Measurement bias in caregiver-report of early childhood behavior problems across demographic factors in an ECHO-wide diverse sample.

Background: Research and clinical practice rely heavily on caregiver-report measures, such as the Child Behavior Checklist 1.5-5 (CBCL/1.5-5), to gather information about early childhood behavior problems and to screen for child psychopathology. While studies have shown that demographic variables influence caregiver ratings of behavior problems, the extent to which the CBCL/1.5-5 functions equivalently at the item level across diverse samples is unknown. Methods: Item-level data of CBCL/1.5-5 from a large sample of young children (N = 9087) were drawn from 26 cohorts in the Environmental influences on Child Health Outcomes program. Factor analyses and the alignment method were applied to examine measurement invariance (MI) and differential item functioning (DIF) across child (age, sex, bilingual status, and neurodevelopmental disorders), and caregiver (sex, education level, household income level, depression, and language version administered) characteristics. Child race was examined in sensitivity analyses. Results: Items with the most impactful DIF across child and caregiver groupings were identified for Internalizing, Externalizing, and Total Problems. The robust item sets, excluding the high DIF items, showed good reliability and high correlation with the original Internalizing and Total Problems scales, with lower reliability for Externalizing. Language version of CBCL administration, education level and sex of the caregiver respondent showed the most significant impact on MI, followed by child age. Sensitivity analyses revealed that child race has a unique impact on DIF over and above socioeconomic status. Conclusions: The CBCL/1.5-5, a caregiver-report measure of early childhood behavior problems, showed bias across demographic groups. Robust item sets with less DIF can measure Internalizing and Total Problems equally as well as the full item sets, with slightly lower reliability for Externalizing, and can be crosswalked to the metric of the full item set, enabling calculation of normed T scores based on more robust item sets.

Delay epidemic models determined by latency, infection, and immunity duration.

We propose new single and two-strain epidemic models represented by systems of delay differential equations and based on the number of newly exposed individuals. Transitions between exposed, infectious, recovered, and back to susceptible compartments are determined by the corresponding time delays. Existence and positiveness of solutions are proved. Reduction of delay differential equations to integral equations allows the analysis of stationary solutions and their stability. In the case of two strains, they compete with each other, and the strain with a larger individual basic reproduction number dominates the other one. However, if the basic reproduction number exceeds some critical values, stationary solution loses its stability resulting in periodic time oscillations. In this case, both strains are present and their dynamics is not completely determined by the basic reproduction numbers but also by other parameters. The results of the work are illustrated by comparison with data on seasonal influenza.

A framework for testing non-inferiority in a three-arm, sequential, multiple assignment randomized trial.

Sequential multiple assignment randomized trial design is becoming increasingly used in the field of precision medicine. This design allows comparisons of sequences of adaptive interventions tailored to the individual patient. Superiority testing is usually the initial goal in order to determine which embedded adaptive intervention yields the best primary outcome on average. When direct superiority is not evident, yet an adaptive intervention poses other benefits, then non-inferiority testing is warranted. Non-inferiority testing in the sequential multiple assignment randomized trial setup is rather new and involves the specification of non-inferiority margin and other important assumptions that are often unverifiable internally. These challenges are not specific to sequential multiple assignment randomized trial and apply to two-arm non-inferiority trials that do not include a standard-of-care (or placebo) arm. To address some of these challenges, three-arm non-inferiority trials that include the standard-of-care arm are proposed. However, methods developed so far for three-arm non-inferiority trials are not sequential multiple assignment randomized trial-specific. This is because apart from embedded adaptive interventions, sequential multiple assignment randomized trial typically does not include a third standard-of-care arm. In this article, we consider a three-arm sequential multiple assignment randomized trial from an National Institutes of Health-funded study of symptom management strategies among people undergoing cancer treatment. Motivated by that example, we propose a novel data analytic method for non-inferiority testing in the framework of three-arm sequential multiple assignment randomized trial for the first time. Sample size and power considerations are discussed through extensive simulation studies to elucidate our method.

Survivorship Care for Women Living With Ovarian Cancer: Protocol for a Randomized Controlled Trial.

