connect to the VNs with larger degrees in the channel LDPC code . MoreoveIn this paper, a generalized SC-CV linking matrix is introduced into the D-LDPC coding system. The conventional SC-CV linking matrix consists of a zero matrix and an identity matrix, i.e., both the row and column weights being 1, which implies a one-to-one mapping between the source coding and channel coding. However, this mapping may not take full advantage of the source redundancy and channel state information. Therefore, a more general linking matrix is introduced for the purpose of providing more connections between the CNs of the source LDPC code and the VNs of the channel LDPC. Consequently, the identity matrix in the SC-CV linking matrix will be replaced by a non-identity matrix. Note that the identity matrix , includiIn recent years, a majority of the work for D-LDPC code systems has been studied in order to improve the bit error rate (BER) performance in the water-fall region and error-floor region. The former is evaluated by the channel decoding threshold and the latter is evaluated by the source decoding threshold. For DP-LDPC code systems, a joint protograph extrinsic information transfer (JPEXIT) algorithm  was propHowever, the aforementioned D-LDPC code systems are all based on the identity SC-CV linking matrix. The introduction of the non-identity linking matrix enables a more effective decoding information  transfer between the source and channel LDPC codes.The novelty and contributions of this paper can be summarized as follows.(1)A general SC-CV linking matrix is introduced into the D-LDPC code system and the corresponding encoding and decoding algorithms are generalized.(2)In order to analyze the impacts of the general SC-CV linking matrix on both the channel decoding threshold and source decoding threshold, the corresponding EXIT algorithm is proposed.(3)Given several pairs of source and channel protographs, some general linking matrices constructed by a matrix operation are optimized.The remainder of this paper is organized as follows. j-th VN to the i-th CN.An LDPC code can be represented by the sets Consequently, a JSCC system based on D-LDPC codes can be represented by the following parity-check matrix source check–channel variable (SC-CV) linking matrix, indicating the connections between CNs of source variable–channel check (SV-CC) linking matrix, indicating the connections between VNs of Remark 1.The non-zerolowers error floors but increases channel decoding thresholds for a given code pairandFor simplicity, the caseis considered in this paper. As all that really matters is the partthe linking matrix only denotes thein the following content unless otherwise stated. Thus, the joint parity-check matrixis changed to beIn the conventional D-LDPC coding system, For an independent and identically distributed (i.i.d.) Bernoulli  to i-th CN  at the k-th iteration. As shown in Let The information from the VNs to CNs is calculated for The information from the CNs to VNs is calculated for k-th iteration, the LLRs of the estimated bits At the end of the k reaches the predetermined total number K of iterations, the decoding will stop and turn to Step 6; otherwise, the procedure goes back to Step 1 and starts the next iteration.IfThe estimated information sequence Different from the separated source LDPC coding and channel LDPC coding systems, the conventional D-LDPC code system sets up its connections via a general linking matrix, i.e., non-identity matrix However, the one-to-one connection defined by The source coding procedure can be re-written as follows. A generated matrix with a systematic form Thus, in order to obtain the compressed bits b is the .When Taking the channel coding procedure  into conBy doing so, the overall joint parity-check matrix ure from  to 11)  HJ can bure from  should bIn order to illustrate the advantages of the application of the general linking matrix in the D-LDPC code system, the structured protograph LDPC codes are considered here. Different from the degree distribution representation of an irregular LDPC code, a protograph LDPC code is defined by a small protomatrix lgorithm . The proThe joint protomatrix of a double protograph LDPC (DP-LDPC) code system is represented byIf a punctured protograph is used, then we denote by In order to obtain the corresponding parity-check matrix In the D-LDPC coding system, two decoding thresholds should be considered, i.e., channel decoding threshold In order to determine the channel and source decoding thresholds, the JPEXIT algorithm has to be described. Let us first define the following five types of mutual information (MI).j-th VN to i-th CN;i-th CN to j-th VN;j-th VN to i-th CN;i-th CN to j-th VN;j-th VN and the corresponding bit In addition, two functions Moreover, Furthermore, the update procedure of the MI can be summarized as follows.The MI update from VNs to CNs:For For If For The MI update from CNs to VNsFor For The evaluation of In summary, the ppv(j)=1 .The channel decoding threshold tes from  to 29)  (Eb/N0)tThe source decoding threshold analysis ,13, it iIn all, introducing the general linking matrix will only affect the channel decoding threshold of the DP-LDPC coding system.In order to efficiently optimize the general linking matrix, we should first discuss its structure. Multiply a non-zero value to one row of the matrix;Add a multiple of one row in the matrix to another row;Change the position of two rows in the matrix.Therefore, the general linking protomatrix The elementary column transformation can also be defined via replacing the “row” with “column” in the definition above. Motivated by this, a non-singular square protomatrix (e.g., otograph .In order to further illustrate the structures of the general linking protomatrix, we take the following joint protomatrix as an example, i.e.,Select an appropriate Determine