Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.

BACKGROUND: Major depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data; distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. OBJECTIVE: We aimed to address these 3 challenges to inform future work in stratified analyses. METHODS: Using smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the individual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. RESULTS: We demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. CONCLUSIONS: This work contributes to our understanding of how these mobile health-derived features are associated with depression symptom severity to inform future work in stratified analyses.

Defining Antibiotic Inertia: Application of a Focused Clinical Scenario Survey to Illuminate A New Target for Antimicrobial Stewardship During Transitions of Care.

In clinical scenario surveys, inpatient providers were more likely to report continuing inappropriate (odds ratio, 2.02 [95% confidence interval, 1.35-3.03]; P<.001) or broad-spectrum (1.8 [1.27-2.56]; P=.001) antibiotic therapy when initiated by emergency department providers, than to change to appropriate or narrow-spectrum therapy, respectively. Antibiotic inertia could represent a significant antibiotic stewardship target.

Human health risk-based soil environmental criteria (SEC) for park soil in Beijing, China.

Urban parks are important places that allow urban residents to experience nature but are also associated with the risk of exposure to contaminated soil. Therefore, it is necessary to establish appropriate soil environment criteria (SEC) to manage park soil quality. Studies on the demographic characteristics and behavioral patterns of urban park visitors are helpful for the selection of sensitive receptors and the determination of parameters in the establishment of SEC. This study explored the park visitors' demographic characteristics and behavioral patterns, and applied the results to derive SEC. Eighty-six parks in Beijing were selected, and mobile phone data were obtained to analysis the demographic characteristics and residence time of the visitors. Kruskal-Wallis test, kernel density estimation and random forest model were used for data analysis. The CLEA model was used to derive SEC. The results showed that the demographic characteristics and behavioral patterns of visitors in different types of parks were quite different. Parks were mostly used by males and visitors aged 31-45. Most visitors stayed in the park for 1-2 h, and the distance from a given visitor's home to the park was the most important factor affecting stay time. Then, several parameters such as the parameters related to the receptors and occupation period were optimized, and the SEC of sensitive parks and non-sensitive parks were derived. Exposure frequency may be the main reason for the difference of SEC between the two types of parks. The SECs of sensitive parks were higher than the soil screening values (SSVs) for class 1 land in GB36600-2018, indicating that the current SSVs for some parks may be too conservative. This study provides a reference for the formulation and revision of soil environmental standards for park land, and suggests strengthening research on human behavioral patterns.

Predicting student performance using sequence classification with time-based windows.

A growing number of universities worldwide use various forms of online and blended learning as part of their academic curricula. Furthermore, the recent changes caused by the COVID-19 pandemic have led to a drastic increase in importance and ubiquity of online education. Among the major advantages of e-learning is not only improving students' learning experience and widening their educational prospects, but also an opportunity to gain insights into students' learning processes with learning analytics. This study contributes to the topic of improving and understanding e-learning processes in the following ways. First, we demonstrate that accurate predictive models can be built based on sequential patterns derived from students' behavioral data, which are able to identify underperforming students early in the course. Second, we investigate the specificity-generalizability trade-off in building such predictive models by investigating whether predictive models should be built for every course individually based on course-specific sequential patterns, or across several courses based on more general behavioral patterns. Finally, we present a methodology for capturing temporal aspects in behavioral data and analyze its influence on the predictive performance of the models. The results of our improved sequence classification technique are capable to predict student performance with high levels of accuracy, reaching 90% for course-specific models.

PALOT: Profiling and Authenticating Users Leveraging Internet of Things.

Continuous authentication was introduced to propose novel mechanisms to validate users' identity and address the problems and limitations exposed by traditional techniques. However, this methodology poses several challenges that remain unsolved. In this paper, we present a novel framework, PALOT, that leverages IoT to provide context-aware, continuous and non-intrusive authentication and authorization services. To this end, we propose a formal information system model based on ontologies, representing the main source of knowledge of our framework. Furthermore, to recognize users' behavioral patterns within the IoT ecosystem, we introduced a new module called "confidence manager". The module is then integrated into an extended version of our early framework architecture, IoTCAF, which is consequently adapted to include the above-mentioned component. Exhaustive experiments demonstrated the efficacy, feasibility and scalability of the proposed solution.

Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing.

Neuro Linguistic Programming (NLP) is a methodology used for recognition of human behavioral patterns and modification of the behavior. A significant part of this process is influenced by the theory of representational systems which equates to the five main senses. The preferred representational system of an individual can explain a large part of exhibited behaviors and characteristics. There are different methods to recognize the representational systems, one of which is to investigate the sensory-based words in the used language during the conversation. However, there are difficulties during this process since there is not a single reference method used for identification of representational systems and existing ones are subject to human interpretations. Some human errors like lack of experience, personal judgment, different levels of skill and personal mistakes may also affect the accuracy and reliability of the existing methods. This research aims to apply a new approach that is to automate the identification process in order to remove human errors, thereby increasing the accuracy and precision. Natural Language Processing has been used for automating this process, and an intelligent software has been developed to identify the preferred representational system with increased accuracy and reliability. This software has been tested and compared to human identification of representational systems. The results of the software are similar to a NLP practitioner, and the software responds more accurately than a human practitioner in various parts of the process. This novel methodology will assist the NLP practitioners to obtain an improved understanding of their clients' behavioral patterns and the associated cognitive and emotional processes.

Effects of random food deprivation and refeeding on energy metabolism, behavior and hypothalamic neuropeptide expression in Apodemus chevrieri.

Maintaining adaptive control of behavior and physiology is the main strategy used by animals in responding to changes of food resources. To investigate the effects of random food deprivation (FD) and refeeding on energy metabolism and behavior in Apodemus chevrieri, we acclimated adult males to FD for 4weeks, then refed them ad libitum for 4weeks (FD-Re group). During the period of FD, animals were fed ad libitum for 4 randomly assigned days each week, and deprived of food the other 3days. A control group was fed ad libitum for 8weeks. At 4 and 8weeks we measured body mass, thermogenesis, serum leptin levels, body composition, gastrointestinal tract morphology, behavior and hypothalamic neuropeptide expression. At 4weeks, food intake, gastrointestinal mass, neuropeptide Y (NPY) and agouti-related protein (AgRP) mRNA expressions increased and thermogenesis, leptin levels, pro-opiomelanocortin (POMC) and cocaine- and amphetamine-regulated transcript (CART) expressions decreased in FD compared with controls. FD also showed more resting behavior and less activity than the controls on ad libitum day. There were no differences between FD-Re and controls at 8weeks, indicating significant plasticity. These results suggested that animals can compensate for unpredictable reduction in food availability by increasing food intake and reducing energy expended through thermogenesis and activity. Leptin levels, NPY, AgRP, POMC, and CART mRNA levels may also regulate energy metabolism. Significant plasticity in energy metabolism and behavior was shown by A. chevrieri over a short timescale, allowing them to adapt to food shortages in nutritionally unpredictable environments.

Direct links between resource availability and activity budget better reveal ecological patterns of endangered Coimbra-Filho's titi monkey.

Many primatological studies do not assess direct indexes of food availability to make inferences about behavioral strategies. We related the diet and behavior of a group of Callicebus coimbrai in northeastern Brazil to fruit availability indexes and compared this pattern between seasons (direct and indirect assessment of food availability) to assess whether direct and indirect approaches detect similar ecological patterns. We monitored the study group for 33 months (5 days/month) via scan sampling. The monthly availability of fruits and new leaves was recorded in phenological transects. Fruit availability varied across years based on fruit prevalence, and timing and duration of the abundant seasons. We did not find evidence of a time-minimizing strategy, since C. coimbrai did not change its activity levels according to food availability. However, the negative relationship between foraging and fruit availability indicates that C. coimbrai can compensate for the lower fruit availability by increasing the search for alternative food sources. Monthly fruit consumption was positively correlated to fruit availability and negatively related to the consumption of other food items. However, the behavioral and feeding profiles did not vary between seasons and were not related to rainfall levels. Primate studies should directly relate behavioral and feeding profiles to fruit availability indices, thus avoiding using seasons as proxies of food availability.

Comparative Analysis of Academic, Behavioral, and Psychophysiological Variables in Male and Female Vocational Training Students.

