Raising prices through taxation on tobacco and alcohol products is a common strategy to raise revenues and reduce consumption. However, taxation policies are product specific, focusing either on alcohol or tobacco products. Several studies document interactions between the price of cigarettes and general alcohol use and it is important to know whether increased cigarette prices are associated with varying alcohol drinking patterns among different population groups. To inform policymaking, this study investigates the association of state cigarette prices with smoking, and current, binge, and heavy drinking by age group.The 2001-2006 Behavioral Risk Factor Surveillance System surveys  were pooled and analyzed using multiple regression equations to estimate changes in smoking and drinking pattern response to an increase in cigarette price, among adults aged 18 and older. For each outcome, a multiple linear probability model was estimated which incorporated terms interacting state cigarette price with age group. State and year fixed effects were included to control for potential unobserved state-level characteristics that might influence smoking and drinking.Increases in state cigarette prices were associated with increases in current drinking among persons aged 65 and older, and binge and heavy drinking among persons aged 21-29. Reductions in smoking were found among persons aged 30-64, drinking among those aged 18-20, and binge drinking among those aged 65 and older.Increases in state cigarette prices may increase or decrease smoking and harmful drinking behaviors differentially by age. Adults aged 21-29 and 65 and older are more prone to increased drinking as a result of increased cigarette prices. Researchers, practitioners, advocates, and policymakers should work together to understand and prepare for these unintended consequences of tobacco taxation policy. Alcohol and tobacco use lead to enormous human and economic costs in the U.S. In the past few decades overall rates of smoking and drinking have declined ,2. HowevBiological, genetic, behavioral, socio-demographic, and policy factors can provide insight into understanding the link between alcohol and tobacco use and co-use that may, in turn, influence how tobacco control policies influence drinking behavior. Studies suggest there are biological and shared genetic components in using and becoming dependent on alcohol and nicotine both separately and together -23. BehaSocio-demographic factors such as age, gender, race/ethnicity, education, socio-economic status, marital status, and employment status are associated with differences in smoking and drinking ,26. For Socio-economic and governmental practices and policies influence use. As an example, tobacco and alcohol companies use similar advertising and marketing practices which have been found to increase consumption of tobacco and alcohol ,33. GoveEconomics provides an understanding of further mechanisms influencing smoking and drinking. According to the theory of consumer demand, an increase in the price of a good (e.g. cigarettes) would be predicted to lower consumption of that good . HoweverIn policy-making, cross-price relationships of goods may lead to intended and unintended consequences. For instance, increases in the price of cigarettes through taxation may decrease consumption of cigarettes (an intended consequence) and decrease harmful alcohol consumption if the goods are complements, arguably a positive unintended consequence. However, if the goods are substitutes and harmful drinking patterns amplify, then a negative unintended consequence might occur after cigarette prices increase. As policymakers may focus on the reduction of cigarette and alcohol consumption by youth and young adults as a reason for raising excise taxes, whether these taxes are associated with cigarette and alcohol use by young, in comparison with older persons, may be of interest to them.While some literature examines the influence of cigarette prices on the prevalence and consumption of alcohol, there is no consensus among researchers on whether drinking increases or decreases as a result of cigarette prices ,16-18,38Only one of these studies investigated the impact of increases in cigarette price on current and binge drinking . No studGiven public health goals of preventing and reducing binge and heavy drinking, and the sharp differences in drinking patterns by age, this study aimed to address the significant gap in the literature on the impact of increased state cigarette price on alcohol drinking behaviors across age groups, with a particular focus on younger age groups. Since most of the U.S. research suggests that increases in cigarettes prices are associated with reductions in smoking and increases in drinking among the young, the primary hypothesis of this research was that increases in state cigarette prices would produce stronger reductions in current smoking, and stronger increases in current, binge, and heavy drinking among young adults (those under 30 years of age), than among those aged 30-64 and 65 and older.This study analyzed six years (2001-2006) of nationally representative data from the Behavioral Risk Factor Surveillance System (BRFSS) surveys. Full details of the BRFSS design are available elsewhere . The priDue to different stratification sampling approaches, the U.S. territories were dropped from the sample, as were observations from Maine, New Hampshire, and Rhode Island  which did not report results for the beer price variable. This yielded a sample size of 1,623,615 independent observations. Listwise deletion was used to address missing data  , leavingThe four dichotomous outcome measures were current smoking; and current, binge, and heavy drinking. Participation in current smoking; and current, binge, and heavy drinking were coded as 1 for survey participants who responded that they participated in these behaviors and coded 0 otherwise. During 2001-2006 the BRFSS defined current smoking as having smoked in the last 30 days, and current drinking as having at least one alcoholic beverage in the past 30 days . For menThe main explanatory variable was cigarette price, a continuous variable reflecting weighted average price of cigarettes (including generic brands) in dollars by state and year . To corrThe age variable consisted of categories of those aged 18-20, 21-29, 30-64, and 65 years and over, in order to observe hypothesized variation between younger age groups (those under the age of 30) and older age groups. Binge and heavy drinking rates are highest among younger age groups and drop dramatically after age 65; an overall flattening of prevalence rates occurs between ages 30-64. Thus, we focus on differentiating the age groups of those under 30. Also, increases in excise taxes are passed by policy makers to reduce the prevalence of smoking and drinking among young people .Additional individual-level variables were used to adjust for potential influences on smoking and drinking behaviors: gender; race/ethnicity; educational level; and partner, employment, and poverty status. Gender was a dichotomous variable, with males being the reference group. Race/ethnicity was an eight-category variable with Non-Hispanic whites as the reference group. The educational level variable had four categories with college graduates and above as the reference category.Since drinking and smoking may vary by partner, employment, and poverty status, as described above, we used them for adjustment purposes. We collapsed them into categories that would have meaning for both alcohol and tobacco use. Partners (i.e. married or in an unmarried couple) were coded as 1 and those who were not in a partnership  were coded as 0. Employment status included the categories unemployed, employed (reference group), or not in the labor force. Poverty status was a categorical variable that was calculated using U.S. Department of Health and Human Services (DHHS) guidelines which included household income, household size, and state of residence . The BRFBeer price data from the American Chamber of Commerce Researchers Association (ACCRA) reported the retail price of a six-pack of Heineken and included federal, state, and local taxes, but excluded sales taxes and deposits . ACCRA’sWe developed an ordinal variable measuring smoking restrictions (range 0-12) for each state. Drawing on prior work ,53, the To adjust for overall trends in state-level economic indicators, yearly state poverty rates were included as a continuous covariate. State median household income and state unemployment rate were considered as potential co-variates, but because of their high correlations with other variables, they were excluded from final analyses. The four state-level variables that had the strongest support in the literature and the data available for inclusion remained: state cigarette price, state beer price, the magnitude of state smoke-free laws, and state poverty rate.Year and state dummy variables were included as fixed effects to account for other unmeasured factors at the state level that might have been correlated with smoking and drinking. The survey year  and state of residence (one out of a possible 47 possible states and the District of Columbia) were included as dichotomous variables. Finally, we weighted all data using the BRFSS weights. These weights adjust for non-response and non-coverage for geographical strata, to adhere to sample estimates of those geographical areas, and to take into account state stratification by age, gender, and race/ethnicity. Full details of the BRFSS design and weighting are available elsewhere .To test study hypotheses and address clustering that may occur at the state level over time, we estimated a series of linear regression equations using state and year as fixed effects . A conceUnivariate and bivariate analyses were conducted to determine variable means and relationships between cigarette price, age and smoking, and similarly for the three drinking variables. For each of the four outcome variables we estimated a linear probability model (LPM), using interaction terms (which interacted each age group with mean state cigarette price) to test hypotheses. All models included the same variables. Although the outcomes were binary, for which logistic regression usually is used, our inclusion of interaction terms introduces challenges with interpretation in nonlinear models. LPM has been found to be an appropriate and useful method for interpreting interaction terms when estimating models for binary outcomes ,14,56-59All statistical analyses were performed using SAS version 9.2 , utilizing procedures that address the complex sampling design of the BRFSS and adjust standard errors using the Taylor linearization method for computing variances . The LPMTable Table Regression results in Table Table Cigarette price was associated with current, binge, and heavy drinking differentially by age group. For current drinking, a $1 increase in cigarette price was associated with an increase in drinking prevalence of 3.72 percentage points for those aged 65 and older, and a reduction of 4.02 percentage points for those aged 18-20. A $1 increase in price was associated with an increase in binge drinking of 4.06 percentage points for those aged 21-29, and a reduction of 1.95 percentage points for those aged 65 and older. Finally, an increase in cigarette price was associated with a significant increase of 1.15 percentage points in heavy drinking for those aged 21-29, a population that already has higher rates of drinking. An increase in cigarette price did not significantly impact any drinking pattern for those adults 30-64.This study examined the associations of state cigarette prices with smoking, and current, binge, and heavy drinking by age group. The study’s novel findings are that increases in cigarette price are associated with increased smoking and drinking among those 65 and older, and increased binge and heavy drinking among those aged 21-29. These associations were not necessarily in the directions initially hypothesized. As shown in Table , smoking among the age groups under 30 was not associated with a significant response to cigarette price in this study. This finding is similar to Sloan and Trogdon, who also did not detect significant