Size Estimation Research Articles

Efficacy and cost-effectiveness of a digital guided self-management intervention to support transition from intensive care to community care in anorexia nervosa (TRIANGLE): pragmatic multicentre randomised controlled trial and economic evaluation

There is uncertainty regarding how best to support patients with anorexia nervosa following inpatient or day care treatment. This study evaluated the impact of augmenting intensive treatment with a digital, guided, self-management intervention (ECHOMANTRA) for patients with anorexia nervosa and their carers. In this pragmatic multicentre randomised controlled trial and economic evaluation, patients with a diagnosis of anorexia nervosa or atypical anorexia nervosa, aged 16+ and attending one of the 31 inpatient or day-patient services in the UK were randomised with one of their carers to receive ECHOMANTRA plus treatment as usual (TAU), or TAU alone. ECHOMANTRA was hosted on a digital platform and included a workbook, recovery-oriented video-clips and online facilitated groups (patients only, carers only, joint patient-carer). Participants were randomised on a 1:1 ratio using a minimisation algorithm to stratify by site (N=31) and severity (defined by BMI <15 and≥15kg/m2 at baseline). The primary outcome was patient depression, anxiety, and stress at 12months. Primary and secondary outcomes were compared between trial arms on an intention-to-treat basis (ITT). This trial is registered with the ISRSTN registry, ISRCTN14644379. Between July 01, 2017 and July 20, 2020, 371 patient-carer dyads were enrolled and randomly assigned to ECHOMANTRA+TAU (N=185) or TAU alone (N=186). There were no significant differences between trial arms with regards to the primary outcome (completed by N=143 patients in the TAU group, Mean=61.7, SD=29.4 and N=109 patients in the ECHOMANTRA+TAU group, Mean=58.3, SD=26.9; estimated mean difference 0.48 points; 95% CI-5.36 to 6.33; p=0.87). Differences on secondary outcomes were small and non-significant (standardised effect size estimates ≤0.25). Five patients died (2 from suicide and 3 from physical complications) over the course of the trial, and this was unrelated to their participation in the study. ECHOMANTRA added to TAU was not superior to TAU alone in reducing patient depression, anxiety, and stress symptoms. This may be explained by limited engagement with the intervention materials and changes in usual care practices since the beginning of the trial. National Institute for Health Research (NIHR), under its Health Technology Assessment Programme (HTA) Programme (Grant Reference Number 14/68/09). NIHR Maudsley Biomedical Research Centre (BRC), South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, Psychology and Neuroscience, and King's College London. NIHR Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust.

Tamanhos de parcelas e amostras para variáveis biométricas em mudas de alface

ABSTRACT: In order to ensure reliable inferences in scientific experiments, sampling criteria should be determined and defined during the experimental design phase. Determining plot and sample sizes without scientific criteria could result in resource and labor inefficiencies with no gain in experimental precision. In this work we estimate plot and sample sizes for biometric variable analyses in lettuce seedlings. The seedlings were sown in four expanded polystyrene foam transplant trays with 128 and 200 cells. Foliar area, stem diameter, shoot height, root length, root volume, root area, fresh and dry shoot and root masses. The methods described by Paranaiba (PARANAIBA et al., 2009) and Cochran (COCHRAN, 1977) were used for plot size and sample size estimations, respectively. Sample size varied according to the variables analysed and transplant tray cell number. Root variables required the highest number of samples. For a 10% margin of error, 12 seedlings were necessary for evaluations in a 128 cell tray, while 11 seedlings were required for analysis in 200 cell trays.

Study design features increase replicability in cross-sectional and longitudinal brain-wide association studies.

