Mindfulness-Based Stress Reduction for Symptom Management in Older Individuals with HIV-Associated Neurocognitive Disorder.

The growing number of people aging with HIV represents a group vulnerable to the symptom burdens of HIV-associated neurocognitive disorder (HAND). Among younger groups, Mindfulness-Based Stress Reduction (MBSR) has been shown to help people living with HIV manage HIV-related and other life stress, and although there is some theoretical and empirical evidence that it may be effective among those with cognitive deficits, the approach has not been studied in older populations with HAND. Participants (n = 180) 55 years or older with HIV and cognitive impairment were randomly assigned to either an 8-week MBSR arm or a waitlist control. We assessed the impact of MBSR compared to a waitlist control on psychological outcomes [stress, anxiety, depression, and quality of life (QOL)] and cognitive metrics (e.g., speed of information processing, working memory, attention, impulsivity) measured at baseline, immediately post intervention (8 weeks) and one month later (16 weeks). Intent to treat analyses showed significant improvement in the MBSR group compared to control on symptoms of depression from baseline to 8 weeks, however, the difference was not sustained at 16 weeks. The MBSR group also showed improvement in perceived QOL from baseline to 16 weeks compared to the waitlist control group. Cognitive performance did not differ between the two treatment arms. MBSR shows promise as a tool to help alleviate the symptom burden of depression and low QOL in older individuals living with HAND and future work should address methods to better sustain the beneficial impact on depression and QOL.

Phase behavior of patchy colloids confined in patchy porous media.

A simple model for functionalized disordered porous media is proposed and the effects of confinement on self-association, percolation and phase behavior of a fluid of patchy particles are studied. The media are formed by randomly distributed hard-sphere obstacles fixed in space and decorated by a certain number of off-center square-well sites. The properties of the fluid of patchy particles, represented by the fluid of hard spheres each bearing a set of the off-center square-well sites, are studied using an appropriate combination of the scaled particle theory for the porous media, Wertheim's thermodynamic perturbation theory, and Flory-Stockmayer theory. To assess the accuracy of the theory a set of computer simulations have been performed. In general, predictions of the theory appeared to be in good agreement with the computer simulation results. Confinement and competition between the formation of bonds connecting the fluid particles, and connecting fluid particles and obstacles of the matrix, gave rise to a re-entrant phase behavior with three critical points and two separate regions of the liquid-gas phase coexistence.

Development of Heteroatomic Constant Potential Method with Application to MXene-Based Supercapacitors.

We describe a method for modeling constant-potential charges in heteroatomic electrodes, keeping pace with the increasing complexity of electrode composition and nanostructure in electrochemical research. The proposed "heteroatomic constant potential method" (HCPM) uses minimal added parameters to handle differing electronegativities and chemical hardnesses of different elements, which we fit to density functional theory (DFT) partial charge predictions in this paper by using derivative-free optimization. To demonstrate the model, we performed molecular dynamics simulations using both HCPM and conventional constant potential method (CPM) for MXene electrodes with Li-TFSI/AN (lithium bis(trifluoromethane sulfonyl)imide/acetonitrile)-based solvent-in-salt electrolytes. Although the two methods show similar accumulated charge storage on the electrodes, the results indicated that HCPM provides a more reliable depiction of electrode atom charge distribution and charge response compared with CPM, accompanied by increased cationic attraction to the MXene surface. These results highlight the influence of elemental composition on electrode performance, and the flexibility of our HCPM opens up new avenues for studying the performance of diverse heteroatomic electrodes including other types of MXenes, two-dimensional materials, metal-organic frameworks (MOFs), and doped carbonaceous electrodes.

E(n) Equivariant Graph Neural Network for Learning Interactional Properties of Molecules.