the connecting VNs of the channel protomatrix by employing the identity protomatrix Design the specific structure of As mentioned above, the protomatrix trix. In , it is iThe main tested parameters in the optimization are shown in Example 1.We start from a joint protomatrix mized in , i.e.,Θ here is set to be where 4JA code  and BP iBy comparing Example 2.Another joint protomatrix with a larger size at source statistic given in . In addiand it has a channel decoding threshold of −1.666 dB. Next, the specific structure of general linking protomatrix is optimized asThe corresponding joint protograph is denoted by In the case of By observing the optimized general linking matrix, it is found that the VN with the largest degree is located in the same column as the VN with the largest degree of the channel protomatrix. Although this is not derived by mathematical proof, such experience can reduce the search complexity of the optimization.The BER simulation is carried out to verify the analysis of the JPEXIT algorithm. The BER simulation is performed over AWGN channels and the maximum iteration number of the joint BP decoding algorithm is set to 100.R is 1/2.The effect of introducing the general linking protomatrix Therefore, it can be concluded that the introduction of the general linking matrix plays an important role in the water-fall region, but it has limited effect on the error-floor region.The superiority of optimizing the general linking matrix In the BP decoding, the update in the CNs dominates the total complexity, which is represented by the average degree In conventional D-LDPC code systems, an identity linking matrix sets up the one-to-one connection between the source coding and channel coding, but this connection can not take full advantage of the decoding information. In this paper, a general linking matrix providing more connections is introduced into the D-LDPC code system to generalize the joint encoding procedure. Moreover, protograph LDPC codes are taken as examples for demonstrating the strengths of the proposed general linking matrices. By the aid of the JPEXIT algorithm, several general linking protomatrices to improve the channel decoding threshold are optimized. The simulation results are in line with the JPEXIT analysis, and the coding gain of the proposed DP-LDPC is 0.36–1.57 dB, which verify the superiority of the D-LDPC coding system with the proposed linking matrix.It should be pointed out that the proposed optimization of the general linking matrix and DP-LDPC code system can also be applicable to other types of LDPC codes. The optimization of the general linking matrices over the other scenario, e.g., the joint shuffled scheduling decoding , the Gau


The involvement of lay people in health care decision‐making processes is now the norm in many countries. However, one important aspect of participation has not received sufficient attention in the past and remains underexplored: representation.This paper explores the question of how public participation efforts in collective health care decision‐making processes can attempt to aim for legitimate representation so that those individuals or groups not present can be taken into account in the decisions affecting them. This paper argues that to make decisions that effectively address those affected, representation needs to be seen as a relevant part of any participatory setting. To support this argument, the paper outlines the concepts of participation and representation and transfers them to health care contexts.A conceptual reflection on responsiveness and the characteristics of representative actors in representative‐participatory settings is introduced, which could provide actors planning to conduct participatory health care projects with tools to reflect on the merits and possible flaws of participatory constellations.The paper contributes to improving public participation in health care decision‐making. The antipsychiatry movement, for instance, was at the forefront of demanding that lay people have a voice in decision‐making and be taken seriously as autonomous and political subjects rather than being stigmatized and confined to psychiatric institutions.,p.1229 we understand public participation in health care as ‘the contribution of patients or their representing organizations in shaping health and social care services by means of active involvement in a range of activities at the individual, organizational and policy level that combine experiential and professional knowledge’. This contribution is especially relevant to decision‐making processes, which are usually defined as processes or sequences of activities that are initiated upon the recognition of an underlying problem or condition and usually result in a decision to act or not to act to respond to such problem or condition.When it comes to public involvement, the terms ‘participation’, ‘involvement’ and ‘engagement’ are often used interchangeably.Evidence on the effects of involving lay participation in such processes is, however, scarce2,p.96 By speaking and acting on behalf of others who cannot be present themselves, representatives allow these others to be present by making certain characteristics visible. Representation can relate to many things, including preferences, interests, identities and values.Representation is a form of social interaction in which different types of actors are brought into relation to each other.,p.144 who highlighted the often‐used etymological meaning of representation as ‘making present again something that is not literally present’. She further defined a representative as ‘someone who has been authorized to act’.,p.38 According to this approach, the represented individuals' will could be seen as evident and objectively tangible by the representative. Pitkin's understanding of representation was, however, rather static