Variation in longitudinal control in driving has been discussed in both traffic psychology and transportation engineering. Traffic psychologists have concerned themselves with “driving style”, a habitual form of behavior marked by it’s stability, and its basis in psychological traits. Those working in traffic microsimulation have searched for quantitative ways to represent different driver-car systems in car following models. There has been unfortunately little overlap or theoretical consistency between these literatures. Here, we investigated relationships between directly observable measures  in a simulated driving task where the driving context, vehicle and environment were controlled. We found individual differences in the way a trade-off was made between close but jerky vs. far and smooth following behavior. We call these “intensive” and “calm” driving, and suggest this trade-off can serve as an indicator of a possible latent factor underlying driving style. We posit that pursuing such latent factors for driving style may have implications for modelling driver heterogeneity across various domains in traffic simulation. In any biological system, including human behavior, variability is the norm. Average behavior, “ideal” forms, or population means may capture overall central tendencies, but to understand the complexity and dynamical interactions of most real systems it is necessary to take into account the fact that for any system of interacting agents capable of complex individual behavior—be that birds in flock or motorists travelling down a freeway—real behavior rarely follows a single, simple rule.Such rules can provide deep insight into system properties, and describe the dynamics at a level of detail that are sufficient for improving understanding and even deriving practical applications. Nevertheless, models that make a simplifying assumption of population homogeneity have their limits. To make progress, the issue of heterogeneity needs to be addressed.This is the situation currently in the domain of traffic flow modelling—a domain at the intersection of physics (dynamic systems), engineering (transportation systems design) and behavioral science (driver psychology and behavior). Here, we look a the problem of car following (CF), a core behavior in road traffic flow. A deep understanding of CF would have important implications in alleviating congestion and improving traffic system performance. CF is also a fundamental form of vehicle-vehicle interaction that needs to be understood to better design autonomous vehicles that will need to interact with human drivers in mixed fleets.Traditionally, CF models used in traffic simulation have assumed a fleet of identical drivers, modeled as a simple rule that associates their observations (such as distance to the leading vehicle or current speed) to desired behavior (acceleration or target headway). The validation of model parameters has typically been done by reference to an “average” driver. In recent years, interest in heterogeneous driver modelling has been increasing, with several studies addressing the problem –4. In soDespite decades of theoretical and empirical work, the field of traffic psychology has failed to converge on a clear and precise definition of the concept of “driving style”, and its psychological underpinnings and relation to important issues such as accident causation remain debated. Work on high-level traffic psychology concepts could benefit from a more concrete approach, such as direct performance measures and experimentally simple scenarios, which are susceptible to rigorous computational modelling.In this article, we investigate individual variation of car following dynamics, particularly through the relationships between time headway, acceleration and jerk. Previous research has been lacking a theoretical framework to discuss variation in observable CF dynamics, which is something that Sagberg et al.  have recWithin traffic psychology, the question of stable individual differences in how a driver chooses to go about the business of normal everyday driving, “driving style”, has been the subject of extensive discussion for decades. In a comprehensive review of the literature, Sagberg et al.  find thadriving styles differ across individuals or groups of individuals,driving style is a stable, habitual feature in driving behaviour,driving style is a choice, which many authors equate with a conscious preference.The authors themselves omit the last criterion of consciousness, and define driving style as “a habitual way of driving, which is characteristic for a driver or a group of drivers”. In this article, we adopt their definition. According to Sagberg et al. , drivingIn traffic psychology, driving style is operationalized in terms of a whole host individual preferences, such as speed control, time gap acceptance and thresholds for overtaking or merging into traffic, time headways (e.g. tailgating), and tendency to display emotions to other road users or commit driving violations , 9. The Sagberg et al.  propose Empirical research has not yet addressed the question of whether these specific styles are correlated, but Sagberg et al. suggest that they should be: a global style, e.g. “aggressive driving” is a latent factor that will be expressed in specific situations as tailgating, honking the horn, or accelerating hard from traffic lights.A large part of the research has approached driving style as the search of such latent factors in the hope that they in turn would be correlated with individual crash risk . The goaWhile questionnaire-based studies to uncover these latent motivations and goals are abundant, there is no consensus yet on the proper taxonomy of global or specific styles. According to Sagberg et al. , relevanSeveral observable measures  have been used for driving style classification for the purpose of developing vehicles themselves, with particular emphasis on cruise control and fuel consumption . “Drivinconfliction, which indicates time spent in the near region behind a leading vehicle.A report on a Field Operational Test for Intelligent Cruise Control  describeMurphey et al.  proposedacceleration from non-zero speed) metrics—such as acceleration, jerk and quickness—were shown to differentiate between “comfortable”, “dynamic” and “everyday” driving styles. These driving behaviours were cued by corresponding instruction to the participants. The results suggest that the participant’s conception of comfort is linked to verifiable physical measures.Bellem et al.  have disMost often, the studies mentioned have concentrated on one measure. While these studies are relevant to the discussion of driving style and driver heterogeneity, they lack an attempt to study the interplay of several variables to describe variation in longitudinal control. The categories of classification are important for singular applications, but may be difficult to generalize.It’s been acknowledged since the very beginning of car following modeling that different drivers and different vehicles can have substantially different car following dynamics, and that this has effects on the traffic flow , 20. In However, some recent work has more rigorously studied the heterogeneity and its results on traffic flow. Heterogenous traffic population, especially a mixture of cars and trucks, has been found to explain some of the complex traffic flow dynamics observed in congested traffic . FurtherKim and Mahmassani  investigDirect usage of CF model parameterizations has obvious benefits for establishing more realistic parameter distributions for simulation software. However, estimating parameters for modern CF models is a rather complex issue , and resAlso, many of the recent results are based on relatively short trajectories recorded in normal traffic, which makes it difficult to estimate how much of the parameter variance and correlation is due to driver heterogeneity, and how much due to vehicle and driving situation heterogeneity. Pariota et al.  measuredIt has been well established that individual differences in longitudinal driver behaviour occur, and that they have an effect on traffic flows and are correlated to risky road behavior. While the measures of acceleration, jerk, and time headway have been used to parameterize driving style in particular contexts and for specific reasons, most studies use only one of those for classification and have no theoretical framework to build on or generalize the results in a comparable way. Following Sagberg et al. , a hypotWe tested this hypothesis in a driving simulator, where 15 drivers drove in controlled car-following conditions for an extended period of time. Measuring acceleration, jerk and time headway, our aim was to discover the connection between these measures to provide an tentative account of the physical characteristics of longitudinal driving style.15 participants  took part in the study. The participants were required to hold a valid driver’s license for a passenger vehicle (Finnish driving license class B), and have over 30 000km of self-assessed driving experience or to have held a driver’s license for more than 5 years. Participants were recruited through personal contacts and university mailing lists.An informed consent to participate was obtained in writing from each participant before starting the experiment. This was done in accordance with the instructions of the ethics committee in the form of a fixed-format consent form explaining the purpose of the study, the procedure, and intended use of the data (for scientific purposes only). The study was conducted following the research ethical guidelines of Finnish National Advisory Board on Research Ethics and Helsinki Ethical Review Board in the Humanities and Social and Behavioural Sciences. As per the guidelines, ethical review for the experiment was waived, as the experiment didn’t include any of the criteria that warrant for such review. Apart from e-mail addresses, no identifying information was gathered in the study. The e-mail addresses were removed from the data set in the first step of preprocessing and were stored in a separate file only on the data logging computer and one workstation.After giving consent, the participants filled an electronic questionnaire with nine questions. This included information about their age, gender, driving license class, driving experience and habits of playing video games. The majority, 73% only had a passenger car driving license (Finnish class B). The subject’s self-reported lifetime driving experience varied between 1000–300 000 km, with gaming experience ranging from “none” to “daily”. The detailed background information can be found in the The driving simulator was located in the Traffic Research Unit, Faculty of Behavioral Sciences, Uni. Helsinki. The experimental space was a small room which was closed at the time of experimentation. The simulator consisted of a 55” screen (LG 55UF851V), driving game controller with a steering wheel and pedals (Logitech G25) and an adjustable driving seat (Playseat Evolution Alcantara). The seat could be manually adjusted with sliders, allowing the participant to choose a comfortable distance from the wheel. The exact viewing distance to the screen depended on the participant’s body size and preference, but was generally within 80–90 cm. This created an approximately 70 degree viewing angle to the 55” screen, which is the same as the virtual angle of view used in the software. Simulated engine noise was presented through the screen’s speakers. For a more detailed description of the driving simulator, see .The driving simulator software was developed in-house and is available under an open source license . The parThe experiment consisted of a training phase and a car-following phase. The purpose of the training phase was to familiarize the participant with the dynamics and dimensions