Low birth weight (LBW) is a leading risk factor for infant morbidity and mortality in the United States. There are large disparities in the prevalence of LBW by race and ethnicity, especially between African American and White women. Despite extensive research, the practice of clinical and public health, and policies devoted to reducing the number of LBW infants, the prevalence of LBW has remained unacceptably and consistently high. There have been few detailed studies identifying the factors associated with LBW in California, which is home to a highly diverse population. The aim of this study is to investigate recent trends in the prevalence of LBW infants (measured as a percentage) and to identify risk factors and disparities associated with LBW in California.A retrospective cohort study included data on 5,267,519 births recorded in the California Birth Statistical Master Files for the period 2005–2014. These data included maternal characteristics, health behaviors, information on health insurance, prenatal care use, and parity. Logistic regression models identified significant risk factors associated with LBW. Using gestational age based on obstetric estimates (OA), small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA) infants were identified for the periods 2007–2014.The number of LBW infants declined, from 37,603 in 2005 to 33,447 in 2014. However, the prevalence of LBW did not change significantly (6.9% in 2005 to 6.7% in 2014). The mean maternal age at first delivery increased from 25.7 years in 2005 to 27.2 years in 2014. The adjusted odds ratio showed that women aged 40 to 54 years were twice as likely to have an LBW infant as women in the 20 to 24 age group. African American women had a persistent 2.4-fold greater prevalence of having an LBW infant compared with white women. Maternal age was a significant risk factor for LBW regardless of maternal race and ethnicity or education level. During the period 2017–2014, 5.4% of the singleton births at 23–41 weeks based on OE of gestational age were SGA infants (preterm SGA + term SGA). While all the preterm SGA infants were LBW, both preterm AGA and term SGA infants had a higher prevalence of LBW.In California, during the 10 years from 2005 to 2014, there was no significant decline in the prevalence of LBW. However, maternal age was a significant risk factor for LBW regardless of maternal race and ethnicity or education level. Therefore, there may be opportunities to reduce the prevalence of LBW by reducing disparities and improving birth outcomes for women of advanced maternal age.The online version of this article (10.1186/s40748-018-0084-2) contains supplementary material, which is available to authorized users. The terminology currently used to describe infants with a low birth weight (LBW) for a given gestational age varies, including the terms small for gestational age, intrauterine growth restriction, and fetal growth restriction (FGR) , 2. SmalThe prevalence of LBW is greater in resource-limited countries. While current data show that up to 10% of term infants in developed countries have LBW, that figure is 20% in developing countries . A recenPerinatal mortality increases in infants with LBW, whether they are born at term or preterm , 4, 5. PIn 1995, David Barker first proposed that the fetal environment and early infant health status permanently program the development of the individual into old age, a theory known as the Barker hypothesis, or “fetal origins of adult disease” , 8. SeveLife course health development models may be used to improve public health outcomes, including in the maternal and child health community . As PiesThe aim of this study is to examine the current trends in the prevalence of LBW in California, using the Birth Statistical Master Files (BSMF) compiled by the California Department of Public Health (CDPH), and to identify significant predictors of LBW and racial and ethnic disparities in LBW. By identifying these risk factors and disparities, intervention strategies can be developed to reduce the prevalence of LBW and improve the health of the general population, now and into the future.We consulted the BSMF, compiled by the CDPH, for the period 2005 through 2014. The study was approved by the California Committee for the Protection of Human Subjects (Protocol ID: 16–10-2759) and the CDPH Vital Statistics Advisory Committee.In this retrospective cohort study, we collected data on Californian resident births in the years 2005 to 2014. Descriptive statistics were used to characterize all resident births and the prevalence of LBW each year, according to maternal characteristics and perinatal health behavior variables obtained from the BSMF data set.The response variable in this study was LBW infants. Birth weight was obtained from the birth files and coded as a dichotomous variable to indicate whether the infant was LBW (< 2500 g). Data cleaning was performed before analysis to exclude births with missing information on birth weight and those with any out-of-range values. There were 877 excluded birth records out of 5,267,519 resident births from 2005 to 2014.2). Using the criteria of the World Health Organization, underweight is classified as a BMI < 18.5 kg/m2, normal weight as 18.5 to 24.9 kg/m2, overweight as 25.0 to 29.9 kg/m2; obesity class I as 30.0 to 34.9 kg/m2, obese obesity class II as 35.0 to 39.9, kg/m2 and obesity class III as ≥ 40 kg/m2 [The explanatory variables considered were maternal sociodemographic status, prenatal health behavior, health insurance status, prenatal care use during the first trimester, and parity . Materna40 kg/m2 . The typGestational age affects fetal growth and birth weight can be categorized as small for gestational age (SGA) (< 10th percentile), appropriate for gestational age (AGA) (10th to 90th percentile), and large for gestational age (LGA) (> 90th percentile), using new gender specific intrauterine growth curves based on United States data by Olsen et al. (2010) .We extended these three categories to six categories by characterizing gestational age of 23–41 weeks for singleton births as preterm (< 37 weeks of gestation) and term (≥ 37 weeks of gestation) births: preterm SGA, preterm AGA, preterm LGA, term SGA, term AGA, and term LGA [To identify significant risk factors among the maternal characteristics and perinatal maternal health behaviors associated with LBW, we performed both unadjusted and adjusted logistic regression analysis. The adjusted analysis used multivariable logistic regression, controlling for potential confounding variables in maternal and perinatal health behaviors.p values are presented in the tables.The analysis was extended to study the prevalence of LBW based on all births according to two different interaction scenarios: first, between maternal age and maternal race and ethnicity; and second, between maternal education level and maternal race and ethnicity. Finally, multivariate logistic regression modeling approaches were used to study these two interaction scenarios after controlling for appropriate confounding variables. Multivariate modeling was stratified by maternal age and maternal education level to elaborate disparities in race and ethnicity and to identify the high-risk subgroups. The reference groups for maternal age, race and ethnicity, and education level were the age group 20–24 years, white race, and an education level of a bachelor’s degree or higher, respectively. Calculated adjusted odds ratios (AORs) with 95% confidence intervals (95% CI) and p = 0.05. All analyses were conducted using SAS, version 9.3 .The logistic regression models were restricted to singleton births. The significance level was set at The descriptive statistics for the 5,267,519 resident births that occurred in California during the 10-year period from 2005 to 2014 are listed in Additional file Table p < 0.001).Both unadjusted and adjusted logistic regression analyses Table  showed sThe prevalence of births in younger women declined over the study period . Pacific Islanders were 50% more likely to give birth to an LBW infant than White women , and Hispanic women were 30% more likely to give birth to an LBW infant than White women   were 49% more likely to have an LBW infant than were women of normal prepregnancy weight   , 4.9% were term SGA births, 81.7% term AGA births, and 6.4% term LGA births. Among term SGA births, the prevalence of LBW was 28.6% . However, the prevalence of LBW was 0.6% greater in Hispanic births compared with births in White women (6.3% vs. 5.7%) in 2014. Therefore, given the increasing number of Hispanic births in California, the findings of this 10-year study provide an alert to the increasing gap in birth weights between Hispanic and White babies.Overall, the prevalence of LBW when the mother is 40–54 years of age is double that when she is 20–24 years of age. This finding holds true for all groups except for Asian women and those a Multirace origin. Even at the highest education level, African American women had a greater prevalence of LBW compared with other ethnic groups, suggesting persistent disparities based on ethnicity.The prevalence of United States adults who smoke cigarettes declined, from 20.9% in 2005 to 16.8% in 2014 . ConsistData on maternal smoking and prepregnancy height and weight have been collected in California only since 2007; this study is the first to report trends in prepregnancy BMI. The results of our study provide population-based information on BMI for women of childbearing age. The prevalence of births in women who were underweight or of normal weight, based on prepregnancy BMI, decreased during the study period, but the prevalence of births to women who were in the obese I, obese II, and obese III categories increased significantly  reported on the role of perinatal care in preventing LBW. Our results confirm their finding, that attendance at perinatal care during the first trimester is associated with reduced LBW .Maternal parity is a well-recognized predictor of infant birth weight; the lowest birth weights are found in infants born to primiparous women . Our resBoth preterm AGA and term SGA births demonstrated a high prevalence of LBW infants. Infants born SGA, whether term or preterm, carry a considerably higher risk of mortality and morbidity in the neonatal period and beyond when compared with AGA infants . The risThere are several limitations to this study. Maternal characteristics were restricted to those contained within the BSMF compiled by the CDPH from 2005 to 2014. Maternal age, race and ethnicity, education level, smoking status during pregnancy , and prepregnancy height and weight were self-reported. Despite these limitations and the inclusion of many possible confounding variables, our study demonstrates significant trends in LBW over a 10-year period in the highly diverse population of California and includes analysis of almost 5 million births.There was no significant decline in the prevalence of LBW during this 10-year period in California, but maternal age, race and ethnicity, education level, smoking status during pregnancy, and parity are significant risk factors for LBW. Therefore, there may be opportunities to reduce LBW by improving birth outcomes for women giving birth at an advanced maternal age, and by developing public health models to address the identified risk factors and improve the health of the population. The findings of this study illustrate the opportunities to improve fetal, infant, and adult health outcomes, not only in California but throughout the United States. Given the complexity of the etiology of LBW, further research is required on the genetic and epigenetic factors that interact with the social, ethnic, and age-related influences identified in this study.Additional file 1:Table S1. Recorded births and percentage of births according to maternal characteristics and perinatal health behaviors in California for the period 2005–2014. Table S2. Likelihood of low birth weight listed as adjusted odds ratios  for maternal age for each maternal race and ethnic group, after accounting for confounding effects in California for the period 2005–2014. Table S3. Likelihood of low birth weight listed as adjusted odds ratios  for maternal education for each maternal race and ethnic group, after accounting for confounding effects in California for the period 2005–2014. (DOCX 52 kb)