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behavior associations. Several recent studies showed that thousands of study participants are required for good replicability of BWAS because the standardized effect sizes (ESs) are much smaller than the reported standardized ESs in smaller studies. Here, we perform analyses and meta-analyses of a robust effect size index using 63 longitudinal and cross-sectional magnetic resonance imaging studies from the Lifespan Brain Chart Consortium (77,695 total scans) to demonstrate that optimizing study design is critical for increasing standardized ESs and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger variability in covariate have larger reported standardized ES. In addition, the longitudinal studies we examined reported systematically larger standardized ES than cross-sectional studies. Analyzing age effects on global and regional brain measures from the United Kingdom Biobank and the Alzheimer's Disease Neuroimaging Initiative, we show that modifying longitudinal study design through sampling schemes improves the standardized ESs and replicability. Sampling schemes that improve standardized ESs and replicability include increasing between-subject age variability in the sample and adding a single additional longitudinal measurement per subject. To ensure that our results are generalizable, we further evaluate these longitudinal sampling schemes on cognitive, psychopathology, and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset. We demonstrate that commonly used longitudinal models can, counterintuitively, reduce standardized ESs and replicability. The benefit of conducting longitudinal studies depends on the strengths of the between- versus within-subject associations of the brain and non-brain measures. Explicitly modeling between- versus within-subject effects avoids averaging the effects and allows optimizing the standardized ESs for each separately. Together, these results provide guidance for study designs that improve the replicability of BWAS.

The Saudi educational and learning capitals–perspectives from gifted and non-gifted students and their parents

ABSTRACT Evaluations of gifted education in the Kingdom of Saudi Arabia are hampered by the lack of clear policy objectives as well as practical difficulties in obtaining data. Furthermore, it is unclear if the specific needs of gifted students are unique or shared across non-gifted students. In the current research, both gifted and non-gifted Saudi students (n = 284) and their parents completed Saudi-language versions of the Student Educational and Learning Capitals Questionnaire and the Family Educational and Learning Capitals Questionnaire, respectively, to assess the availability of 11 educational and learning capitals. Additionally, parents reported the major challenges to their child’s learning and what they did to support their children. Rasch modeling was used to assess the measurement properties of the two instruments and to transform the raw scores into Rasch scores (logits). The results indicated that gifted students and their parents differed in their evaluations of economic and social educational capitals, as well as organismic, telic, and attentional learning capitals that support their learning success, with estimates of effect size ranging from small to large. However, the differences between non-gifted students and their parents are similar, showing that the challenges facing Saudi gifted students are shared more generally among non-gifted students.

A multicenter randomized trial to compare automatic versus as-needed follow-up for children hospitalized with common infections: The FAAN-C trial protocol.

Physicians commonly recommend automatic primary care follow-up visits to children being discharged from the hospital. While automatic follow-up provides an opportunity to address postdischarge needs, the alternative is as-needed follow-up. With this strategy, families monitor their child's symptoms and decide if they need a follow-up visit in the days after discharge. In addition to being family centered, as-needed follow-up has the potential to reduce time and financial burdens on both families and the healthcare system. As-needed follow-up has been shown to be safe and effective for children hospitalized with bronchiolitis, but the extent to which hospitalized children with other common conditions might benefit from as-needed follow-up is unclear. The Follow-up Automatically versus As-Needed Comparison (FAAN-C, or "fancy") trial is a multicenter randomized controlled trial. Children who are hospitalized for pneumonia, urinary tract infection, skin and soft tissue infection, or acute gastroenteritis are eligible to participate. Participants are randomized to an as-needed versus automatic posthospitalization follow-up recommendation. The sample size estimate is 2674 participants and the primary outcome is all-cause hospital readmission within 14 days of discharge. Secondary outcomes are medical interventions and child health-related quality of life. Analyses will be conducted in an intention-to-treat manner, testing noninferiority of as-needed follow-up compared with automatic follow-up. FAAN-C will elucidate the relative benefits of an as-needed versus automatic follow-up recommendation, informing one of the most common decisions faced by families of hospitalized children and their medical providers. Findings from FAAN-C will also have implications for national quality metrics and guidelines.

Statistical Considerations for the Design and Analysis of Pragmatic Trials in Aging Research.