of the virtual vehicle. In the car-following phase all visual dials were removed from the screen and the participant had to judge his own speed with no objective speedometer. A braking light was present in the leading vehicle. Steering was disabled for the entire duration of the experiment, and the participant controlled the vehicle only through the gas and brake pedals.The driving environment consisted of a single road with two lanes, separated by a center line. The right-hand lane was used for the experiment, with no oncoming traffic present. The landscape consisted of a sand-like ground texture, with some rocks scattered in the scenery. The textures and rocks provided for an optic flow pattern when the subject vehicle was moving, which aided the participants in determining their own speed. See screenshot in In order to create a car-following scenario, a speed profile for the leading vehicle was decided. Four speeds were chosen as the targets of the leading vehicle:10 km/h: Very slow. Crawling speed.30 km/h: Slow. Residential area speed limit.50 km/h: Moderate. City limit.80 km/h: Fast. Basic speed limit for non-motorway traffic in rural areas.blocks. Each block started and ended in a standstill, with a unique permutation of the four leader target speeds in between. The entire car-following phase was formed by 24 blocks, representing the 24 possible permutations of the four target speeds. Order of the blocks was randomized for each participant. To prevent participant fatigue, the series was divided into four block segments, in between which the participants were allowed take a short pause.The entire course of the car-following phase consisted of a series of m/s2, 4.0m/s2 and 7.0m/s2.The throttle and brake of the leading vehicle were controlled by a proportional-integral controller, which was given an per-transition independently randomized target acceleration/deceleration from the set of 1.5As the leading vehicle reached a particular non-zero target speed, it stayed at that speed for 20 seconds with a ±5 second random deviation. When the vehicle came to a full stop between the blocks, it remained stationary for 5 ± 2 seconds after the participant vehicle had come to a full stop. The stochasticity was introduced to prevent the participant from being able to guess when the next accelerating or decelerating maneuver was required.The duration of the entire experiment was within 46–56 minutes and the car following task analyzed amounted to approximately 30 kilometers of driving per participant.The drivers were instructed to drive normally, “like driving on a highway”, and that while colliding was not forbidden, if a crash should occur they would have to drive the current segment again and the experiment would be prolonged accordingly. Only one collision in total occurred in the experiment, and the segment where it occurred was omitted from the analyses.Although the participants could not see other cars than the one ahead, they were told that they were driving in the middle of a queue, and that this was the cause of the fluctuation in traffic. Finally, the participants were instructed to keep the sort of gap which “feels appropriate” and that there was no chance of overtaking.absolute values averaged over time. For time headway, we use a geometric mean in order to curtail the influence of the “long tail” of the distribution. For brevity, these variables are simply referred as mean acceleration, mean jerk, and mean time headway. The subject means are calculated from the entire length of the experiment.The car following dynamics were operationalized using acceleration, jerk and time headway for each subject. For acceleration and jerk we use their transitions, or by their endpoints in brackets, e.g. {50, 80}. The beginning of a transition is marked by the onset of a new target speed for the lead vehicle. We consider only the first 15 seconds from that moment. We also further categorize the individual pass-throughs of these transitions based on the time headway the driver held at the start of the transition, dividing them into four quartiles. The first quartile contains the shortest observed time headways and the fourth one the highest.Acceleration is also analyzed as a function of time. For this analysis, we treat the different speed changes (e.g. from 50km/h to 80km/h) separately, and refer to them as The quartile-clustered time series are re-sampled and averaged to provide a graph that represents the average response to lead vehicle speed change. This process is illustrated in After inspecting the linearity between the subject means for mean acceleration, mean jerk and mean time headway, we use simple linear regression to model the connections. To avoid multicollinearity in having several correlated predictors and more importantly, to show that the measures can be adequately represented with a single factor, we use Principal Component Analysis (PCA) to validate the central claim of the paper.Average acceleration of the following vehicle shows systematic variation when categorized into quartiles by time headway. From the averaged time series in Figs On subject mean level, the results show a clear relationship between time headway, acceleration and jerk. From R2 = 0.92. Slopes of the regressions are significant at p < 0.001.Quantitative regression results for acceleration and jerk vs. time headway are shown in In order to test whether the measures can be reduced to a single dimension, a Principal Component Analysis (PCA) was performed. The PCA reveals that the first component explains 91% of all between-subjects variation in these measures. The second component explains 7%. This suggests that most across-driver variation in time headway, acceleration and jerk can be attributed to variation in single latent “driving style” factor. Details, including loadings, of the PCA can be found in the supplements .Lastly, we investigated correlations between the physical measures and background information. The correlations are generally small, with the largest ones found between age and mean jerk, mean time headway and the first PCA component (PCA1). Correlation between the second PCA component (PCA2) and driving distance in the past year also reached statistical significance at CL 95%. Full results can be seen in The results show a clear trade-off between jerky driving and time headway for the participants. On average, drivers opt either to match the leader’s speed at close distance, necessitating more intensive maneuvers when the leading vehicle accelerates or decelerates, or to stay further behind and regulate their speed in a more “calm” manner. This main finding supports the notion that the indicators of jerky driving and tailgating as outlined by Sagberg et al.  are reflWe propose that the correspondence between time headway and jerky driving reflects a trade-off that can be interpreted as an “intensity-calmness” parameter of driving style, i.e. the psychological component. We prefer to use the term “intense” instead of “aggressive”, as aggressiveness in traffic psychology literature most typically refers to an emotional state or trait, characterized by feelings of anger and socially hostile behavior. Instead, intensity is used to describe only the observed driving behavior, and may be a product of several psychological mechanisms.The latent structure of any global driving style is at present unknown, as shown by the variable results of questionnaire-based studies , 12. QueThe influence of driving experience to our measures was found to be small or non-existent, which could indicate that the differences are not a result of skill difference, but rather a learned preference. Moderate correlation between the second principal component and self-reported driving experience could be hypothesized to indicate differences in skill leading to “deviation from the trade-off line”, but our participant sample isn’t large enough to make such conclusion.A similar caveat should be recognized for gender and age, as our sample was predominantly female (66%) and fairly young (mean age 31 years). Both variables are known to affect driving behavior, with unsafe attitudes and risky driving often associated with males and young people , 28. WhiOne possible contender for the underlying mechanism for the trade-off is a difference in “mental effort” that drivers allocate to the driving task. A car following study with very similar setting to this article found that drivers strongly adapt their headway to attentional demands , with sirisk and the mechanisms that allow drivers to keep the risk level low enough not to crash, while accepting some risk in order to accomplish speedy travel [The theoretical discussion of speed control in traffic psychology has largely centered around y travel . In a lay travel  the concThe theories of risk which aim to explain how such trade-off gets established have somewhat different views on the role of risk in speed control. In what are usually called “target-risk theories” drivers continuously assess the risk in the situation and adapt their behavior to stay at a some subjective non-zero risk level –35. In oThe “zero-risk theory” disagrees with this view and argues that drivers habituate to different preferred safety margins (such as time headway or time to line crossing), which become “normal” for them, and any crash risk associated with the particular habitual choice of margins will not be subjectively experienced , 37. An The heterogeneity among driver-vehicle systems in terms of longitudinal speed control could and should be decomposed into a “psychological component” , a “vehicle” component (e.g. differences between truck and passenger car driving) and an “ambient” component . This psychological component would correspond to what in traffic psychology is referred to as driving style.The suggested implication that this discussion has on modelling heterogeneous drivers for traffic simulation is simple: With a more general description of inter-driver differences, one can begin to formulate model parameters which affect driver heterogeneity across different maneuvers.It is by now well known that driver heterogeneity affects traffic flow , 2, 22. The usual approach to estimating the parameter distributions has been to calibrate car following models per-driver to trajectory data, which has practical benefits, but the results are problematic to generalize across models and data sets. Establishing a more parsimonious and “model independent” driving style parameterization could be used to generalize driver heterogeneity results across models and across traffic situations. We propose that, alongside model-specific parameter studies, driver heterogeneity should be also studied using direct measures in order to establish more general, quantitative understanding of how driver, vehicle and situation dependent factors are exhibited in more specific driving tasks.Although providing strong and perhaps more generalizable results, the clear downside of direct measures is that they do not translate to modelling efforts in a trivial manner. To be usable in microsimulation models, future work should study how the driving style can be systematically related to such mechanistic models and their parameterizations. Also the global driving style hypothesis predicts more generally that the style should be reflected in variety of driving behavior, such as gap acceptance, curve negotiation and lane changing tendencies.In general, the veridicality of a driving simulator can not be guaranteed without comparison to on-road studies. Nevertheless, our experiment was kept at minimal complexity and the participant was not presented with extra tasks or more information that is available to a driver of a real vehicle. In addition, the task was framed by the instruction to resemble real driving to prime the participant into using prior knowledge about driving on a