For the ankle accelerometer statistical significance was only achieved between data from the non-medicated children in the experimental group and the control group. Using a Convolutional Neural Network (CNN) to automatically extract embedded acceleration patterns and provide an objective measure to help in the diagnosis of ADHD, an accuracy of 0.875 for the wrist sensor and an accuracy of 0.9375 for the ankle sensor was achieved.Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder, which is characterized by inattention, hyperactivity and impulsive behaviors. In particular, children have difficulty keeping still exhibiting increased fine and gross motor activity. This paper focuses on analyzing the data obtained from two tri-axial accelerometers (one on the wrist of the dominant arm and the other on the ankle of the dominant leg) worn during school hours by a group of 22 children (11 children with ADHD and 11 paired controls). Five of the 11 ADHD diagnosed children were not on medication during the study. The children were not explicitly instructed to perform any particular activity but followed a normal session at school alternating classes of little or moderate physical activity with intermediate breaks of more prominent physical activity. The tri-axial acceleration signals were converted into 2D acceleration images and a Convolutional Neural Network (CNN) was trained to recognize the differences between non-medicated ADHD children and their paired controls. The results show that there were statistically significant differences in the way the two groups moved for the wrist accelerometer ( Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder, which affects 3 to 5% of school-aged children ,2. ChildA diagnosis of ADHD ) requires individuals to demonstrate, in more than one setting, a minimum number of symptoms in all three dimensions . The Di) requireAlthough the direct observation of ADHD individuals in controlled environments may be a useful adjunct in diagnosing ADHD, unfamiliar settings may provoke differences in behavior, especially for children, consequently, unobtrusive monitoring of ADHD children in their natural environment while attending regular classes at school has been proposed . The curSeveral research studies have already focused on the investigation of objective measures and methods that could be used in the assessment of ADHD patients based on body worn sensors. In previous studies, the analysis of the data gathered from several body worn sensors has been used both for hypothesis testing and for pattern recognition. Hypothesis testing based on wearable sensors data has shown statistically significant differences in several parameters measured from ADHD patients compared with non-ADHD controls ,12. PattThe authors in  used objThe study in  also shoAs previous studies found differences in the way ADHD children move compared to typically developing non-ADHD controls, O’Mahoni et al. attempted to develop an objective measure to help in the diagnosis of ADHD by characterizing the movements of each group in terms of a set of features, and then quantifying these features to classify each individual into likely ADHD and non-ADHD groups. The authors used two inertial measurement units (IMUs) comprising a tri-axial accelerometer and a gyroscope, one attached to the waist and the other to the ankle of the dominant leg, and took continuous measurements during an approximately 1-h visit to a psychiatric consultancy. The authors combined time domain as well as frequency domain calculations to extract 668 different features. Using a support vector machine (SVM), the results showed up to 95% for both accuracy and sensitivity.In summary, previous studies have shown statistically significant differences in the way children with ADHD and typically developing non-ADHD control children move as captured by body worn sensors attached to different parts of the body. Both dominant and non-dominant limbs have been used to record acceleration data. Moreover, previous studies have shown that, based on the results of the acceleration measures taken while performing a predefined and controlled set of activities, typically developing non-ADHD controls and non-medicated children with ADHD can be automatically classified with a relatively high accuracy. In the current paper, we extend these studies by using two minimally invasive tri-axial accelerometers to record movement data in a “free-living” environment while at school. By “free-living”, in the context of this study, we mean that no additional requirements was given to participants. They followed their normal, everyday activities. Moreover, there were no other requirements for two participants from two different schools (or from the same school but monitored on different days) to follow (a similar script of activities was not required). Although a first study presented in this paper only focuses on the data of two accelerometers (worn at school on both dominant limbs), a complete dataset including 4 tri-axial accelerometers during an entire day period, one on each wrist and ankle has been recorded., We have only used the data from the dominant hand and leg in order to simplify the data measuring and handling process in this first study. Moreover, in order to compare results in a similar environment, only acceleration data while at school was analyzed. The complete dataset of all 4 tri-axial accelerometers for the full day will be presented in subsequent papers. Instead of predefining a set of features to be computed from the sensor data, a Convolutional Neural Network (CNN) was used to automatically learn the optimal features to separate children in each group. The use of CNNs in human activity recognition (HAR) applied to wearable sensor acceleration data has recently shown promising results compared to other non-deep learning approaches based on hand-crafted features ,16,17,18Participants were children and or young people aged 6–15, diagnosed with ADHD as reported by their parents who confirmed they had been fully assessed and diagnosed by the Paediatric Neurodisability or Child and Adolescent Menytal Health Services. Age matched controls were also aged 6–15, did not have a diagnosis of ADHD, and were not siblings of a child with diagnosed ADHD. (ADHD is highly heritable)Members of the research team recruited participants diagnosed with ADHD living in South Yorkshire via a community group for parents of children with ADHD. Parents were referred to these groups by their child’s clinician. A convenience sample of control participants was recruited using a snowball sampling method. All participants were visited in their homes by a member of the research team. The parent/legal guardian provided informed consent to confirm their child’s participation in the study. The children also signed assent forms to agree to participate. Additionally, the parents/legal guardians completed a SNAP IV questionnaire to indicate the current severity of their child’s hyperactive behaviors. The researcher placed a labelled sensor (embedded in a black sweat band) on each wrist and ankle of every child which were worn for 24 h including when they were in bed. Parents were shown how to position the sensors in the wristband should this be required i.e. if the sensors came out or the participant removed them to ensure they were in the correct position and orientation during the 24 h. Sensors were removed for bathing and showering. Parents were asked to record if the sensors had been removed and for what reason. This would then explain any data anomalies such as periods of complete inactivity.A set of 22 children in 11 pairs were recruited in the first phase (more children will be recruited for future studies). Among the 11 children diagnosed with ADHD, five were not taking medication for their ADHD when data was recorded and six were on medication. The mean short SNAP IV score  has beenParticipants with ADHD were recruited from a managing ADHD group in Sheffield. Referral to this group is only available to parents of children diagnosed with ADHD who have been assessed formally by the Paediatric Neurodisability or Child and Adolescent Mental Health Services. in Sheffield Childrens NHS Foundation Trust. This involves a standard assessment and diagnosis process which adheres to NICE guidelines and the DSM 5 criteria. Participants’ parents also completed a SNAP symptom questionnaire to assess their current symptoms. Naturally some control participants may be undiagnosed and may be near to the threshold of the SNAP questionnaire but this does not confirm a diagnosis of ADHD.Ethics approval was provided by the School of Health and Related Research (ScHARR) ethics committee at the University of Sheffield (Reference: 013209). Participant information sheets were written for different age groups to ensure all participants understood the study. The sensors used were two Runscribe™ inertial sensors  containing a tri-axial accelerometer which were applied to the wrist and ankle of the dominant arm and leg by aligning their long axis with limb and placing them within an elasticated ‘sweat’ band, see i” can therefore be represented as The tri-axial acceleration is sampled at 10 Hz. Each sample therefore comprises 3 acceleration values (one per axis). The sample “i” in the sensor coordinate axes is estimated by using a moving average based low pass filter using the following Equation (similar to the method proposed in )  convolution2dLayer  batchNormalizationLayer  reluLayer  maxPooling2dLayer  convolution2dLayer  batchNormalizationLayer  reluLayer  maxPooling2dLayer  convolution2dLayer  batchNormalizationLayer  reluLayer  fullyConnectedLayer(2)  softmaxLayer  classificationLayer];The graphical representation for the architecture for the CNN is captured in The output layer assigns probabilities for each image to each group  based on the softmax layer and selects the group with a higher probability. For the hypothesis testing algorithm, each acceleration image has been assigned to one of the groups n = 20 as the size of the set of consecutive images to be computed together (52.5 s of data). A threshold th  is then used to assess whether or not a particular