and normative and limited to the political field. Later approaches, like those of Rehfeld or Saward, expanded the approach to more constructivist spheres, according to which representation could be perceived in terms of dynamic processes between those being represented and their representatives.Probably the most prominent approach to this topic was made by Pitkin,,p.1003 He did so by developing a theory of the representative claim, according to which actors are in an ongoing competition to claim the right to represent certain groups of individuals.responsiveness and is conceptualized as a mechanism of accountability and authorization.,p.360 accountability refers to how representatives explain and justify their actions towards those they represent,p.102 Besides elections, various other manifestations of such mechanisms are thinkable and in place, for instance (but not limited to) starting or terminating membership of an organization, organizational meetings in which the representatives' actions need to be approved by the members, publishing publicly available annual reports.Saward conceptualized representation ‘not as a fact that results from election, but rather as a process of making claims in electoral but also many other contexts’.Although the concept of responsiveness is conceptually quite well developed and follows a certain tradition in political theory ,3In the course of the past decades, several frameworks have been developed to enable lay people to participate, which address the activation of participantsIn health care settings, participation is used not only in various areas, such as service development, planning, the delivery and evaluation of care, the education and training of health care providers, health technology assessment and research,Gemeinsamer Bundesausschuss). Its main task is to define the detailed content of health care and to decide which services are to be included in the benefits catalogue of the German statutory health insurance. To perform this task, the FJC passes guidelines that have the status of sublegal norms and are legally binding for all actors within the statutory health insurance. This body of decision‐making includes members appointed by the Central Federal Association of Health Insurance Funds, the German Hospital Federation, the National Association of Statutory Health Insurance Physicians and the National Association of Statutory Health Insurance Dentists. In addition, four POs are allowed to appoint representatives who have the right to codetermination and make motions. Taking a closer look, it becomes clear that the selection of appropriate patient representatives is an administratively complex and demanding process. According to article 140f of the German Social Code, Volume V, the four relevant patient and self‐help organizations are responsible for proposing and mutually appointing patient representatives in the context of the Coordinating Committee of the FJC.Systems of lay participation in health care planning and research are more or less strongly implemented in most high‐income countries. In Germany, for example, lay participation in health care planning has been continually expanded over the past decades. The main decision‐making body on health care planning in Germany is the Federal Joint Committee ,To this end, a number of aspects must be taken into account, especially in the health care sector. Patients do not have common values or an identity that would distinguish them from other social groups. The experiences they have are based on experiences of illness, care and other aspects. These experiences do not represent a fixed quantity, but are always in flux and, moreover, can vary greatly, which is why they are not able to characterize groups of individuals appropriately. Therefore, the goal of descriptive representation cannot be to identify representatives who exhibit exactly the experiences or other criteria that a patient collective can exhibit. Rather, descriptive representation can help to establish a relationship of trust between representatives and their proclaimed constituency,,p.730f. argues that ‘descriptive representation must entail mutual relationships and maybe skills of the representatives, and not just shared characteristics, so that the dynamic process of genesis of interests is considered’ .Mechanisms of authorization and accountability and the descriptive character of representatives are interconnected. While the former is indispensable for legitimate representation, descriptive representation can have a protective effect if such mechanisms are only insufficiently in place. Descriptive representation may therefore facilitate successful representation without necessarily being a prerequisite of it. Similarly, Dovi4.2who and how of representation and also define the criteria used to judge whether or not the actions performed are representative. Furthermore, they may define and establish the mechanisms of authorization and accountability. Accordingly, they have immense power over the act of bringing representation into being.In many cases, a participatory setting is organized by an actor who may or may not take part in the actual process of participation. These organizers shape the ,p.395 In the context of the FJC, POs are given legal freedom to designate their representatives, but this can certainly not be applied to all conceivable settings in which representation is present. In the event that an organizer selects the participating representatives, the organizer may reflect on relevant responsiveness criteria to reinforce the importance of the setting in terms of decision‐making in advance.In already‐established participatory decision‐making settings, organizers can further the process by functioning as a mediator between those involved. Mediation can facilitate the realization of legitimate participation by providing