highway.Nevertheless, the possible influence of simulated rather than real driving to the results can not be ruled out. In understanding the task, drivers may adopt a different mindset than in the real world. Video games often require the player to find an optimal solution to the task at hand, and the simulator could have cued behavioral patterns more reminiscent of gaming experience. If, contrary to instruction, the participant understood the task to be “follow the leader as closely as you can”, the result might end up in the the small-gap, high-jerk part of the scale. Conversely, if the participant is trying to optimize for not having to stop or slow down and reasons that the leading vehicle behaves erratically, an unrealistically large-gap, low-jerk strategy might occur. However, the dispersion of the participants along the trade-off axis is quite even, with little extreme behaviour observed. The described behavioral extremes are also valid for real driving.The trade-off we observed in our experimental setting concerned between-subject variation, and can’t provide information on whether such trade-off occurs within-subject, for example in response to hurry or difficult driving conditions.We also acknowledge that the magnitude of accelerations and decelerations displayed by the simulated car may be excessive compared to real driving. Because the participants sat still in a closed room, they did not experience a vestibular or somatosensory response, which are produced by real-world accelerations of the body. The kinaesthetic sensations are highly important in judging one’s own acceleration in real driving, to the extent where decoupling visual and vestibular stimuli may cause motion sickness.While we believe that the sample size is sufficient in demonstrating the existence of a relationship between choice of acceleration, jerk and time headway, it is possible that a larger sample may have revealed more robust correlations between the observed measures and background information, e.g. driving experience. It is unlikely that the size of the sample is adequate for making population-level estimates of the parameters of the trade-off line.In this study we have demonstrated a clear relationship between time headway, acceleration and jerk at the subject level. If this dependency truly serves as an indicator of “global driving style”, as has been discussed, it would be useful to investigate whether it extends to other domains. Visual sampling rate might be a good candidate for future investigation, as closer following distances make it increasingly risky to drive without paying attention to the leader. Considering visual sampling behavior also raises the question of lateral control. Most models of visual control of driving deal mainly with lateral control . ThWe did not try to correlate the “intensity” of driving style to more traditional psychological measures such as personality, sensation seeking, extraversion or self-reported driving incidents or accidents. This would be an interesting aspect to study in the future, as these connections have been long pursued in traffic psychology. As noted above, it seems plausible that a connection between driving intensity and accident risk exists, especially if coupled with attentional variation or mental effort. It is probable, however, that a detailed explanation of accident risk would need to take into account the driver’s skill as well as driving style—habitual driving patterns alone are likely not sufficient for accurate prediction of risky driving. Even so, we would contend that at the very least, directly observable behavioral measures can provide new information and ultimately contribute to predicting risky behavior.Another interesting question to study would be the effect of both situational factors and the vehicle with respect to these results. One might presume that participants might change their behaviour if pushed to “hurry” or “slow down”, or do anything else which constricts their freedom to self-determine the task.Perhaps the largest undertaking is, however, to establish a clear connection between direct measures and the parameters of CF models. Given the potential benefits of looking at direct measures, this could include reformulating the models, or at least demonstrating that the simulated driver population reflects known relationships and obeys their boundary conditions.In summary, this article has made an effort to tie together discussions of driver variability in both psychology and engineering, and demonstrated that relevant measures in longitudinal speed control vary together—supporting the idea that one or many latent variables underlie habitual driving.S1 TableTable describing the relevant background information collected on the 15 participants. Driving experiences are self-reported estimates, with 8 discretized categories for lifetime experience (from “Less than 1000 km” to “Over 1 000 000 km”) and 9 categories for the last 12 months (from “None” to “Over 50 000 km”).(PDF)Click here for additional data file.S1 FileFor completeness, we provide figures for all the per-transition average accelerations.(PDF)Click here for additional data file.S2 FileDetails of the Principal Component Analysis for variables containing subject averages (N = 15)—mean acceleration, mean jerk and mean time headway. They include eigenvalues, eigenvectors and the loadings for each component.(PDF)Click here for additional data file.S1 FigThese figures represent the linear fit for the accelerating and decelerating cases for the subject averages of jerk and time headway. The lines are Ordinary Least Squares (OLS) fits along with their confidence intervals at CL 95%.(PDF)Click here for additional data file.S2 FigScatter plot showing mean time headway on the x-axis and mean jerk on the y-axis. Male participants in orange, females in green.(PDF)Click here for additional data file.S3 FigScatter plot showing the first two PCA components, with gender of the participants differentiated by colour. Should the two groups form distinct clusters, one would be able to see them here. No such pattern arises with this amount of participants.(PDF)Click here for additional data file.


Background: Research findings suggest that attitudes towards psychotherapy predict willingness to seek therapy. However, understanding how medical students think about using and referring their patients for psychotherapy is limited. Aims: The aims of this study are to measure medical students’ attitudes towards professional help seeking, and to investigate the reasons for whether or not they would refer their patients to psychotherapy in their future role as doctors. Method: The participants were 127 medical students in their first and second year of the MBBS4 programme at the Cyprus campus of St George’s University of London, who completed a self-report measure of attitudes towards psychotherapy and a semi-structured interview. Findings: Participants showed general positive attitudes towards psychotherapy, but were reluctant to use or refer their patients, largely due to perceived stigma and accessibility. Conclusions: Medical students should be further trained in order to become more confident in using psychotherapy and referring their patients. A number of research studies have provided evidence supporting the effectiveness of psychotherapy in the treatment of several mental health disorders. Psychotherapy has proved effective in treating people diagnosed with anxiety disorders such as obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and panic attacks ,3,4,5,6.Interestingly, attitudes towards psychotherapy seem to influence the willingness of an individual to seek or not seek professional help. That is, individuals who perceive professional help seeking in a positive respect are more likely to seek mental health treatment than those that have a negative attitude towards it ,9. A quaIn addition to negative attitudes affecting individuals’ responses to psychological treatment, factors such as past experience with psychotherapy and racial differences may also influence decisions to seek psychological help. Certain studies have examined the role of past experiences with psychotherapy and racial differences as factors that impact the attitudes of college students towards seeking professional psychological help. Masuda et al.  found thAlthough individuals may acknowledge the benefits of psychotherapy, certain barriers may prevent them from seeking professional help. The most common barrier to seeking psychotherapy seems to be public and self-stigma . So et aDespite the wealth of studies on the general college population regarding attitudes towards psychotherapy, little is known about the attitudes of medical students. It has been documented that medical students experience high levels of stress and anxiety ,21 durinAn in-depth understanding of medical students’ attitudes towards psychotherapy is very important, because as future practitioners, they might come across patients who would benefit from professional psychological support. Studies show that patients with a chronic disease are more likely to adhere to their prescribed therapy and eventually achieve positive health outcomes when they receive psychotherapy or other psychological support. More specifically, although von Wietersheim and Kessler  did not The existing research in understanding medical students’ attitudes towards psychotherapy is limited. In order to fill this gap, we aimed to use a mixed research methodology, so as to achieve a deeper understanding of medical students’ attitudes towards psychotherapy treatment. For the quantitative part, we used a standardized and reliable measure: the short version of the Attitudes Toward Seeking Professional Psychological Help-Scale  in orderThe sample consisted of 127 medical students in their first and second year of the MBBS4 programme of St George’s, University of London Medical Programe at the University of Nicosia Medical School. Fifty-nine participants were female (46%) and 67 were male (52%). Participants were between 20 and 54 years of age, with a mean age of 25.01. One participant did not fill in demographic data regarding gender. An ethnic classification  that is widely used in the United States was adapted for the study, and the results yielded participants from four ethnic groups: 68 Whites, 9 Black/African-Americans, 21 Asians, and seven from a mixed ethnic group. Twenty-three participants did not state their nationality. Twenty-five participants reported having had psychotherapy in the past, and 102 stated that they had never received any form of psychotherapy. From this sample , 12 participants were interviewed using the semi-structured questionnaire. The participants were first and second year students who did not have any specialised training in psychotherapy. However, they had to undertake 30 h of lectures in sociology and psychology, and a 30-h course in communication skills. During those sessions, participants were informed about the different types of psychological interventions and their effectiveness, and they were specifically taught about the use of cognitive behavioural therapy (CBT) and how it can be applied to patients with anxiety disorders. For example, in one of these sessions during their second year of studies, students learned how they could explain CBT to a patient and discuss its effectiveness with them. This enabled patients to reflect on situations where they had to cope with and manage stress in their lives, as well as understand somatic symptoms related to anxiety disorders such as pain, palpitations, or diarrhoea.The ATSPPH-S was originally developed in 1970, and revised in 1995 by Fischer and Farina. The updated version is a shortened 10-item scale that produces a single score representing the respondent’s core attitude toward seeking professional psychological help. According to Fischer and Farina , the intThe items are rated on a four-point Likert scale  for items 1, 3, 5, 6, 7. Items 2, 4, 8, 9, 10 are reversely scored . Scores range between 0 and 30. A high score indicates a more positive attitude toward seeking psychological help. Internal consistency and reliability have been found to be adequate for this scale ,28. TotaA semi-structured interview questionnaire based on the interview protocol used by Hill et al.  was used1. What comes to mind when you think about psychotherapy? 