BACKGROUND: Ovarian cancer ranks 12th in cancer incidence among women in the United States and 5th among causes of cancer-related death. The typical treatment of ovarian cancer focuses on disease management, with little attention given to the survivorship needs of the patient. Qualitative work alludes to a gap in survivorship care; yet, evidence is lacking to support the delivery of survivorship care for individuals living with ovarian cancer. We developed the POSTCare survivorship platform with input from survivors of ovarian cancer and care partners as a means of delivering patient-centered survivorship care. This process is framed by the chronic care model and relevant behavioral theory. OBJECTIVE: The overall goal of this study is to test processes of care that support quality of life (QOL) in survivorship. The specific aims are threefold: first, to test the efficacy of the POSTCare platform in supporting QOL, reducing depressive symptom burden, and reducing recurrence worry. In our second aim, we will examine factors that mediate the effect of the intervention. Our final aim focuses on understanding aspects of care platform design and delivery that may affect the potential for dissemination. METHODS: We will enroll 120 survivors of ovarian cancer in a randomized controlled trial and collect data at 12 and 24 weeks. Each participant will be randomized to either the POSTCare platform or the standard of care process for survivorship. Our population will be derived from 3 clinics in Texas; each participant will have received some combination of treatment modalities; continued maintenance therapy is not exclusionary. RESULTS: We will examine the impact of the POSTCare-O platform on QOL at 12 weeks after intervention as the primary end point. We will look at secondary outcomes, including depressive symptom burden, recurrence anxiety, and physical symptom burden. We will identify mediators important to the impact of the intervention to inform revisions of the intervention for subsequent studies. Data collection was initiated in November 2023 and will continue for approximately 2 years. We expect results from this study to be published in early 2026. CONCLUSIONS: This study will contribute to the body of survivorship science by testing a flexible platform for survivorship care delivery adapted for the specific survivorship needs of patients with ovarian cancer. The completion of this project will contribute to the growing body of science to guide survivorship care for persons living with cancer. TRIAL REGISTRATION: ClinicalTrials.gov NCT05752448; https://clinicaltrials.gov/study/NCT05752448. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48069.

Study protocol for clinical trial of the FIT Families multicomponent obesity intervention for African American adolescents and their caregivers: Next step from the ORBIT initiative.

INTRODUCTION: This study will test the effectiveness of FIT Families (FIT), a multicomponent family-based behavioural intervention, against a credible attention control condition, Home-Based Family Support (HBFS). This protocol paper describes the design of a randomised clinical trial testing the efficacy of the FIT intervention. The protocol will assess the efficacy of FIT to improve health status in African American adolescents with obesity (AAAO) and their primary caregivers on primary (percent body fat) and secondary (physical activity, metabolic control, weight loss) outcomes and its cost-effectiveness. METHODS: 180 youth/caregiver dyads are randomised into FIT or HBFS, stratified by age, gender and baseline per cent overweight. The proposed study follows a two condition (FIT, HBFS) by four assessment time points. Tests will be conducted to identify potential relationship of baseline demographic and clinical variables to our dependent variables and see whether they are balanced between groups. It is hypothesised that youth/caregiver dyads randomised to FIT will show significantly greater reductions in percent body fat over a 12-month follow-up period compared with AAAO receiving HBFS. Preliminary findings are expected by November 2023. ETHICS: This protocol received IRB approval from the Medical University of South Carolina (Pro00106021; see 'MUSC IRB 106021 Main Approval.doxc' in online supplemental materials). DISSEMINATION: Dissemination activities will include summary documents designed for distribution to the broader medical community/family audience and submission of manuscripts, based on study results, to relevant peer-reviewed scientific high-impact journals. TRIAL REGISTRATION NUMBER: NCT04974554.

Understanding the implications of under-reporting, vaccine efficiency and social behavior on the post-pandemic spread using physics informed neural networks: A case study of China.

