Statistical Programming Environment Research Articles

A Federated Database for Obesity Research: An IMI-SOPHIA Study.

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Investigation of the ecological and climatic niche of the protected species Erythronium sibiricum (Fisch. et Mey.) Kryl.

The Siberian kandyk (Erythronium sibiricum (Fisch. et Mey.) Kryl.) is listed in the Red Books of the Russian Federation and in the regions where it grows. The Siberian kandyk is widespread in Southern Siberia and Mongolia. This species has many useful qualities, for example, it is used for decorative purposes, for introduction, in folk medicine and for obtaining honey. The purpose of the work is to identify the ecological and climatic niche of the species and build on its basis a model of suitable habitats in the conditions of modern climate. The MaxEnt 3.4.4 and BIOCLIM methods implemented in the statistical programming environment R (CRAN) were chosen as tools for analysis and modeling. For visualization and information of previously obtained layers, the ArcGIS 10.8 program is convenient. As a result of the work done, it became obvious that the current distribution of the species as a whole corresponds to the obtained model of distribution of favorable conditions for the growth of the species, and the reduction in the number of plants is caused by other reasons.

Introducing SourceXplorer, an open-source statistical tool for guided lithic sourcing

Archaeologists' access to analytical infrastructure has grown exponentially over the last two decades. This is especially the case for benchtop X-ray fluorescence (XRF) and portable XRF (pXRF) instruments, which are now practically commonplace in archaeological laboratories and provide users with a non-destructive and rapid means to analyze the elemental compositions of archaeological specimens. As XRF has become more accessible, the volume of analytical measurements available in archaeological datasets as well as the number and diversity of researchers participating in data collection have inherently increased. Those researchers, who have various levels of experience with the nuances of lithic sourcing procedures, are also often the ones attempting to interpret the elemental data they produce. While standardized analytical procedures have enabled inexperienced analysts to take accurate and reproducible XRF measurements, interpreting the resulting data is more difficult to convert and standardize with the same degree of user-friendliness. To address this challenge, we have bundled a series of statistical approaches and data exploration tools into an intuitive open-source graphical user interface designed to facilitate reproducible and robust outcomes during lithic sourcing studies. Our application, SourceXplorer, permits easy access to and exploration of numeric baseline data using a map interface while facilitating a guided interpretation of source affiliations for archaeological specimens (e.g., lithics) within any natural context using multivariate statistical analyses. We demonstrate SourceXplorer's functionality in relation to a complex archaeological challenge by examining evidence for the procurement and use of lithic material from previously undocumented toolstone source locations in southwestern British Columbia, Canada. We also provide open access to SourceXplorer, including both a deployed version of the application that can be used with any Internet browser and the packaged script, which can be run locally in the open-source R statistical programming environment.

Translation, cross-cultural adaptation and validation of the sickle cell self-efficacy scale (SCSES)

To translate, cross-culturally adapt and validate the Sickle Cell Self-Efficacy Scale for application in the Brazilian cultural context. This is a methodological study performed in 6 steps: 1- Forward translation; 2- Translation synthesis; 3- Back-translation; 4- Assessment by expert committee, with computation of the Content Validity Index (CVI); 5- Cultural adequacy (pre-test); 6- Reproducibility. A pre-test was performed with the participation of 10 adolescents/young adults with sickle cell disease through a telephone call and their responses were recorded on a form in a web platform. The instrument validation step was carried out with 55 adolescents/young adults with sickle cell disease, 43 of them having participated in the retest. The analysis of internal consistency and reproducibility was calculated using the Cronbach's alpha coefficient and the Intraclass Correlation Coefficient (ICC), in the R statistical programming environment. The translated instrument had good acceptance among the experts, reaching an average CVI of 1.0. In assessing reliability, the scale showed acceptable internal consistency, with a Cronbach's alpha of 0.84. In the agreement analysis, the ICC was 0.923 (95% CI: 0.857 to 0.958), which indicates good temporal reproducibility. Following the process of translation, cross-cultural adaptation and validation, we obtained the Brazilian version of the Sickle Cell Self-Efficacy Scale, considered valid and reliable to be applied to adolescents and young adults with sickle cell disease in Brazil.