2. What are your beliefs about psychotherapy? 3. How did you develop these beliefs about psychotherapy? 4. When should a person seek psychotherapy? 5. At what point would you personally consider seeking psychotherapy for yourself? 6. Under what circumstances would you refer a patient for psychotherapy? 7. What is the client’s role in psychotherapy? 8. What is the therapist’s role in psychotherapy? 9. What are the benefits of seeking psychotherapy? 10. What are the barriers to seeking psychotherapy? 11. What would prevent you from referring a patient for psychotherapy? For the purposes of this paper, we focused on the results that related largely to the reasons why medical students felt positive about psychotherapy, and what they perceived as barriers to seeking professional help. Permission to carry out this study was granted by the Research Ethics Committee of the University of Nicosia, where the study took place, and by the Cyprus National Bioethics Committee. A convenience sampling method was used to recruit medical students studying at the University on a volunteer basis. The students were told that the study would examine the attitudes of medical students toward seeking professional psychological help. The questionnaires were distributed to the entire year 1 and 2 cohorts, who were asked to complete them anonymously and return them to the researchers. For the semi-structured interviews, students were informed about the study by email, and those who expressed an interest in participating were given an appointment and interviewed by one of the researchers. The interviews took a maximum of 30 min each, and were audio recorded. The coding and analysis of ATSPPH-S was done through SPSS, which helped us measure the mean score of the participants, and show whether the score was positive or negative towards psychotherapy. A correlation between the score and a number of participants’ characteristics such as gender, nationality and prior experience with psychotherapy was also investigated. All interviews were transcribed verbatim. The study relied on both deductive and inductive approaches. The deductive part consisted of four pre-determined areas of inquiry, namely: understanding of psychotherapy, use, barriers, and the roles of clients and therapists. Within these four areas, we used a “general inductive approach”  and geneWe created a codebook on the basis of the pyramid above. In the first layer of the pyramid, we identified 401 raw codes, which directly related to our research question. We then identified codes that fell under similar areas and ended up with 20 themes (second layer). We used these 20 themes in order to interpret the data by addressing our research question and the areas of inquiry. To ensure that we had enough data for analysis, we checked for data saturation . We measM = 17.01, SD = 5.94) and females, ; t (124) = 0.45, p = 0.65. Descriptive statistics showed that the mean attitude score was 17.2, which indicated positive attitudes. Independent-samples t-tests were conducted to compare the attitudes scores of males and females. As per M = 16.22, SD = 5.72) and Asian students ; t (28) = −19, p = 0.85, and between Black  and Mixed race students ; t (14) = 1.80, p = 0.09. The difference between Asian  and Mixed race students ; t = (26) = 1.74, p = 0.09 did not show statistical significance. Furthermore, there was no statistically significant difference found between White  and Black students ; t = (75) = 0.73, p = 0.47, and between Asian  and White participants ; t = (86) = 0.65, p = 0.52. However, White  participants were more positive than Mixed race participants ; t = (72) = 2.88, p = 0.005, and this was statistically significant.With regard to nationality , there wM = 20.64, SD = 4.93) and those who did not use it in the past ; t = (125) = 3.28, p = 0.001.Finally, as per In this part, we analyzed the results from the qualitative interviews in order to shed light on medical students’ attitudes towards psychotherapy. We focused on medical students’ beliefs about psychotherapy, their willingness to use psychotherapy or refer their patients for it, and the reasons for not using psychotherapy.“I support it, I think everyone should have it, but not necessarily everyone has to do it because a lot of people have their coping mechanisms, which are either their friends or families, but not all people have that—ability to talk to someone. So, in some cases and especially in very traumatic cases, or if someone has very complicated problems, it’s best probably addressed by someone who is professional and knows what they are doing.”Participants used an utilization approach when they expressed their beliefs about psychotherapy. All participants had a positive belief about psychotherapy in terms of its utility, as they perceived it as helpful for people in need and part of a more holistic understanding and intervention. More specifically, a participant said:Overall, participants would recommend psychotherapy to someone they thought would benefit from it. Participants’ beliefs came from a variety of sources, but could be organized into two main areas. First, participants had institutionally-induced beliefs. That is, they had beliefs that were influenced by the institutions they were socialized in, such as education and the media. Second, participants’ beliefs came from their own experience, whether personal or that of other close people’s experiences, such as friends and family. Interestingly, although all participants expressed positive views towards psychotherapy, there was a difference between those who used psychotherapy in the past and those who did not in terms of the words they used to describe it. The participants who used psychotherapy in the past used adjectives that added more value to its mere utility, such as “great”, “wonderful”, and “powerful”. The participants who did not use psychotherapy in the past described it merely in terms of its usefulness and used words and phrases such as “helpful”, “useful”, and “treatment tool”.Participants were asked to express their views about the use of psychotherapy for someone else and themselves, as well as explain what the benefits were and under what circumstances they would refer a patient for psychotherapy. Participants’ views about the use of psychotherapy aligned with their positive beliefs. That is, they maintained that someone (including themselves) would use psychotherapy when they had a disrupting experience in their life or when they were encouraged to do so by other people, such as family members. Thereafter, psychotherapy would be a useful tool for re-establishing their psychological well-being. In addition, psychotherapy would not only make them feel better psychologically, it would also help them regain their position in society, such as being productive and effective in the workplace, at home, and among their peers. The use of psychotherapy, interestingly, would mean the re-institutionalization of the individual—that is, the re-integration of the individual in social institutions. For these reasons, participants would generally refer their patients for psychotherapy. Some participants explained that another reason for seeking professional help would be an individual’s decision not to talk to friends or family about their problems, and seek professional help as a result.To support their views about the benefits of psychotherapy, participants used a generalization and specification approach. More specifically, they generalized the benefits from psychotherapy based on the knowledge they acquired from their studies and the media, and they referred to specific cases that involved their friends or family members. Interestingly, participants understood the use of psychotherapy as a tool for the management of a problem, but not for preventive purposes or for personal development. For example, they would not think to use psychotherapy themselves or refer a patient for psychotherapy when they experienced difficulties in their life that they thought they could handle, before developing any psychological disorders. This finding possibly accorded with participants’ preoccupation with a possible stigma (see next sub-section for more information) that might attach to someone who is seeking professional help for psychological problems. That is, they would seek help only when there was no other way out. In that case, getting well would be more important than being stigmatized. “The stigma that exists in psychotherapy and all the treatments related to psychiatric illnesses is really important”.The main barrier for not using psychotherapy, which was expressed by all participants, was stigma. Participants explained that the fear of being stigmatized as “crazy” would be an important obstacle for someone or themselves not to use psychotherapy, or not to refer their patients for it. For example, a participant said:“One is just the social barrier of ‘I’m not crazy, I don’t wanna go and see a psychotherapist, I’m not crazy, I’m not that person’”.The stigma was mentioned by almost all participants as a strong barrier. Another participant was even more specific:Another perceived barrier was accessibility. To participants, inaccessibility meant two things: the financial cost of psychotherapy, and second, a lack of knowledge about the usefulness of psychotherapy. The barriers that prevented medical students to seek out psychotherapy support for themselves, as mentioned above, were the same barriers that would prevent them from referring patients for such support as future doctors. If an individual perceived psychotherapy as a stigma for themselves, then they perceived it as a stigma for others as well, and would thus refrain from referring others to this kind of support. Other reasons participants would not refer patients for psychotherapy included their belief that psychotherapy would potentially culminate in other problems or difficulties. In addition, participants would not refer their patients to a psychotherapist if the patients were not be willing to have an active role in the psychotherapy process, or could solve their problems themselves. Based on their previous views on benefits, participants used what we call “a reverse reasoning alignment”; that is, they would not refer their patients for psychotherapy if the reasons for referring  were not present or were reversed. One of the aims of the study was to assess medical students’ attitudes towards professional help seeking using a quantitative standardized measure. The findings from the quantitative data reveal that medical students have positive attitudes towards psychotherapy. No difference was found between males and females. However, there was a difference between white and mixed race participants, with white participants showing more positive attitudes than the mixed race group. This supports research findings by Masuda  that proThe results from the qualitative interviews helped explain why medical students were generally positive towards psychotherapy. Medical students expressed positive beliefs because they considered it a tool that people can use to solve a problem they cannot solve on their own. This positive belief derived mainly from their training at a university, the media, and from prior experience with psychotherapy. This finding is in accordance with Hill et al.’s  study, wMedical students scored an average