Pragmatic trials aim to assess intervention efficacy in usual patient care settings, contrasting with explanatory trials conducted under controlled conditions. In aging research, pragmatic trials are important designs for obtaining real-world evidence in elderly populations, which are often underrepresented in trials. In this review, we discuss statistical considerations from a frequentist approach for the design and analysis of pragmatic trials. When choosing the dependent variable, it is essential to use an outcome that is highly relevant to usual medical care while also providing sufficient statistical power. Besides traditionally used binary outcomes, ordinal outcomes can provide pragmatic answers with gains in statistical power. Cluster randomization requires careful consideration of sample size calculation and analysis methods, especially regarding missing data and outcome variables. Mixed effects models and generalized estimating equations (GEEs) are recommended for analysis to account for center effects, with tools available for sample size estimation. Multi-arm studies pose challenges in sample size calculation, requiring adjustment for design effects and consideration of multiple comparison correction methods. Secondary analyses are common but require caution due to the risk of reduced statistical power and false-discovery rates. Safety data collection methods should balance pragmatism and data quality. Overall, understanding statistical considerations is crucial for designing rigorous pragmatic trials that evaluate interventions in elderly populations under real-world conditions. In conclusion, this review focuses on various statistical topics of interest to those designing a pragmatic clinical trial, with consideration of aspects of relevance in the aging research field.

RoA: visual analytics support for deconfounded causal inference in observational studies

The gold standard in medical research to estimate the causal effect of a treatment is the Randomized Controlled Trial (RCT), but in many cases these are not feasible due to ethical, financial or practical issues. Observational studies are an alternative, but can easily lead to doubtful results, because of unbalanced selection bias and confounding. Moreover, RCTs often only apply to a specific subgroup and cannot readily be extrapolated. In response, we present Rod of Asclepius (RoA), a novel visual analytics method that integrates modern techniques designed for identification of causal effects and effect size estimation with subgroup analysis. The result is an interactive display designed to combine exploratory analysis with a robust set of techniques, including causal do-calculus, propensity score weighting, and effect estimation. It enables analysts to conduct observational studies in an exploratory, yet robust way. This is demonstrated by means of a use case involving patients undergoing surgery, for which we collaborated closely with clinical researchers.

Estimation of red blood cell aggregation size using power spectrum considering density of red blood cells in focal region

We have studied a noninvasive and quantitative method for measuring the aggregate size of red blood cells (RBCs). In our previous study, the scattering power spectrum obtained from the vascular lumen was fitted to the reference scattering spectra calculated from the scattering spectrum of a single-sphere scatterer. In this paper, we propose a method for calculating the reference scattering spectra by summing the scattering spectra for numerous scatterers in the ultrasound focal region. By applying this method to the size estimation of microparticles simulating RBC aggregates, the estimated sizes are found to be close to the true values. In in vivo measurements, the estimated sizes at rest are equivalent to the size of a single sphere with the same volume as an RBC, and those during avascularization are larger than those at rest, which is reasonable. The proposed method has the potential to accurately estimate the size of RBC aggregates.

Navigating uncertainty in maximum body size in marine metazoans.

Body size is a fundamental biological trait shaping ecological interactions, evolutionary processes, and our understanding of the structure and dynamics of marine communities on a global scale. Accurately defining a species' body size, despite the ease of measurement, poses significant challenges due to varied methodologies, tool usage, and subjectivity among researchers, resulting in multiple, often discrepant size estimates. These discrepancies, stemming from diverse measurement approaches and inherent variability, could substantially impact the reliability and precision of ecological and evolutionary studies reliant on body size data across extensive species datasets. This study examines the variation in reported maximum body sizes across 69,570 individual measurements of maximum size, ranging from <0.2 μm to >45 m, for 27,271 species of marine metazoans. The research aims to investigate how reported maximum size variations within species relate to organism size, taxonomy, habitat, and the presence of skeletal structures. The investigation particularly focuses on understanding why discrepancies in maximum size estimates arise and their potential implications for broader ecological and evolutionary studies relying on body size data. Variation in reported maximum sizes is zero for 38% of species, and low for most species, although it exceeds two orders of magnitude for some species. The likelihood of zero variation in maximum size decreased with more measurements and increased in larger species, though this varied across phyla and habitats. Pelagic organisms consistently had low maximum size range values, while small species with unspecified habitats had the highest variation. Variations in maximum size within a species were notably smaller than interspecific variation at higher taxonomic levels. Significant variation in maximum size estimates exists within marine species, and partially explained by organism size, taxonomic group, and habitat. Variation in maximum size could be reduced by standardized measurement protocols and improved meta-data. Despite the variation, egregious errors in published maximum size measurements are rare, and their impact on comparative macroecological and macroevolutionary research is likely minimal.