In late 2019, the emergence of COVID-19 in Wuhan, China, led to the implementation of stringent measures forming the zero-COVID policy aimed at eliminating transmission. Zero-COVID policy basically aimed at completely eliminating the transmission of COVID-19. However, the relaxation of this policy in late 2022 reportedly resulted in a rapid surge of COVID-19 cases. The aim of this work is to investigate the factors contributing to this outbreak using a new SEIR-type epidemic model with time-dependent level of immunity. Our model incorporates a time-dependent level of immunity considering vaccine doses administered and time-post-vaccination dependent vaccine efficacy. We find that vaccine efficacy plays a significant role in determining the outbreak size and maximum number of daily infected. Additionally, our model considers under-reporting in daily cases and deaths, revealing their combined effects on the outbreak magnitude. We also introduce a novel Physics Informed Neural Networks (PINNs) approach which is extremely useful in estimating critical parameters and helps in evaluating the predictive capability of our model.

Maintaining Program Fidelity in a Changing World: National Implementation of a School-Based HIV Prevention Program.

Large-scale, evidence-based interventions face challenges to program fidelity of implementation. We developed implementation strategies to support teachers implementing an evidence-based HIV prevention program in schools, Focus on Youth in The Caribbean (FOYC) and Caribbean Informed Parents and Children Together (CImPACT) in The Bahamas. We examined the effects of these implementation strategies on teachers' implementation in the subsequent year after the initial implementation during the COVID-19 pandemic. Data were collected from 79 Grade 6 teachers in 24 government elementary schools. Teachers completed training workshops and a pre-implementation questionnaire to record their characteristics and perceptions that might affect their program fidelity. School coordinators and peer mentors provided teachers with monitoring, feedback, and mentoring. In Year 1, teachers on average taught 79.3% of the sessions and 80.8% of core activities; teachers in Year 2 covered 84.2% of sessions and 72.9% of the core activities. Teachers with "good" or "excellent" school coordinators in the second year taught significantly more sessions on average (7.8 vs. 7.0, t = 2.04, P < 0.05) and more core activities (26.3 vs. 23.0, t = 2.41, P < 0.05) than teachers with "satisfactory" coordinators. Teachers who had a "good" or "satisfactory" mentor taught more sessions than teachers who did not have a mentor (7.9 vs. 7.3; t = 2.22; P = 0.03). Two-level mixed-effects model analysis indicated that teachers' program fidelity in Year 1, confidence in the execution of core activities, and school coordinators' performance were significantly associated with Year 2 implementation dose. Implementation of FOYC + CImPACT was significantly associated with improved student outcomes. Teachers maintained high fidelity to a comprehensive HIV prevention program over 2 years during the COVID-19 pandemic. Future program implementers should consider additional implementation support to improve the implementation of school-based programs.

Opening the Black Box of Family-Based Treatments: An Artificial Intelligence Framework to Examine Therapeutic Alliance and Therapist Empathy.

The evidence-based treatment (EBT) movement has primarily focused on core intervention content or treatment fidelity and has largely ignored practitioner skills to manage interpersonal process issues that emerge during treatment, especially with difficult-to-treat adolescents (delinquent, substance-using, medical non-adherence) and those of color. A chief complaint of "real world" practitioners about manualized treatments is the lack of correspondence between following a manual and managing microsocial interpersonal processes (e.g. negative affect) that arise in treating "real world clients." Although family-based EBTs share core similarities (e.g. focus on family interactions, emphasis on practitioner engagement, family involvement), most of these treatments do not have an evidence base regarding common implementation and treatment process problems that practitioners experience in delivering particular models, especially in mid-treatment when demands on families to change their behavior is greatest in treatment - a lack that characterizes the field as a whole. Failure to effectively address common interpersonal processes with difficult-to-treat families likely undermines treatment fidelity and sustained use of EBTs, treatment outcome, and contributes to treatment dropout and treatment nonadherence. Recent advancements in wearables, sensing technologies, multivariate time-series analyses, and machine learning allow scientists to make significant advancements in the study of psychotherapy processes by looking "under the skin" of the provider-client interpersonal interactions that define therapeutic alliance, empathy, and empathic accuracy, along with the predictive validity of these therapy processes (therapeutic alliance, therapist empathy) to treatment outcome. Moreover, assessment of these processes can be extended to develop procedures for training providers to manage difficult interpersonal processes while maintaining a physiological profile that is consistent with astute skills in psychotherapeutic processes. This paper argues for opening the "black box" of therapy to advance the science of evidence-based psychotherapy by examining the clinical interior of evidence-based treatments to develop the next generation of audit- and feedback- (i.e., systemic review of professional performance) supervision systems.