Scientific Progress of Global Research on BCG Vaccine: A Scientometric Study

ABSTRACT The study presents an overview of global research output on the Bacille Calmette-Guerin (BCG) vaccine from 1989–2021 using various scientometric indicators. The objective is to inform and present a comprehensive analysis of BCG vaccine research to health practitioners, researchers, and librarians that has not been explored from the perspective of scientometrics. Using a search strategy, data was collected from the Web of Science database and 2416 original articles were identified. Computed analysis of the literature was done through the software bibloshiny (a web interface for bibliometrix analysis) in the R statistical programming environment. The study examined the pattern of growth of research output, prolific authors, institutions, key journals, and countries involved in BCG vaccine research. Findings reveal an increase in research output on BCG vaccine from 2008 onwards. The highest number of articles 163 were published in 2016. Key journals, authors, and institutions working in the field of BCG vaccine research have been identified. A Sankey diagram has been used to depict the evolution of BCG vaccine research. This article reports the evolution of BCG vaccine research in terms of annual growth of publications, relevant authors, institutions, countries, and the evolution of author keywords and the growth of BCG vaccine research areas.

The artemis package for environmental DNA analysis in R

AbstractWe introduce artemis, a new package for the R statistical programming environment designed to analyze quantitative polymerase chain reaction (qPCR) data from environmental DNA studies. The artemis package directly addresses several challenges for analyzing eDNA survey data, including the censorship of data generated by qPCR analysis. The performance of artemis models is compared with commonly used regression approaches using both simulated and experimental data. We demonstrate that the models in artemis have several favorable characteristics compared with standard regression approaches, yielding more accurate estimates, less bias, and better prediction performance while offering similar ease of use. Lastly, we discuss trade‐offs and considerations for choosing the most appropriate analysis approach for eDNA survey data.

T-Cell Lymphomas in Mexico: Experience of a Third Level Reference Hospital

Introduction ——- Mature T-cell lymphomas have a global incidence ranging from 9.3% to 13.4% of the total amount of non-Hodgkin lymphomas worldwide. However, in Asian and South and Central America countries, incidence has been reported up to 20%. This suggests that there is a wide range of environmental and racial factors that modify the frequency of T-cell lymphomas and its subtypes. The common subtypes of these lymphomas also have been reported to vary greatly across the world. Studies have placed the NK/T cell lymphoma as the most prevalent T-cell lymphoma of Mexico, with 40% of all T cell lymphomas diagnosed, while the US reported frequency ranges in the 5 to 6%. Our objective is to report our experience in a third level reference Hospital in northeast Mexico.Materials and Methods —- A retrospective and observational study was conducted. Utilizing the database manager Pathox, we collected all the cases of patients diagnosed with lymphoma from January 2010 to January 2017. We included in the study all cases that were diagnosed with a variant of T-cell lymphoma that had available material for revision. They were assigned to groups by sex, subtype of lymphoma in accordance to the World Health Organization (WHO) classification of lymphoid neoplasms 2016, and the anatomical location of the primary tumor. Data analysis was performed in the statistical programming environment R version 3.3.2. Descriptive statistics were reported as percentages, central tendency and dispersion statistics.Results ——— We found a total of 771 lymphomas in our study. 88 of those had a diagnosis of T-cell lymphoma. The location of the primary tumor was a lymph node in 36.26% of the cases, and in the rest of the primary tumors, the skin was the most frequent location with 57.14%; the nasal and retronasal tissue followed, with 5.49%. For the subtypes, the most frequent was mycosis fungoides (MF) (29.67%) followed by Peripheric T-cell Lymphoma, Not Otherwise Specified, (PTCL, NOS) (23.08%). NK/T-Cell lymphoma nasal type, accounted for 10.99%. Anaplastic Large Cell Lymphoma (ALCL) ALK+ (4.4%), ALCL ALK - (7.69%), Angioinmunoblastic T-cell lymphoma (AITL) (2.20%) and subcutaneous Panniculitis- like T-cell lymphoma (1.1%) were also reported. The rest of the cases were reclassified into a non T-cell lymphoma or different diagnosis. Of the IHQ stains used to for diagnosis, the most commonly used were CD20, CD4, CD3, CD7 and CD8, with an average number of IHQ stains of 4.4 per case.Conclusions — Available literature places the frequency of T-cell lymphomas between 5 and 15% for developed countries, in concordance to our frequency (11.4%). For anatomic location of the primary tumor, the most frequent location was the skin (57.14%), followed by the lymph nodes (36.26%) and the nasal tissue (5.49%), while the rest distributed among the bone marrow, soft tissues, and tonsils. Frequency was not significant among males or females. Subtype frequency predominated for MF (29.67%) and PTCL, NOS (23.08%). NK/T-cell lymphomas account for only 10.99%. Our data suggests that the environmental, geographical and race factors create wide variations in the frequency of these lymphomas and their subtypes, giving way for additional studies to find and explain this variations. DisclosuresNo relevant conflicts of interest to declare.