Energy-based seismic design method for seismically isolated structures with friction pendulum systems

Friction pendulum systems (FPSs) serve as effective isolators that can help ensure adequate seismic performance of structures against significant aftershocks. A commonly used method for FPS design is the equivalent static analysis method outlined in ASCE 7-22. However, this method risks underestimating the seismic performance of FPSs due to its inability to account for energy dissipation from multiple hysteresis loops exceeding two cycles. Moreover, it is not well-suited for designing FPSs with conical friction surfaces, which exhibit nonlinear elastic behavior and hysteresis. A straightforward solution to address these issues is to apply an energy-based seismic design method. In this study, we propose and analytically validate one such method tailored for seismically isolated structures employing FPSs. Our analysis considers FPSs with both spherical (ISF) and conical (ICF) friction surfaces. For ISFs, the design follows the energy-based seismic design method proposed by Akiyama, whereas, for ICFs, it is based on the energy input to the device and its geometric approximation to an ISF. The conclusions of this study are summarized as follows: (1) the proposed energy-based design method effectively predicts the maximum FPS deformation, facilitating a rough estimation of FPS size; (2) because the design assumes symmetrical seismic response of the isolation layer in both the positive and negative directions and the friction surfaces of the ISF and ICF are geometrically similar, in the proposed method, the maximum deformation of an isolation layer with a natural period greater than 2 s depends solely on the friction coefficient, regardless of the friction surface type; (3) to satisfy the relevant conditions, the appropriate FPS design range is determined through nonlinear analysis. The results of this study demonstrate that the proposed energy-based seismic design method provides a reliable and effective means of designing FPSs for enhanced seismic performance.

Age is not just a number: How incorrect ageing impacts close-kin mark-recapture estimates of population size.

Population size is a key parameter for the conservation of animal species. Close-kin mark-recapture (CKMR) relies on the observed frequency and type of kinship among individuals sampled from the population to estimate population size. Knowledge of the age of the individuals, or a surrogate thereof, is essential for inference with acceptable precision. One common approach, particularly in fish studies, is to measure animal length and infer age using an assumed age-length relationship (a 'growth curve'). We used simulation to test the effect of misspecifying the length measurement error and the growth curve on population size estimation. Simulated populations represented two fictional shark species, one with a relatively simple life history and the other with a more complex life history based on the grey reef shark (Carcharhinus amblyrhynchos). We estimated sex-specific adult abundance, which we assumed to be constant in time. We observed small median biases in these estimates ranging from 1.35% to 2.79% when specifying the correct measurement error standard deviation and growth curve. CI coverage was adequate whenever the growth curve was correctly specified. Introducing error via misspecified growth curves resulted in changes in the magnitude of the estimated adult population, where underestimating age negatively biased the abundance estimates. Over- and underestimating the standard deviation of length measurement error did not introduce a bias and had negligible effect on the variance in the estimates. Our findings show that assuming an incorrect standard deviation of length measurement error has little effect on estimation, but having an accurate growth curve is crucial for CKMR whenever ageing is based on length measurements. If ageing could be biased, researchers should be cautious when interpreting CKMR results and consider the potential biases arising from inaccurate age inference.

Particle Sizing and Surface Area Measurements: A Comparative Assessment of Commercial Air Permeability and Laser Light Diffraction Instruments

Six different commercial powders, finer than 45 μm, were used for examining the effects of particle characteristics on mean particle size and specific surface area. The measurements were carried out using the most commonly used air permeability- and laser light diffraction (scattering) techniques. As the air permeability method has been used as a benchmark for decades in the powder metallurgy (P/M) industry, the physical phenomena that govern the passage of gas through the powder bed under laminar flow conditions were also presented. The experimental data indicate that both methods give similar results for spherical powders. The advantage of laser light systems over gas permeameters is the ability to provide additional information on particle size distribution. Irregularly shaped powders should be analyzed by both techniques, relying on gas permeametry for surface area measurements and on laser light diffraction for the estimation of mean particle size and size distribution. Application of scanning electron microscopy as a complementary technique was found very helpful in the interpretation of data through visualization of individual particles.

Real world study of racial disparities associated with toxicities of sacituzumab govitecan.