associations in a study including those aged 21-24 [In terms of current smoking, the response for those aged 30-64 mirrored the bulk of the literature: an increase in cigarette price was associated with a decrease in smoking ,11. Howe4ed 21-24 . While aed 21-24 . Those yed 21-24 ,63.For current drinking, and consistent with some other studies ,64, thisA concerning finding from this study is that higher cigarette prices were associated with higher rates of both binge and heavy drinking among those aged 21-29, the age group that already has the highest prevalence of smoking and current, binge and heavy drinking of any age group. The response of binge and heavy drinking to cigarette price did not vary across the other age groups, with the exception of a reduction in binge drinking for those aged 65 and older. Only one other study, by Dee , comparePrevious studies have found that drinking increases in response to increases in cigarette price ,18,38, bThis study has limitations and strengths. First, BRFSS does not collect data on persons who live in institutions, the military, and the homeless. Second, as a telephone survey, the dataset may have bias due to its under-coverage of those individuals who do not have landlines. BRFSS documentation acknowledges that some populations  are less likely to have landlines and the data may not be representative of those populations . HoweverIn summary, age matters, as cigarette prices can be associated with unintended consequences on smoking and drinking behaviors among and across different age groups. Understanding the effects of cigarette taxation policy on different populations is important, as there has been a trend over the last decade for states to increase cigarette taxes, both to advance public health goals, as well as to fill dwindling state coffers. This study adds some cautionary information to decision-makers regarding the attainment of public health goals. Although increasing cigarette taxes has been used widely to prevent and reduce tobacco use, this study suggests there may be unintended consequences for policymakers to consider. Increases in cigarette taxes may result in reductions in: smoking among those aged 30-64, drinking among those aged 18-20, and binge drinking among those aged 65 and older. However, increases in cigarette price through taxation could increase: smoking and drinking among those 65 and older, and binge and heavy drinking among those aged 21-29. Preparing for potential increases in problematic drinking among these age groups could be considered through targeted programming to populations and outreach to practitioners.Additionally, while there are many researchers and advocates in the alcohol prevention and tobacco control fields, few study both topics. More interdisciplinary behavioral, economic, and health research would benefit our understanding of the prevention, use and co-use of alcohol and nicotine. Advocates and policy-makers could also collaborate and coordinate on policy-making after research has been conducted and plans made for unintended consequences. To our knowledge, a national, purposive, simultaneous campaign to increase alcohol and tobacco prices together has not been conducted, and it is unclear whether such efforts have occurred on the state level. Before creating a campaign to increase simultaneously taxes on alcohol and tobacco products, economic modeling is needed both to arrive at an optimal tax and to understand potential unintended consequences, like the ones found in this study. Tobacco control and alcohol prevention researchers, advocates, practitioners, and policymakers should work together to understand and prepare for unintended consequences of tobacco taxation policy.BRFSS, Behavioral risk factor surveillance system survey; LPM, Linear probability model; SE, Standard error.The authors declare that they have no competing interests.DM conceptualized the study, conducted the analyses, interpreted data, and drafted the article. DH advised on study design and analyses. DH, PF, SR, and CH contributed to interpretation and manuscript revisions. All authors read and approved the final manuscript.


The observation of conspecifics influences our bodily perceptions and actions: Contagious yawning, contagious itching, or empathy for pain, are all examples of mechanisms based on resonance between our own body and others. While there is evidence for the involvement of the mirror neuron system in the processing of motor, auditory and tactile information, it has not yet been associated with the perception of self-motion.We investigated whether viewing our own body, the body of another, and an object in motion influences self-motion perception. We found a visual-vestibular congruency effect for self-motion perception when observing self and object motion, and a reduction in this effect when observing someone else's body motion. The congruency effect was correlated with empathy scores, revealing the importance of empathy in mirroring mechanisms.The data show that vestibular perception is modulated by agent-specific mirroring mechanisms. The observation of conspecifics in motion is an essential component of social life, and self-motion perception is crucial for the distinction between the self and the other. Finally, our results hint at the presence of a “vestibular mirror neuron system”. Self-motion perception is crucial for the survival of the species to distinguish between one's own body motion and the motion of the external world, including conspecifics and objects located around us. Various studies have demonstrated the contribution of vestibular In this study, we investigate whether the observation of conspecifics can influence self-motion perception. The present research question is motivated by the importance of shared body representations between the self and others In this study 21 healthy volunteers participated . All participants were right-handed except one, as confirmed by the Edinburgh Handedness inventory Motion stimuli were generated using a six degrees of freedom motion platform (MOOG 6DOF2000E) . Nine paVisual stimuli consisted of three categories of videos. Videos were either of the participant (self video), another unknown participant , or a cylindrical white object located on the same motion platform (object video)  with their index fingers. Participants were instructed to press a button with their right index finger if the perceived self-motion was directed to their right. Conversely, they had to press a button with their left index finger if the perceived self-motion was directed to the left.Video  ×2 Motion Congruency (congruent vs. incongruent motion direction of the video and the motion platform) ×4 Velocity  design, with 16 repetitions of each of the 24 stimulus combinations. Thus, each participant completed 384 trials. In order to create conflict between vestibular and visual signals, we manipulated the congruency between the direction of the observer's body rotation and that of the object seen in the video , with response times being shorter for higher angular velocities of the motion platform . That is, response times were longer when self-motion and the motion displayed in the video were incongruent.The average response time was analyzed using repeated-measures ANOVA with the within-subject factors: Velocity , Motion Congruency , and Video . F2,40 = 3.76, P = 0.03), indicating that visual-vestibular congruency effects were modulated by the social information provided by the video  and object video , but not for the other video . The mean congruency effect (CE), calculated as the difference in response times between the incongruent and congruent trials, was 107±36 ms for the self video and 87±36 ms for the object video. Post-hoc analysis revealed that the mean CE for the other video (7±29 ms) was significantly reduced when compared to the CE for the self videos  and the object videos (P = 0.016). There was no difference between the CE for self videos and object videos (P = 0.64). These results indicate that the observation of one's own body motion, or the motion of an object, disrupts self-motion perception when the motion is incongruent. A post-hoc analysis of the interaction of Motion congruency×Video revealed that response times for incongruent trials when viewing the self video are significantly higher than when viewing the other video   which is illustrated in F2,40 = 0.61, P = 0.55) and no significant interaction of Velocity×Video  and of Velocity×Motion Congruency .Noteworthy is the nearly significant three-way interaction between Velocity, Video, and Motion Congruency . As illustrated in F1,20 = 12.68, P<0.005). The participants discriminated better their own body motion when observing a video moving congruently (i.e. in a specular way) than when observing a video moving incongruently. There was a nearly significant main effect of the Video , suggesting that the information displayed in the video influences the performance (t-tests) revealed overall better performance for self-motion perception when participants saw their own body in the video , irrespective of the motion congruency. The analysis also revealed a significant interaction of Velocity×Video , suggesting that task difficulty (the velocity of the platform) influenced differently self-motion perception according to the item depicted in the video. Post-hoc analyses (two-tailed paired t-test) showed higher accuracy for self videos than object videos for platform velocities of 0.6°/s , 1.1°/s (P<0.05) and 4°/s (P<0.05), as well as higher accuracy for self videos than other videos for platform velocities of 0.6°/s (P<0.05). The opposite effect, i.e. higher accuracy for object videos than other videos and self videos, was found only for platform velocity of 1.1°/s (P<0.05). Finally, there was no interaction of Video×Motion Congruency , of Velocity×Motion Congruency , and the three-way interaction of Velocity×Video×Motion Congruency  was not significant.The same repeated-measures ANOVA was run on the percentage of correct answers  and Object videos , while the social skills subscale was positively correlated with the CE for Object videos . At first sight, the correlation of empathy scores with CE when seeing another person may appear counterintuitive. The mean CE is strongly reduced in this condition. However, individual CEs range from −268 ms to +223 ms. Those participants who showed higher empathy scores also showed a positive CE, albeit much less than for the self and object conditions .Individual CEs for each video type were correlated with participant scores on the Empathy Quotient The key finding of this experiment shows that self-motion perception is influenced by the observation of the self and objects in motion, but, to a lesser extent when viewing others in motion.one's own body in motion. A first important result is that participants performed on average better (higher accuracy) when they saw their own body being moved than the body of someone else or an object being moved. This result is in line with previous studies on multimodal integration showing an advantage of seeing one's own body for various aspects of self perception. Serino et al. These findings provide the first demonstration that self-motion perception is modulated by the observation of one's own body in motion is that the observation of the self in motion, in a specular way , results in more efficient self-motion perception than the observation of non-specular motion . Thus, our data indicate that visual-vestibular associations subserving self-motion perception operate in a specular way, instead of in an anatomical way . A similar trend has been observed regarding tactile perception in mirror-touch synesthetes, a population of individuals who experience tactile sensations when observing touch applied to another's body. Indeed, most synesthetes experienced touch on their body part (e.g. right cheek) that is opposite to the touch seen on the other's corresponding body part (e.g. left cheek), as is they were looking at their own body in a mirror The second new and important result concerning the observation of another's body in motion may have a similar influence as the observation of one's own body in motion. While our data show similar visual-vestibular congruency effects on the accuracy of