Spatially resolved infrared radiofluorescence: single-grain K-feldspar dating using CCD imaging

Abstract. The success of luminescence dating as a chronological tool in Quaternary science builds upon innovative methodological approaches, providing new insights into past landscapes. Infrared radiofluorescence (IR-RF) on K-feldspar is such an innovative method that was already introduced two decades ago. IR-RF promises considerable extended temporal range and a simple measurement protocol, with more dating applications being published recently. To date, all applications have used multi-grain measurements. Herein, we take the next step by enabling IR-RF measurements on a single grain level. Our contribution introduces spatially resolved infrared radiofluorescence (SR IR-RF) on K-feldspars and intends to make SR IR-RF broadly accessible as a geochronological tool. In the first part of the article, we detail equipment, CCD camera settings and software needed to perform and analyse SR IR-RF measurements. We use a newly developed ImageJ macro to process the image data, identify IR-RF emitting grains and obtain single-grain IR-RF signal curves. For subsequent analysis, we apply the statistical programming environment R and the package Luminescence. In the second part of the article, we test SR IR-RF on two K-feldspar samples. One sample was irradiated artificially; the other sample received a natural dose. The artificially irradiated sample renders results indistinguishable from conventional IR-RF measurements with the photomultiplier tube. The natural sample seems to overestimate the expected dose by ca. 50 % on average. However, it also shows a lower dose component, resulting in ages consistent with the same sample's quartz fraction. Our experiments also revealed an unstable signal background due to our cameras' degenerated cooling system. Besides this technical issue specific to the system we used, SR IR-RF is ready for application. Our contribution provides guidance and software tools for methodological and applied luminescence (dating) studies on single-grain feldspars using radiofluorescence.

Translation, cross-cultural adaptation, and validation of the Leuven Knowledge Questionnaire for congenital heart disease instrument into Brazilian Portuguese

ObjectiveTo translate the Leuven Knowledge Questionnaire for Congenital Heart Disease into Brazilian Portuguese and to validate its psychometric properties with parents and family caregivers of children with congenital heart disease. MethodThis was a six-step methodological study, including the translation, synthesis, back-translation, evaluation of the version translated by the committee of experts, pre-testing, and validation, for which two pilot tests were used including the think-aloud protocol. The content validity index and the frequency of socioeconomic data were calculated in a statistical programming environment. ResultsIn content validation, the instrument showed good applicability among experts, with average content validity index of 0.8–1, while kappa agreement analysis was between 0.76 to 1; both results were considered adequate for validation. ConclusionsThe results suggest reliability among the evaluators, indicating the instrument’s accuracy and the possibility of using it to assess the knowledge of parents and family caregivers about congenital heart disease.

GazeR: A Package for Processing Gaze Position and Pupil Size Data

Eye-tracking is widely used throughout the scientific community, from vision science and psycholinguistics to marketing and human-computer interaction. Surprisingly, there is little consistency and transparency in preprocessing steps, making replicability and reproducibility difficult. To increase replicability, reproducibility, and transparency, a package in R (a free and widely used statistical programming environment) called gazeR was created to read and preprocess two types of data: gaze position and pupil size. For gaze position data, gazeR has functions for reading in raw eye-tracking data, formatting it for analysis, converting from gaze coordinates to areas of interest, and binning and aggregating data. For data from pupillometry studies, the gazeR package has functions for reading in and merging multiple raw pupil data files, removing observations with too much missing data, eliminating artifacts, blink identification and interpolation, subtractive baseline correction, and binning and aggregating data. The package is open-source and freely available for download and installation: https://github.com/dmirman/gazer . We provide step-by-step analyses of data from two tasks exemplifying the package's capabilities.