1572 Background: Sacituzumab govitecan (SG) is approved in the treatment of metastatic hormone receptor positive and triple negative breast cancer (BC). The efficacy of SG across racial subgroups is known but no real-world data compares the racial differences in toxicities. We aim to expand knowledge about racial disparities regarding SG toxicities and any ineffective treatment or drug failure. Methods: We utilized TriNetX, a multi-health care organization electronic health record database, to identify African American (AA) and Caucasian (C) cohort for outcome comparison. Inclusion criteria required a C50 ICD-10-CM diagnosis code and at least one SG treatment. Age, gender, and race-controlled Cox proportional-hazard (CPH) model was used to analyze the time until the first pause or cessation of SG (defined as first deviation from the approved 21-day SG cycle). Several measures of deviation were noted 0, ±1 and ±3 days. Association between race and toxicity outcomes (controlled for age and gender) for anemia, neutropenia, thrombocytopenia, nausea and inpatient encounters were evaluated using multiple logistic regression (MLR). The odds (OR) and hazard (HR) ratios with corrected p-values are reported as an effect size and significance estimation. Results: 823 patients met the inclusion criteria (545 C, 116 AA &amp; 162 unknown). The mean age (in years) at the initiation of 1st SG treatment was 58.22 ± 12.7 for C and 58.19 ± 12.18 for AA. AA had a 1.26 times higher hazard of SG treatment pause/cessation as compared to C. Blacks experienced an 88% increase in the odds of having a delay longer than 7-days between 2 doses of 1st cycle SG. Males were found to have an 80% increase in the pause/cessation rate as compared to females. The median number of SG treatments was 6 (3 cycles) for both AA and C. SG was noted as 4th chemo line (median) among all races. When compared to C, AA had decreased odds for neutropenia, increased odds for anemia and increased odds for hospitalization. Hazard Ratio and corrected p-values for outcomes comparing the AA and C cohorts. Conclusions: Survival analysis indicates that AA and male patients have an increased SG treatment pause/cessation rate. While the result is sensitive to specific conditions used to calculate the deviation, an increased odds of delay in treatment is also found using logistic regression modeling. Additionally, AA experience increased odds for anemia and late-stage hospitalization. These findings highlight the impact of race on BC outcomes, treatment toxicities and the need for further research to enhance treatment outcomes in diverse populations. [Table: see text]

Sample Size Estimation in Clinical Trials

Sample size estimation remains as a cornerstone in the meticulous planning and execution of clinical trials, pivotal for ensuring studies possess the requisite statistical power to discern meaningful treatment effects. Insufficient sample sizes compromise the robustness of findings, whereas excessively large samples inflate costs and compromise data integrity. This article meticulously explains the multifaceted factors that outline sample size determination, encompassing various factors such as research design, types of hypotheses, error thresholds, effect size considerations, validity and precision. It investigates into the scope of methodologies available for sample size computation, spanning from intricate statistical formulas to pragmatic tabular approaches. Moreover, it underscores the significance of post-hoc power analysis in retrospectively evaluating completed studies, shedding light on their statistical robustness. This literature review furnishes a nuanced understanding of the sample size estimation landscape in clinical trials, delineating their strengths, limitations, and real-world applications. Anticipating participant attrition assumes paramount importance for proactively adjusting sample sizes, ensuring studies remain methodologically sound. Equipped with a profound grasp of these principles, researchers are empowered to conduct scientifically rigorous and impactful clinical trials, furnishing compelling evidence to inform judicious decision-making in healthcare interventions.

Lifestyle predictors of colorectal cancer in European populations: a systematic review

BackgroundColorectal cancer (CRC) is the second most prevalent cancer in Europe, with one-fifth of cases attributable to unhealthy lifestyles. Risk prediction models for quantifying CRC risk and identifying high-risk groups...