An epidemic model with time delays determined by the infectivity and disease durations.

We propose an epidemiological model with distributed recovery and death rates. It represents an integrodifferential system of equations for susceptible, exposed, infectious, recovered and dead compartments. This model can be reduced to the conventional ODE model under the assumption that recovery and death rates are uniformly distributed in time during disease duration. Another limiting case, where recovery and death rates are given by the delta-function, leads to a new point-wise delay model with two time delays corresponding to the infectivity period and disease duration. Existence and positiveness of solutions for the distributed delay model and point-wise delay model are proved. The basic reproduction number and the final size of the epidemic are determined. Both, the ODE model and the delay models are used to describe COVID-19 epidemic progression. The delay model gives a better approximation of the Omicron data than the conventional ODE model from the point of view of parameter estimation.

Platform trials to evaluate the benefit-risk of COVID-19 therapeutics: Successes, learnings, and recommendations for future pandemics.

BACKGROUND: In response to the COVID-19 global pandemic, multiple platform trials were initiated to accelerate evidence generation of potential therapeutic interventions. Given a rapidly evolving and dynamic pandemic, platform trials have a key advantage over traditional randomized trials: multiple interventions can be investigated under a master protocol sharing a common infrastructure. METHODS: This paper focuses on nine platform trials that were instrumental in advancing care in COVID-19 in the hospital and community setting. A semi-structured qualitative interview was conducted with the principal investigators and lead statisticians of these trials. Information from the interviews and public sources were tabulated and summarized across trials, and recommendations for best practice for the next health crisis are provided. RESULTS: Based on the information gathered takeaways were identified as 1) the existence of some aspect of trial design or conduct (e.g., existing network of investigators or colleagues, infrastructure for data capture and relevant statistical expertise) was a key success factor; 2) the choice of treatments (e.g., repurposed drugs) had major impact on the trials as did the choice of primary endpoint; and 3) the lack of coordination across trials was flagged as an area for improvement. CONCLUSION: These trials deployed during the COVID-19 pandemic demonstrate how to achieve both speed and quality of evidence generation regarding clinical benefit (or not) of existing therapies to treat new pathogens in a pandemic setting. As a group, these trials identified treatments that worked, and many that did not, in a matter of months.

Response to health warnings on cigarette packs as a predictor of future smoking among current tobacco smokers.

The United States (US) Food and Drug Administration (FDA) requires health warning labels on all cigarette packages as part of a campaign to reduce tobacco smoking. Prior research has revealed the mixed effectiveness of these health warning labels. The present study used nationally representative, longitudinal data from the Population Study of Tobacco and Health (PATH) Study to assess whether reported reactions to health warning labels on cigarette packs predict smoking frequency and smoking cessation two years later. We hypothesized that individuals who reported strong reactions to health warnings at Wave 1 of the PATH Study would engage in less frequent smoking behavior and would be more likely to have completely quit cigarette smoking two years later (Wave 3), compared with individuals who did not report strong reactions. Multinomial and binary logistic regressions were used to estimate the associations between attitudes toward health warning labels and later smoking frequency and smoking cessation. Our hypotheses were partially supported; results indicated that several attitudes toward health warnings predict later smoking behaviors. These findings indicate general effectiveness of health warning labels and support the FDA's initiative to require more attention-grabbing health warning labels on cigarette packs.

Efficacy of Delta Plate in Condylar Fracture: a Case Series with Review.

Open reduction and internal fixation (ORIF) of mandibular condylar fracture with a three dimensional stabilization has been a controversial topic in oral and maxillofacial surgery. Miniplates and many 3D plates have been used till now for fixation of condylar fracture and delta plate is one of them. Present literature has less evidence about which one is superior over another. We have tried to evaluate the clinical performance of the delta miniplate in this study. A total of 10 patients presenting mandibular condylar fracture were treated by ORIF using delta miniplate. Dimensional details were measured of 10 dry human mandibles. At the end of 1-year follow-up period, all patients had satisfactory results, both clinically and radiologically. Delta plate showed better stability in the condylar region and less complication associated with plating system.