A descriptive study of racial and ethnic differences of drug overdoses and naloxone administration in Pennsylvania

IntroductionDrug overdose is a significant public health problem, yet little is known about racial/ethnic differences in drug overdose rates and/or in responses to a drug overdose following naloxone administration. This paper examines differences in rates of survivorship, response, revival and administration of naloxone by race and ethnicity among those who experienced a drug overdose in Pennsylvania between January 1, 2018 and December 31, 2019. Spatio-temporal variations in drug overdose locations were examined to facilitate understanding of service development, planning, and delivery of effective treatment need. MethodsTen thousand two hundred and ninety drug overdose incidents were analyzed from the Pennsylvania Overdose Information Network (ODIN). The ODIN is a centralized repository that contains information on drug overdoses victims including age, gender and race/ethnicity, naloxone administrations and survivorship, drug(s) suspected of causing the overdose, victim outcomes (e.g. hospitalizations and arrests) and average naloxone dosage per victim. Between group differences were tested using χ2 -tests of independence. Multivariate logistic regression was used to estimate the predicted probability of survivorship according to victim characteristics. All statistical analyses and mapping were performed using the R statistical programming environment. ResultsAbout eighty-seven percent of drug overdose response victims were white, and seventy-one percent were between the ages of 20–39. White females were more likely to receive an overdose response compared to black or Hispanic females. A non-opioid was indicated more frequently in overdoses involving black victims compared to either whites or Latinos. Latinos and blacks were more likely to survive a drug overdose. However, following naloxone administration, no racial or ethnic differences in survivorship were noted. Differences in responsiveness to naloxone and transitions to care following the drug overdose event were also found. Finally, overdoses among Blacks and Latinos demonstrated a stronger spatial patterning across counties compared to whites. ConclusionsThis study found a significant, disparate impact of race/ethnicity on fatal drug overdoses when naloxone is not administered. Further, individuals who were administered naloxone and subsequently received medical care in a hospital experienced lower drug-related mortality, suggesting that first responders are critical intervention points for individuals in need of medical treatment following a drug overdose. However, while naloxone administration is a necessary first step in the recovery process, longitudinal pathways towards treatment are critical to stem the drug overdose crisis.

Modeling massive spatial datasets using a conjugate Bayesian linear modeling framework

Geographic Information Systems (GIS) and related technologies have generated substantial interest among statisticians with regard to scalable methodologies for analyzing large spatial datasets. A variety of scalable spatial process models have been proposed that can be easily embedded within a hierarchical modeling framework to carry out Bayesian inference. While the focus of statistical research has mostly been directed toward innovative and more complex model development, relatively limited attention has been accorded to approaches for easily implementable scalable hierarchical models for the practicing scientist or spatial analyst. This article discusses how point-referenced spatial process models can be cast as a conjugate Bayesian linear regression that can rapidly deliver inference on spatial processes. The approach allows exact sampling directly (avoids iterative algorithms such as Markov chain Monte Carlo) from the joint posterior distribution of regression parameters, the latent process and the predictive random variables, and can be easily implemented on statistical programming environments such as R.

Adverse events associated with bone-conduction and middle-ear implants: a systematic review.

To review types and frequencies of adverse events (AE) associated with bone-conduction hearing implants (BCHIs) and active middle-ear implants (aMEIs) as reported in the literature. Cochrane, PubMed, and EMBASE libraries were searched for primary articles in English or German language that reported on adverse events following BCHI or aMEI implantation, included at least five patients and were published between 1996 and 2016. Study characteristics, demographics, and counts of adverse events were tabulated and analyzed within the R statistical programming environment. Following assessment of the reporting quality of adverse events, we present a brief guideline that potentially improves AE reporting in this field of research. For the full dataset, we summarize study-level adverse event frequencies in terms of ratio of events to ears (REE) by AE groups and by device. For a subset of studies, we also report cumulative incidence (risk) for minor- and major adverse-events by device and by device groups. Data analyzed in this review show that: (1) the reporting quality of adverse events associated with BCHI and aMEIs is often very low; (2) adverse events associated with BCHI and aMEIs are qualitatively different and not equally frequent among devices; (3) state-of-the-art implantable BCHIs and aMEIs are a safe treatment option for hearing loss.