Prolonged interval to surgery following neoadjuvant chemoradiotherapy in locally advanced rectal cancer: A meta-analysis of randomized controlled trials

BackgroundLong-course neoadjuvant chemoradiotherapy (NCRT), followed by surgery after an interval of 6–8 weeks, represents standard of care for patients with locally advanced rectal cancer (LARC). Increasing this interval may improve rates of complete pathological response (pCR) and tumour downstaging. We performed a meta-analysis comparing standard (SI, within 8 weeks) versus longer (LI, after 8 weeks) interval from NCRT to surgery. MethodsPubMed, Embase, and Cochrane databases were searched up to 31 August 2022. Randomized controlled trials (RCTs) comparing SI with LI after NCRT for LARC were included. The primary endpoint was pCR rate. Secondary endpoints included rates of R0 resection, circumferential resection margin positivity (+CRM), TME completeness, lymph node yield (LNY), operative duration, tumour downstaging (TD), sphincter preservation, mortality, postoperative complications, surgical site infection (SSI) and anastomotic leak (AL). Random effects models were used to calculate pooled effect size estimates. ResultsFour RCTs encompassing 867 patients were included. There were 539 males (62.1%). LI was associated with a higher pCR rate (OR 0.61, 95%CI ​= ​0.39–0.95, p ​= ​0.03), and more TD (OR 0.60, 95%CI ​= ​0.37–0.97, p ​= ​0.04) compared to SI. However, there was no difference in rates of R0 resection (p ​= ​0.87), +CRM (p ​= ​0.66), sphincter preservation (p ​= ​0.26), incomplete TME (p ​= ​0.49), LNY (p ​= ​0.55), SSI (p ​= ​0.33), AL (p ​= ​0.20), operative duration (p ​= ​0.07), mortality (p ​= ​0.89) or any surgical complication (p ​= ​0.91). ConclusionsA LI to surgery after NCRT for LARC increases pCR and TD rates. Local recurrence or survival were not assessed due to unavailable data. We recommend deferring TME until after an interval of 8 weeks following completion of NCRT.

A pharmacokinetic framework describing antibiotic adsorption to cardiopulmonary bypass devices.

Cardiopulmonary bypass (CPB) can alter pharmacokinetic (PK) parameters and the drug may adsorb to the CPB device, altering exposure. Cefazolin is a beta-lactam antibiotic used for antimicrobial prophylaxis during cardiac surgery supported by CPB. Adsorption of cefazolin could result in therapeutic failure. An exvivo study was undertaken using CPB devices primed and then dosed with cefazolin and samples were obtained over 1 hour of recirculation. Twelve experimental runs were conducted using different CPB device sizes (neonate, infant, child, and adult), device coatings (Xcoating™, Rheoparin®, PH.I.S.I.O), and priming solutions. The time course of saturable binding, using Bmax (binding capacity), Kd (dissociation constant), and T2off (half-time of dissociation), described cefazolin adsorption. Bmax estimates for the device sizes were neonate 40.0 mg (95% CI 24.3, 67.4), infant 48.6 mg (95% CI 5.97, 80.2), child 77.8 mg (95% CI 54.9, 103), and adult 196 mg (95% CI 191, 199). The Xcoating™ Kd estimate was 139 mg/L (95% CI 27.0, 283) and the T2off estimate was 98.4 min (95% CI 66.8, 129). The Rheoparin® and PH.I.S.I.O coatings had similar binding parameters with Kd and T2off estimates of 0.169 mg/L (95% CI 0.01, 1.99) and 4.94 min (95% CI 0.17, 59.4). The Bmax was small (< 10%) relative to a typical total patient dose during cardiac surgery supported by CPB. A dose adjustment for cefazolin based solely on drug adsorption is not required. This framework could be extended to other PK studies involving CPB.

Interaction-focused music therapy with cancer-affected children and their significant others: a randomized controlled feasibility study with subsequent intervention (INMUT)