child belonged to the ADHD or the typically developing non-ADHD control group. Let m be number of acceleration images classified as ADHD in the set of n consecutive images. We determined if the particular child belonged to the ADHD group if The “leave one out” schema was used to train the CNN. The data from all children with ADHD and typically developing non-ADHD controls, except for one child, were used to train the CNN, with the left-out child used to validate the results. The CNN automatically learned common acceleration traces or patterns (represented as acceleration images) associated with children with ADHD and typically developing non-ADHD controls. For the child not used in the training phase, the trained CNN was used to classify each acceleration image into an ADHD or control group. As there were many acceleration images common to both groups, some of the images were miss-classified. A counter was therefore added after the CNN to count the number of positive images (acceleration images classified in the ADHD group) in a set of consecutive images. We have selected p value of a 2-sample t-test. The null hypothesis was that there was no statistically significant difference in the values of segments marked as ADHD candidates.The complete set of acceleration images for each pair of participants was used to label each 20 consecutive images as ADHD or control for each If statistically significant differences in the acceleration patterns of those with ADHD and typically developing non-ADHD controls were found, algorithms could be designed to apply pattern recognition to the data in order to classify unknown samples. As mentioned in the related work section, some machine learning algorithms based on a predefined hand-crafted set of features calculated from an inertial measurement unit (IMU) have already shown good classification results in order to automatically distinguish ADHD patients from typically developing non-ADHD controls when performing a continuous performance test (CPT) in a controlled environment  but therThe acceleration images previously described were used as input to a Convolutional Neural Network (CNN) as in the hypothesis testing scenario but the classification algorithm was modified in order to add the confidence of the CNN while classifying a new acceleration image to the decision process. The proposed schema is shown in i represents the class  and The same CNN structure as shown in the previous subsection has been used . In this case:Both a 4-fold cross-validation and a leave-one-out schemas were used to validate results. In the 4-fold cross-validation approach, for each participant, 1.5 h of acceleration data were separated for validation purposes while 4.5 h were used in order to train the CNN. Both training and validation samples were selected in consecutive periods of time. For each image in the validation data, the likelihood of belonging to each class was calculated as shown in the previous Equation. The combined likelihood box sums the probabilities for all the images in the validation set for each participant according to the following Equation:th = 0) and the further positive or negative the output is, the greater the confidence in the result of the classification process.The output of the combined likelihood box should be positive for true positives (participants with ADHD classified as such) and negative for true negatives . In this case, the threshold will be zero  versus the data from all typically developing children (control group) and to the data of only non-medicated participants (experiment group) versus the data from all typically developing children . The results for the p-values for each threshold are presented in p-values for the wrist sensor in the case of all participants are captured in the first results column in th from 5 to 19. The results for the ankle acceleration images are not captured in th. The last two columns in p-values in the case that only non-medicated children are taken into account for the ADHD group. Appropriate treatment with medication for ADHD is likely to affect movements and may therefore introduce some distortion in the results. The last two columns in p-values for both the wrist and ankle acceleration images for all values of th for a value of In order to validate if there was a statistically significant difference between the acceleration images captured as described in th is low, there will be more segments for a typically developing non-ADHD control participant that will be classified as ADHD and therefore the value of the computed p-value will be non-optimal. On the other hand, if the value of the threshold tends to the size of the entire set of consecutive images, there will be many children with ADHD that will be considered as belonging to the control group leading again to a non-optimal number for the computed p-value. t-test, only found statistical significance for the art course, but the authors only used the mean ratios of activity acceleration in a 1-min epoch between the groups, which differed significantly (p < 0.05) at the 0.5–0.8 G and 1.3–2.8 G regions (G being the gravity caused acceleration). Authors in [p = 0.036). The authors in [p = 0.003). Other parameters also showed statistically significant differences such as rhythmicity of finger tapping (p = 0.008), dexterity (p = 0.007) and aiming and catching (p = 0.042) movements. The results in our study extend these previous studies to a different setting in a familiar environment which minimizes the requirements for participants.The results in , using athors in  also fouthors in  also foup-values from the previous section indicate that there are statistically significant differences in the acceleration data from both groups. In this section, we present the results of using the schema proposed in The In this first case of using a 4-fold cross-validation schema, the CNN was trained with 4.5 h of acceleration data from each of the ADHD non-medicated participants and the same amount of data from the typically developing non-ADHD control group. A distinct 1.5 h of acceleration data for the same children were used for validation. All children wore accelerometers during the entire period at school and were instructed to follow the normal day at school. Each acceleration image in the validation set was fed into the CNN and the probability assigned after the softmax output layer for each group  was recorded per image. A final score per participant was calculated by adding the probabilities for all the images per group so that the bigger the difference the more likely it is that this particular child belongs to the most likely class (as shown by Equation (2). Similar results for the data obtained from the ankle accelerometer are presented on The proposed automatic classification schema could also be used to measure the effect that medication has on ADHD children. i.e., does medicine move the acceleration patterns of ADHD children towards similar patterns to typically developing non-ADHD controls? In the leave-one-out validation, we used all the acceleration images for all the typically developing non-ADHD controls and all the non-medicated ADHD diagnosed children while in school except for one of them at a time in order to train the CNN. The acceleration images for the left aside child were used for validation. The process was repeated for each child.These results expand those reported by previous papers using sensors to measure differences between children diagnosed with ADHD and paired typically developing non-ADHD controls to a “free living” environment when participants were following their normal activities in their own school, A novel method that uses acceleration data in both dominant limbs  to feed a deep learning architecture based on a Convolutional Neural Network (CNN) has shown both that there are statistically significant differences in the way non-medicated children with ADHD move while in school compared to paired typically developing non-ADHD controls, and that these differences can be used to automatically classify children into the correct group with an accuracy of 0.9375 using a leave-one-out approach to assess the generalization of results. This method could be used as a complementary tool in the diagnosis of the disorder and to perform a non-intrusive follow up monitoring e.g. during medication optimization.The acceleration patterns capture all the different movements performed by each child. Using a 5 s window has been shown to be able to capture the details in sporadic movements as well as movements with some periodicity. Other window sizes could be explored in future work in order to find other movement patterns.Previous studies using acceleration data to characterize the movement patterns of ADHD children have shown differences both when using the data from the dominant limbs as well as the non-dominant limbs. While fine and precision movements tend to be executed using the dominant limbs (with a secondary support of the non-dominant limbs in some cases), involuntary or background patterns are more easily observed from the non-dominant limbs since the acceleration data in non-dominant limbs tends to have less influence from the execution of precision movements. In this paper, we have looked for characterizing patterns in both dominant arm and leg. The results corroborate that there are statistically significant differences that can be used to differentiate between children with ADHD and typically developing non-ADHD controls including the information in many tasks that are executed mainly with the dominant hand while in school (such as writing). The data from the non-dominant limbs have also been recorded and will be used to complement results in future studies.Many of the acceleration images show scores at the output of the Convolutional Neural Network (CNN) which assign similar probabilities to both classes. This means, that many of the acceleration patterns are similar for all the children. However, there are some acceleration images which are more characteristic of one group or the other. A further study of these characteristic acceleration segments could provide a further insight to assess the ways in which ADHD affects movement.The results also show that medication use modifies acceleration patterns in children with ADHD making their acceleration patterns more like those found in normal children. If the SNAP IV score indicates a high severity in the disorder, the acceleration patterns tend to retain more ADHD like characteristics. However, for ADHD children with smaller SNAP score values, medication can influence the way they move to be closer to typically developing non-ADHD controls. This may indicate levels of optimization of medication and could be useful clinically.The study has shown important insights in a group of 22 children during their school hours. The study will be extended to more children for their entire day in future work to further validate the generalization of results. The study will also be extended to deal with other limitations of the current results by increasing the recording time to several days for each participant, and increasing the sampling frequency to 50 Hz, to monitor the adherence to wear the sensor and to assess the effects of medication over time.