BACKGROUND/OBJECTIVES: The purpose of this study was to investigate whether or not there are notable differences between male and female vocational training students in terms of academic, behavioral, and psychophysiological characteristics. METHODS: A total of 411 vocational training students, 210 of whom were male and 201 of whom were female, participated in an online survey that assessed academic, behavioral, and psychophysiological patterns. RESULTS: In terms of extraversion and openness to experience, our research revealed that no statistically significant differences were noticed. When it came to agreeableness, however, significant differences were seen, with female students getting higher marks than male students. Furthermore, we found that there were significant gender differences in terms of neuroticism and conscientiousness, with female students achieving higher scores than male students. When compared to their male counterparts, females displayed higher performance in terms of academic success. They also demonstrated superior values in terms of reported stress, anxiety, and cognitive inflexibility. CONCLUSIONS: The findings of this study provide a more in-depth understanding of the numerous factors that have an impact on students engaging in vocational training. This will serve as a foundation for the development of individualized instructional and support programs.

Exploring Large Digital Bodies for the Study of Human Behavior.

Internet access has become a fundamental component of contemporary society, with major impacts in many areas that offer opportunities for new research insights. The search and deposition of information in digital media form large sets of data known as digital corpora, which can be used to generate structured data, representing repositories of knowledge and evidence of human culture. This information offers opportunities for scientific investigations that contribute to the understanding of human behavior on a large scale, reaching human populations/individuals that would normally be difficult to access. These tools can help access social and cultural varieties worldwide. In this article, we briefly review the potential of these corpora in the study of human behavior. Therefore, we propose Culturomics of Human Behavior as an approach to understand, explain, and predict human behavior using digital corpora.

Research on the psychologically restorative effects of campus common spaces from the perspective of health.

Contemporary college students are suffering from increasingly serious psychological health problems, such as attention fatigue, psychological stress and negative emotions. A growing body of evidence has revealed that restorative environment design is conducive to psychological health. As the main choice of venue for students' daily activities, campus common spaces are supposed to be restorative to some extent. Given the above, the author studied 22 common spaces in the South China University of Technology (SCUT) Wushan Campus from the perspective of college students' behavioral patterns based on theories pertaining to restorative environments, then constructed a structural equation model (SEM) analyzing the psychologically restorative effects exerted by the characteristics of campus common spaces upon college students through a scale design and questionnaire survey. With the analysis of 478 valid questionnaires, the research found that the characteristics of campus common spaces with psychologically restorative effects mainly comprise the architectural environment, landscape environment, rest facilities and activity facilities. Among them, the characteristics of activity facilities and the landscape environment have the greatest impact on psychologically restorative effects, accounting for 33 and 30% of the total effects, respectively; they are followed by those of the architectural environment, which accounts for 21% of the total effects; those of the rest facilities have the least impact, accounting for 16% of the total effects. The research also found that the characteristics of campus common spaces can both directly influence college students' psychological recovery and produce psychologically restorative effects mediated by college students' behavioral patterns. The mediation effect of college students' behavioral patterns accounts for approximately 41% of the total effect of psychological restoration, in which the psychologically restorative effect of dynamic exercise behaviors is 2.5 times that of static leisure behaviors. The research reveals how the characteristics of campus common spaces promote the psychological restoration of college students, and it provides inspiration for healthy environment design in campus common spaces.

Social media reporting on agricultural adaptation to climate change in Pakistan: Measures and implications for sustainability.

The agricultural sector is the backbone and single-largest sector of the Pakistani economy. Pakistan's agricultural productivity is suffering due to climate change. The study aimed at finding how social media reporting can change patterns of attitudes among farmers to cope with sudden weather changes. A correlation-experimental research design was used to find the relationships and effects of climate change on agriculture in Punjab (Pakistan) and the mediating effect of social media reporting. A purposive sampling technique was used to collect samples from 120 male farmers. Online surveys, with the help of Google Docs, were used to collect participants' responses about the type of behavior they used to adopt when getting information about climate change through social media. After determining their reliability and validity through piloting, two self-constructed questionnaires were used: (i) Measuring Farmers' Behavior Influenced by Social Media Reporting of Climate Change and (ii) Effects of Social Media Reporting of Climate Change on Agriculture. Data were analyzed using SPSS-21, and correlation analysis was done to find out the relationship between social media reporting and farmers' behavior. Linear regression was used to measure the functional relationship between social media reporting about climate change and farmers' attitudes towards adopting precautions to increase annual yield. The coefficient of social media reporting was positively and significantly related to farmers' attitudes towards the selection of crops, land management, and water storage. Based on the findings, the social media reports significantly predicted patterns of farmers' behavior towards the adaptation of advanced measures to select crops, reduce pest attacks, manage land, and store water.