self-motion perception when viewing the self or another body in motion, another important finding from this study is that the analysis of the response times revealed a marked reduction in the CE during the observation of another body in motion. We found that the range of the CE was shifted to lower values during observation of other videos (−268 ms to +223 ms) as compared to self videos (−223 ms to +504 ms), showing a reduced impact of observing another's body on self-processing. This indicates that while a mechanism of perceptual resonance with others does exist (positive CEs are reduced but present in some participants), there appear to be higher-order cognitive processes that can modulate resonance between self and others in the present task. This is in line with the view that the mirror neuron system's tendency to simulate another person's actions and feelings is modulated by several cognitive, social and emotional factors . If the Simon effect were driving our results, it would have affected all visual conditions , which was evidently not the case. There was no difference between the response times for congruent and incongruent trials when the participants were exposed to the video showing another person . Although the videos used in the present study did not include a coherent optic flow (i.e. an optokinetic stimulation) that could induce a proper illusory self-motion perception ion e.g. . For exaWe found that visual-vestibular CE correlated with emotional reactivity when viewing others in motion, lending support to the view that shared body representations between the self and others are linked to empathy abilities The results from this study propose that self-motion information and social visual information converge in multimodal brain regions. Vestibular signals are processed mostly in the temporo-parietal junction, as well as in the insular, superior temporal, posterior parietal, and cingulate cortices vestibular mirror neuron system and will hopefully stimulate further research questions for basic and clinical research alike.In conclusion, the present study provides evidence for vestibular resonance when viewing the self, others and objects moving within our environment, but also suggests different mechanisms when observing other people in motion. The observation of conspecifics in motion is an essential component of social life, and self-motion perception is crucial for the distinction between the self and the other. Our results hint at the presence of a


A randomized controlled trial of screening, brief intervention, and referral to treatment (SBIRT) for drinking and related problems among at-risk and dependent drinkers was conducted in an emergency department (ED) at the US-Mexico border among Mexican-origin young adults. Data collection over a period of 17 months resulted in 698 patients recruited into the study and randomized to one of three conditions: screened only (n=78), assessed (n=310), and intervention (n=310). Patients in the assessment (77%) and intervention (72%) conditions were blindly reassessed at three months via one telephone interview. No difference was found in baseline demographic or drinking characteristics between the assessment intervention groups. At follow-up, the intervention group showed significantly greater decreases in five of six outcome variables: number of drinking days per week, average number of drinks and per drinking day, maximum number of drinks, RAPS4 score as an indicator of alcohol dependence and number of negative consequences related to drinking. Using analysis of covariance to control for baseline measures, the intervention group was lower on all drinking and problem measures than the assessment group, and significantly so on four of the measures. When the interaction of intervention by injury status (injury vs. non-injury), drinking within six hours prior to the event, causal attribution of the event to drinking and risk taking disposition were examined, only causal attribution had a significant effect for two of the problem measures – the intervention effect for the RAPS4 and negative consequences was greater for those who believed their injury or illness was related to their drinking. Findings here suggest that brief intervention was effective in this population compared to assessment at three month follow-up, and may be most effective for those linking the reason for their ED visit to their drinking.


Video communication is increasingly used to connect people around the world. This includes connecting young children with their parents and other relatives during times of separation. An important issue is the extent to which video communication with children can approximate a physical presence such that familial relationships can be truly maintained by this means.The current study employed an adaptation of the Separation and Reunion Paradigm with children (17 months to 5 years) to investigate the potential for video communication with a parent to afford a sense of proximity and security to children. The protocol involved a free-play session with the parent, followed by two separation-reunion episodes. During one of the separation episodes the parent was ‘virtually available’ to the child via a video link. Our results revealed three important differences. First, children left alone played longer in a strange room when their parent was virtually available to them compared to when the children were left alone with neither physical nor video contact with their parent. Second, younger participants sought physical contact with their parent less at the end of the video separation episode compared to when they were left entirely alone. Finally, the comparison between free play with video and free play with parent, revealed that the children exhibit a similar level of interactivity with their parent by video as they did in person.For young children a video connection can have many of the same effects as a physical presence. This is a significant finding as it is the first such empirical demonstration and indicates considerable promise in video communication as a tool to maintain family relationships when physical presence is not possible. Since Bowlby Communication via the internet is a particularly popular means of maintaining contact with family members. In a recent survey of online users, almost half of over 6000 respondents indicated that the internet has improved relationships with their family overall, with 42% reporting that they had engaged in video communication with family or friends Video communication is also increasingly prevalent in connecting young children and their relatives. Encouraging and supporting such interactions has been the development of purpose-built internet software and the marketing of specially designed devices th century Advances in technology are often credited with dramatic social changes with potentially widespread (and often unpredictable and/or negative) effects on children's psychological and physical development Of potentially greater relevance to the focus of this paper, children are also separated from their parents for a variety of reasons. Almost half of divorces involve children, and more than half of young children (<5 years) from separated families see their non-custodial parent less than once a fortnight During such times of separation, video communication may provide these young children with the connection to their parent(s) and assist the children by psychologically lessening the distance caused by geographical separation.Video communication is a seemingly rich experience, however a large body of research exists illustrating that young children treat people on video differently than people that they see face-to-face Our experimentation strategy involved a modified version of the Separation and Reunion Paradigm Conversely, an alternative hypothesis was that the presence of the parent via the video link would serve only as a reminder to the child that their parent was not actually present, and that children of some ages would find the virtual presence of their parent distressing rather than reassuring. This later hypothesis reflects previous research findings that demonstrate that toddlers treat face-to-face and online interaction differently The experiment was conducted in two adjoining lab spaces; a playroom and a computer room. A 175 cm×300 cm lab was set up as the play room and contained a couch and age appropriate toys including a drawing easel and pens, blocks, a train set and soft toys. The computer monitor sat on a shelf 1 m high positioned across the front wall with the computer box located out of reach of the children. An Ethernet cable connected the computer in the play room to a computer in the next room.Three cameras were positioned within the play room: Camera A was attached to the wall in the back left corner of the room, behind the couch; Camera B was attached to the couch arm in the back right corner of the room; and Camera C was attached to the computer monitor. See security score was obtained by averaging those item scores. Comparable to the Q Set scoring, a score of +1 would reflect a perfect positive correlation to a prototypically secure child whereas a score of −1 would reflect a perfect negative correlation to a prototypically secure child. Positive scores would therefore indicate a child is securely attached. Results for the subset of participants whose parent completed this questionnaire revealed that all security scores corresponded to that of a secure child . The findings of the current study are likely reflective only of securely attached children.A sub-set of participants (n = 28) completed a questionnaire based on the Attachment Q Set . The questionnaire asked parents to rank on a 5 point Likert scale  ranging from −1 = “not at all like my child”, to 1 = Very much like my child, the degree to which statements (borrowed from the Attachment Q Set cards), are generally characteristic of their child. For the current study only the specific behavioral characteristic that would be most descriptive of the prototypically secure child, have been considered and a M = 35.2, SD = 14.3), including 21 females and 20 males. Ten children were aged 17 months <2 years, 7 were aged 2<2.5 years, 8 were aged 2.5<3 years, 8 were aged 3 years, 6 were aged 4 years and 3 were aged 5 years. The majority of children (85%) participated with their mother rather than their father. Participants were recruited through various avenues including advertisements online and in newsletters, and word-of-mouth referrals.Forty-five children participated in the experiment, however, as a result of technical problems in our apparatus four participants have been excluded from the analysis. Participants included in the analysis were 41 children aged 16.9–64.8 months  that the child was physically alone in the room until they began to cry and continued crying for 10 seconds, or tried to leave the room. This variable had a maximum value of 300 seconds, as this was the maximum duration of each separation episode.From the video recordings of the episodes, the measure proximity variable was created, noting whether or not the child moved towards the parent when they entered the room after each separation. This variable was only investigated in children under 3 years of age, as proximity seeking behavior is normal for such children and less usual for older children in Phase 4 of the development of attachment To compare the reunion episodes following the video and non-video separation episodes, a To investigate the amount of time that the child played with toys and/or interacted with their parent, each 10 second period of the free-play, the video separation and the non-video separation episodes were coded. Only the first five minutes (I.e. 300 seconds) of the free-play session was coded to allow comparisons to be drawn between the free-play session and the separation episodes. Thus there were thirty 10-second intervals in each of the three periods (or less in the cases when the child remained in the room for less than the full 300 seconds of the separation episode).play criterion and the interaction criterion were defined as the number of 10-second periods during which the participant touched/played with the toys or otherwise interacted with their parent, respectively. The