We have developed a multi-input E(n) equivariant graph convolution-based model designed for the prediction of chemical properties that result from the interaction of heterogeneous molecular structures. By incorporating spatial features and constraining the functions learned from these features to be equivariant to E(n) symmetries, the interactional-equivariant graph neural network (IEGNN) can efficiently learn from the 3D structure of multiple molecules. To verify the IEGNN's capability to learn interactional properties, we tested the model's performance on three molecular data sets, two of which are curated in this study and made publicly available for future interactional model benchmarking. To enable the loading of these data sets, an open-source data structure based on the PyTorch Geometric library for batch loading multigraph data points is also created. Finally, the IEGNN's performance on a data set consisting of an unknown interactional relationship (the frictional properties resulting between monolayers with variable composition) is examined. The IEGNN model developed was found to have the lowest mean absolute percent error for the predicted tribological properties of four of the six data sets when compared to previous methods.

Rapid Remission of Chronic, Progressive Conditions and Reducing Polypharmacy by Utilizing Lifestyle Therapy to Target Insulinemic Lifestyle Components.

This case study provides evidence that homeostatic control in a patient with hyperglycemia and other metabolic abnormalities associated with insulin resistance can be rapidly restored utilizing lifestyle therapy. The patient, an overweight, non-Hispanic White male aged 70 years, had been medicated for hypertension and Type 2 diabetes mellitus for 12 years. From baseline during 21 months of follow-up, HbA1c decreased from 6.6% to 5.4%, mean fasting glucose decreased from 125 mg/dL to 94 mg/dL, blood pressure decreased from 130/85 mmHg to 100/64 mmHg, estimated glomerular filtration rate increased from 50 ml/min/1.73m² to 58 ml/min/1.73m², waist circumference decreased from 118.8 cm to 90.8 cm, and liver function improved with aspartate transaminase decreasing from 44 IU/L to 17 IU/L and alanine transaminase decreasing from 34 IU/L to 21 IU/L. Each of these metabolic corrections was observed while eliminating respective disease-specific medications. These metabolic improvements were achieved using primary recommended lifestyle therapy specifically targeting known insulinemic lifestyle components. This case study shows that the utilization of primary recommended, ongoing lifestyle therapy targeting insulinemic lifestyle components can rapidly improve markers of insulin resistance and normalize abnormal laboratory values while eliminating the risk of polypharmacy and the direct costs of medication.

PROMIS: Physical, Mental and Social Health Outcomes Improve From Before to Early After LVAD Implant: Findings From the Mechanical Circulatory Support: Measures of Adjustment and Quality of Life (MCS A-QOL) Study.

Study participants (n = 272) completed 12 Patient-Reported Outcomes Measurement Information System (PROMIS) physical, mental and social health measures (questionnaires) prior to implantation of a left ventricular assist device (LVAD) and again at 3 and 6 months postimplant. All but 1 PROMIS measure demonstrated significant improvement from pre-implant to 3 months; there was little change between 3 and 6 months. Because PROMIS measures were developed in the general population, patients with an LVAD, their caregivers and their clinicians can interpret the meaning of PROMIS scores in relation to the general population, helping them to monitor a return to normalcy in everyday life.

Grandmothers residing with grandchildren: Social determinants of health, health behaviors, and health outcomes.

The purpose of this study was to explore the associations between social determinants of health, health behaviors, and physical and mental health among African American and Hispanic caregiving grandmothers. We use cross-sectional secondary data from the Chicago Community Adult Health Study, originally designed to understand the health of individual households based on residential context. In a multivariate regression model, discrimination, parental stress, and physical health problems were significantly associated with depressive symptoms in caregiving grandmothers. Considering the multiple sources of stress experienced by this grandmother sample, researchers should develop and strengthen contextually relevant interventions for improving the health of caregiving grandmothers. Healthcare providers must be equipped with skills to address caregiving grandmothers' unique needs related to stress. Finally, policy makers should promote the development of legislation that can positively influence caregiving grandmothers and their families. Expanding the lens through which caregiving grandmothers living in minoritized communities are viewed can catalyze meaningful change.

MoSDeF-GOMC: Python Software for the Creation of Scientific Workflows for the Monte Carlo Simulation Engine GOMC.