A more powerful test for three-arm non-inferiority via risk difference: Frequentist and Bayesian approaches.

Necessity for finding improved intervention in many legacy therapeutic areas are of high priority. This has the potential to decrease the expense of medical care and poor outcomes for many patients. Typically, clinical efficacy is the primary evaluating criteria to measure any beneficial effect of a treatment. Albeit, there could be situations when several other factors (e.g. side-effects, cost-burden, less debilitating, less intensive, etc.) which can permit some slightly less efficacious treatment options favorable to a subgroup of patients. This often leads to non-inferiority (NI) testing. NI trials may or may not include a placebo arm due to ethical reasons. However, when included, the resulting three-arm trial is more prudent since it requires less stringent assumptions compared to a two-arm placebo-free trial. In this article, we consider both Frequentist and Bayesian procedures for testing NI in the three-arm trial with binary outcomes when the functional of interest is risk difference. An improved Frequentist approach is proposed first, which is then followed by a Bayesian counterpart. Bayesian methods have a natural advantage in many active-control trials, including NI trial, as it can seamlessly integrate substantial prior information. In addition, we discuss sample size calculation and draw an interesting connection between the two paradigms.

An age-dependent immuno-epidemiological model with distributed recovery and death rates.

The work is devoted to a new immuno-epidemiological model with distributed recovery and death rates considered as functions of time after the infection onset. Disease transmission rate depends on the intra-subject viral load determined from the immunological submodel. The age-dependent model includes the viral load, recovery and death rates as functions of age considered as a continuous variable. Equations for susceptible, infected, recovered and dead compartments are expressed in terms of the number of newly infected cases. The analysis of the model includes the proof of the existence and uniqueness of solution. Furthermore, it is shown how the model can be reduced to age-dependent SIR or delay model under certain assumptions on recovery and death distributions. Basic reproduction number and final size of epidemic are determined for the reduced models. The model is validated with a COVID-19 case data. Modelling results show that proportion of young age groups can influence the epidemic progression since disease transmission rate for them is higher than for other age groups.

Postoperative pulmonary complication as an emerging complication in major head and neck cancer surgery: A retrospective study.

Purpose: Postoperative pulmonary complications (PPCs) are one of the most significant complications following head and neck cancer surgery (HNCS). Patients requiring tracheostomy, free tissue transfer reconstruction, and postoperative ventilation in an intensive care unit (ICU) may have a high incidence of PPCs. This study aimed to identify the most likely situations for developing PPCs in HNCS. Materials and Methods: A retrospective analysis of 40 patients who had undergone HNCS has been conducted. We individually traced each patient for 7 days postoperatively and collected data on various parameters. Result: The incidence of PPCs after HNCS is more with free flap reconstruction. Patient-related risk factors with PPCs were advanced age, smoking, body mass index (BMI) >25, and bilateral or unilateral neck dissection. Postoperative ICU stay was significantly related to an increased incidence of PPCs. In terms of specific surgical sites, both the maxilla and mandible also showed significant relationship with PPCs. Tracheostomy was also considered a related factor in developing PPCs. Conclusion: To reduce PPCs in HNCS, patients with one or more of these risk factors should be subjected to exaggerated postoperative pulmonary care.

Nonlinear electrostatic ion cyclotron wave collapse and formation of wave packets in the presence of trapped electrons.

The weakly nonlinear and dispersive electrostatic ion cyclotron wave dynamics in the presence of Schamel distributed trapped electrons is studied in collisionless plasmas. The dynamics of the nonlinear wave is shown to be governed by a Schamel-Ostrovsky type equation. Analytical and numerical solutions of this equation reveal the collapse of a solitary (localized) pulse at a critical time that depends on the trapping parameter and the strength of the magnetic field. The time-dependent computational result is noteworthy, which predicts the formation of wave packets (wave group) beyond the critical time. The results are in good agreement with the astrophysical observations in auroral plasmas.

A randomized, sham-controlled, quintuple-blinded trial to evaluate the NET device as an alternative to medication for promoting opioid abstinence.