maximum score for any episode was 30. Variables were also computed to investigate the percentage of each episode that participants played, and percentage of each episode that participants interacted with their parent, since separation episodes were not all of equal duration. For example if a child played for 15 of the thirty 10-second intervals for which the child was in the room, the play percentage was 50%.Using the results of the 10-second interval coding the proximity , and play  with 40% of cases. Additionally there was an inter-coder correlation of 99% on contentment duration (p<.001).Cohen's Kappa was computed to determine inter-rater reliability for Preliminary statistical analyses indicated that the child's gender and previous video communication experience did not have any effects on the dependant variables. Therefore these variables have been eliminated from further analysis. Individual participant data can be found as The duration of contentment showed a marked difference across the two separation conditions with participants content to remain separated from their parent for significantly longer during the video separation episode compared to the non-video separation episode. In entirety, 85% of the participants were content for the whole video separation interval; whereas only 37% remained content when there was not a video link available.2 = 35.86, p<.001. Median values showed that participants played most during the free-play session, followed by the video separation episode and least during the non-video separation episode. Further planned comparisons using Wilcoxon Signed Ranks tests indicated that participants played significantly more during the free-play episode than during either the video or non-video separation episodes, and participants played significantly more during the video separation episode than during the non-video separation episode.We compared the amount of time that participants played during the free-play session, the video separation episode, and the non-video separation episode. A Friedman test indicated these conditions differed, χ2 = 35.58, p<.001. Median values showed that participants played for the greatest percentage of time during the free-play session, whereas they played for only about half the time in both separation episodes. Further planned comparisons indicated that participants played significantly more during the free-play episode than both the video and non-video separation episodes, however the separation episodes did not significantly differ.To control for the differences in the amount of time that participants remained in the room across the free-play and the two separation episodes, the percentage of time periods during which participants played while they were in the room was compared across conditions. A Friedman test showed that the percentage of time spent playing varied significantly, χComparing the amount of time that participants spent interacting with their parent during the free-play and video separation episode showed that participants interacted to the same degree with their parent during the video separation episode as the free-play episode.For the children under three years-of-age, we also tested for proximity seeking behavior after each separation episode. Significantly more children of these ages moved towards their parent during the reunion that followed the non-video separation than the reunion that followed the video separation.n = 10: 1.5<2 years, Gp2, n = 7: 2<2.5 years, Gp3, n = 7: 2.5<3 years, Gp4, n = 7: 3<4 years, Gp5, n = 9: 4<6 years). No significant age differences were found for three of the variables: the percentage of interaction during the video separation episode; the difference in contentment duration between the video and non-video separation episodes; and the duration of contentment for the non-video separation episode.To examine other possible age differences Kruskal-Wallis tests were performed to compare results across different age groups  = 10.531, p = .032. The 3<4 year-old and the 4<5 year-old participants were content equally for the longest period of time (Md = 300 s) and the 2<2.5 year-old participants were content for the shortest period of time (Md = 70 s). See Age groups differed significantly on 2 = 10.676, p = .030. The 3<4 year-old and the 4<5 year-old participants were most likely to continue for the entire 300 seconds and the 2<2.5 year-old participants were the least likely.Moreover, there was a significant difference across age groups in the number of participants who were content for the entire 300 seconds of the video separation, χThe fundamental contribution of this research is the discovery that a parental presence via video link is sufficient to allow young children to feel secure in an unfamiliar environment. This empirical verification is crucial in considering the potential of video communication to play a role in the maintenance or formation of secure attachments.Our conclusions are based on four measures of child behavior: duration of contentment, interaction with the parent, engagement in play, and response to reunion, all of which are common indices of attachment security Firstly, we consider duration of contentment, as that is arguably the most direct measure of how secure our participants felt when they were in the room. Children of all ages were content to be alone without a parent physically present significantly longer in the video separation than the non-video separation episode. Further, a greater percentage of children were content for the entire five-minute video separation than non-video separation. Interestingly almost all of the participants that did not remain content for the entire five minutes of the separation, showed signs of distress within two minutes of their parent leaving the room. Despite the brevity of the separations, it is probable that provided the opportunity, the content participants would have remained content far beyond the given five minutes, however future studies should address this question.Secondly, our interaction measures revealed that children interacted slightly (though not significantly) more with their parent during the time that the parent was in the room than during the video separation episode. Notably however, there was no significant difference between the two episodes in the percentage of time that children interacted with parents. Thus, when children were content in the room they interacted with their parent as much in the video separation as they did when the parent was actually present. This is important because it suggests significant similarities between the quality of the virtual presence compared with real presence.Thirdly, play was also an important measure in our study as it is an indicator of the extent to which a virtual parental presence can substitute for a physical secure base for exploration. Results indicated that children across all ages played for longer during the video separation than the non-video separation. However this result may arise, at least in part, because children could only play for the duration that they were in the room. Children who are content longer will have more time to play in the room and thus did so. Conversely, children who feel secure enough to use the video as a secure base for exploration will also be likely to stay in the room longer (and consequently play for longer).In an attempt to partially control for duration of contentment we compared the percentage of time that they played for while they were content to be in the room. However, results revealed that children only played for about half of the time that they were in the room during both separations compared to when they were present with their parent. The failure to find differences in percentage of play between the video separation episode and the non-video separation episode may, however, be due to other differences in the nature of interaction in these two separation episodes.Furthermore, the interaction measure should be considered in any interpretation of how much children played. Since video communication is still a relatively unusual activity in most households, the novelty of talking to a parent over a video link could be interpreted as “play” for many children. This might explain why the play percentage was not higher in the video separation condition than the non-video condition. That is, the play measure may be underestimating play during the video separation episode since we did not include video interaction with their parent within the measure play. Collapsing across interaction and play measures may be considered an option to overcome this discrepancy, however this variable would not allow comparison with the non video separation as there was no opportunity for interaction during that episode.Additionally, there may be subtleties of how one interacts, plays and talks with a parent when they are actually present rather than virtually present that accounts for differences in play between these conditions. When playing and interacting within the presence of the parent, a child can interact, talk and play simultaneously and can readily assume that their parent is watching them. However, during the video separation, children may have paused more often in their play to turn and look at their parent on the monitor to interact with them. This may be especially so when children are not familiar with this medium, or when the video separation is occurring in a strange situation.Finally, observations of the reunions demonstrated that the younger participants (under 3 years), were significantly more likely to move to contact their parent following the non-video separation than the video separation. This result is consistent with the literature that suggests that a child tends to seek proximity when attachment behavior is intensely activated In sum, our results form compelling evidence that a parent's virtual presence is sufficient to increase the level of security felt by young children with pre-existing strong attachments in an unfamiliar environment. This is an important finding as it suggests that relationships between children and their parents could benefit from video communication when face-to-face contact is not possible.It is conceivably possible that some children were happier during virtual communication because they were distracted from their separation by the novelty of talking to a parent via video. Although studies are underway to assess this possibility, it is important to note that a video of a person could also remind the child of the person's absence, rather than distract them from it. To some extent, the novelty issue was addressed through our analysis of the children's prior experiences with video communication. Children with less video communication experience would arguably be more likely to be subject to such a “novelty effect.” However, our results did not reveal effects of previous video communication experience on any dependent variable.However, as video communication becomes more commonplace in society the role of prior experience with this medium may change, particularly if children are exposed to video communication at a very early age. These children may develop a level of expertise that allows them to better understand the precise extent to which a video can stand in for an actual person and where it suffers limitations. This might affect results in studies such as ours by attenuating the effect of age on duration contentment, or how play and interaction with the parent is negotiated via video. Investigation of which aspects of this communication medium are the most beneficial or problematic for young children is also required. As previous research has shown that young children have difficulties with traditional telephone conversations The study described here investigates the developmental effects of a relatively new technology, but somewhat ironically its usage has the potential to bring us closer to societal norms that existed in the past. Whereas only a few decades ago multiple generations often lived under one roof (or at least within the same neighborhood), extended families are increasingly separated by large distances so face-to-face contact is limited Data S1Supporting data.(XLS)Click here for additional data file.