- Solving the probability regression models by using R programming environment - Case Study For patients Epilepsy in Basra

The technology for dealing with accurate calculations progresses very quickly . and be a major impetus for scientific progress. and the perfect mastery of R in higher levels is necessary for many applications . The R statistical programming environment provides an ideal stage to conduct the study because of its powerful programming capability , graphics and a comprehensive set of statistical functions , it contains more than 11164 packages . The aim is to study the phenomenon of epilepsy and to identify the most important factors affecting patients with epilepsy in the province of Basra. And the cause of this disease of social and economic effects on the patient and his family. and also this study is to solve the probability regression models represented by probit, tobit and logit ,as well as identifying the variables of the study (sex and age) that affect or increase the incidence epilepsy for the data of 2296 patients in Basra. The study design , is the represent by estimating the three probable regression models by probit, tobit and logit for the effect of sex and age factors on the risk of developing epilepsy ,and the tools used is to make statistic program ,then we find the R programming language was give the good and correct answer, Then the statistical analysis using R language in which the written orders are implemented directly without the need to build a complete program to implement the programming statements using the regression function for each probability regression models (Probit, Tobit and Logit) and the results showed that the regression of the probabilistic functions is that both the age factor and the sex factor have a significant effect in the case of the disease in terms of being inpatient or outpatient. This is confirmed by the Wold test. and Also the conclusion shows that functions represented the best representation, which was confirmed by the coefficient of selection as it reached 0.96.

Manipulation, analysis, and visualization of data from the demographic and family health survey with the R program

The Demographic and Family Health Survey (ENDES, in Spanish) is a national population-based survey with representation at the departmental level and area of residence, constituting a source of information on the health status of the Peruvian population. In order to standardize its processing and subsequent reuse by the academic community and other stakeholders, we documented the code for the manipulation, analysis, and visualization of data from the ENDES 2017 health questionnaire, through an example on the prevalence of hypertension and obesity, using the R statistical programming environment and language. The R code is presented and detailed sequentially, as well as the theoretical support of the survey structure for the manipulation of databases, considering that the complex structure of the ENDES could be a potential barrier faced by researchers. Finally, this example can serve as a basis for generating further studies based on the ENDES that are relevant to public health decision-making.

QueryMed: Semantic Web functions for linking pharmacological and medical knowledge to data.

In public health research and more precisely in the reuse of electronic health data, selecting patients, identifying specific events and interpreting results typically requires biomedical knowledge. The queryMed R package aims to facilitate the integration of medical and pharmacological knowledge stored in formats compliant with the Linked Data paradigm (e.g. OWL ontologies and RDF datasets) into the R statistical programming environment. We show how it allowed us to identify all the drugs prescribed for critical limb ischemia (CLI) and also to detect one contraindicated prescription for one patient by linking a medical database of 1003 CLI patients to ontologies. queryMed is readily usable for medical data mappings and enrichment. Sources, R vignettes and test data are available on GitHub (https://github.com/yannrivault/queryMed) and are archived on Zenodo (https://doi.org/10.5281/zenodo.1323481).

RMyCoPortal - an R package to interface with the Mycology Collections Portal.

The understanding of the biodiversity and biogeographical distribution of fungi is still limited. The small number of online databases and the large effort required to access existing data have prevented their use in research articles. The Mycology Collections Portal was established in 2012 to help alleviate these issues and currently serves data online for over 4.3 million fungal records. However, the current process for accessing the data through the web interface is manual, therefore slow, and precludes the extensive use of the existing datasets. Here we introduce the software package rMyCoPortal, which allows users rapid, automated access to the data. rMyCoPortal makes data readily available for further computations and analyses in the open source statistical programming environment R. We will demonstrate the core functions of the package, and how rMyCoPortal can be employed to obtain fungal data that can be used to address basic research questions. rMyCoPortal is a free and open-source R package, available via GitHub.

HomoplasyFinder: a simple tool to identify homoplasies on a phylogeny.