Using an Online Disturbance Rejection and Anticipation System to Reduce Hyperglycemia in a Fully Closed-Loop Artificial Pancreas System.

INTRODUCTION: Hyperglycemia following meals is a recurring challenge for people with type 1 diabetes, and even the most advanced available automated systems currently require manual input of carbohydrate amounts. To progress toward fully automated systems, we present a novel control system that can automatically deliver priming boluses and/or anticipate eating behaviors to improve postprandial full closed-loop control. METHODS: A model predictive control (MPC) system was enhanced by an automated bolus system reacting to early glucose rise and/or a multistage MPC (MS-MPC) framework to anticipate historical patterns. Priming was achieved by detecting large glycemic disturbances, such as meals, and delivering a fraction of the patient's total daily insulin (TDI) modulated by the disturbance's likelihood (bolus priming system [BPS]). In the anticipatory module, glycemic disturbance profiles were generated from historical data using clustering to group days with similar behaviors; the probability of each cluster is then evaluated at every controller step and informs the MS-MPC framework to anticipate each profile. We tested four configurations: MPC, MPC + BPS, MS-MPC, and MS-MPC + BPS in simulation to contrast the effect of each controller module. RESULTS: Postprandial time in range was highest for MS-MPC + BPS: 60.73 ± 25.39%, but improved with each module: MPC + BPS: 56.95±25.83 and MS-MPC: 54.83 ± 26.00%, compared with MPC: 51.79 ± 26.12%. Exposure to hypoglycemia was maintained for all controllers (time below 70 mg/dL <0.5%), and improvement came primarily from a reduction in postprandial time above range (MS-MPC + BPS: 39.10 ± 25.32%, MPC + BPS: 42.99 ± 25.81%, MS-MPC: 45.09 ± 25.96%, MPC: 48.18 ± 26.09%). CONCLUSIONS: The BPS and anticipatory disturbance profiles improved blood glucose control and were most efficient when combined.

Attention Deficit Hyperactivity Disorder Assessment Based on Patient Behavior Exhibited in a Car Video Game: A Pilot Study.

Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) include excessive activity, difficulty sustaining attention, and inability to act in a reflective manner. Early diagnosis and treatment of ADHD is key but may be influenced by the observation and communication skills of caregivers, and the experience of the medical professional. Attempts to obtain additional measures to support the medical diagnosis, such as reaction time when performing a task, can be found in the literature. We propose an information recording system that allows to study in detail the behavior shown by children already diagnosed with ADHD during a car driving video game. We continuously record the participants' activity throughout the task and calculate the error committed. Studying the trajectory graphs, some children showed uniform patterns, others lost attention from one point onwards, and others alternated attention/inattention intervals. Results show a dependence between the age of the children and their performance. Moreover, by analyzing the positions by age over time using clustering, we show that it is possible to classify children according to their performance. Future studies will examine whether this detailed information about each child's performance pattern can be used to fine-tune treatment.

Discriminant analysis predicted undisciplined policemen.

In the wider spectrum of Taiwanese public service spheres, the herculean services and dedication of its committed Police personnel have long been recognized, respected, and admired. However, regrettably, question marks concerning their conduct, discipline, and abuse of power have surfaced on intermittent occasions. A classic example that lingers in the public memory is the bribing of Taiwanese video game companies to some unscrupulous elements of the police department, in the closing decades of the 20th century that triggered public outrage and called for scrutiny concerning serious lapses in the discipline and conduct of Police personnel. This research paper endeavors to understand, analyze and address some of those issues based on empirical data on the police personnel of certain specific work zones/areas taking into account holistically both the sentenced police officers vis-à-vis the law-abiding police officers. This module looks into and sieves through available data for seven critical variables, including their degree of variation through the Identification and Analysis Method to develop a Predictive Model on Police Ethics and the important factors that affect Police Ethics. Concretely based on the integrated research, it is proposed that this Predictive Model has good applicability as well as accurate predictive ability in addressing the core issues that affect Police Ethics. It is hoped that through this Early Warning Predictive Model-all the stakeholders that are Policy and Decision-makers, Regulatory Police Agencies but more importantly the Police personnel themselves would effectively address the criticality of the issues that affect the Police Ethics so as to undertake competent and effective measures to erase/lessen the menace and provide an early rehabilitative care/assistance to build a strong, constructive and visionary Taiwanese Police Force to meet the challenges of 21st century and beyond.