Aspergillus nidulans. Fluorescence analysis of haploid and diploid strains expressing KapB::GFP and/or KapA::mRFP showed patches of both karyopherins concurrently translocating long distances in apically-growing cells. Anterograde and retrograde movements allowed those patches to reach cell tips and distal regions with an average speed in the range of μm/s. This bidirectional traffic required microtubules as well as kinesin and dynein motors, since it is blocked by benomyl and also by the inactivation of the dynein/dynactin complex through nudA1 or nudK317 mutations. Deletion of Kinesin-3 motor UncA, required for the transport through detyrosinated microtubules, strongly inhibited KapA and KapB movement along hyphae. Overall, this is the first report describing the bidirectional dynamics of the main nuclear import system in coenocytic fungi. A functional link is proposed between two key cellular machines of the filamentous fungal cell: nuclear transport and the tip-growth apparatus.Karyopherins are transporters involved in the bidirectional, selective and active transport of macromolecules through nuclear pores. Importin-β1 is the paradigm of karyopherins and, together with its cargo-adapter importin-α, mediates the general nuclear import pathway. Here we show the existence of different cellular pools of both importin-α and -β1 homologues, KapA and KapB, in the coenocytic ascomycete  Cells develop polarity to orient their activities in a variety of different ways . For exaNeurospora crassa and Aspergillus nidulans 82]. Video S1KapB::GFP movement through the cytoplasm of vegetative hyphae . Videos were constructed using MetaMorph® and/or ImageJ software . Time scale is indicated in sec. Note the movement of KapB::GFP patches through the cytoplasm to the tip and distal regions. Patches crossed SPBs and cytoplasmic MTOCs.(AVI)Click here for additional data file.Video S2KapA::mRFP movement through the cytoplasm of vegetative hyphae . Video displays 7 fs and time scale is in sec. KapA::mRFP moves to the tip and distal regions in patches.(AVI)Click here for additional data file.Video S3Movement of KapB::GFP and KapA::mRFP patches through the cytoplasm of diploid vegetative hyphae . Both fusions move simultaneously. KapB::GFP and KapA::mRFP analysis was done using a dual-channel acquisition device . The video combines three streams: green/GFP (up) and red/mRFP (middle) channels with a third merged video in magenta (bottom). Video displays 5 fs and time is indicated in sec.(AVI)Click here for additional data file.Video S4Comparison of KapB::GFP with RabA(Rab5)::mRFP labeled early endosomes . Video displays 7 fs and time is indicated in sec. The upper video shows the green channel (KapB::GFP) and the middle video the red channel (RabA::mCh). The lower is the merged video in magenta.(AVI)Click here for additional data file.Video S5uncA hyphae Click here for additional data file.Video S6uncA hyphae Click here for additional data file.


Autism is on the rise, with 1 in 88 children receiving a diagnosis in the United States, yet the process for diagnosis remains cumbersome and time consuming. Research has shown that home videos of children can help increase the accuracy of diagnosis. However the use of videos in the diagnostic process is uncommon. In the present study, we assessed the feasibility of applying a gold-standard diagnostic instrument to brief and unstructured home videos and tested whether video analysis can enable more rapid detection of the core features of autism outside of clinical environments. We collected 100 public videos from YouTube of children ages 1–15 with either a self-reported diagnosis of an ASD (N = 45) or not (N = 55). Four non-clinical raters independently scored all videos using one of the most widely adopted tools for behavioral diagnosis of autism, the Autism Diagnostic Observation Schedule-Generic (ADOS). The classification accuracy was 96.8%, with 94.1% sensitivity and 100% specificity, the inter-rater correlation for the behavioral domains on the ADOS was 0.88, and the diagnoses matched a trained clinician in all but 3 of 22 randomly selected video cases. Despite the diversity of videos and non-clinical raters, our results indicate that it is possible to achieve high classification accuracy, sensitivity, and specificity as well as clinically acceptable inter-rater reliability with nonclinical personnel. Our results also demonstrate the potential for video-based detection of autism in short, unstructured home videos and further suggests that at least a percentage of the effort associated with detection and monitoring of autism may be mobilized and moved outside of traditional clinical environments. In the United States, autism spectrum disorder (ASD) is typically diagnosed in children at four years of age with an estimated 27% undiagnosed by eight years of age Significant prior work has focused on creating structured questions and standardized approaches to evaluate home videos by retrospectively examining early videos of children later diagnosed with ASD. This allows researchers to combine additional clinical features, such as age and IQ, with the video to develop a more complete representation of behavioral development. To standardize the home videos, most research focuses on a common event such as first or second birthday, and/or pivotal developmental milestones .We sought to expand the concept and feasibility of home video analysis by applying the Autism Diagnostic Observation Schedule (ADOS) The use of videos from YouTube was approved for exemption by the Institutional Review Board at Beth Israel Deaconess Medical Center (protocol #2012P-000307), under exemption number 4  of the Code of Federal Regulations, 45 CFR 46.101(b).www.youtube.com) for videos of ASD and non-ASD children using the following keywords in the video title or description: autism, ASD, autism spectrum disorder, Asperger’s, autistic child, autistic kid, autistic behavior, PDD-NOS, son, daughter, child, birthday party. We required each video to be under 10 minutes long, have clear audible sound quality, have continuous activity, and to contain a majority of footage on a child between the ages of 1 and 15. When age was not provided it was estimated based on a consensus from two or more investigators (pertinent to 7 of the 100 videos collected). In total, we identified 100 unique subject videos, 45 ASD and 55 non-ASD. We identified non-ASD videos as controls by matching age, gender, and race as closely as possible. Videos were labeled as ASD if the video title, video description, or meta-tag included autism, ASD, Asperger’s, or hand-flapping/stimming; otherwise, the video was labeled non-ASD. The full list of videos is provided in Table S1.We searched YouTube (http://www.wpspublish.com/). Four non-clinical raters independently scored the 29 questions on ADOS module 1 for each video. Raters were purposely given minimal instructions to code only when the video clearly depicted a behavior and/or contained opportunities for the child to exhibit the behavior in question, and otherwise to code the behavioral item as not applicable (N/A). Two of the four raters participated in the acquisition of the home videos from YouTube, and thus were not naïve to videos titles. An ADOS-certified clinical practitioner performed a blinded evaluation of a random subset of 22 videos (13 ASD and 8 non-ASD) that we used as a clinical standard for comparison to outcomes from the four non-clinical raters. We calculated the typical ADOS score as indicated in the exam instructions for the ADOS algorithm and followed the convention of converting all scores of three to two ADOS scoring instruments were purchased from Western Psychological Services . For videos where there was no majority (2 out 4) we did not make a classification and labeled it “no call.” We performed all such analyses in R We identified and analyzed 100 videos on YouTube that met our criteria for ASD (45 videos) and non-ASD (55 videos). A complete summary of video characteristics is provided in The high classification accuracy (96.8%) supported the feasibility of applying ADOS module 1 questions to videos on YouTube Table 2.Because two of the raters helped to locate videos appropriate for this study, they were not always naïve to the diagnoses. To address this possible bias, we recruited a research reliable and professionally trained ADOS clinical practitioner (blinded to the diagnosis) to score 22 randomly selected videos to ensure the non-clinical raters were not unduly influenced by their prior knowledge The absence of any reliable molecular, neurological or physical features to characterize ASD means the best-estimate behavioral diagnosis is still the gold standard. For this reason, previous studies focused on identifying a core set of primary deficits from home videos for early age detection, to allow behavioral intervention at key stages in child development. Here, we take a different approach and apply standard diagnostic questions from ADOS module 1 to a diverse collection of videos of children in a non-clinical environment using non-clinical raters. Our results show high classification accuracy and inter-rater reliability and together demonstrate that the ADOS module 1 questions can be used by non-clinicians on unstructured videos to effectively distinguish behavioral differences among children with and without ASD.While not all questions on the ADOS were expected to be relevant to the YouTube videos, we did find that a majority of the questions could be applied. In particular, questions regarding vocalization, use of words or phrases, unusual eye contact, responsive social smile, and repetitive interests or behaviors were the most relevant to the broad assortment of videos. Adding even a limited set of criteria to meet when capturing home videos for prospective studies may increase the likelihood that the less detectable behaviors identified in this study are captured. We observed the length of time to screen a video was never more than one minute over the length of the video and that the average assessment times were ∼4 min for ASD and ∼3∶30 min for non-ASD. These results could have important implications for faster screening approaches in the future.There are important limitations to this proof-of-concept study. First, because we did not contact the individuals, we cannot confirm the diagnosis, gender, age, and race. Second, although by design, our raters were not trained clinicians, were not certified as research-reliable to perform ADOS and were not professionally qualified to confirm a diagnosis. Third, we applied ADOS module 1 to all the videos despite the typical recommendation that it be applied to children with single word vocabulary and mental age less than 3 years of age. However, the high agreement among the non-clinical raters, as well as the agreement of the raters to a research-reliable ADOS practitioner suggests that these limitations did not heavily bias the results.In conclusion, we demonstrate the feasibility of applying a standard diagnostic questions to ASD and non-ASD videos from YouTube. Our results show that despite the short length (<4 minutes), home-quality, and diversity of scenarios captured within the videos it is possible to achieve good inter-rater reliability and high classification accuracy, sensitivity, and specificity. Our results also indicate that it is possible for non-clinical raters to correctly detect the presence of autism with high inter-rater reliability and >94% accuracy. These results support the potential role for short home videos in rapidly screening for a potential autism diagnosis. Based on these results, we hypothesize that it may be possible to apply other testing modules, including highly abbreviated approaches Table S1Details on the 100 YouTube videos. Forty-five autism spectrum disorder (ASD) and 55 non-ASD samples were collected in total. The Table contains the original download URL, the self-reported diagnosis, the gender and age of the subject, length of video, and the total number of YouTube views (as of 12/10/13).(XLSX)Click here for additional data file.