A homoplasy is a nucleotide identity resulting from a process other than inheritance from a common ancestor. Importantly, by distorting the ancestral relationships between nucleotide sequences, homoplasies can change the structure of the phylogeny. Homoplasies can emerge naturally, especially under high selection pressures and/or high mutation rates, or be created during the generation and processing of sequencing data. Identification of homoplasies is critical, both to understand their influence on the analyses of phylogenetic data and to allow an investigation into how they arose. Here we present HomoplasyFinder, a java application that can be used as a stand-a-lone tool or within the statistical programming environment R. Within R and Java, HomoplasyFinder is shown to be able to automatically, and quickly, identify any homoplasies present in simulated and real phylogenetic data. HomoplasyFinder can easily be incorporated into existing analysis pipelines, either within or outside of R, allowing the user to quickly identify homoplasies to inform downstream analyses and interpretation.

Knowledge of professional healthcare providers about sickle cell disease: Impact of a distance education course

ObjectiveTo assess the impact of the distance education course “Sickle Cell Disease: Primary Health Care Line” on knowledge acquisition of professional healthcare providers. MethodsA cross-sectional study was conducted with a quantitative approach at the Educational and Support Center for Hemoglobinopathies (Cehmob-MG), state of Minas Gerais, Brazil, in 2016. One hundred and fifty-three out of 300 professional healthcare providers were invited to participate in the proposed distance course. Of the participating professional healthcare providers, 72 (47%) successfully concluded the course (Group A), whereas 81 (53%) did not complete their course assignments and did not meet the minimum requirements for regular attendance (Group B). Knowledge acquisition was assessed with the Knowledge of Sickle Cell Disease Instrument, DFConhecimento, applied using the web tool eSurv. Univariate analysis by Poisson regression was employed to assess the influence of sociodemographic variables on the DFConhecimento score and to select variables to compose the initial multivariate regression model (p-value<0.20). The analysis was performed in the statistical programming environment R. ResultsThe average score was 9.76 for Group A and 6.54 for Group B. The two groups were considered statistically different (p-value<0.05) for all items with the proportion of correct items being greater in Group A. Professional healthcare providers who concluded the course had a significantly higher DFConhecimento score (45%) when compared to those who did not successfully conclude the course. ConclusionParticipation in a distance education course on sickle cell disease had a positive impact on the acquisition of knowledge about the disease by professional healthcare providers.

T106. IMPROVING PSYCHIATRIC DIAGNOSIS BY ADDING MOTOR FUNCTION NEXT TO MENTAL HEALTH FUNCTION: A NETWORK APPROACH

BackgroundCurrently, the predictive value of psychiatric diagnosis is inadequate compared to other medical fields. It has been suggested that the use of a network model might aid in acquiring new insights into the underlying connections between symptoms (Bringmann et al., 2013). In addition, previous research (Bakker et al., 2012) has revealed associations between dysregulated mental- and motor function. As such, the network graphs might be enhanced by adding non-mental factors.MethodsBaseline data from a 4-year prospective naturalistic study (Bakker et al., 2012) was used to obtain data about 207 psychiatric long-stay patients. (i) Drug-induced movement disorders: tardive dystonia (TD), akathisia, parkinsonism, and dyskinesia. (ii) ratings of the clinical global impression-schizophrenia (CGI) scale, and (iii) age and total defined daily dose to account for potential confounders. Statistical programming environment R (Epskamsp, Cramer, Waldorp & Borsboom, 2012) was used to visualise several psychopathology-severity networks.ResultsInterpretation of the graphs is based on the “centrality” of the symptoms. Centrality indicates the influence of a symptom on the network. Parkinsonism scored a low centrality score in graphs depicting high psychopathology in contrast with the other levels. Dyskinesia scored a low centrality score in medium psychopathology contrary to the other levels. The network graphs show a consistent positive correlation between age and parkinsonism (0.25, 0.53, and 0.19 for low, medium, and high psychopathology, respectively.), and a negative correlation between age and akathisia (-0.32, -0.47, and -0.21, respectively). High severities of psychopathology negatively correlated with parkinsonism (-0.16) and positively correlated with high levels of TD (0.33).DiscussionThe usage of a network model including motor factors has provided useful information to take into consideration when examining psychopathology of a patient. TD and parkinsonism draw the most attention. More research with the dataset, combined with further developing the network architecture technique is needed to accurately map motor- and mental factors.