of 17.2 in the ATSPPH-S scale, which showed that they were generally positive towards psychotherapy. However, they could have scored much higher. The highest score that could have been reached was 30, given that they had some exposure to the different types of psychotherapy  and were educated as to their importance during the first two years of their study. What is not clear from the score itself is why they did not score higher. The qualitative results have been very illuminating. It seems that some of the barriers to using or referring patients for psychotherapy are powerful enough to keep medical students at a distance. The strongest barrier that this study found is that of stigma. Medical students considered a potential stigmatization of being labelled “crazy” as an obstacle either for utilizing psychotherapy themselves, or referring their patients for it. This is in line with other studies, which found that the fear of breaking confidentiality was a serious barrier for their participants , and thaOther barriers to seeking psychotherapy were related to issues of accessibility and related to financial cost or lack of knowledge of the benefits of psychotherapy. Participants were also reluctant to refer patients for psychotherapy if they believed that patients would not have an active role in the therapeutic process. Our findings are supported by Vogel et al. , who proThe most important findings from this study that can contribute to the improvement of help-seeking behaviours are that medical students are positive when they have been exposed to psychotherapy themselves, and that they are not willing to either utilize psychotherapy or refer their patients for it when the perceived stigma outweighs the perceived benefits and outcomes. These two main findings can have important future implications, which are discussed below. We now know that medical students are generally positive towards psychotherapy, but they may not use it themselves or refer patients for it due to the impact of stigma. Based on this finding, medical students could be trained on two levels. First, they could be trained more thoroughly on the importance of psychotherapy and how it can be used in medical practice. Medical students would then further appreciate the importance of psychotherapy, not only in terms of it helping their patients deal with issues they cannot handle on their own, but also in the sense of doing their job more effectively as doctors, communicating better with their patients, improving their patients’ adherence, and eventually achieving positive health outcomes. The second level on which medical students could be trained involves teaching them ways to override the socially constructed stigma, either for themselves or their patients. By learning that stigma is a purely social product and there is nothing objective behind it, students can understand it as a manageable perception and focus more on the importance and effectiveness of psychotherapy instead. The doctors’ job in handling stigma would be much easier if the general public was informed about its nature, as well as ways to deal with it. Such public awareness and education could have taken place from an early age during school years.Furthermore, as the financial cost of therapy and the lack of knowledge regarding the usefulness of psychotherapy were mentioned as barriers to seeking help, medical schools could consider providing free counseling services for their students, while health care systems could incorporate free psychotherapy services to patients and their families alongside their other services. One of the limitations of this study was the small size of the sample. Participants were also students recruited from year one and two of one specific medical school; therefore, the results are largely indicative of medical students’ attitudes toward psychotherapy. Furthermore, although a statistically significant difference was found between white and mixed race participants, with whites showing more positive attitudes than the mixed race group, this should be treated with a degree of caution since there were only seven students in the mixed race group. The number is too small and these findings need to be replicated in larger samples before firm conclusions can be drawn in relation to differences in attitudes towards professional help seeking between white and mixed race samples.This paper discusses the findings of a study of medical students’ attitudes toward psychotherapy in order to fill in the gap that exists in the literature in this area. To ensure adequate and deep understanding of medical students’ attitudes towards psychotherapy, the study relied on a mixed research design. That is, it combined quantitative findings derived from the completion of the validated questionnaire, The Attitudes toward Seeking Professional Psychological Help-Scale (ATSPPH-S) by 127 medical students and qualitative data from 12 in-depth interviews. The results indicated that medical students are generally positive about psychotherapy (score 17.2/30), but perceived barriers prevented them from scoring higher. Though the financial cost of psychotherapy and poor awareness of its benefits are understood as barriers to either using psychotherapy themselves or referring their patients for it, the most important barrier for medical students is perceived stigma and how psychotherapy can portray its user as crazy or insane to the rest of society. Interestingly enough, although the participants had some form of exposure to the different types of psychotherapy and its effectiveness, and had received a lot of information on cognitive behavior therapy (CBT) and how it can benefit certain patients, when asked the hypothetical question of whether they would refer their patients for such support, their response was that they would do so only if the benefits  outweighed the perceived cost from stigma. These research findings highlight the importance of providing further education and exposure about the positive effects of psychotherapy on patients. The results of the study could have been different if the participants were fully acquainted with the concept of psychotherapy and its uses as well as its benefits during their medical school training. Future studies could investigate the impact of knowing about psychotherapy on attitudes towards professional help seeking.


This study examined differences in self-regulation among college-age expert, moderately expert, and non-expert video game players in playing video games for fun. Winne's model of self-regulation Winne,  guided t Call of Duty: Advanced Warfare, has been played over a billion hours since its release in November 2014, while the PEW Teens, Social Media, Technology Overview , Experts are recognized for their extensive experience and deep knowledge in a given field, but we also know that becoming an expert is not an easy process. It is generally accepted that one typically needs to study and practice thousands of hours in a domain in order to become an expert .In order to bring quantitative and qualitative parts of the research together, a mixed methods question then was utilized to guide the study, framed within a sequential explanatory design , each tracing back to one or more different self-regulated learning models that offer different perspectives on how self-regulated learners function  in order to win a battle or progress in the game. Inputs may include the information presented as products of the task definition  and goal setting and planning phases . In the enacting tactics phase, players may create new products using new approaches  and evaluating the effectiveness of these tactics in comparison to standards. Finally, in the evaluation and adaptation phase, video game players may assess their whole game play; then, based on their analysis, they may decide to abandon the way they previously played or search for new ways to play in the game's social world, in other words in the game's affinity spaces  design  were female and 27% (35) were male. Student reporting their ethnicity as Caucasian comprised 88% of the sample, while 3% were African-American, 2% were Asian/Pacific Islander, and 7% were multiracial and other. Thirty-two (24.8%) students identified themselves as sophomores, 52 (40.3%) indicated they were juniors, and 43 (33.3%) reported they were seniors. Two participants (1.6%) were graduate students.Of this group, 87 participants (67.4%) labeled themselves as non-expert video gamers, five (3.9%) reported that they considered themselves expert video gamers, and 37 (28.7%) indicated that they were moderately expert video gamers. Participants also were asked to estimate the number of years they had been playing video games. This number ranged from zero to 26 years, with a mean of 9.8 years, a median of 10 years, and a mode of 15 years.All needed permissions were obtained from the course supervisor, course instructors, and the university's Institutional Review Board (IRB) process prior to presenting the survey to students in the targeted courses. Those students who agreed to participate were administered the VGPS, which included three sections:General information about participants' video game playing. This section of the survey inquired about general video gaming habits and expertise level and included eight items asking participants about the hours they played video games and experiences with games of various genres. In order to permit identification of participant subgroups based on their expertise in video game playing, questions . The second part of the survey consisted of a measure, the Playing My Video Game Scale (PMVGS), in which participants were questioned about their actual processes of self-regulation during recreational gaming. The PMVGS scale was constructed to reflect each of the four posited categories of Winne's ( Winne's  model ofN = 20) from the same general participant pool as the study's primary participants. Cronbach's alpha reliability for the overall scale in the pilot study was 0.94 but due to the limited number of participants in the pilot study, however, exploratory factor analysis (EFA) was not conducted to find possible subscales of the PMVGS. Based on results from the pilot test, a near-final set of items once again was reviewed by the researchers for final edits in wording and methods of scale administration made to make the measure more suitable for college age video game playing students.Preliminary versions of the PMVGS were further refined through discussion with faculty members and graduate students with expertise in video games and educational research. It then was pilot-tested with a set of college students  was calculated, which again showed the scale to have high reliability (α = 0.97).In the study itself, however, EFA was used to determine if there were possible subscales or results at any level corresponding to the dimensions proposed by Winne and colleagues  and re-running the analysis, thus providing further evidence of the validity and practical significance of the three cluster solution. When these results were compared with the participants' original cluster assignments, 77% of the subjects were classified correctly allowing for confidence in distinct and stable clusters according to participants' amount of hours spent playing video games and video gaming expertise.Hierarchical cluster analysis showed the presence of three main clusters in the participant group. In order to validate these three clusters, data were analyzed via non-hierarchical k-means cluster analysis in which a three-cluster solution was used as an input  representing participants who were not video game experts, Cluster 2 (n = 55) representing participants who were moderately expert, and Cluster 3 (n = 10) representing expert video game players.The three clusters were utilized to represent overall video gaming expertise