The time of onset and the duration of treatment effect are important considerations in the choice of the medication to be prescribed in treating children, adolescents, and adults with ADHD. Early onset of effect may facilitate preparation for school, improved behavior during the trip to school, and attention during morning classes. Sustained treatment effect through afternoon and evening hours can be important because impairments associated with ADHD are not limited to the naturalistic classroom. Laboratory school protocols (LSPs) provide a simulated, rigorously controlled classroom setting environment and have proven valuable for providing pharmacokinetic and pharmacodynamic information about medications, and other treatments used in managing ADHD in school-aged children and across the lifespan.This paper is an invited mini-review of LSPs of stimulant medication, which includes data from multiple, randomized, double-blind, and placebo-controlled medication trials for ADHD. Assessment endpoints included the permanent product measure of performance (PERMP), Swanson, Kotkin, Agler, M-Flynn, and Pelham (SKAMP) rating scale in the preschool assessment laboratory (PAL), child/adolescent, and adult workplace environment (AWE) studies. These measures allow the study of improvement in attention and behavior in individuals with ADHD.Analog classroom settings (LSP or AWE) have been used to assess immediate and modified-release stimulant formulations of medications to treat ADHD in multiple age groups. Results based on both subjective  and objective  measures are used as clinical outcomes in testing drugs currently in development for ADHD.The LSP and its extension to PAL and AWE settings continue to be used to assess the time-course of effect of ADHD medications because they provide valuable information in their respective structured, controlled environments. The laboratory school protocol (LSP) and its associated methodology are important tools for measuring treatment onset, duration, and efficacy in individuals with ADHD. The LSP in its final form was developed by Drs. James Swanson, Sharon Wigal and colleagues in the early 1990’s at the University of California, Irvine (UCI). Much of this work in school-aged children has been defined and described elsewhere , 2002 asUnlike some other classes of medications, weight-based dosing of stimulants has not proven effective, and age has failed to predict an effective dose . In addi® Methylphenidate Hydrochloride  in August of 2000. The most recent U.S. FDA approvals were in August of 2018 for HLD200, a delayed-release and extended-release methylphenidate   , and in Treatment efficacy is generally similar amongst stimulants, but they differ by dosing, time course effects including duration of action and tolerability as measured by adverse events. Clinical efficacy is typically measured using the SKAMP Rating Scale , and theonly during the classroom probes and do not include any attention or behavior performance outside of the laboratory classroom during time spent with parents, counselors, coordinators, or site clinical research investigators. These raters must remain neutral and non-interactive with patients in any supportive or otherwise clinically meaningful ways during the laboratory classroom study days. In fact, their role as trained observers in the classroom precludes their involvement in any other form of study data collection. They are not permitted, by the LSP, to be involved in clinical ratings, phlebotomy, electrocardiography or blood pressure measurements, for example, in order to maintain their neutrality in data collection.The SKAMP rating scale was developed for a short rating period in a classroom setting rather than assessing long rating periods in home and/or clinical settings, and ratings may occur multiple times across the day during a schedule of structured classroom sessions followed by recess, meal, and playground activities. Various scoring methods have been used to categorize the SKAMP ratings representing attention and deportment as well as total score and work output, for example. Ratings are conducted on a seven-point scale of impairment in which 0 represents no impairment  and 6 represents maximal impairment. Although perhaps obvious, it must be stated that these ratings reflect data collected The study of stimulant responses using math tests in controlled settings traces back to –A repetitive activity that the individual can perform with near 100% accuracy so that effort, not correctness, is the critical measurement.–Yields a permanent product that is quantifiable.–A variation in difficulty can be matched to the individual’s ability.–A variation in the activity  minimizes learning or practice effects across days/weeks.–An interest factor high enough for an individual to complete multiple times a day.–A set of materials inexpensive enough so that multiple individuals can do the task at the same time.The permanent product measure of performance assesses response to treatment, and it is related to at least 5 symptoms of ADHD . Unlike a continuous performance task (CPT), for example, which is only related to one ADHD symptom , the PERMP has a much better chance of detecting response to treatment given the heterogeneity of symptoms in individual subjects with ADHD.The defining characteristic of ADHD is not simply an attention deficit , but rather inconsistent and misdirected attention. The expression of ADHD is usually contingent on context and task demands. Certain contexts or situations increase the likelihood of misdirected attention. Situations that are most likely to “bring out” ADHD symptoms are those that are boring, have delayed consequences (or infrequent feedback), are very familiar, include group settings, and have low salience. A defining characteristic of ADHD is that symptoms and impairments are variable throughout the day. ADHD may be described as a failure to manage the limited resource of attention depending on the individual and the context or demands on attention resources at any given time.These laboratory school protocols measures are supposed to provide an index of “doing better” for patients, also referred to as response to treatment with the clinical goal of reduced impairment. Data analysis on each of these outcomes may examine average scores across the study day and/or statistical significance of treatment at specific time points when compared to placebo. The use of a randomized, double blind placebo control study design for inclusion of a placebo group across the study day is critically important for assessing such time course effects.objectified the subjective ratings and allowed for discrimination between treatment conditions.The initial laboratory school studies in elementary aged children described in a priori selected a specific mean time point, 4 h, as the primary efficacy outcome measure to show significance of the active treatment on the SKAMP-Combined score rather than either averaging all time points or examining each time point of interest. In addition, the other time points tested, 0.75, 2, 8, 10, and 12 h each were significantly improved with treatment   liquid fment see . This tyment see , has alsment see . One obsIt became evident at the time of the preschool ADHD treatment study (PATS) see  that resAs the ADHD populations studied in clinical trials broadened, the LSP was adapted to allow for the evaluation of adult populations. The version of the LSP known as the adult workplace environment (AWE) was designed  to provoThe AWE was first used in the study of adults with the triple bead formulation of Adderall treatment about 14 years ago, although these results were just recently published . A chronThe exemplar studies cited in this invited mini-review illustrate the adaptability of the LSP to shift the timing and dosing of treatment and its associated measures. Specifically, the objective measures of performance known as the PERMP, used in school-aged children, adolescents and adults, and bead stringing, used in preschoolers, allow measurement of treatment onset and offset effects. These measures are not sensitive to language based disabilities or cultural differences. The LSP also allows for continuity of measurement across the lifespan from preschool ages through older adults. Finally, the U.S. FDA has continued to request SKAMP and LSP study designs for drug development and timing of medication effects. In fact, there were only five clinical outcome assessments that were accepted by the FDA to determine if a drug treatment for ADHD has benefit. They are: the ADHD-RS, Conners, CGI-I, SKAMP, and PERMP . More reAlthough external validity of the LSP can be inferred from the original In summary, the LSP and AWE study designs provide FDA-approved methods to measure efficacy, onset, time response, and duration of effect of medication treatment. These outcomes are difficult to obtain in the clinic or naturalistic or a real-world setting. The LSP/AWE allows for structure in a controlled setting with rigorous objective and subjective measurements. These are the very features that may be seen as limitations  compared to naturalistic studies as described below. These LSP measures allow the study of improvement in seatwork compliance, attention, and deportment, for endpoint analyses of symptom change related to environment . The pairing of these two types of results from the laboratory classroom probes with more naturalistic clinical assessment outside of the laboratory classroom can help characterize the full picture of efficacy in the evaluation of new and existing drug treatments.n = 1.As mentioned, a key planned feature as well as limitation of the laboratory classroom design is the tight rigor that is incorporated in the scheduling of the study day. This coupled with the lengthier “school day” than is typical for any age group studied in the LSP and the inclusion of only subjects diagnosed with ADHD undermines the ecological validity of the data collected. Unfortunately, the study of healthy control subjects, either on stimulant treatment or without treatment for comparison in the LSP, have not been conducted nor published for reasons including ethical constraints. In addition, the novelty of the setting for participants, at least in initial test sessions, could reduce their response to treatment. While the LSP retains some aspects of the naturalistic setting such as a group setting, a boring task, structure that includes defined rules for expected behavior, and specific stop and start times, the measures used represent surrogates of real-world activities. The clinical value of data collected in any LSP study design is how well they guide community medical practitioners in naturalistic medication use and management of individual patients diagnosed with ADHD. Ultimately, the optimization of ADHD medication treatment in the clinic could be viewed as a naturalistic laboratory school study with SW conceived the mini-review, wrote and revised the manuscript, and read and approved the submitted version.SW was employed by AVIDA Inc., Newport Beach, CA, United States and has received research support from Akili Interactive Labs, Ironshore Pharmaceuticals & Development, Inc., Neurovance, Inc., NLS Pharma, NuTec, Otsuka, Pfizer, Purdue Pharma, Rho, Rhodes Pharmaceuticals, Shire, Sunovion Pharmaceuticals, Inc., and Tris Pharma, Inc. She has consulted for Arbor Pharmaceuticals, Atentiv, Ironshore Pharmaceuticals & Development, Inc., Neos Therapeutics, Neurovance, Inc., NLS Pharma, NuTec, Otsuka, Pfizer, Purdue Pharma, Rho, Rhodes Pharmaceuticals, Shire, Sunovion Pharmaceuticals, Inc., and Tris Pharma, Inc.; and served on speaker/advisory boards for Cingulate Therapeutics, Ironshore Pharmaceuticals & Development, Inc., NLS Pharma, NuTec, Otsuka, Pfizer, Purdue Pharma, Rho, Rhodes Pharmaceuticals, Shire, Sunovion Pharmaceuticals, Inc., Supernus Pharmaceuticals, Inc., TouchPoint Solutions, and Tris Pharma, Inc.