Functional Constructivism Approach to Multilevel Nature of Bio-Behavioral Diversity.

Attempts to revise the existing classifications of psychiatric disorders (DSM and ICD) continue and highlight a crucial need for the identification of biomarkers underlying symptoms of psychopathology. The present review highlights the benefits of using a Functional Constructivism approach in the analysis of the functionality of the main neurotransmitters. This approach explores the idea that behavior is neither reactive nor pro-active, but constructive and generative, being a transient selection of multiple degrees of freedom in perception and actions. This review briefly describes main consensus points in neuroscience related to the functionality of eight neurochemical ensembles, summarized as a part of the neurochemical model Functional Ensemble of Temperament (FET). None of the FET components is represented by a single neurotransmitter; all neurochemical teams have specific functionality in selection of behavioral degrees of freedom and stages of action construction. The review demonstrates the possibility of unifying taxonomies of temperament and classifications of psychiatric disorders and presenting these taxonomies formally and systematically. The paper also highlights the multi-level nature of regulation of consistent bio-behavioral individual differences, in line with the concepts of diagonal evolution (proposed earlier) and Specialized Extended Phenotype.

Evaluation of copper nanoparticles and copper sulfate effect on immune status, behavior, and productive performance of broilers.

OBJECTIVE: This study was conducted to compare between the nanoparticles of copper (Cu-NP) and copper sulfate (CuSO4) effect on immunity, pro-inflammatory cytokine, oxidant/antioxidant balance, different behavioral patterns, growth rate, and weight gain by adding them in drinking water of broilers. MATERIALS AND METHODS: One hundred and fifty broiler chicks of 1-day-old were randomly divided into three groups: the first group was the control, the second group received CuSO4 in drinking water (10 mg/l), and the third group received Cu-NP in drinking water (10 mg/l) with replicates (n = 25) for 5 weeks of age. Blood samples collected for estimating immunoglobulins (A, G, and M), superoxide dismutase, pro-inflammatory (IL-6), erythrocyte sedimentation rate, heterophil/lymphocyte (H/L) ratio, malondialdehyde (MDA), corticosterone hormone, and lymphoid organs index weight. Moreover, behavioral observations were undertaken from the 2nd week until the 5th week of age for measuring different behavioral patterns (feeding, drinking, crouching, body care, and comfort behaviors). Chicks were individually weighed weekly (gm); also, the weight gain, the intake of food, and the ratio of feed conversion were calculated. RESULTS: Cu-NP administration has improved the blood profile, lymphoid organs index weight in Cu-NP treated broilers in relation to control and CuSO4 treated groups. Conversely, erythrocyte sedimentation rate, H/L ratio, MDA, and corticosterone hormone were reduced by Cu-NP treatment. Moreover, Cu-NP has a positive effect on all behavioral patterns more than other groups which significantly reflect on the weight of the body, gaining of weight, and the intake of food in the Cu-NP treated group of birds. CONCLUSION: The findings in this study stated that when the drinking water of broilers was supplemented with Cu-NP, there might be an improvement in the immunity, behavior, and productive performance more efficiently than CuSO4.

Is It Possible to Predict an Athlete's Behavior? The Use of Polar Coordinates to Identify Key Patterns in Taekwondo.