Hepatocellular adenoma (HCA) in pregnant women requires special considerations because of the risk of hormone induced growth and spontaneous rupture, which may threaten the life of both mother and child. Due to scarcity of cases there is no evidence-based algorithm for the evaluation and management of HCA during pregnancy. Most experts advocate that women with HCA should not get pregnant or advise surgical resection before pregnancy. Whether it is justified to deny a young woman a pregnancy, as the biological behavior may be less threatening than presumed depends on the incidence of HCA growth and the subsequent clinical events during pregnancy.We aim to investigate the management and outcome of HCA during pregnancy and labor based on a prospectively acquired online database in the Netherlands.The Pregnancy And Liver adenoma Management (PALM) - study is a multicentre prospective study in three cohorts of pregnant patients. In total 50 pregnant patients, ≥ 18 years of age with a radiologically and/or histologically proven diagnosis of HCA will be included in the study. Radiological diagnosis of HCA will be based on contrast enhanced MRI. Lesions at inclusion must not exceed 5 cm. The study group will be compared to a healthy control group of 63 pregnant patients and a group of 63 pregnant patients with diabetes mellitus without HCA. During their pregnancy HCA patients will be closely monitored by means of repetitive ultrasound (US) at 14, 20, 26, 32 and 38 weeks of gestation and 6 and 12 weeks postpartum. Both control groups will undergo US of the liver at 14 weeks of gestation to exclude HCA lesions in the liver. All groups will be asked to fill out quality of life related questionnaires.The study will obtain information about the behaviour of HCA during pregnancy, the clinical consequences for mother and child and the impact of having a HCA during pregnancy on the health related quality of life of these young women. As a result of this study we will propose a decision-making model for the management of HCA during pregnancy.Dutch trial register: NTR3034 Hepatocellular adenoma (HCA) is rare benign tumor of the liver that occurs particularly in women during their reproductive years. The incidence is not exactly known. Studies performed years ago show an estimate incidence of 1-1.3 per 1,000,000 in women who have never used oral contraceptives (OC), compared to 30-40 per 1,000,000 in long-term users . The assRegardless of the exact etiology and risk factors all female patients should be advised to stop OC’s and other hormone medication such as hormone replacement therapy, since regression of HCA may occur when steroids are withdrawn -13 and oHCA in pregnant women requires special considerations because of the risk of hormone induced growth and spontaneous rupture, due to increased levels of steroid hormones during pregnancy that may threaten the life of both mother and child. Most experts advocate that women with HCA should not get pregnant or advise surgical resection before pregnancy ,18. CobeIn this study we will investigate the management and outcome of HCA during pregnancy and labor based on a prospectively acquired online database in the Netherlands.Main objective of the PALM-study • To investigate the incidence of HCA growth during pregnancy and labor.Secondary objectives of the PALM-study • To investigate in which trimester of pregnancy growth of HCA occurs; • To investigate the degree of growth of HCA during pregnancy; • To investigate whether there is regression of HCA postpartum; • To investigate the HCA-related interventions during pregnancy and labor; • To investigate the incidence of bleeding of HCA during pregnancy and labor; • To investigate liver-related clinical signs during pregnancy; • To investigate elevated liver enzymes during pregnancy; • To evaluate the health related quality of life of pregnant patients with HCA; • To investigate whether there is a difference between health related quality of life of pregnant patients with HCA and pregnant patients with other comorbidity that have an indication for pregnancy care at the obstetrician in secondary care and healthy pregnant patients.The PALM-study is a multi-centre prospective study in three cohorts of pregnant women. The study started on November 1 2011 and inclusion of patients will be a period of minimal 3 to maximal 5 years. In total 50 pregnant patients with HCA < 5 cm will be included in the study. These patients will be compared to a healthy control group consisting of 63 pregnant patients without HCA and a group consisting of 63 pregnant patients with diabetes mellitus (DM). Approval of the Medical Ethics Committee of Erasmus Medical Centre was obtained, NL36058.078.11.Properly Dutch speaking, pregnant patients, 18 years of age or older with a radiologically and/or histologically proven diagnosis of HCA can be included in the study. Radiological diagnosis of HCA will be based on contrast enhanced magnetic resonance imaging (MRI) and if available in combination with (contrast enhanced) ultrasonography (US). Lesions must not exceed 5 cm. In the first weeks of pregnancy patients will be referred to the obstetrician for pregnancy care. Baseline starts at 14 (+/−3) weeks of gestation. At this day and every 6 weeks patients will undergo US of the HCA lesion at the radiologist. Before US of the HCA lesions patients will be asked to fill out generic health related quality of life questionnaires (12-item Short Form SF 12 and EuroQol questionnaire EQ-5d), a generic anxiety questionnaire (State-Trait Anxiety Inventory STAI-6) and the Impact of Event Scale (IES) questionnaire for thoughts and feelings about HCA around the US. One week afterwards the study group will be asked to fill out the STAI-6 en IES again. At 14 and 32 weeks of pregnancy patients will undergo venapunction.Properly Dutch speaking, healthy pregnant patients, 18 years of age or older without HCA.In the Netherlands, pregnant women will start pregnancy care with an independently practicing midwife early in pregnancy at the primary care level . The midPatients presenting at the practicing midwife will be asked to participate in the study. Thereafter, the patients will be included in the study by the study investigator. Patients will undergo US of the liver at 14 (+/-3) weeks of gestation to exclude HCA lesions in the liver. At this day and every other 6 weeks patients will be asked to fill out the SF-12 and EQ-5d questionnaire. At 14 and 32 weeks of pregnancy patients will undergo venapunction. In case of an uncomplicated pregnancy, the patient remains under the care of her practicing midwife during her pregnancy and postpartum.Properly Dutch speaking, pregnant patients, 18 years of age or older with Diabetes Mellitus, can be included in the study. These patients have an indication for pregnancy care at the obstetrician in secondary care. Patients will undergo US of the liver at 14 (+/-3) weeks of gestation to exclude HCA lesions in the liver. At this day and every other 6 weeks patients will be asked to fill out the SF-12 and EQ-5d questionnaire. At 14 and 32 weeks of pregnancy patients will undergo venapunction.For all groups informed consent is mandatory. A patient can always withdraw her consent at anytime during the study where after she is referred for the present standard of care.Pregnancy may be allowed in case of one or more known HCA < 5 cm (without previous intervention), because a HCA < 5 cm will not disturb the course of pregnancy.Disrupted course of pregnancy: • interventions during pregnancy . • Decreased quality of life and/or anxiety in patients during pregnancy related to the presence of HCA in the liver and possible growth during pregnancy.We have previously reported that more than half of the HCA are discovered after the patient has sustained at least one pregnancy and none of these patients have reported problems during their pregnancies . As mentDuring their pregnancy HCA patients will be closely monitored by means of repetitive US (and MRI in case of growth of the lesion) at 14 (+/−3) and 20 and 26 and 32 and 38 weeks of gestation and 6 and 12 weeks postpartum. At the same days both control groups will be asked to fill out the SF-12 and EQ-5d questionnaire at 14 (+/−3) and 20 and 26 and 32 and 38 weeks of gestation and at 6 and 12 weeks postpartum . The study group will be asked to fill out the SF-12, EQ-5d, STAI-6 and IES questionnaires before and one week after US of the HCA lesion(s). Both control groups will undergo US of the liver at 14 (+/−3) weeks of gestation to exclude HCA lesions in the liver. At 14 and 32 weeks of pregnancy all patient groups will undergo venapunction.We established a website which allows hepatologists, surgeons and gyneacologists to submit clinical data in an online database. Each centre will have a code to log in and patients will be consecutively assessed a unique number. Registration of a new patient includes entry of the following data: date of birth, weight, height, date of hospital admission, symptoms at presentation, known risk factors for HCA such as glycogenosis and familial polyposis,  previousFollow-up of patients takes place at 6 and 12 weeks postpartum postpartum by means of US (and MRI in case of growth) to document the size of HCA postpartum  at 14 (+/−3) and 20 and 26 and 32 and 38 weeks of gestation.Secondary outcome: General health and pain scales as a measure for quality of life and anxiety related questionnaires for thoughts and feelings of adenomas around US. Other secondary outcomes are complications due to growth of the HCA during pregnancy possibly followed by interventions during pregnancy, incidence of hemorrhage and rupture of the HCA, incidence of liver-related clinical signs during pregnancy , incidence of elevated liver enzymes during pregnancy.In our previous study we measured growth of HCA in 4 out of 17 pregnancies (24%) or in 3 out of 12 women (25%). On a yearly basis approximately 50 new patients with HCA are seen at the outpatient clinic of the Erasmus University Medical Centre. The expectation is that 5% (5) of these women get pregnant. The expectation is that a total of 50 pregnant HCA patients from different tertiary referral centres in the Netherlands can be included in the study during a period of 3 to maximum 5 years.t test was performed with a two-sided significant level of 0.05 and a power of 0.80.A difference of 0.5 Cohen’s D in health-related quality of life is a relevant difference . We