levels  = 115.82, p < 0.001], in a typical week when classes were in session , in a typical week when there were no classes , and in a typical recent week in which they played their most played game .As seen in Table F = 102.83, p < 0.001] and in the game they played most often . In conclusion, it could be said that these groups clearly were distinct from one another.Table PMVGS item scores. This analysis revealed significant differences  among expert, moderately expert, and non-expert video game players. Post-hoc follow up analyses using the Scheffe criterion for significance  self-regulated more than moderately expert video gamers , and that non-expert video gamers , and moderately expert gamers self-regulated more than non-experts .In order to examine if there were any differences among these groups in terms of self-regulation of video gaming, the researchers conducted one-way analysis of variance utilizing participants' self-regulation of gaming scores, which was the sum of p < 0.01) on all of the self-regulation items, indicating that experts reported utilizing a wider variety of self-regulation processes during their video game playing compared to non-experts. For the majority of items, similar differences appeared in comparisons of expert and moderately expert players.It should be noted that the scores of experts and non-experts were significantly different  were contacted via email. As indicated by Creswell and Plano Clark , this nuqual designs typically is to explore and elaborate on the results of the statistical tests , and game context. The role(s) and functions of these five themes then were analyzed across all three expertise groups.characteristics of expert video gamers, emerged from participant responses about expert video game players themselves. One of these characteristics, identified by every participant, was that they spent a lot of time with playing video games and practicing their skills. A second characteristic identified by all interview participants was that an expert video gamer almost always wins either at different levels of a game or against an opponent. Video game experts also indicated a third characteristics—that they had a variety of strategies to play with. Statements of moderately expert and non-experts illustrate this clearly. Mersin, a moderately expert gamer, shared that an expert is someone who is “…looking up all the different like ways to win game or to better (their) score.” Dolunay, a non-expert, stated “…they talk to their friends about different ways to beat the games.” The fourth and fifth characteristics of expert game players were constructed from statements of expert and non-expert game players. Participants indicated that an expert video game player understands every game quickly. Finally, a fifth characteristic of expert game players that both expert and non-expert participants agreed upon was that expert players were skillful and experienced. It seemed that expert participants focused more on experience and non-expert participants emphasized becoming more skillful and competitive.The first theme, This theme had mostly to do with where, when, and with what video gamers played video games and how they viewed themselves as video game players. In general, participants in the qualitative part of this study reported playing video games both on and off campus, with expert participants mostly reporting that playing video games in their own home or room and their parents' or friends' homes.Almost all participants reported playing video games anytime they were available. Moderately expert and non-expert video gamers tended to report that they played on the weekends or school break, while expert video gamers reported playing almost any time they had free time. Koray, an expert participant, stated “I would just say (I play) almost whenever, usually in my free time.” Likewise, Canay from the same group shared “…pretty much whenever I have a free minute I'll do it.” Mersin, from the moderately expert group, said “…when I have free time, like before class (when) I don't have like anything else that I need to be doing. So just more of a free time type of activity.” Dolunay, from the non-expert group also agreed “When I have free time. More on breaks, like summer break and like winter break.”Wii. Tamay, a moderately expert participant, agreed “…most video games that I play are like Wii or stuff that (is) on my phone.” While Hanay, from the non-expert group, stated “If I've ever play video game (sic), it is usually on my phone,” Gurelay, an expert participant, indicated using a special game device by saying “I have an Xbox which is set up in my living room,” Self-reported confidence of participants also varied by level of expertise, with expert participants being more confident than their moderately expert and non- expert counterparts.The devices participants reported playing also varied by level of expertise. Non-expert participants mostly reported playing on their phone, while moderately expert participants indicated playing with their phones as well as on computers and special game devices such as the The variety of approaches by which game players began interaction with a game varied along such dimensions as visiting a game's affinity space or discussion group or by observing a group of game players. This theme was clear through participant statements about how they attempted to figure out game rules and context, monitor and control their current play, and utilize prior experiences. Specifically, participants from the expert group—more than the other two groups—reported that they preferred to “…go straight in to the video game and figure it out as I am going” (Canay). Similarly, Koray, another expert, stated that “I am more of a player that (goes) through and mash buttons—like I try to figure it out myself before I go to read the tutorials or something like that.” Expert participants also reported using monitoring and control processes more the other two groups.Temple Run you have to get like X amount of coins in order to like move on to like a harder level.”As participants were figuring out the game they sought affordances in the environment in order to progress. Two experts and one non-expert participant talked about this in the qualitative interviews. Canay and Gurelay, respectively, stated “…you skim to the menu to see what's available to you” and “I usually look up the control buttons other than that I usually figure that out as I go.” Hanay, from the non-expert group, noted “…just figuring out like the points I guess. So like for This theme included participants' statements about their goals and tactics, the way they seek help, and how they adapt play for the next time. In regard to goal setting, expert and moderately expert participants reported setting goals more than the non-expert participants. However, although the expert and moderately expert participants implicitly indicated that they set specific goals, the non-experts explicitly noted forming goals before or during playing video games. Renay, a non-expert, stated “I probably set goals. I guess just kind of for time limits. Say I set goals. Like OK, I can only play until I get 3 stars from this level and then be done.” or “3 stars in these 5 levels and then I'm done.” Similarly Dolunay, a non-expert, shared that “I usually have a goal. I usually try to beat whatever I had last. And if I can't beat the level I keep trying and trying—I don't skip it until I beat it.”Expert and moderately expert participants reported how they use tactics when game playing while non-experts generally talked about finding the best way to move forward. For instance, Canay, an expert participant, stated:I like to, extra like (to) just explore the game so if it's like a role playing game or I usually get in that world, then you get to actually explore the role; you can just finish the quest you're supposed to [in order to] go on or you could just run around the world and figure it out. I like to run around the world to figure it out a little bit before actually completing all the quests. I like to complete the game in a 100% entirety so I must figure out what it will take beforehand—what quest that I am gonna have to complete to get that done? Like you can go to, like if you have played or bargained or weapons or anything like that you need to get. You skim to the menu to see what's available to you.Tamay, a moderately expert participant, reported that “I guess I try to think of what comes next. Because what you do right doesn't really matter so much because you have already kind of thought through it. So you try to make yourself think a step before you are actually doing.”Hanay, from the non-expert group stated that “I guess (I) just figure out the rules and then I just figure out what best choice to like play” and Dolunay, a non-expert said that “ If something didn't work last time then I don't want to do it again.”Participants from all expertise groups indicated that their game play changed from game to game. Koray, an expert, shared how he decides how to play, “…it is all very circumstantial. It depends on what is going on in the game.” Gurelay, another expert, reported, “I guess it changes from circumstance to circumstance and from game to game. Different types of the games I assume would be completely different in how you approach them.” Mersin, a moderately expert player, agreed, saying that “…what I really do depends on what game I guess.” Similarly, Renay from the non-expert group stated that “It depends on the game.”Skyrim, I look up some stuff on the internet just to figure out what I am doing.” Canay, another expert, gave this example:Relative to the help-seeking processes of self-regulation, both expert and non-expert participants reported seeking help. Gurelay, an expert, noted “For some games, like …and if I am stuck in a level and need help, say I can't get past this level, it is going to drive me insane. What can I do? So they usually are more than willing to help me as I am figuring (something) out or if it's a friend I call them.But non-experts also reported seeking help. One of these, Renay, stated that “…looking at online strategies that other people have used and maybe even finding cheat codes.” Dolunay, another non-expert, indicated that “If I don't understand the game I'll ask maybe a friend who plays the same one.”The game context theme refers to how the video game players used the game environment to support them in monitoring their progress in the game, whether they talked about a game with anybody, and whether the way they studied was similar to the way they played video games. The majority of moderately expert and non-expert participants reported relying on the game itself to keep track of their progress while they are playing. One non-expert participant, Hanay, when asked how she tracks her progress stated “…usually it [the game] keeps track.” Tamay, a moderately expert player, noted that “During the play I guess usually the computer does it for me. But you can also keep tracking in your head like how many coins that I can get on the last one. Like if count above like how many coins that you have over the top you can keep counting as you go through.” Moderately expert and non-expert participants also reported talking with others about a game.Unlike moderately expert and non-expert participants, however, all of the expert participants made associations between how they studied and how they played video games. Canay, an expert, stated: “Basically, I would say like the way I map out my homework to get my homework done and making sure I am completing everything would be the same as the way I would map out a game to see that I am actually completing everything in that level to pass forward to it. I kind of try to make sure I cover the basics and I (have) done everything that I need to be done. So that's very similar and I