MoSDeF-GOMC is a python interface for the Monte Carlo software GOMC to the Molecular Simulation Design Framework (MoSDeF) ecosystem. MoSDeF-GOMC automates the process of generating initial coordinates, assigning force field parameters, and writing coordinate (PDB), connectivity (PSF), force field parameter, and simulation control files. The software lowers entry barriers for novice users while allowing advanced users to create complex workflows that encapsulate simulation setup, execution, and data analysis in a single script. All relevant simulation parameters are encoded within the workflow, ensuring reproducible simulations. MoSDeF-GOMC's capabilities are illustrated through a number of examples, including prediction of the adsorption isotherm for CO2 in IRMOF-1, free energies of hydration for neon and radon over a broad temperature range, and the vapor-liquid coexistence curve of a four-component surrogate for the jet fuel S-8. The MoSDeF-GOMC software is available on GitHub at https://github.com/GOMC-WSU/MoSDeF-GOMC.

Validity of Patient-Reported Outcomes Measurement Information System Physical, Mental, and Social Health Measures After Left Ventricular Assist Device Implantation and Implications for Patient Care.

BACKGROUND: A better understanding is needed of the burdens and benefits of left ventricular assist device (LVAD) implantation on patients' physical, mental, and social well-being. The purpose of this report was to evaluate the validity of Patient-Reported Outcomes Measurement Information System (PROMIS) measures for LVAD patients and to estimate clinically important score differences likely to have implications for patient treatment or care. METHODS: Adults from 12 sites across all US geographic regions completed PROMIS measures ≥3 months post-LVAD implantation. Other patient-reported outcomes (eg, Kansas City Cardiomyopathy Questionnaire-12 item), clinician ratings, performance tests, and clinical adverse events were used as validity indicators. Criterion and construct validity and clinically important differences were estimated with Pearson correlations, ANOVA methods, and Cohen d effect sizes. RESULTS: Participants' (n=648) mean age was 58 years, and the majority were men (78%), non-Hispanic White people (68%), with dilated cardiomyopathy (55%), long-term implantation strategy (57%), and New York Heart Association classes I and II (54%). Most correlations between validity indicators and PROMIS measures were medium to large (≥0.3; p<0.01). Most validity analyses demonstrated medium-to-large effect sizes (≥0.5) and clinically important differences in mean PROMIS scores (up to 14.8 points). Ranges of minimally important differences for 4 PROMIS measures were as follows: fatigue (3-5 points), physical function (2-3), ability to participate in social roles and activities (3), and satisfaction with social roles and activities (3-5). CONCLUSIONS: The findings provide convincing evidence for the relevance and validity of PROMIS physical, mental, and social health measures in patients from early-to-late post-LVAD implantation. Findings may inform shared decision-making when patients consider treatment options. Patients with an LVAD, their caregivers, and their clinicians should find it useful to interpret the meaning of their PROMIS scores in relation to the general population, that is, PROMIS may help to monitor a return to normalcy in everyday life.

Intergenerational transmission of the effects of maternal exposure to childhood maltreatment in the USA: a retrospective cohort study.