Match analysts and sport psychologists can help elite athletes develop planned competition strategies from a technical-tactical perspective by analyzing of previous performances. The aim of this study was to analyze the behavioral patterns used to score points in the 2012 London Olympic Games by a mixed observational methodology and polar coordinate analysis. This analysis is a representation of four quadrants of the relationships between focal behavior [i.e., scoring, (SC)] and conditioned behaviors as key factors in taekwondo before and after focal behavior of two lags (-2, +2). A total of 151 combats, with a total of 24,940 actions were analyzed by the Taekwondo Observational Tool, which consists of 24 categories grouped into seven criteria (tactics, techniques, kicking zone, laterality, kicking leg, guard, and score). Our analysis confirms 49 significant associations (21 in females and 28 in males) between different types of scoring actions (SC1: to the trunk, SC2: to the trunk with a previous spin, SC3: to the head and SC4: to the head with a previous spin) and a variety of technical-tactical aspects. Females SC1 after cut, direct attacks with circular techniques to the chest, with back right leg; SC2 after direct attacks to the head, and SC3 after cuts, posterior counterattacks with the back leg. Males SC1 after spin anticipate counterattack with back leg and dodges, SC2 after simultaneous counterattacks (SCAs) to the head, SC3 after cuts and posterior counterattacks with back leg while SC4 after blocks and SCAs in close guard with the forward right leg. The observed relationships provide objective data regarding successful behavioral patterns, and are important for coaches and psychologists to train and develop psychological strategies to prepare athletes. For instance, they can be used to individualize training sessions, including visualization of specific combat situations. Coaches and psychologists could use these findings for specific tasks related to technical-tactical improvement of scoring effectiveness or defensive strategies against these specific actions.

Behavioral Patterns of Children Involved in Bullying Episodes.

This study applied a systematic observation strategy to identify coercive behavioral patterns in school environments. The aim was to describe stability and change in the behavioral patterns of children identified as victims of bullying. To this end, the following specific objectives were defined: (1) to identify episodes of bullying based on the frequency of negative behaviors received and power imbalances between bully and victim; (2) to describe stability and behavioral changes in student victims based on their social and academic conduct and the aggression they receive from peers and teachers; and (3) to describe the functional mechanisms responsible for the process of social organization (i.e., the Social Effectiveness, Social Responsiveness, and Social Reciprocity Indexes). The sample consisted of nine children identified as victims, nine classified as bullies, and nine matched controls, all elementary school students from the study developed at the National Autonomous University of Mexico files. A multidimensional/idiographic/follow-up observational design was used. Observational data describes asymmetry between victims and bullies based on microanalyses of the reciprocity of their behavioral exchanges. In addition, the behavioral patterns of victimized children were identified in relation to their academic activity and social relationships with peers. A model of coercive reciprocity accurately describes the asymmetry found among bullies, victims, and controls. A reduction in victimization was found to be related to: (1) responsiveness to the initiation of social interactions by peers and teachers; and (2) the time allocated to academic behavior during the study.

A study of behavioral and disease patterns among transgenders in a tertiary care center.

INTRODUCTION: Transgenders are a group whose sexual identity, orientation, and practices differ from majority of the society. AIM: The aim of the study is to highlight the presence of infectious and noninfectious dermatological and venereal diseases among transgender population. MATERIALS AND METHODS: A retrospective study was conducted on 120 transgender patients who attended DVL OPD from January 2011 to April 2015. The demographic profile, behavioral patterns, and prevalence of infectious and noninfectious dermatological and venereal diseases were studied. RESULTS: All transgenders were male to females. Almost 46.6% (56) of transgenders belonged to age group 21-30, 25% (30) to 11-20 and 30-40, and 3.4% to >40 years. Nearly 61.3% (74) completed high school, 14.7% (18) graduation, 12% (14) primary school, 9% (10) higher secondary, and 1.3% (2) were illiterate and postgraduates each. All had multiple sex partners at certain point of time, of which 25% (31) are now committed to a single partner and 15% (19) involved in commercial sex. The safe sexual practice was followed by 68% (84). Among sexual practices, oral contributed 97.3% (117), anal 92% (110.4), finger 9% (11), thigh 6% (7), and vaginal 24% (28.8). Of 120 patients, 63.3% (76) had infectious diseases, 42.5% (51) had noninfectious diseases, and 5.9% (7) had both. Nearly 76.3% (58) had infectious dermatological diseases 76.3 (58) and 23.7% (18) had venereal infections. Noninfectious dermatological diseases accounted for 96.1% (49) and venereal diseases for 4% (2). CONCLUSION: There was relatively lower prevalence of infectious venereal diseases among transgender population, attributable to the good level of awareness among them.