Background: There is an unmet need for non-medication approaches to illicit opioid discontinuation and relapse prevention. The NET (NeuroElectric Therapy) Device is a non-invasive, battery-operated, portable, re-useable device designed to deliver bilateral transcranial transcutaneous alternating current electrical stimulation, and is intended to treat opioid use disorder (OUD) without medication. The device is a CE-marked Class IIa, non-significant risk, investigational medical device. Objective: This prospective trial (NRC021) tests the hypothesis that the NET Device provides safe and effective neurostimulation treatment for persons with OUD who express a desire to be opioid abstinent without medications for opioid use disorder (MOUD). Methods: NRC021 is a randomized, parallel-group, sham-controlled, quintuple-blinded, single-site study. Persons with OUD entering a residential treatment facility for opioid detoxification are assigned to active or sham treatment (n = 50/group). Group assignment is stratified on presence of any current non-opioid substance use disorder and by sex. The biostatistician maintains the blinding so that the study sponsor, principal investigator, research assistants, treatment staff, and participants remain blinded. Following discharge from the inpatient facility, participants are assessed once weekly over 12 weeks for substance use (using timeline followback interview and video assessment of observed oral fluid sample provision and testing). The primary efficacy endpoint is each participant's overall percentage of weekly abstinence from illicit opioid use without use of MOUD. The secondary efficacy endpoint is each participant's percentage of non-opioid drug-free weeks. Safety outcomes are also measured. Conclusion: NRC021 is designed to assess the efficacy of a novel non-medication treatment for OUD. Clinical trial registration: ClinicalTrials.gov with the identifier NCT04916600.

Efficacy and toxicity of the DPCPX nanoconjugate drug study for the treatment of spinal cord injury in rats.

Effects of the Adenosine A1 blockade using 8-cyclopentyl-1,3-diprophyxanthine (DPCPX) nanoconjugate on inducing recovery of the hemidiaphragm paralyzed by hemisection have been thoroughly examined previously; however, the toxicology of DPCPX nanoconjugate remains unknown. This research study investigates the therapeutic efficacy and toxicology of the nanoconjugate DPCPX in the cervical spinal cord injury (SCI) rat model. We hypothesized that a single injection of nanoconjugate DPCPX in the paralyzed left hemidiaphragm (LDH) of hemisected rats at the 2nd cervical segment (C2Hx) would lead to the long-term recovery of LDH while showing minimal toxicity. Adult male rats underwent left C2Hx surgery and the diaphragms' baseline electromyography (EMG). Subsequently, rats were randomized into a control group and four treated subgroups. Three subgroups received a single intradiaphragmatic dose of either 0.09, 0.15, or 0.27 µg/kg, and one subgroup received 0.1 mg/kg of native DPCPX two times per day intravenously (i.v.) for 3 days (total 0.6 mg/kg). Rats were monitored for a total of 56 days. Compared with control, the treatment with nanoconjugate DPCPX at 0.09 µg/kg, 0.15 µg/kg, and 0.27 µg/kg doses elicited significant recovery of paralyzed LDH (i.e., 67% recovery at 8 wk) (P < 0.05). DPCPX nanoconjugate-treated rats had significant weight loss for first 2 wk but recovered significantly by day 56 (P < 0.05). The levels of gold in the blood and body tissues were below the recommended levels. No sign of weakness, histology of tissue damage, or organ abnormality was observed. A dose of DPCPX nanoconjugate can induce long-term diaphragm recovery after SCI without observed toxicity.NEW & NOTEWORTHY The intradiaphragmatic administration of nanoconjugate is safe and has the promise to significantly reduce the therapeutic dosage for the treatment and achieve long-term and possibly permanent recovery in respiratory muscle dysfunction after SCI. No toxicity of nanoconjugate was found in any of the experimental animals.

An Epidemic Model with Time-Distributed Recovery and Death Rates.

A compartmental epidemiological model with distributed recovery and death rates is proposed. In some particular cases, the model can be reduced to the conventional SIR model. However, in general, the dynamics of epidemic progression in this model is different. Distributed recovery and death rates are evaluated from COVID-19 data. The model is validated by the epidemiological data for different countries, and it shows better agreement with the data than the SIR model. The time-dependent disease transmission rate is estimated.