BACKGROUND: Childhood maltreatment is associated with adverse health outcomes and this risk can be transmitted to the next generation. We aimed to investigate the association between exposure to maternal childhood maltreatment and common childhood physical and mental health problems, neurodevelopmental disorders, and related comorbidity patterns in offspring. METHODS: We conducted a retrospective cohort study using data from the Environmental influences on Child Health Outcomes (ECHO) Program, which was launched to investigate the influence of early life exposures on child health and development in 69 cohorts across the USA. Eligible mother-child dyads were those with available data on maternal childhood maltreatment exposure and at least one child health outcome measure (autism spectrum disorder, attention-deficit hyperactivity disorder [ADHD], internalising problems, obesity, allergy, and asthma diagnoses). Maternal history of childhood maltreatment was obtained retrospectively from the Adverse Childhood Experiences or Life Stressor Checklist questionnaires. We derived the prevalence of the specified child health outcome measures in offspring across childhood and adolescence by harmonising caregiver reports and other relevant sources (such as medical records) across cohorts. Child internalising symptoms were assessed using the Child Behavior Checklist. Associations between maternal childhood maltreatment and childhood health outcomes were measured using a series of mixed-effects logistic regression models. Covariates included child sex (male or female), race, and ethnicity; maternal and paternal age; maternal education; combined annual household income; maternal diagnosis of depression, asthma, ADHD, allergy, or autism spectrum disorder; and maternal obesity. Two latent class analyses were conducted: to characterise patterns of comorbidity of child health outcomes; and to characterise patterns of co-occurrence of childhood maltreatment subtypes. We then investigated the association between latent class membership and maternal childhood maltreatment and child health outcomes, respectively. FINDINGS: Our sample included 4337 mother-child dyads from 21 longitudinal cohorts (with data collection initiated between 1999 and 2016). Of 3954 mothers in the study, 1742 (44%) had experienced exposure to abuse or neglect during their childhood. After adjustment for confounding, mothers who experienced childhood maltreatment were more likely to have children with internalising problems in the clinical range (odds ratio [OR] 2·70 [95% CI 1·95-3·72], p<0·0001), autism spectrum disorder (1·70 [1·13-2·55], p=0·01), ADHD (2·09 [1·63-2·67], p<0·0001), and asthma (1·54 [1·34-1·77], p<0·0001). In female offspring, maternal childhood maltreatment was associated with a higher prevalence of obesity (1·69 [1·17-2·44], p=0·005). Children of mothers exposed to childhood maltreatment were more likely to exhibit a diagnostic pattern characterised by higher risk for multimorbidity. Exposure to multiple forms of maltreatment across all subtypes of maternal childhood maltreatment was associated with the highest risk increases for most offspring health outcomes, suggesting a dose-response relationship. INTERPRETATION: Our findings suggest that maternal childhood maltreatment experiences can be a risk factor for disease susceptibility in offspring across a variety of outcomes and emphasise the need for policies focusing on breaking the intergenerational transmission of adversity. FUNDING: Environmental influences on Child Health Outcomes Program, Office of the Director, National Institutes of Health.

Structure-Dynamics Interrelation Governing Charge Transport in Cosolvated Acetonitrile/LiTFSI Solutions.

Concentrated ionic solutions present a potential improvement for liquid electrolytes. However, their conductivity is limited by high viscosities, which can be attenuated via cosolvation. This study employs a series of experiments and molecular dynamics simulations to investigate how different cosolvents influence the local structure and charge transport in concentrated lithium bis(trifluoromethane-sulfonyl)imide (LiTFSI)/acetonitrile solutions. Regardless of whether the cosolvent's dielectric constant is low (for toluene and dichloromethane), moderate (acetone), or high (methanol and water), they preserve the structural and dynamical features of the cosolvent-free precursor. However, the dissimilar effects of each case must be individually interpreted. Toluene and dichloromethane reduce the conductivity by narrowing the distribution of Li+-TFSI- interactions and increasing the activation energies for ionic motions. Methanol and water broaden the distributions of Li+-TFSI- interactions, replace acetonitrile in the Li+ solvation, and favor short-range Li+-Li+ interactions. Still, these cosolvents strongly interact with TFSI-, leading to conductivities lower than that predicted by the Nernst-Einstein relation. Finally, acetone preserves the ion-ion interactions from the cosolvent-free solution but forms large solvation complexes by joining acetonitrile in the Li+ solvation. We demonstrate that cosolvation affects conductivity beyond simply changing viscosity and provide fairly unexplored molecular-scale perspectives regarding structure/transport phenomena relation in concentrated ionic solutions.

Exploring Retention, Usage, and Efficacy of Web-Based Delivery of Positive Emotion Regulation Skills During the COVID-19 Pandemic.