calcMedical data with which the identity of a patient could be traced will be replaced by a code number. The coordinating investigator is the only one who has the key to the code numbers and knows which code number stands for which patient. The principal investigator has only access to the coding system of his or her patients and will never be able to open the database from other centres. Only members of the investigating team and members of the medical ethical committee of the participating centres will have access to the medical data. All data will be collected in a prospectively acquired database by the principal investigators and managed by the coordinating investigator.Once the diagnosis of HCA has been established, patients will be advised to discontinue OC. Expert opinions are very variable regarding treatment and follow up in complex situations were multiple factors play a role in determining the management strategy, like pregnancy .As to date there are limited data about the behavior of HCA during pregnancy and labor and therefore we cannot identify precisely those at risk for complications. However, in 2006 we reported a series of 48 patients of which in 44% HCA were discovered after the patient had sustained at least one pregnancy . None ofThe Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) provided guidelines for diagnosis, treatment, and use of laparoscopy for surgical problems during pregnancy . HoweverOne should be aware of the potential risks as an intervention may still be indicated during pregnancy. In approximately one in 635 pregnancies a non-obstetric operation during pregnancy is required, especially appendectomy, cholecystectomy and adnexal precedures . Howeverth week of gestation) [Based on a systematic review of the literature, Wilson et al. suggested angioembolisation and formal resection in case of haemorrhage of HCA during pregnancy and suggested this strategy to be safe for both the mother and the fetus with good clinical outcomes . The roltation) .The influence on the course of pregnancy, since a woman is aware of having a HCA, is also unknown. Patients can get horrified when confronted with the new diagnosis of a hepatic mass  and it iOur main point of interest is whether it is justified to deny a young woman with a HCA < 5 cm a pregnancy. With this study we hope to obtain information about the behaviour of HCA during pregnancy and the impact of HCA during pregnancy on the life of these young women. Furthermore we hope to propose a decision-making model for the management of HCA during pregnancy.HCA: Hepatocellular Adenoma; US: Ultrasound; OC: Oral Contraceptives; DM: Diabetes Mellitus; MRI: Magnetic Resonance Imaging; SF 12: 12-item Short Form; EQ-5d: EuroQol questionnaire 5d; STAI-6: State-Trait Anxiety Inventory; IES: Impact of Event Scale; SAGES: Society of American Gastrointestinal and Endoscopic Surgens; CEUS: Contrast Enhanced Ultrasound; RFA: Radiofrequency ablation.The authors declare that they have no competing interests.SMA and MEEB are responsible for the drafting of the manuscript and study design, these authors contributed equally to this work. JJB, HJDK, RADM, EAPS, EWS, TT and JNMIJ are responsible for the study design and revision of the manuscript. All authors have read and approved the manuscript.Stichting CoolsingelFonds NutsOhraAcademic Medical Center, Amsterdam, Department of SurgeryT.M. van Gulik, MD, PhD University Medical Centrer Utrecht, Department of SurgeryR. van Hillergersberg, MD, PhD , MD, PhD Academic Hospital Maastricht, Department of SurgeryC.H.C. de JongMedical Spectrum Twente, Department of SurgeryJ. Klaase, MD Deventer Hospital, Department of SurgeryM.S.L. Liem, MD University Medical Center Groningen, Department of SurgeryR.J. Porte, MD, PhD Amphia Hospital Breda, Department of SurgeryA.M. Rijken, MD Máxima Medical Center Veldhoven, Department of SurgeryR.M.H. Roumen, MD Leiden University Medical Center, Department of SurgeryA.F.M. Schaapherder, MDVU Medical Center Amsterdam, Department of SurgeryM.P. van den Tol, MD University Medical Center St. Radboud, Department of SurgeryJ.H.W. de Wilt, MD, PhD The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-230X/12/82/prepub


Video quality as perceived by human observers is the ground truth when Video Quality Assessment (VQA) is in question. It is dependent on many variables, one of them being the content of the video that is being evaluated. Despite the evidence that content has an impact on the quality score the sequence receives from human evaluators, currently available VQA databases mostly comprise of sequences which fail to take this into account. In this paper, we aim to identify and analyze differences between human cognitive, affective, and conative responses to a set of videos commonly used for VQA and a set of videos specifically chosen to include video content which might affect the judgment of evaluators when perceived video quality is in question. Our findings indicate that considerable differences exist between the two sets on selected factors, which leads us to conclude that videos starring a different type of content than the currently employed ones might be more appropriate for VQA. Recently, there has been a tremendous increase in usage of mobile devices to access the Internet and its services. Fierce competition on the end-user electronics market has caused smartphones to become accessible to everyone, and the telecommunications made broadband Internet access cheap and ubiquitous. As a consequence, vast majority of the population in developed countries now owns a cell phone , while oIn essence, there are two ways to express the quality of a given video content: the first one is to leverage objective measurements that are inherent to a given sequence in order to derive “objective quality” of the video, while the other is to rely on subjective assessment scores obtained from human evaluators. Ideally, one should be able to use the former to predict the latter. Video Quality Assessment (VQA) algorithms attempt to do this automatically , but their performance sometimes leaves much to be desired, and there is considerable room for improvement . In factThe ground truth data that is used to measure the performance of quality assessment algorithms—which in the domain of VQA takes the form of degraded sequences and Mean Opinion Scores (MOS)—is gathered mostly in laboratory tests on human observers . However, there is an array of cognitive biases specific to a human mind, such as contrast error or halo effect  which inThe research presented in this paper aims to define the mental response properties of video stimuli that are pertinent to its content and to propose variables that ought to be taken into account when dealing with the subjective video quality assessments. In order to do that, a standard video quality database commonly used for VQA has been compared to a custom-constructed one based on various content-specific properties that have been shown to influence subjective evaluation such as: user's familiarity with the content and the expectancy of the content (cognitive component), induced emotions (affective component), and user's intent to watch the video again or to recommend it to a friend (conative component). The results indicate a significant difference between the two databases on the observed components and identify the properties of videos that have the highest discriminative power when it comes to subjective video quality perception. In addition, a relationship between video content and the perceived video quality was identified.The rest of the paper is organized as follows. A recent survey by Winkler provides a fairly exhaustive list of publicly available video quality databases , which cEven though the majority of video quality models and objective metrics rely heavily on the low level sensory processing of HVS, research has shown that low level models are not sufficient in characterizing the video quality judgments. For example, a study by McCarthy et al.  has showWhen information assimilation is the primary aim of multimedia presentation, content plays an important role in the perception of multimedia video quality, as reported by Gulliver et al. . They diFinally, Jumisko et al.  show thaVisual perception may be broadly defined as mental organization and interpretation of sensory information received via individual's sight. Human visual perception, while being relatively objective by its means (the sight) and constant in terms of properties of the object being watched , is still often significantly subjective due to various factors residing in the observer's mind. Since perception requires interpretation of any received information and since interpretation is a complex phenomenon that is unique to every individual, it is evident that visual perception is heavily influenced by internal and external subjective factors that are often hard to grasp. Visual perception is, still, not fully understood by contemporary science: there are competing theories that concentrate on different aspects of it and offer explanations that are often in discordance with one other . FurtherAlso, some cognitive biases are known to distort our interpretation and assessment of what we see and evaluate : attentiFinally, bottom-up processing is known to be driven by the stimulus presented  and someTV series,movies,informative shows,entertainment,news,music shows,sports, andother.As related research reveals, assessors are by no means indifferent to the content they evaluate. This has potential implications for real-world applications, since subjective perception of quality of some “neutral” content selected on basis of its suitability for introducing particular impairments to video stream  might differ from quality perception of content that the assessor is familiar with or interested in and pays more attention to . To test this hypothesis, we created an alternative set of videos for comparison with the commonly used ones, which ought to activate mental responses that are not activated to a greater extent within commonly used VQA databases and should thus reflect more truthfully the perceived quality of real-life video sequences as experienced by the end-users when impaired. We will refer to this set as the proposed set. As familiar video content was shown to sometimes get lower quality rating at the same impairment level than the unrecognized one, we included a number of videos that should be fairly