Best-fit Model Research Articles

Developmental trajectories of professional preparedness among senior nursing students during clinical placement: A longitudinal study

BackgroundNewly graduated nurses' lack of professional competence is associated with inadequate preparation during their clinical placement as nursing students. Clinical placement is a critical stage in the development of nursing students' professional preparedness. However, research on the trajectory of nursing students' professional preparedness during clinical placement has not yielded findings with the same specificity. ObjectivesThe aim of this study is to estimate differences in professional preparedness levels at different clinical placement stages, to identify distinct patterns of professional preparedness trajectories during clinical placement, and to evaluate predictors of these trajectory group memberships. DesignA quantitative longitudinal study. SettingsParticipants were recruited on a voluntary basis using convenience sampling at a tertiary hospital in Nanning, China. Participants224 senior nursing students were initially invited to participate in the study. A total of 178 nursing students successfully completed the follow-up assessments at baseline, as well as at 1 month, 4 months, and 8 months into their clinical placement. MethodsParticipants completed four online surveys, during which their professional preparedness level was measured using the Perceived Professional Preparedness questionnaire for senior nursing students. Professional preparedness scores at different time points were compared using one-way repeated measures ANOVA and latent growth model. Group-based trajectory model was applied to identify professional preparedness trajectories. Multiple logistic regression was adopted to determine the predictors of trajectory group memberships. ResultsThe entire sample of Senior nursing students experienced a significant increase in professional preparedness during clinical placement. The best-fitting group-based trajectory model delineated three distinct trajectories: low-slowly increase trajectory (27.53 % of sample), moderate-rapidly increase trajectory (47.19 % of sample) and a high-stably increase trajectory (25.28 % of sample). Male, good and excellent academic performance, and very high degree of professional interest are the predictors of the moderate-rapidly increase trajectory. While male, good and excellent academic performance, high and very high degree of professional interest and participating in medical-related part-time employment are the predictors of the high-stable increase trajectory. ConclusionsSenior nursing students exhibit different levels of professional preparedness throughout their clinical placement. Simultaneously, three different trajectories were identified among the sample of nursing students. Therefore, in future research, greater attention should be directed towards the professional preparedness levels of nursing students with different trajectories, and early identification and targeted interventions should be prioritized.

Direct inference of the distribution of fitness effects of spontaneous mutations from recombinant inbred Caenorhabditis elegans mutation accumulation lines.

The distribution of fitness effects of new mutations plays a central role in evolutionary biology. Estimates of the distribution of fitness effect from experimental mutation accumulation lines are compromised by the complete linkage disequilibrium between mutations in different lines. To reduce the linkage disequilibrium, we constructed 2 sets of recombinant inbred lines from a cross of 2 Caenorhabditis elegans mutation accumulation lines. One set of lines ("RIAILs") was intercrossed for 10 generations prior to 10 generations of selfing; the second set of lines ("RILs") omitted the intercrossing. Residual linkage disequilibrium in the RIAILs is much less than in the RILs, which affects the inferred distribution of fitness effect when the sets of lines are analyzed separately. The best-fit model estimated from all lines (RIAILs + RILs) infers a large fraction of mutations with positive effects (∼40%); models that constrain mutations to have negative effects fit much worse. The conclusion is the same using only the RILs. For the RIAILs, however, models that constrain mutations to have negative effects fit nearly as well as models that allow positive effects. When mutations in high linkage disequilibrium are pooled into haplotypes, the inferred distribution of fitness effect becomes increasingly negative-skewed and leptokurtic. We conclude that the conventional wisdom-most mutations have effects near 0, a handful of mutations have effects that are substantially negative, and mutations with positive effects are very rare-is likely correct, and that unless it can be shown otherwise, estimates of the distribution of fitness effect that infer a substantial fraction of mutations with positive effects are likely confounded by linkage disequilibrium.

Integration of Spinal Musculoskeletal System Parameters for Predicting OVCF in the Elderly: A Comprehensive Predictive Model.

Systematic literature review. To develop a predictive model for osteoporotic vertebral compression fractures (OVCF) in the elderly, utilizing current tools that are sensitive to bone and paraspinal muscle changes. A retrospective analysis of data from 260 patients from October 2020 to December 2022, to form the Model population. This group was split into Training and Testing sets. The Training set aided in creating a nomogram through binary logistic regression. From January 2023 to January 2024, we prospectively collected data from 106 patients to constitute the Validation population. The model's performance was evaluated using concordance index (C-index), calibration curves, and decision curve analysis (DCA) for both internal and external validation. The study included 366 patients. The Training and Testing sets were used for nomogram construction and internal validation, while the prospectively collected data was for external validation. Binary logistic regression identified nine independent OVCF risk factors: age, bone mineral density (BMD), quantitative computed tomography (QCT), vertebral bone quality (VBQ), relative functional cross-sectional area of psoas muscles (rFCSAPS), gross and functional muscle fat infiltration of multifidus and psoas muscles (GMFIES+MF and FMFIES+MF), FMFIPS, and mean muscle ratio. The nomogram showed an area under the curve (AUC) of 0.91 for the C-index, with internal and external validation AUCs of 0.90 and 0.92. Calibration curves and DCA indicated a good model fit. This study identified nine factors as independent predictors of OVCF in the elderly. A nomogram including these factors was developed, proving effective for OVCF prediction.