COVID-19 prompted distress and increased reliance on digital mental health interventions, which previously demonstrated low rates of retention and adherence. This single-arm trial evaluated whether self-guided, web-based, positive affect regulation skills (PARK) were engaging and associated with changes in well-being during the pandemic. Over 6 weeks, PARK delivers brief lessons and practices in skills designed to increase positive emotions: noticing positive events, savoring, gratitude, mindfulness, positive reappraisal, personal strengths, and self-compassion. Patient-Reported Outcome Measurement Information System (PROMIS) computer adaptive tests of anxiety, depression, social isolation, positive affect, and meaning and purpose were administered at baseline, post-intervention, and 6 months after baseline. Retention and usage of PARK were measured by the web-based assessment and intervention platforms. The sample (n = 616) was predominantly female, non-Hispanic, white, and well-educated. Of those who completed baseline, only 42% completed a follow-up assessment; 30% never logged into PARK. Among those who did, 86% used at least one skill, but only 14% completed PARK. Across retention and usage metrics, older age predicted more engagement. In multivariable models, people of color and people with greater baseline anxiety were more likely to complete PARK. All well-being indicators improved over time, with greater improvements in anxiety and social isolation among participants who accessed at least one PARK skill compared to those who did not. Retention and usage rates mirrored pre-pandemic trends, but within this select sample, predictors of engagement differed from prior research. Findings underscore the need for additional efforts to ensure equitable access to digital mental health interventions and research. Trials registration: NCT04367922.

Universal Ligands for Dispersion of Two-Dimensional MXene in Organic Solvents.

Ligands can control the surface chemistry, physicochemical properties, processing, and applications of nanomaterials. MXenes are the fastest growing family of two-dimensional (2D) nanomaterials, showing promise for energy, electronic, and environmental applications. However, complex oxidation states, surface terminal groups, and interaction with the environment have hindered the development of organic ligands suitable for MXenes. Here, we demonstrate a simple, fast, scalable, and universally applicable ligand chemistry for MXenes using alkylated 3,4-dihydroxy-l-phenylalanine (ADOPA). Due to the strong hydrogen-bonding and π-electron interactions between the catechol head and surface terminal groups of MXenes and the presence of a hydrophobic fluorinated alkyl tail compatible with organic solvents, the ADOPA ligands functionalize MXene surfaces under mild reaction conditions without sacrificing their properties. Stable colloidal solutions and highly concentrated liquid crystals of various MXenes, including Ti2CTx, Nb2CTx, V2CTx, Mo2CTx, Ti3C2Tx, Ti3CNTx, Mo2TiC2Tx, Mo2Ti2C3Tx, and Ti4N3Tx, have been produced in various organic solvents. Such products offer excellent electrical conductivity, improved oxidation stability, and excellent processability, enabling applications in flexible electrodes and electromagnetic interference shielding.

Controlling the Ion Transport Number in Solvent-in-Salt Solutions.

Solvent-in-salt (SIS) systems present promising materials for the next generation of energy storage applications. The ion dynamics is significantly different in these systems from that of ionic liquids and diluted salt solutions. In this study, we analyze the ion dynamics of two salts, Li-TFSI and Li-FSI, in highly concentrated aqueous and acetonitrile solutions. We performed high-frequency dielectric measurements covering the range of up to 50 GHz and molecular dynamics simulations. The analysis of the conductivity spectra provides the characteristic crossover time between individual charge rearrangements and the normal charge diffusion regime resulting in DC conductivity. Analysis revealed that the onset of normal charge diffusion occurs at the scale of ∼1.5-3.5 Å, comparable to the average distance between the ions. Based on the idea of momentum conservation, distinct ion correlations were estimated experimentally and computationally. The analysis revealed that cation-anion correlations can be suppressed by changing the solvent concentration in SIS systems, leading to an increase of the light ion (Li+ in our case) transport number. This discovery suggests a way for improving the light cation transport number in SIS systems by tuning the solvent concentration.

NMR and Theoretical Study of In-Pore Diffusivity of Ionic Liquid-Solvent Mixtures.