BackgroundPaediatric oncology/haematology patients and their families are confronted with a life-threatening situation for which music therapy can be a cross-linguistic field of action. The creative act of making music together offers the possibility to strengthen competences and make conflicts tangible. Besides its complementing of evidence-based biomedical care, there is little research on the feasibility and efficacy of interactive music therapy including the diagnosed child and their significant others.MethodsWe conducted an assessor blind, prospective, multicentric feasibility randomized controlled trial (RCT) with subsequent intervention. Including overall 52 child-significant other dyads, INMUT investigates interaction-focused music therapy with cancer-affected children and their significant others (INMUT-KB; n = 21) compared to music therapy only with the child (MUT-K; n = 21) and a wait-list group (WLG; n = 10). The measurement points include the screening for a cancer diagnosis, psychometric baseline (pre-T1), initial assessment (T1/T2), music therapy sessions (T3–T9), final assessment (T10), final psychometric evaluation (post-T10), and 3-month follow-up (cat-T11). Feasibility and acceptability of the (1) research methodology, (2) intervention and (3) estimation of effect sizes will be assessed using qualitative and quantitative data. The proposed primary outcome includes the parent–child interaction (APCI), and the proposed secondary outcomes refer to subjective goal achievement (GAS), quality of life (KINDL), system-related functional level (EXIS), psychosocial stress (BAS), psychosomatic complaints (SCL-9k), and resources (WIRF). We plan to investigate the efficacy of INMUT-KB and MUT-K post-intervention (post-T10) within the RCT design and at 3-month follow-up (cat-T11).DiscussionThis study will provide insights into the feasibility of INMUT and the final sample needed for a confirmatory RCT. We will reflect on successfully implemented study procedures and, if necessary, provide recommendations for changes considering the design, procedures, measures, and statistical analyses. The discussion will conclude with an evaluation whether a confirmatory RCT is worth the investment of future resources, including the calculated number of child-significant other dyads needed based on the efficacy trends derived from this feasibility study.Trial registrationClinicalTrials.gov: NCT05534282; date of registration: June 23, 2022.

Estimating body volumes and surface areas of animals from cross-sections.

Body mass and surface area are among the most important biological properties, but such information is lacking for some extant organisms and most extinct species. Numerous methods have been developed for body size estimation of animals for this reason. There are two main categories of mass-estimating approaches: extant-scaling approaches and volumetric-density approaches. Extant-scaling approaches determine the relationships between linear skeletal measurements and body mass using regression equations. Volumetric-density approaches, on the other hand, are all based on models. The models are of various types, including physical models, 2D images, and 3D virtual reconstructions. Once the models are constructed, their volumes are acquired using Archimedes' Principle, math formulae, or 3D software. Then densities are assigned to convert volumes to masses. The acquisition of surface area is similar to volume estimation by changing math formulae or software commands. This article presents a new 2D volumetric-density approach called the cross-sectional method (CSM). The CSM integrates biological cross-sections to estimate volume and surface area accurately. It requires a side view or dorsal/ventral view image, a series of cross-sectional silhouettes and some measurements to perform the calculation. To evaluate the performance of the CSM, two other 2D volumetric-density approaches (Graphic Double Integration (GDI) and Paleomass) are compared with it. The CSM produces very accurate results, with average error rates around 0.20% in volume and 1.21% in area respectively. It has higher accuracy than GDI or Paleomass in estimating the volumes and areas of irregular-shaped biological structures. Most previous 2D volumetric-density approaches assume an elliptical or superelliptical approximation of animal cross-sections. Such an approximation does not always have good performance. The CSM processes the true profiles directly rather than approximating and can deal with any shape. It can process objects that have gradually changing cross-sections. This study also suggests that more attention should be paid to the careful acquisition of cross-sections of animals in 2D volumetric-density approaches, otherwise serious errors may be introduced during the estimations. Combined with 2D modeling techniques, the CSM can be considered as an alternative to 3D modeling under certain conditions. It can reduce the complexity of making reconstructions while ensuring the reliability of the results.

Estimating statistical power for structural equation models in developmental cognitive science: A tutorial in R : Power simulation for SEMs.

Determining the compositional structure and dimensionality of psychological constructs lies at the heart of many research questions in developmental science. Structural equation modeling (SEM) provides a versatile framework for formalizing and estimating the relationships among multiple latent constructs. While the flexibility of SEM can accommodate many complex assumptions on the underlying structure of psychological constructs, it makes a priori estimation of statistical power and required sample size challenging. This difficulty is magnified when comparing non-nested SEMs, which prevents the use of traditional likelihood-ratio tests. Sample size estimates for SEM model fit comparisons typically rely on generic rules of thumb. Such heuristics can be misleading because statistical power in SEM depends on a variety of model properties. Here, we demonstrate a Monte Carlo simulation approach for estimating a priori statistical power for model selection when comparing non-nested models in an SEM framework. We provide a step-by-step guide to this approach based on an example from our memory development research in children.