haven't thought it before but that's very similar. Koray stated that “…because of like I said if I know something is not working then I am not gonna do it again. I guess that kind of trial and error aspect is similar.” Along the same line Gurelay added, “Actually, I‘ve learned a lot of history from playing certain games. It helped me with umm I guess some of my history classes I suppose.”Both quantitative and qualitative analyses comparing video game players in the three expertise groups revealed significant differences in self-regulation favoring the experts. Specifically, expert game players used processes of self-regulation considerably more than moderately expert players, and moderately expert participants self-regulated more than non-experts  friend's house.” As indicated in Winne's model of self-regulation, conditions are important inputs to the self-regulated learning process. Furthermore, prior SRL studies have shown that the more students were aware of task requirements, context, and their surroundings, the more likely they are to use processes of SRL and succeed in a task  rather than on the strategies that produced those outcomes.Both expert and non-expert participants in the present study quite clearly indicated that they This difference in focus perhaps can be explained by the dissimilarities within the goal setting and planning phase where the expert participants set more game-related goals than moderately expert and non-expert participants. Presumably, the expert players could be more specific and purposeful about what they were aiming for and the steps they believed were needed to accomplish their goals . Some studies in the literature  this difference did not appear in comparisons of expert and moderately expert participants. On close examination, it was noted that members of both groups included other gamers' inputs to their present game play. That is, in order to play better both expert and moderately expert participants reported utilizing tactics tied to other video game players, including judging how they are playing (Item 9), emulating successful players (Item 14), and co-playing with another player (Item 18). In other items related to tactics that included just themselves and no other players , the expert participants scored significantly higher than moderately expert ones.In contrast to the expert players who tended to apply all available tactics—their own and others—moderately expert participants mostly relied on tactics that included other players. This could mean that the experts possess a larger repertoire of tactics than moderately expert and non-expert participants, consistent with earlier studies of expertise  could be analyzed in terms of what self-regulation processes are driving these visits.Unlike other dimensions in the adapting metacognition phase , expert game players reported more adaptations in their play from one time to the next than did the non-experts. Specifically, expert players on average rated items focused on their thinking of new ways to pass a challenging level of a game and being open to suggestions to improve their play higher than the moderately expert players. For instance, Koray, from the expert group, shared the following view: “You can see how I play right after the game and what kind of progress there is. In sports games they put the stats right in front of you so you don't have to think about whether or not you did well, all you have to do is look. But for Call of Duty, if things aren't going well, I will do a kind of mental inventory of the things that I have tried and what is and isn't working.”Finally, among the items addressing the PMVGS and across all the categories of self-regulation represented . Also, given that the quantitative portion of the current study was conducted using a convenience sampling method, future studies aimed at understanding how the self-regulation of expert and less-expert game players in varying age groups might differ should be valuable. Focusing especially on specific dimensions of self-regulation utilized by expert players  likewise should lead to better understanding of how game-related self-regulation processes might be generalized to more academic tasks and contexts. That is, understanding how expert video game players manage these processes may help educators encourage student learning and cognitive growth by exploiting commonalities between successful game playing and self-regulated learning more generally Gee, .Call of Duty) players must become familiar with their weapons and practice using them, as well as improving their map reading skills. In a strategy game , in contrast, players need to determine their goals before taking next steps and to analyze neighbors' investments in order to allocate their resources successfully. In light of such differences, future studies examining interactions between specific game features and the application of self-regulation processes almost certainly will prove to be valuable.Finally, it should be noted that the current study—as a preliminary exploration of self-regulation processes in recreational video game playing—did not focus extensively on particular video games or game types. However, both participants' statements and the researchers' observations clearly indicate that different types of games require varied skills and modes of self-regulation for mastery. For example, in a first person-shooter game . Drafting the work or revising it critically for important intellectual content . Final approval of the version to be published . Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Dear Editor, I read the recent publication on “Misconduct in Research and Publication” with great interest. I agreeAn important question is whether such measures are suitable corrective actions. In general, if the misconduct is detected, reporting to the researchers’ organization, as well as retraction of the articles with public announcement by the journal, are recommended. Nevertheless, there is often no incurred penalty or response from the researchers under question or their affiliated organizations. If those committing the misconducts are senior academics, they might receive no penalty and may even be further promoted based those questionable publications. Sometim


In genetics, transformation describes a process of transferring DNA to another cell, and in medicine, “malignant transformation” means the transition from normal to tumor cell growth. Social transformation refers to the fundamental metamorphosis of a political system into another; in architecture, it means the conversion of existing buildings, and the term “digital transformation” keeps popping up in talk shows. It almost seems as if "transformation" is a ubiquitous phenomenon inherent to the world of things which tags standstill as a failure. The world of medical education is no exception, although if looked at cursorily, the players’ willingness to embrace change may not always and not immediately be noticeable [https://de.wikipedia.org/wiki/Labor cited 2016 Jan 24] have been set up for the systematic and longitudinal training of skills can only be interpreted as part of a transformation process, i. e. the professionalization of medical education.One particularly successful major project in this area is documented in the present special issue “Clinical skills”: 20 years of development of "skills labs" in the D-A-CH region (Germany/Austria/Switzerland)! Clinical practical skills have been taught before, according to training regulations and laws. However, the fact that an impressive number of laboratories  of Vienna, was first, followed by Berlin (1999), Heidelberg and Frankfurt a.M. (2000), Cologne (2003), Mainz (2003), and others. The accompanying transformation of education in human medicine can be described in many ways: historically , economically , outcome-oriented , or with regard to the supported processes of change in medical education:The transition from pure knowledge-based higher education to a competency-based orientation without systematic inclusion of skills training is simply unthinkable.The systematics inherent in action-oriented skills training (“see one – do one”) offers the transition “from teaching to learning” an inherent field for assisted self-regulation in the learning process by providing specific contexts, scenarios and – often formative – feedback.The democratization of knowledge through peer teaching often employed in the skills labs finds resonance in the medical faculties by virtue of the changed roles in the learning process.The training of practical skills can be seen as practiced, active patient protection.If form follows function, the transformation of the organization of the skills labs must be - and has been - understood as a response to the professionalization happening in medical education. While it often started as a students‘ initiative, full-time management is today’s standard. In the beginning, the skills part of the curriculum could often only be offered as an added option, but nowadays, curricular integration seems adequate. While at first, skills labs would be housed in buildings set for demolition on the edge of hospital grounds in recognition of the effort spent, new, designated buildings are now being built on prime real estate. Formerly, training centers for patient-centered skills developed one-dimensionally toward the fulfillment of tasks in the study of medicine, but today, they are in demand by continuing education and training programs both in medicine and other health professions; hence, they are becoming true nuclei of interprofessional education. http://www.nklm.de cited 2016 April 14]: as a source of ideas for the formulation of “competence levels” and the “milestones of skill acquisition” as well as the basis of chapter 14b, “Clinical practical skills”. Currently, the accreditation regulations appropriate to higher education and concerning education, advanced and continuing training of clinical practical skills are being developed, to be become effective this year.While formerly, skills lab employees were without outside support, since 2007, they have been able to rely on an established Committee on Practical Skills of the Society for Medical Education which hosts an annual international skills lab symposium (iSLS) of up to 300 participants, and which may be considered as the engine that keeps the described transformation going. Besides providing a platform for scientific exchange, the iSLS focuses on skills lab staff‘s continuing education and networking, with meetings for the student employees, regular skills lab manager meetings (sLiT), and the Committee meetings ultimately serving the professionalization of skills labs in the D-A-CH region. There, the content of the “Consensus Statement on Practical Skills in Medical School”  was defiFinally, this transformation raises the question of further development of centers for learning clinical practical skills. Although the future is open by its very nature, key questions can already be derived whose answers will shape tomorrow‘s discourse:Following “competence”, what metaphor will govern the discussion on further development of medical education, and what - deliberate - role will the skills labs play in it?What are the effects of the profanation of the skills labs accompanying their professionalization in the context of medical schools ?Furthermore, what is the role of hands-on experience  with regard to “augmented reality”, or, in other words: will the digital revolution transform the - as yet physical - skills labs into “holodecks” in the future?https://www.aphorismen.de/zitat/108609 cited 2016 July 5].“They say that the ‘little man’ cannot achieve anything. But, if everybody finds another little man, many little men can achieve a lot.” (Thomas Häntsch (*1958), photographer [The authors declare that they have no competing interests.