Despite having a lower energy density than common batteries, electric double-layer capacitors (EDLCs) offer several advantages for high-power applications, including high power density, quick charge and discharge time, and long cycle life. Room-temperature ionic liquids (RTILs) have been intensely studied as promising electrolytes for applications in ELDCs because of their wide potential window, low volatility, as well as thermal and chemical stability. The main deficiency of neat RTILs in such applications is the sluggish diffusivity, which restricts the EDLCs' power density. To alleviate the slow diffusivity, RTILs can be used in a mixture with organic solvents. In this study, we applied two-dimensional exchange nuclear magnetic resonance spectroscopy (2D EXSY NMR) and molecular dynamics (MD) simulations to investigate the diffusivity of anions of an RTIL, namely, 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (BMIM+-TFSI-), dissolved in five different organic solvents, in the micropores of activated carbon. We determined that the relative concentrations of ions in solutions in the micropores were higher than those in the bulk solutions and were also solvent-dependent. The ion diffusivities in the pores were found to be almost 2 orders of magnitude slower than in the bulk solutions, with methanol showing the largest relative disparity. These results suggested that the interactions of solvents with the activated carbon are critical not only to the power density of EDLCs but also to the energy density. The comparisons of ion diffusivities between the experiments and the MD simulations suggest the need to consider also the surface functionalities of activated carbon for the simulation of ion diffusion in the micropores of activated carbon.

High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning.

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.

Direct Correlation of the Salt-Reduced Diffusivities of Organic Solvents with the Solvent's Mole Fraction.

Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in organic solvents (especially propylene carbonate) has demonstrated extraordinary pseudocapacitive performance as an electrolyte in the supercapacitor configuration ( Nat. Energy 2019, 4, 241-248). However, the influence of the solvated ions on the diffusivity of the solvent molecules is yet to be understood. We examine the impact of LiTFSI on the diffusivity in five organic solvents: acetonitrile (ACN), tetrahydrofuran (THF), methanol (MeOH), dimethyl sulfoxide (DMSO), and propylene carbonate (PC) using a combination of neutron scattering, conductivity measurements, and molecular dynamics simulations. The extent of the diffusivity reduction in the concentration regime of ≤1 M directly correlates with the solvent mole fraction at which the solvation shells around Li+ ions are of similar size in all the solvents, resulting in a universal ∼50% reduction in the solvent diffusivity. These results provide guidance for formulation of the new electrolytes to enhance the performance of energy storage devices.

Investigation of Multilayered Structures of Ionic Liquids on Graphite and Platinum Using Atomic Force Microscopy and Molecular Simulations.

The molecular-level orientation and structure of ionic liquids (ILs) at liquid-solid interfaces are significantly different than in the bulk. The interfacial ordering influences both IL properties, such as dielectric constants and viscosity, and their efficacy in devices, such as fuel cells and electrical capacitors. Here, we report the layered structures of four ILs on unbiased, highly ordered pyrolytic graphite (HOPG) and Pt(111) surfaces, as determined by atomic force microscopy. The ILs investigated are 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([emim][Tf2N]), 1-ethyl-3-methylimidazolium perfluorobutylsulfonate ([emim][C4F9SO3]), 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene bis(trifluoromethylsulfonyl)imide ([MTBD][Tf2N]), and 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene perfluorobutylsulfonate ([MTBD][C4F9SO3]). Molecular dynamics simulations provide complementary information on the position and orientation of the ions. These ILs form a cation layer at the IL-solid interface, followed by a layer of anions. [Emim]+ and [MTBD]+ have similar orientations at the surface, but [MTBD]+ forms a thinner layer compared to [emim]+ on both HOPG and Pt(111). In addition, [Tf2N]- shows stronger interactions with Pt(111) surfaces than [C4F9SO3]-.

Linking the Child Behavior Checklist to the Strengths and Difficulties Questionnaire.

The Child Behavior Checklist (CBCL) and Strengths and Difficulties Questionnaire (SDQ) both measure emotional and behavioral problems in children and adolescents, and scores on the two instruments are highly correlated. When administrative needs compel practitioners to change the instrument used or data from the two measures are combined to perform pooled analyses, it becomes necessary to compare scores on the two instruments. To enable such comparisons, we score linked three domains (Internalizing, Externalizing, and Total Problems) of the CBCL and SDQ in three age groups spanning 2-17 years. After assessing linking assumptions, we compared item response theory (IRT) and equipercentile linking methods to identify the most statistically justifiable link, ultimately selecting equipercentile linking with loglinear smoothing due to its minimal bias and the ability to link raw SDQ scores with both T-scores and raw scores from the CBCL. We derived crosswalk conversion tables to convert scores on one measure to the metric of the other and discuss the use of these tables in research and practice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).