familiar to assessors, instead of focusing solely on content that was supposed to induce different emotions or other mental responses. First, based on the reports of national television service  as well While most of the categories are self-explanatory, the “Informative shows” category comprises content that covers a specific topic or event . Using television program ratings as a guideline , we seleAs the first research goal was to determine if the LIVEVQDB video set is similar in ability to activate mental responses to a set of real-life videos observed by media consumers, an experimental research design with two independent sets was adopted. The two sets were compared on a number of relevant variables that identified level of mental activation. Mental response, in this context, was regarded as any kind of an individual's conscious mental activity that is directly induced by specific visual stimuli presented to that individual. From various classifications of mental activities available, the widest nomenclature was used in this research: the tripartite classification of mental activities (responses) into cognition, affection, and conation. This classification has been in use since the eighteen century and is still widely used nowadays to address various aspects of human mental state and responses .Cognitive mental activities are mostly observed as a “rational,” or “objective” peace of mind. These activities are thought to be responsible for processing information that people get from their sensory systems via attention and memory. In order to measure cognitive response, we propose variables we named “interesting” and “familiar” to measure the potential of a stimulus to attract attention and to assess its novelty or the lack of it. In contrast to the cognitive activities, affective activities  are thought to be very subjective and relative to the person who is receiving certain stimuli. As identified in the western cultures by Ekman et al.  and reafA measurement of subjectively perceived video quality was expressed in terms of Mean Opinion Score (MOS), which is calculated as the average score for a video sequence over all assessors. It was measured on a 5-point quality scale, ranging from 1 (bad) to 5 (excellent). Finally, to be able to keep track of content that was recognized by the assessors, a variable “seen before” was introduced. Complete set of variables and scales used to measure them is presented in Experimental setup in general and laboratory setup in particular, closely resembled the one proposed by the International Telecommunication Union (ITU) in their recommendations for VQA tasks . SequencAfter the experiment, a number of different analyses were performed. All of them were conducted with two considerations in mind: (1) we operated with a sample size that could possibly be considered small in comparison to established norms for behavioral sciences but at the same time is considered more than adequate for VQA tasks and (2) we operated dominantly with ordinal level of measurement (for the dependent variables).The data obtained was observed relative to the two video sets: (1) the proposed one and (2) the LIVEVQDB set. Separate dimensions were compared, followed by a comparison of subsequently computed variables for the three mental response categories.U test, results of which are shown in Tables To test this hypothesis against the alternative one (that the two observed populations are the same), we ran the Mann-Whitney As shown in The proposed set also achieved higher ranks in all of the six basic emotions observed, as shown in The proposed video set was also found to activate conative dimensions of subjects' mental activity to a greater extent than the LIVEVQDB set did. These dimensions are especially important, because they cast a new light on both the cognitive and the affective dimensions. If conative part of one's mind is in idle state, the chances are that the cognitive and affective activation did not happen, even if the subject states the opposite. When somebody is presented with interesting content, he or she is likely to do something after seeing it—either watch it again or share it with relevant others.The mean ranks difference can be observed in U test has demonstrated significantly higher mental activation induced by the proposed set than the mental activation induced by the LIVEVQDB set , affective activation (comprising 6 dimensions), and conative activation (comprising 3 dimensions). Again, the Mann-Whitney VQDB set .Finally, relationship between the mental activation dimensions and perceived video quality (MOS) was observed. Since all of the dependent variables were of ordinal type, Spearman's Rho measure of correlation was used, following common guidelines of interpretation for behavioral sciences , 42. ModAlso, video quality assessment was correlated with the three calculated mental components, gaining moderate correlation with cognitive component (.412) and conative activation (.496), while low correlation was found with affective activation (.232), again all significant at the .01 level (2-tailed).Additionally, Spearman's rho correlations were calculated for the three mental components, suggesting a strong correlation between the cognitive and the conative components (.741), while also suggesting a moderate correlation between these two components in relation to the affective component (.351 with cognitive) and (.462 with conative).t-test was run on MOS obtained and it did not show statistically significant differences between the samples, thus confirming our initial assumptions.Unknown to assessors, all videos in the full test set were obtained from the same source and with the same quality settings  and were hence of roughly the same visual quality. Even though we could not control for the impairments and objective video quality of the source sequences (apart from the LIVEVQDB database), close visual inspection of the obtained material assured us that nonexperts should hardly be able to tell the difference between the quality of sequences presented to them . To further confirm our assumption, a subset of 20 sequences was played to three independent video quality experts. Among these videos, 10 were randomly selected from the proposed set, while the other 10 were LIVEVQDB sequences . Playing order was randomized and the experts were asked to vote only on quality  of the videos. Subsequently, unpaired Since a correlation was established between different variables and MOS and LIVEVQDB videos scored constantly lower than the videos from the proposed set, we have tried to further investigate and explain these differences.t-test to be statistically significant . What is even more interesting is that 7 out of 8 categories (for the proposed video set) found their place on the “top 10 interesting videos.” The only category that did not make it was the “movies” category.On average, videos comprising the proposed set scored a MOS value of 3.47, while LIVEVQDB videos scored 2.80. This is a large difference on a 5-point scale, but it only gets larger when individual components shown to affect perceived quality are considered. For example, when interestingness is observed, best ranked LIVEVQDB video was placed 39th (out of 66 videos in the full set). A comparison between the top 10 ranked “interesting” videos (as deemed by assessors) and the sequences from the LIVEVQDB set reveals a mean difference of 1.34 points (2.80 MOS for the LIVEVQDB versus 4.13 MOS for the proposed set), which was further shown by a When comparison of top 10 MOS rated videos pertinent to different emotions versus LIVEVQDB videos is concerned, results comply with previously discovered correlations. Thus, when a positive emotion such as happiness was induced by a sequence, it yielded a high quality score (MOS = 3.96). Videos that caused surprise were also ranked as of higher quality (MOS = 3.81), while negative emotions caused video to plummet on the quality scale (sadness (MOS = 2.86), fear (MOS = 3.00), disgust (MOS = 2.86), and anger (MOS = 2.89)). Interestingly, one of the videos from the LIVEVQDB found its place among the top 10 videos that the assessors were angry with.The most important conclusion we drew from the results obtained in the experiment is that the content of video sequence has a strong impact on activating different cognitive, affective, and conative components within assessors. These components, in turn, have been shown (both by this and previous researches) to play an integral role in VQA tasks, whether assessors are aware of it or not. Thus, we provide a number of recommendations that ought to be taken into account when conducting subjective video quality assessment experiments.First, video content has to be considered very carefully when trying to measure the perceived video quality, as failing to do so might introduce a bias which will reflect in final MOS obtained. It is thus vital to choose the correct type of content for addressing the research question at hand . Having this in mind, the “content” variable needs to be monitored whenever possible. Second, since emotions of disgust, fear, anger, and sadness are found to have different impact on conative mental activities than emotions of happiness and surprise, additional attention should be exhibited if conative activities are to be observed as dependent variables .Finally, we have shown that subjective video quality assessment might not be such a reliable measure of video quality if video content is not controlled. This has potential consequences on both the subjective video quality models already devised that do not take content variable into account and automatic approaches  that try to predict MOS based on existing (possibly biased) results.Since the relationship between video content and perceived video quality was identified, new research directions open up for further investigation. Some of those include identifying and quantifying the strength of this relationship, investigating to what degree can a video be impaired without assessors noticing it (relative to video content), and whether content plays the same role in subjective perception of video quality when sequences are impaired with different levels and types of artifacts. Also, a study at a larger scale might reveal other factors pertinent to different populations  that impact subjective perception of video quality and should thus be taken into account when VQA tasks are in question.