transparency and understanding of the various actors' perspectives. By providing transparency, the represented individuals can understand how decisions are madeAside from the abovementioned prerequisites of organizing actors, which are not necessarily present in every conceivable setting, it is often argued that participants, who are representatives themselves, should have additional skills or characteristics that would enhance their ability to appropriately perform the representation of potentially vulnerable individuals.5The intention of this article was to sensitize institutions that are planning to conduct or are already conducting participation in decision‐making processes to the importance of representation. We mention three ways in which representation can take place in the health care sector, although these aspects may also be similar in other areas. In the first case, there are mechanisms of authorization and accountability, which together can ensure responsiveness between the representative and the represented. As a second aspect, and closely related to responsiveness, we mention descriptive representation as a possible criterion for potential participants. By trying to involve individuals who are descriptively representative of their proclaimed constituency with regard to their preferences, opinions and needs, such responsiveness might generally be facilitated. As a third aspect, we have mentioned a number of skills that enable representatives to construct the will of their proclaimed constituency on the one hand, and on the other,  to incorporate these contents in the concrete decision‐making process. Taken as a whole, the three criteria mentioned may lead to participation being practiced purposefully in the health care system and elsewhere. Nevertheless, it cannot be emphasized enough that in practice, there can probably be no such thing as ideal‐typical representation, and hence representation will always be imperfect.Additionally, in the context of this paper, we have not gone into detail about one group of actors, although certainly, this one is of enormous importance for the health sector: self‐authorized representatives. Their representational practices differ substantially from those of formally appointed representatives, but the mechanics of dynamic representation can and should be applied to them as well. Even more, some argue that these actors could be key to establishing comprehensive and pragmatic representation practices.,p.246 .,p.103 and this could lead to an overrepresentation of the already well‐represented.One reason for organizers planning representation insufficiently is that good representation could make them vulnerable and reveal weaknesses that they do not want to be revealed. It may be for this reason that participation is often reduced to a zeitgeist token. Mediating the perspectives of the involved actors in an efficient and appropriate way is a major task and is of importance to science and society as a whole. Due to the relative complexity of representation, representative claims often pass by without being questioned by independent actors. Accordingly, representation is not always a justified means to an end. Quite the contrary, it may increase the danger of the represented people's voices being misused to justify individual acts. Only when legitimate representation is assured, or at least adequately addressed, can this danger be faced in an appropriate way. With the help of legitimate representation, more inclusive and hence fundamentally better decisions can be made. Reflecting on practiced representation may give valuable insight into where violations against legitimacy are visible. In this way, certain forms of representation that are rarely questioned and are thereby stabilized may be overthrown. Instead of taking representation for granted and thus neglecting it in health care settings, we need to elevate the involvement of lay people beyond tokenism by ensuring legitimate representation in all participatory settings. This is particularly relevant for health settings, where some groups are more marginalized than others and seldom heard and where questions of self‐determination and autonomy in the context of vulnerability are always present. Making an appropriate choice of representatives is therefore an ‘ethical necessity’One of the main issues with representation is that the complex consequences of poor representation often are not necessarily recognizable as problems of representation, but rather as those of decision‐making arrangements, available resources or for other reasons. If, for example, patients are negatively affected by a decision made in the context of the FJC, in most cases, they may not even know who was present for them in the decision‐making process. Therefore, they cannot make a statement about the representation as such but only judge the decision to be negative for them. In this scenario, representation can hardly be identified as a quality criterion of participatory decision‐making. What follows from this is that one might jump to the hasty conclusion that representation is inherently irrelevant. This may lead to the blanket impression that it is unlikely to make any difference in which individuals are included in any given setting. Nevertheless, the ill‐considered selection of representatives, who neither show a dynamic relationship with the group they claim to represent nor necessarily share their identity or have certain abilities, leads to the risk that these representatives will be unable to give any meaningful input to a given decision‐making process. Furthermore, even though patients and other people represented in such settings might be unwilling to monitor the representative legitimacy of such participatory settings and/or function as a representative themselves,The authors declare no conflicts of interest.