Latinos are the largest minority group in the United States, and in California they outnumber non-Hispanic whites. Smoking cessation programs tailored for Latino culture, and this population’s specific smoking patterns, are needed. Online social networks for smoking cessation have high potential for Latinos, but have not been tested to date.Building a research program on social media apps for cancer prevention in diverse populations, this qualitative study assessed acceptability of tobacco treatment that was distributed via social media for Latino smokers.We conducted three focus groups with Latino adults who were former and current smokers recruited from Santa Clara County, California in 2015 (N=32). We assessed participants’ smoking histories, attempts to quit, social media exposure, and receptivity to a social media-based smoking cessation intervention. Audio transcripts were translated and coded for themes.Participants reported factors driving their tobacco use and motivations to quit, and emphasized the importance of community and family in influencing their smoking initiation, cravings and triggers, attempts to quit, and abstinence. Participants valued the communal aspect of social media and suggested strategically tailoring groups based on key features . Participants reported preferring visual, educational, and motivational messages that were connected with existing services.Participants generally voiced acceptability of a social media-delivered intervention to help them quit smoking, viewed the intervention as well-equipped for catering to the strong community orientation of Latinos, and suggested that the platform was able to address variation within the population through strategic group creation. As a group member reflected, “Podemos hacerlo juntos” (We can do it together). Tobacco is the leading preventable cause of death, and is linked to a dozen types of cancer, along with heart and lung disease . TraditiTailoring of cessation treatment strategies to target audiences has been a strategy for increasing reach and engagement. In the early 1990s, a printed Spanish-language smoking cessation guide was found to support quitting and was distributed as a best practice . A 2003 P=.012); 81% of the sample was non-Hispanic white  would help them.Participants reported using various social media platforms, including Facebook, Twitter, Instagram, Skype, Yahoo, and Snapchat. The groups stated a strong preference for Facebook and visual messages. The overall sentiment across groups was acceptability of social media as a vehicle for smoking cessation programs. One participant stated, “I think this idea is very good because… we’re 100% cybernetic… and [social media] is the right weapon to use.” Another asserted, “I think it would be a magnificent idea because… I have people on there [Facebook] that put they feel bad… and we send them a message, and it helps.” Furthermore, social media smoking cessation groups were imagined as supportive of quitting, in contrast to existing social networks of smokers who may encourage continued smoking. Participants also liked the idea of knowing that strangers in a group would withhold judgment toward any failed quit attempts.Not all participants agreed, however, with one participant stating that his family and friends would be better able to support his quitting compared to, “a group of strangers.” One participant resisted the idea of spending more time on her phone, noting that as a parent her time at home is already too hectic. Another respondent voiced concern, explaining:I don’t know how comfortable people would be about going into a group… share with someone that they don’t know. Being anonymous… especially since Latinos… we tend to be more like, who do I know versus I don’t know you. I think that might become an issue.Participants discussed whether the groups should be matched on salient characteristics. One social smoker wanted to be in a group of nondaily social smokers. Another participant suggested creating groups based on common interests, similar to what is done on “dating sites.” A discussion centered on matching participants by age. One young adult participant stated, “If I see a young person trying to stop… we can do it together.” Another participant voiced potential benefits of mixed-age groups, stating:different ages could help. I know that for the young ones, the pressure they have is very difficult, even more if they’re in school, they get stressed out, and they want to relax. So having an adult in that group who has more knowledge could be beneficial to them.Other respondents encouraged the idea of keeping age unknown. One participant, with the perspective that age should not matter, asserted, “Cancer doesn’t look at ages, or race.” Another participant reflected:The most convenient thing is to have the ages unknown because maybe the one who is smoking really needs help. If they say, ‘Oh, it’s a person who is 60,’ and they’ll say, ‘What’s this old man or woman going to know?’Regarding language preference for a Latino-focused smoking cessation intervention on social media, 7 participants preferred a mixed English/Spanish platform, 4 preferred Spanish only, and 1 preferred English only. Three additional participants did not have a preference, and opted for group leaders to choose. The other 17 participants did not voice a preference. All participants, except the one who preferred English only, reported that Spanish was their dominant language.Participants shared advice on the types of smoking messages that would be most effective for individuals trying to quit smoking. There was a preference for nonforceful communication with no demanding messages, such as, “Don’t push; we’ll do it because we want to do it.” Preferred messages were educational and provided motivation and support. One participant emphasized, “It’s important that we know why we are making the decision to quit. It’s good to help us understand why we made decisions to quit.” Participants also recommended linking social media cessation interventions with existing support systems and services, such as the national smokers quit-line (1-800-QUIT-NOW).The use of visual images was also encouraged, reflected by the quote, “A picture has a bigger impact than a word.” One participant shared, “I have a friend and he’s a doctor and he continuously post lungs… [and information] about cigarette filters.” Two participants stated that it was uncommon to see images or information about smoking on social media, while others noted postings of drinking and smoking at parties rather than encouragement to quit.Despite not being part of the discussion guide, e-cigarettes represented an emergent topic with a variety of expressed opinions. Some participants were positive towards e-cigarettes with assertions that, “They’re not as bad as cigarettes”, “They’re cheaper than tobacco”, and not a “bother” to others with a bad smell. Participants reported seeing e-cigarette advertising cessation claims, although no respondent reported successfully quitting smoking using e-cigarettes. Participants reported a willingness to try e-cigarettes, largely out of curiosity instead of a desire to quit smoking.Tweet2Quit in a largely non-Hispanic white sample found that participant engagement  predicted success in quitting smoking [Latino smokers and recent former smokers from the Bay Area of California largely found the concept of a social media tobacco cessation intervention acceptable. Social media was perceived to be well-equipped to meet the social- and community-oriented experiences of Latinos. Participants also noted that social media could allow for further tailoring of support groups based on homophilous characteristics related to age, smoking frequency, and language preference. A preference was stated for Facebook, due to participant familiarity with the platform and the ability to leverage visual as well as text-based content. Visual communication of health information improves comprehension, and enhances attention, memory, and recall . Our tea smoking . More viFocus groups have been used in research to explore the experience of smoking cessation among ethnic minorities and have highlighted the importance of considering levels of acculturation in program tailoring . AlthougFamily orientation, social support, and community were prevailing themes in the focus group discussions of smoking, attempts to quit, and social media use, providing a basis for why social media may be particularly well-suited for a Latino-focused smoking cessation intervention. Participants noted the opportunities for community-building in social media venues, which have not previously been available through traditional websites or quit-line interventions. The Latino experience of quitting smoking is also conceptualized as a family or group effort, and social media may address previous calls to tailor interventions for racial/ethnic-specific processes for quitting.As a local qualitative study, the generalizability of our results is limited. The group moderator was fluent in Spanish, and coding was done via listening in Spanish; however, the final analysis of transcripts was conducted in English, which may have reduced or changed content in unpredictable ways. Despite these limitations, findings with respect to acceptability of social media, importance of family in health behavior change, and preference for visual material are likely broadly relevant.In conclusion, a social media-delivered intervention to support smoking cessation appears to be acceptable for Latino smokers. Regarding immediate implications, the study findings support efforts to develop novel interventions for treating tobacco use via social media. These interventions may be tested as standalone cessation programs or as adjuncts to existing treatments. For cultural relevance, message themes within the program should attend to family and community ties and influences. For maximum engagement and inclusiveness, flexibility in language use  should be permitted and encouraged. The specific social media platform may be determined by usage rates and fit of the technology for the intervention’s approach and privacy concerns. Regardless of platform, community outreach and engagement is essential to treatment impact, and Latino smokers’ tobacco purchasing behaviors may inform channel selection. Based on the focus groups, places to promote a social media quit smoking program would include in gas stations, liquor stores, and corner stores, near where cigarettes are displayed, as well as via word-of-mouth referrals from friends.The use of social media by Latinos is high; however, the use of these media for health behavior change appears to be underdeveloped. As such, our next steps will center on developing and testing a Latino-specific, bilingual, private, support group-based social media intervention for smoking cessation. The examination of homophily in group communications will be of particular interest, to determine whether directed and reciprocated communications align around shared member characteristics .