Background: Deviations in reinforcement sensitivity and frustration-related reactions have been proposed as components of the biopsychosocial mechanisms, which explained the high vulnerability to internet addiction (IA) among individuals with attention-deficit/hyperactivity disorder (ADHD). There is currently limited knowledge on the relationship of IA symptoms with reinforcement sensitivity and frustration intolerance, as well as factors moderating those correlations in this population.Objective: The aims of this study were (1) to examine the associations of IA symptoms severity with reinforcement sensitivity and frustration intolerance and (2) identify the moderators of these associations among adolescents diagnosed with ADHD in Taiwan.Methods: A total of 300 adolescents aged between 11 and 18 years who had been diagnosed with ADHD participated in this study. Their levels of IA severity, reinforcement sensitivity, and frustration intolerance were assessed using the Chen Internet Addiction Scale, behavioral inhibition system (BIS) and behavioral approach system (BAS), and Frustration Discomfort Scale, respectively. The associations of IA severity with reinforcement sensitivity and frustration intolerance were examined using multiple regression analysis. Possible moderators, including medications for ADHD, were tested using the standard criteria.Results: Higher fun seeking on the BAS (p = .003) and higher frustration intolerance (p = .003) were associated with more severe IA symptoms. Receiving medication for treating ADHD moderated the association between fun seeking on the BAS and severity of IA symptoms.Conclusion: Fun seeking on the BAS and frustration intolerance should be considered as targets in prevention and intervention programs for IA among adolescents with ADHD. The negative effects of internet addiction (IA) have become a concern in the past decades. IA is characterized by persistent internet use despite negative consequences, loss of control, preoccupation with internet use, increasing amounts of time spent online, and withdrawal symptoms . InterneAttention-deficit/hyperactivity disorder (ADHD) is the most common comorbidity among adolescents referred for treatment of IA . RelevanKo et al.  proposedReinforcement Sensitivity Theory (RST) was developed by Gray and consists of the behavioral inhibition system (BIS) and behavioral approach system (BAS), which are used to identify an individual’s sensitivity to punishment and reward, respectively . BAS andInternet activities are usually characterized by immediate responses and rapid rewards; therefore, deviations in sensitivity to reinforcement may contribute to vulnerability to IA in patients with ADHD . AbnormaFrustration intolerance refers to the difficulty accepting that reality does not correspond to personal desires . It is aThe aims of the present study were to examine the correlations between IA severity and reinforcement sensitivity and frustration intolerance as well as identify moderators of these correlations in adolescents in Taiwan who have been diagnosed with ADHD. We hypothesized that both reinforcement sensitivity and frustration intolerance exhibit significant correlations with IA severity, and that these correlations may be moderated by sociodemographic characteristics, ADHD symptoms and treatment, psychiatric comorbidities, and parental factors.Participants for this study were recruited from the child and adolescent psychiatric outpatient clinics of two medical centers in Kaohsiung, Taiwan. Adolescents aged between 11 and 18 years, who visited the outpatient clinics and have been diagnosed with ADHD according to the diagnostic criteria specified in the DSM-5 , were coInternet addiction. We used the Chen Internet Addiction Scale (CIAS) to assess participant self-reported severity of IA symptoms in the recent 1 month. The CIAS contains 26 items evaluated on a 4-point Likert scale, with scores ranging from 26 to 104  was used to evaluate the self-reported frustration intolerance belief of participants -derived ADHD subscales of inattention, hyperactivity/impulsivity, and symptoms of oppositional defiant disorder with good criterion and construct validity  of participants were assessed based on the clinical interviews and chart reviews by three child psychiatrists. Those who had been diagnosed with any ASD and low intelligence  or thosParental factors. The present study evaluated the marital status of the parents of participants (married and living together vs. divorced or separated) and assessed their occupational socioeconomic status (SES) using Close-Ended Questionnaire of the Occupational Survey (CEQ-OS) ((CEQ-OS) . Parents(CEQ-OS) . In the The research assistants conducted interviews using the CIAS, BIS/BAS, and FDS to collect data from adolescents. Their parents completed SNAP-IV under the direction of the research assistants. Data analysis was performed using SPSS 20.0 statistical software .t test to select possible factors predicting IA severity for further analysis, including sociodemographic characteristics, ADHD symptoms and treatment, psychiatric comorbidities, parental factors, reinforcement sensitivity, and frustration intolerance. The significant factors in the first step were used in the second step, which consisted of a multiple regression analysis that was used to evaluate the correlations of reinforcement sensitivity and frustration intolerance with IA severity by controlling for the effects of other factors. A two-tailed p value of less than 0.05 was considered statistically significant.Because that there were several factors examined in this study, we used two-step statistical analyses to examine the correlation of IA severity with reinforcement sensitivity and frustration intolerance and reduced the possibility of multiple comparison. In the first step, we used Pearson’s correlation and We also used standard criteria  to examiAs described in the Statistical analysis section, significant factors in the first step were selected for further multiple regression analysis in the second step to detect the independent factors related to IA symptoms  and not in those not receiving medication for ADHD .Because maternal occupational SES and receiving medication for ADHD were significantly associated with IA symptoms, the interactions among the predictors (reinforcement sensitivity and frustration intolerance) and possible moderators  were included in the multiple regression analysis based on the standard criteria proposed by Baron and Kenny  describeThe results of this study revealed that although both BAS fun seeking and frustration intolerance were positively associated with IA symptoms, medication treatment for ADHD moderated the relationship between fun seeking on the BAS and IA severity. To the best of our knowledge, this is the first study to identify the moderators of correlations of IA symptoms with reinforcement sensitivity and frustration intolerance in adolescents with ADHD.BAS fun seeking represents the tendency to seek stimuli and response to proximal rewards . InterneIn the present study, frustration tolerance was demonstrated to be a significant predictor of IA severity after controlling for other correlates in the regression model. The theory underlying rational emotive behavior therapy proposes that irrational beliefs triggered by events lead to subsequent negative consequences . ConversThe current study discovered that lower maternal SES was associated with higher IA severity in adolescents with ADHD. Family SES has been proven to play a pivotal role in adolescent health conditions, and parental SES has been demonstrated to influence depression, obesity, and self-rated health among adolescents in the US . ChildreEstablished treatment modality for IA is lacking. Medications that have been studied included escitalopram, bupropion, methylphenidate, and atomoxetine . MethylpSeveral limitations of this study require careful consideration. Measurements were all self-reported; therefore, common method bias cannot be completely ruled out. Adding clinical interview in the evaluation process will improve the diagnostic validity in future studies. Psychometrics of the Chinese versions of BIS-BAS scale and FDS used in the adolescent population warrant further examination. The cross-sectional design limited the capability of forming conclusions regarding causality. Participants were recruited from outpatient departments, and individuals with ADHD who were not receiving clinical care were not approached, meaning that the results may not be generalizable to all adolescents with ADHD. Medications for treating ADHD were not specified in our study; therefore, variety in the effects of medications may have introduced bias into the results. However, methylphenidate and atomoxetine are the only two compounds that have been approved for treating ADHD in Taiwan and comprise almost all medications used for treating ADHD , 56. LasThe results of the current study indicated that BAS fun seeking and frustration intolerance belief were significantly associated with IA severity in adolescents with ADHD. Differences were observed in the association between BAS fun seeking and IA between participants receiving ADHD medication and those not receiving ADHD medication. Reward sensitivity and frustration intolerance require attention during prevention and management programs for IA in adolescents with ADHD. The effect of ADHD medication should also be considered when evaluating the relationship between reinforcement sensitivity and IA.This study was carried out in accordance with the recommendations of Kaohsiung Medical University with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Kaohsiung Medical University.W-HL: conception and design of the study, drafting the manuscript. W-JC: conception and design of the study, drafting the manuscript. RH: drafting the manuscript. H-FH: acquisition and analysis of data. C-FY: conception and design of the study, acquisition and analysis of data, drafting the manuscript or figures.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.


Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, with a chronic, costly and debilitating course if untreated. Limited access to diagnosis and treatment for adults with ADHD contributes to the cost of the disorder and the burden of disease.This study aims to identify the barriers to care for adults with ADHD.A qualitative analysis of semi-structured interviews with 10 key opinion leaders in the field of adult ADHD in SA was conducted to obtain narratives regarding frustrations experienced when treating adults with ADHD and needs of patients regarding management of ADHD. Qualitative content analysis was completed using Atlas.ti (version 7).Four key themes which emerged from the interviews were ‘lack of recognition of the disorder’, ‘lack of access to diagnosis’, ‘lack of access to treatment’ and ‘a life of perpetual failure’. Core to these themes are the lack of knowledge amongst health care professionals, funders, and society at large.Our findings expand on previous research regarding the need to increase the knowledge base on adult ADHD. A collaborative stakeholder approach is needed to provide research and training for improved diagnosis and treatment for adults with ADHD in the South African context. Attention-deficit hyperactivity disorder (ADHD) has received increased scientific, clinical and public attention over the past few decades and is now recognised as a common neurodevelopmental disorder, present throughout life, with a chronic, costly and debilitating course if untreated. Unfortunately, many patients suffering from ADHD remain undiagnosed, or if diagnosed, they do not receive optimal treatment.1 In South Africa (SA), poor identification and treatment of common mental disorders at primary healthcare level, limited access to specialist resources and a large service delivery and treatment gap remain problematic. In the current environment of a pressured health care system, GPs will play an increasingly important role in the early identification and management of adults with ADHD. 3Improved outcomes are possible if patients suffering from ADHD receive a timely and accurate diagnosis, and receive comprehensive care, which would include psychopharmacological interventions, behavioural interventions and support. Previous research established the knowledge gap amongst general practitioners (GPs) with regard to adult ADHD. In this article, we argue that unless the lack of knowledge with regard to adult ADHD is addressed, the barriers to access to diagnosis and treatment will continue to prevail. Strategies to break down these barriers include research, education, information and communication through multiple stakeholder engagement.4 Estimates of the prevalence of adult ADHD range between 2.5% and 4.3%.6 Extrapolating from population statistics (based on StatsSA population statistics for SA) and known prevalence information, we calculated the expected number of adults in SA between the ages of 20 and 50 affected by ADHD to be around 1 million. In the first South African study exploring the situation with regard to the prevalence and treatment of adult ADHD the population prevalence of adult ADHD was estimated at 1.09%, while the prevalence in clinical psychiatric settings was as high as 52.5% (of which 13.68% were patients with newly diagnosed ADHD).7 This is a conservative estimate and lower than international prevalence rates and may be attributed to a lack of awareness and knowledge amongst health care practitioners (HCPs) – which hampers the diagnosis of patients.The notion that ADHD is a disorder of childhood prevailed until the 1990s. However, rigorous research, including longitudinal studies, has now firmly established the existence of adult ADHD. ADHD affects 2% – 16% of the school-age population.Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5) criteria for the diagnosis of ADHD.8 Core symptoms of ADHD include a persistent pattern of inattention and/or hyperactivity-impulsivity that interferes with functioning or development of the individual. The DSM-5 relaxed the diagnostic criteria for ADHD with the onset of symptoms specified as before 12 years of age and individuals older than 17 years are required to meet fewer criteria (5+ symptoms).As from 01 January 2015, psychiatrists in SA use the 11 Individuals with untreated ADHD, their families and other caregivers must be made aware of the impact that this disorder may have on them at every stage of life and, correspondingly, the improved outcomes that can be achieved with the successful management of ADHD. The presence of adult ADHD increases the prevalence of multiple medical and psychiatric comorbidity (estimated at more than 50% in adults with ADHD), and doubled the healthcare costs of individuals13The core symptoms of ADHD often appear to decrease over time – in number and in severity. However, adults are often more adept at managing these symptoms. Some adults compensate for ADHD-related impairment by choosing lifestyles and careers that suit them. Although they may appear to function well, excessive amounts of energy and time are used to accomplish tasks. Associated symptoms of ADHD include behavioural, cognitive, emotional and social problems. Problems with planning, task-initiation, task-completion, impatience and impulsivity can cause numerous work-related and interpersonal problems. This impairs educational attainment and work performance (reduced productivity and increased absenteeism), and add to significant societal costs (e.g. due to substance abuse and accidents) – impacting negatively on overall quality of life.16Many studies have been conducted and established the efficacy and effectiveness of both stimulant- and non-stimulant medications in the treatment of ADHD in children and adolescents, and more recently also in adults. Pharmacotherapy plays a primary role in the treatment of ADHD, but psychosocial interventions  form an integral part of management.Approval for the project was obtained from the University of Stellenbosch Business School Ethics Committee.A qualitative analysis of semi-structured interviews with key opinion leaders (KOLs) in the field of adult ADHD in SA was conducted. This study formed part of a larger triangulated study  in which the current situation in SA with regard to the prevalence, diagnosis and management of adult ADHD was explored. The aim of the interviews was to elicit narratives of these experts working with patients with adult ADHD.17 The Mental Health Information Centre (MHIC), Health Professions Council of South Africa (HPCSA) and Psychiatry Management Group (PsychMG) were contacted to establish who are seen as the current KOLs in adult ADHD in South Africa. The definition of KOLs was provided to these bodies based on the definitions of Health Connexions and PRWeb, that KOLs are the people within a group who are the most influential. They influence their peers’ medical practice by speaking at conferences, publication, prescribing habits, establishing protocols, advocacy, training and marketing feedback.19 In addition, possible KOLs were also identified from the responses from the 103 psychiatrists who participated in the survey leg of the triangulated study. All 10 KOLs contacted provided consent for participation.Our sample consisted of 10 experienced specialists, nominated by peers and professional bodies, and identified as KOLs according to specified criteria.Semi-structured interviews (telephonic or in-person) were conducted between February 2014 and April 2014. Three open-ended questions were asked, with probes where needed to extend the answers provided without leading the desired response, with regard to the frustrations experienced when treating adults with ADHD, the needs the patients have with regard to management of ADHD, and suggestions and solutions for better management of these patients. All interviews were recorded once respondents had given permission for the recording as specified in the ethical procedures for this study.20Recorded interviews were transcribed by an external professional , checked for accuracy by R.S., followed by qualitative content analysis of the data by means of Atlas.ti (version 7), a Computer Aided Qualitative Data Analysis Software (CAQDAS) programme.21 Although this approach reflects the original accounts and observations of the people studied (an inductive process), it starts deductively from pre-set aims and objectives (subcategories were built based on items within the main category). The datasets were read to form an overview and to capture the context in which the data exist. Hereafter, dual descriptive level  and conceptual-level analysis (where related codes were categorised into groups and where relationships between categories were sought to identify themes) followed. Data saturation was sensed by interview 7.A framework approach was followed in which the objectives of the investigation were set in advance. In order to protect against researcher bias, the researcher (R.S.) coded all the data and then gave the entire set to an independent analyst (R.A.) to check – eight of which were already coded. The analyst then independently coded the remaining two of the 10 interviews. The researcher and independent analyst met to compare and discuss their coding and used the feedback to ensure the quality of the set of interviews and analysis thereof.The identified KOLs were contacted and consent for interviewing them, and for the recording of the interviews, was obtained. Data was not linked to personal identifiers.The KOLS interviewed were mostly male (90%) and represented the key urban centres , where most psychiatrists are located.The final code list consisted of 219 codes, representing 1011 quotes which were grouped into 24 families: acceptance, access to care, adequate treatment, awareness, chronic condition, comorbidity, complications, comprehensive care, costs, diagnosis, education, family, financial impact, funding, impulse control problems, knowledge gaps, medical schemes, medication, misconceptions, psychotherapy, regulation, stigma, training and work environment.The four key themes which emerged from the interviews are presented . Core toVarious factors contribute to the lack of recognition of adult ADHD as a diagnostic entity. There are misconceptions amongst the general public surrounding ADHD, such as the addictive nature of medication , ADHD as an scholastic or academic problem only , ADHD as a disorder of childhood  and the perception that it is over diagnosed because of financial motives of psychiatrists and pharmaceutical companies (P4 and P7). These misconceptions are further enforced by antipsychiatry groups and incorrect media information (P7 and P8).‘It’s not something that you’re taught about, and it’s sometimes actually even a bit of frowned upon – that it doesn’t exist or this sort of thing.’ (P7)A lack of awareness and knowledge, as well as misconceptions surrounding the diagnosis amongst HCPs and allied HCPs, leaves them unable to have an informed opinion or to psychoeducate patients and the community. Many HCPs received no training on ADHD and even less so on adult ADHD:‘There is always lots of convincing the patient (author clarification: lots of effort in convincing the patient), and you have to convince everyone else: the funders, the colleagues, the general practitioners. There is a lot of resistance to the diagnosis.’ (P6)Although the diagnostic criteria for ADHD have been validated, many HCPs still challenge the relevance and appropriateness of these criteria in the adult population . This further contributes to the controversy surrounding the diagnosis. This lack of knowledge creates a cloud of ignorance surrounding ADHD, which further contributes to the stigma of the disorder and to psychiatry in general as illustrated by the following comment:‘I think that the adults often would come to me, and they would be reluctant to disclose some of their symptoms because they don’t know whether it is really an illness, and they are not always happy to disclose to the workplace or other people that they indeed have adult ADHD.’ (P1)Although there is a perception that adult ADHD is over diagnosed, KOLs reported that this is not the case . Due to a lack of awareness of the disorder, as well as the stigma surrounding the diagnosis and psychiatry in general, many patients suffering from ADHD never present to psychiatrists for diagnosis (P3 and P10):ADHD is a chronic disorder with a differential presentation across the lifespan, for example, hyperactivity which becomes less evident, while interpersonal, financial and work related problems become more evident . Comorbidity such as anxiety disorders, mood disorders and substance use disorders , or complications such as marital distress or driving accidents  often are the presenting problems. ADHD requires a comprehensive assessment , including collateral information. If a HCP do not specifically address this history, the diagnosis of ADHD will be missed, or a patient will be misdiagnosed as suffering from another disorder . A lack of resources – both in terms of manpower  and finances (transport and consultation fees) can further impede the chances of receiving a correct diagnosis (P10). In addition to difficulties with access to diagnosis and treatment, is the acceptance of the patient of suffering from a chronic disorder, and therefore compliance with treatment .KOLs reported that, even when a patient has been diagnosed with adult ADHD, they often do not have access to treatment  – the ideal being a comprehensive, multidisciplinary approach  which includes access to medication, psychotherapy , occupational therapists  and work intervention . Medication options are limited in SA (P5) and the cost thereof high (P4 and P9). Medical schemes do not acknowledge the existence of the disorder in adults  and often discontinue funding for medication as soon as a child leaves school or turns 18 years old (P2 and P6) – attesting to the lack of knowledge of adult ADHD. This hampers continuous treatment, as well as compliance (P4 and P8).Psychotherapy , life coaching and assistance with time management, organisational skills, and support within the work environment  is virtually inaccessible – again both because of a lack of manpower and financial resources. Late diagnosis and inadequate treatment increase the complications and comorbidities associated with adult ADHD . Although the direct costs of ADHD are high, these indirect and hidden costs to society are much higher .‘If you look back into their life, then you can see the chequered work record, relationship failures, the substance abuse, the disruption in their life, the poor financial management over time and the co-morbidities that at interfere over time. That is an enormous cost for that person and for their families.’ (P4)Due to a lack of awareness of the disorder in the community, a lack of knowledge by HCPs and allied HCPs, and therefore a lack of access to diagnosis and treatment, many patients live a life of perpetual failure:‘It’s not just academic performance that’s influenced by ADHD, but actually the general life – the wellness of life – that is influenced by the symptoms of ADHD.’ (P8)Adults with ADHD are often aware that they do struggle, but do not know why (P1). Poor work records , interpersonal (P2 and P3) and marital difficulties , psychiatric and medical comorbidity and complications  and impulsivity with even forensic consequences  often mark there life trajectory. Families are frustrated and fatigued because of interpersonal problems and financial difficulties – both because of untreated ADHD, but also because of the financial impact of treatment :The biggest exhaustive need for patients, families, HCPs, medical schemes and the community at large is access to information on ADHD. It seems that that a lack of knowledge and information feed into misconceptions and stigma about the disorder, and the delayed, missed or misdiagnosis. Informed primary HCPs are crucial in the pathway to care. Clinical strategies to increase knowledge of HCPs include the development of guidelines and pre- and postgraduate training content. A public awareness campaign to increase awareness of both the public and HCPs should be driven by SASOP Special Interest Group for adult ADHD.7 This limits access to optimal comprehensive treatment, adds to the direct and indirect costs of ADHD and the emotional and financial burden of the disease. It is therefore crucial to extend the knowledge base from HCPs to medical funders. It is also crucial for KOLs to have input into benefit design in order to gain funding for the health insurance cover of ADHD.Lack of funding and costs are barriers to treatment which limit access to care and treatment. ADHD is a chronic, costly and debilitating disorder when left undiagnosed and untreated. One of the reasons for lack of funding by medical schemes includes the lack of recognition of adult ADHD as a disorder and a lack of economic studies. The basket of care for adult ADHD has two handles: information and funding. A comprehensive diagnostic assessment can be considered the base, while the post-diagnostic management forms the sides of the basket – containing the patients and their families through a multidisciplinary and multimodal approach.Screening and early detection by primary HCPs.Increasing the awareness of adult ADHD and its ramifications, as well as training of HCPs in the diagnosis and treatment thereof, can facilitate early detection and timely referral. This can have a positive influence on the trajectory of the disease and of the person’s life.Referral to a psychiatrist (or other adequately trained and skilled HCP) for a comprehensive diagnostic assessment.As adult ADHD is diagnostically complex, and comorbidity and complications are rife, an initial diagnostic assessment by a psychiatrist is recommended, especially with regard to the presence, severity and treatment of comorbid conditions. A thorough and comprehensive assessment, and a standardised way of making the diagnosis, could also enhance access to treatment through medical scheme funding. Comprehensive training in diagnosis and treatment of these potentially complex patients are crucial to ensure management by skilled and confident HCPs. This will enhance long term outcomes for these patients.Comprehensive multi-modal and individualised care.Ongoing access to consultations for acute stabilisation, maintenance, and relapse prevention are needed. This should include medication management, psycho-education , therapy  and support (e.g. coaching and workplace intervention). Once a patient has been stabilised, further management can be at GP level.Advance the body of evidence through research .The following specific recommendations are suggested:8 based on our interviews with 10 KOLs in SA, there seems to be a lack of awareness thereof and the stigma surrounding psychiatry are often a barrier for patients to access diagnoses. Furthermore, a lack of awareness amongst HCPs, their own misconceptions regarding diagnosis, and lack of knowledge of the diagnosis and treatment hampers the diagnosis, even when patients present to the HCP.Although adult ADHD is now established as a disorder abroad,4 Our findings form a foundation to break down the barriers limiting access to diagnosis and treatment for individuals with adult ADHD. It is therefore crucial to improve access to knowledge – through research and training  – and to embark on a collaborative approach between stakeholders to provide optimal care for adults with ADHD in the South African context.Our findings highlight and expand on previous research regarding the need of GPs  to increase their knowledge base with regard to adult ADHD.


The estimated glomerular filtration rate (eGFR) increased for patients taking Belatacept but decreased during CNI-based therapy . In a multivariate Cox regression model, Belatacept remained the only significant factor associated with the improvement of eGFR . Belatacept treatment was not a significant risk factor for renal allograft rejection or graft loss. In terms of safety, the only significant risk factor for de novo cardiovascular events was a pre-existing cerebrovascular disease, but Belatacept was not associated with a significant risk reduction. Belatacept treatment was not associated with an increased risk of severe infections, cytomegalo virus (CMV) or BK-virus reactivation, malignancy or death in the multivariate Cox regression analysis. Belatacept is an efficient and safe option for patients after renal transplantation at high cardiovascular risk.Belatacept is an attractive option for immunosuppression after renal transplantation. Renal allograft function is superior when compared to calcineurin inhibitor (CNI) based therapy in “de novo” treated patients and it has also been proposed that individuals at high cardiovascular (CV) risk may benefit most. In this retrospective cohort study, we assessed the efficacy and safety of treating patients at high cardiovascular risk with Belatacept ( Calcineurin inhibitors (CNIs) are currently the standard immunosuppressive therapy after renal transplantation. Their introduction into clinical practice has improved short-term outcomes dramatically. Unfortunately, the rate of late allograft loss has not significantly improved  and it iBelatacept inhibits T-cell activation by blocking a co-stimulatory signal by binding to CD80/CD86 on antigen presenting cells . It is cThus, we conducted a retrospective cohort study in renal allograft recipients at high CV risk and compared the efficacy and safety of Belatacept treatment in 34 patients to the outcomes of 150 patients treated with CNI (mainly tacrolimus) based immunosuppression.n = 34). Eighteen patients were treated de novo and 16 were converted at a median of 1.6 months (interquartile range (IQR), 0.6–4.2 months) after transplantation, mainly due to biopsy confirmed or clinically suspected renal CNI toxicity. No patient in this group was returned to CNI therapy thereafter. As we were interested in studying the efficacy and safety in patients on either CNI or Belatacept therapy, the day of conversion was taken as the baseline in these individuals and all clinical endpoints were adjudicated to the Belatacept group. Due to the early conversion, we excluded the time on CNI from any calculation. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of the Medical University Innsbruck (Project-ID: 1137/2019).Belatacept has been used in 42 renal transplant recipients at our center since 2010 and in this retrospective cohort study, all patients at high cardiovascular risk (definition see below) have been included (n = 309) on CNI-based immunosuppression that received their transplant between 1 January, 2010 and 31 December, 2012 formed the control cohort. Of these, 150 also fulfilled the criteria for high cardiovascular risk. No patients were lost for follow-up, the median follow-up was 48 months and the total analysed period of months on therapy was 7309. High cardiovascular risk was defined by the presence of any significant pre-transplant coronary artery disease (CAD) confirmed on angiography, a history of myocardial infarction, peripheral artery disease (PAD) (cardiovascular disease) or stroke (cerebrovascular disease) or the presence of diabetes mellitus in combination with arterial hypertension.The median observation duration on Belatacept was 35 months, no patient was lost for follow-up and the total period on therapy analysed was 1194 months. All renal allograft recipients  or graft loss. The estimated glomerular filtration rate (eGFR) was calculated using the abbreviated MDRD formula. ΔeGFR was calculated by dividing the difference between eGFR at last follow-up and the baseline by the number of follow-up years. The safety endpoints were de novo cardiovascular events , severe infections , cytomegalo virus (CMV) reactivation , BKV reactivation (as determined by PCR in serum and/or urine), de novo malignancy and death. All efficacy and safety endpoints were identified using patients’ records.2 or Fisher exact tests. Non-parametric tests were used to compare continuous variables. The factors potentially associated with the eGFR, the eGFR-slope (eGFR), and efficacy and safety parameters were assessed using a Cox regression analysis. In particular, those factors were: Belatacept treatment, recipient age, male gender of the recipient, recipient BMI, a CMV high risk mismatch (D+/R-), the presence of diabetes mellitus or arterial hypertension, the presence of cerebrovascular or cardiovascular disease, the time on renal replacement therapy (RRT) before renal transplantation (RTx), number of previous RTx, number of HLA mismatches, intraoperative urine production , number of post-operative (PO)—meaning after renal transplantation—hemodialysis sessions (HDs), the absence or presence of steroids at discharge, the presence of serum-creatinine at discharge, the absence or presence of steroids at the last follow-up, the extended criteria donor (ECD) organ, the male sex of the donor, and donor age. A history of rejection was also included, with an exception for the endpoint rejection episodes. Variables with a p-value < 0.05 in univariate analysis were included in the multivariate analysis, where again a p-value < 0.05 was considered statistically significant. The analysis was performed using SPSS Version 24.The reported values represent either medians and interquartile ranges (IQR) or the number of patients and percentages of the respective cohort. Proportions were compared using the Chip = 0.003).Baseline data are shown in p = 0.001) and eGFR (MDRD) , was significantly worse in Belatacept patients.Concerning renal transplantation RTx, , the donp = 0.084), respectively. Belatacept was continued in all patients with a maintained graft function during follow-up (31/34). The number of patients on steroids at follow-up and the proportion of hypertensive patients were higher in the Belatacept group.The median follow-up  was 14622/year, p = 0.006). The median ΔeGFR in the whole cohort  was + 0.35 mL/min/1.73 m2 , number of postoperative HDs  and higher serum-creatinine at discharge . BMI  and number of postoperative HDs  remained significant after multivariate adjustments. Belatacept was not a risk factor for graft loss .Concerning efficacy, renal allograft function as assessed by serum creatinine/eGFR improved in Belatacept-treated patients and slightly worsened in CNI patients, yielding a non-significant difference between the groups at follow-up (in contrast to the time of discharge after RTx). ΔeGFR of the patients on Belatacept was positive compared to CNI patients . The type of severe infection also differed between the groups, with a higher proportion of diarrhoea, urinary tract infections and sepsis, but fewer instances of pneumonia, in Belatacept-treated patients. In the univariate Cox regression analysis, Belatacept treatment, number of postoperative HDs, the presence of creatinine at discharge, ECD and donor age were significant risk factors for severe infections (p = 0.001) and the presence of serum-creatinine at discharge  of which none remained significant in a multivariate model. A risk factor for BKV reactivation in patients’ plasma was treatment with steroids at follow-up  whereas the male sex of the donor was protective . The treatment with steroids at follow-up remained significant in the multivariate model . BKV reactivation in patients’ urine was significantly correlated with recipient  and donor age , of which recipient age remained multivariately significant .Concerning severe infections, defined as infections leading to the admission of the patient to hospital, we found more infections in the Belatacept group . All other parameters, and especially Belatacept , were not significant. Concerning malignancy, we found no significant factor in the univariate Cox regression. Univariate risk factors for death were recipient age , HLA mismatch  and the presence of creatinine at discharge . Recipient age was the only significant risk factor for death in multivariate Cox regression . The only univariate risk factor for the safety endpoint de novo cardiovascular events was pre-existing cerebrovascular disease , which is in line with the literature [Belatacept was not associated with an increased risk of rejection in our patients. BENEFIT-EXT  reportedterature ,18.Concerning safety and in contrast to Florman et al. , we founIn our cohort, Belatacept treatment was not a risk factor for CMV reactivation, malignancy or death. This is in line with the published data cited above. Additionally, Belatacept treatment was not a risk factor for BKV reactivations either in patients’ serum or urine. Unfortunately, data on these endpoints were not reported in the BENEFIT and BENEFIT-EXT studies. Nevertheless, our data is in line with the phase II studies, which showed only slightly increased cumulative incidence rates 0.85 vs. 0 ) and eve5 vs. 0  n = 35) and 7309 months in CNI patients (n = 150).Published data suggest a beneficial impact of Belatacept on arterial stiffness and metabolic parameters  or post-transplant diabetes mellitus. The authors concluded that this could improve kidney transplant recipients’ survival by reducing events related to those factors ,17,18,20p = 0.084). From our point of view, the duration of follow-up is still significant, although one might argue that a longer follow-up would have been beneficial, especially for the end point “cardiovascular event”. However, the number of studies that have published data of renal allograft recipients on Belatacept-based immunosuppression is generally limited. In total, until the end of 2014, the data of 521 Belatacept patients, which were compared to CNI-treated controls, were published [Our study has limitations. Firstly, this is a retrospective study, which by nature does not provide the same data quality as a prospective design. Secondly, the size of the study population is relatively small, as we included only 34 Belatacept patients and 150 CNI patients as a comparator. Thirdly, the baseline characteristics of time on RRT, primary renal disease, diabetes, cardiovascular disease and arterial hypertension were different between our two populations  and it iublished ,22. The ublished , BENEFITublished  and the In conclusion, we believe that Belatacept is an efficient, beneficial and safe option for renal allograft recipients at high cardiovascular risk. In our cohort, Belatacept treatment was associated with a superior graft function compared to a CNI-treated cohort and was not a risk factor for renal allograft rejection, -loss, severe infection, CMV- or BKV-reactivation, malignancy or death.


Up to 60% of children with Attention-Deficit/Hyperactivity Disorder (ADHD) meet diagnostic criteria for at least one anxiety disorder, including Social, Generalized and/or Separation Disorder. Anxiety in children with ADHD has been shown to be associated with poorer child and family functioning. Small pilot studies suggest that treating anxiety in children with ADHD using cognitive-behavioral therapy (CBT) has promising benefits. In a fully powered randomized controlled trial (RCT), we aim to investigate the efficacy of an existing CBT intervention adapted for children with ADHD and comorbid anxiety compared with usual care.N = 228) from pediatrician practices in Victoria, Australia. Eligibility criteria include meeting full diagnostic criteria for ADHD and at least one anxiety disorder . Eligible children are randomized to receive a 10 session CBT intervention (Cool Kids) versus usual clinical care from their pediatrician. The intervention focuses on building child and parent skills and strategies to manage anxiety and associated impairments including cognitive restructuring and graded exposure. Minor adaptations have been made to the delivery of the intervention to meet the needs of children with ADHD including increased use of visual materials and breaks between activities. The primary outcome is change in the proportion of children meeting diagnostic criteria for an anxiety disorder at 5 months randomization. This will be assessed via diagnostic interview with the child’s parent (Anxiety Disorders Interview Schedule for Children V) conducted by a researcher blinded to intervention condition. Secondary outcomes include a range of child  and parent  domains of functioning assessed at 5 and 12 months post-randomization. Outcomes will be analyzed using logistic and mixed effects regression.This RCT is recruiting children aged 8–12 years . The trial was first registered 29/9/15 and last updated 15/1/19. Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental disorder affecting 5% of the childhood population . ADHD caN = 389), 64% of children with ADHD aged 5 to 13 years met diagnostic criteria for at least one anxiety disorder, including Social (48%), Generalized (34%), and Separation (32%) Anxiety Disorders  at 5 and 12 months. For continuous and count data secondary outcomes, groups will be compared using linear or Poisson mixed effects regression, as appropriate, with results presented as mean differences (and 95% CIs) in outcomes at 5 and 12 months. In addition, we will repeat the analysis adjusted for baseline covariates as appropriate: for example, child sex , child age, medication use (yes/no), comorbidities (yes/no), therapist, and family socioeconomic status). For our primary outcome, whether the child meets criteria for an anxiety disorder  at 5 months, a sensitivity analysis will be conducted using multiple imputation to handle the missing data with analysis via logistic regression applied to the 5 month data only.We will determine the cost-effectiveness of the Calm Kids intervention compared with usual care ‘within-trial’ from a health care perspective and a broader societal perspective. The collection of data on the Child Health Utilities Index Nine Dimension (CHU-9D) , 37 willThe results from this study will provide evidence on whether treating comorbid anxiety in children with ADHD using a CBT approach leads to improvements in anxiety and broader functional outcomes compared with standard care. If the intervention is found to be efficacious, the evidence from this trial will inform efforts to test the translation of this intervention approach into clinical practice. We will publish our results in peer reviewed journals, present at conferences in this field and disseminate findings through professional associations  and ADHD organizations around the world. Eligibility for authorship will be in accordance with the Australian Code for the Responsible Conduct of Research. We also hope that our work will inform adaptations to existing clinical guidelines on the assessment and management of anxiety when it co-occurs with ADHD.Additional file 1. Parent/Guardian Information Statement and Consent Form.