Using Extracted Sugars from Spoiled Date Fruits as a Sustainable Feedstock for Ethanol Production by New Yeast Isolates.

This study focuses on investigating sugar recovery from spoiled date fruits (SDF) for sustainable ethanol production using newly isolated yeasts. Upon their isolation from different food products, yeast strains were identified through PCR amplification of the D1/D2 region and subsequent comparison with the GenBank database, confirming isolates KKU30, KKU32, and KKU33 as Saccharomyces cerevisiae; KKU21 as Zygosaccharomyces rouxii; and KKU35m as Meyerozyma guilliermondii. Optimization of sugar extraction from SDF pulp employed response surface methodology (RSM), varying solid loading (20-40%), temperature (20-40 °C), and extraction time (10-30 min). Linear models for sugar concentration (R1) and extraction efficiency (R2) showed relatively high R2 values, indicating a good model fit. Statistical analysis revealed significant effects of temperature and extraction time on extraction efficiency. The results of batch ethanol production from SDF extracts using mono-cultures indicated varying consumption rates of sugars, biomass production, and ethanol yields among strains. Notably, S. cerevisiae strains exhibited rapid sugar consumption and high ethanol productivity, outperforming Z. rouxii and M. guilliermondii, and they were selected for scaling up the process at fed-batch mode in a co-culture. Co-cultivation resulted in complete sugar consumption and higher ethanol yields compared to mono-cultures, whereas the ethanol titer reached 46.8 ± 0.2 g/L.

Dimensionality and cross-language invariance of Pittsburgh Sleep Quality Index among Indian adolescents and adults.

Sleep quality, key to physical and mental health, requires regular assessment in clinical and non-clinical settings. Despite widespread use, the dimensionality of the Pittsburgh Sleep Quality Index (PSQI) is debated, and its Hindi version's factor structure remains unexplored. Our study evaluates the PSQI's dimensionality among Indian adolescents and adults aiming to demonstrate cross-language (Hindi and English) invariance of its factor structure. The PSQI showed satisfactory item reliability, and a best-fitting two-factor model: "sleep efficiency" (comprising sleep duration and habitual sleep efficiency), and "perceived sleep quality" (comprising remaining five PSQI components). This model showed configural invariance across age groups, sexes, and languages. Metric invariance was noted across age groups, but a partial metric non-invariance was observed across languages and sexes as reflected by differences in factor loadings. The second-order factor structure model had an excellent fit indicating the usefulness of aggregate scores of the two factors as a single index of sleep quality. Our findings better support a two-factor structure of sleep quality (both for English and Hindi versions of PSQI) in India. However, further validation in diverse clinical and non-clinical samples is warranted.

The positive solitude scale (PS): psychometric properties among Chinese older

BackgroundPositive solitude, taken as a meaningful activity, contributes to the improvement of health, well-being, and quality of life of older adults. The purpose of this study was to examine the reliability and validity of the Positive Solitude Scale (PS) among Chinese older to provide a reference for related research.MethodsA convenience sample of 608 older people from 10 provinces in China was used to conduct the survey.ResultsThe Chinese version of the PS consisted of 9 items with a unidimensional structure, which could explain 60.91% of the variance. The factor loadings of each item ranged from 0.67 to 0.82, and the communality ranged from 0.44 to 0.68. The confirmatory factor analysis showed good model fit (χ2/df = 2.771, RMSEA = 0.076, CFI = 0.972, IFI = 0.972, TLI = 0.959, PNFI = 0.665, PCFI = 0.675). It was found from the criterion-related validity test that PS scores were significantly and positively correlated with Satisfaction With Life Scale (SWLS), Autonomy, Competence, and Relatedness scores (r = 0.45 to 0.44); PS scores were significantly and negatively correlated with Short-Form UCLA Loneliness Scale (ULS-6), Kessler Psychological Distress Scale (K10), Ego Depletion Scale (EDS), and Acceptance and Action Questionnaire-2nd Edition (AAQ-II) (r = -0.27 to -0.36). The Cronbach’s α coefficient value for the scale was 0.917; the split-half reliability coefficient value was 0.928. In addition, the PS showed cross-gender consistency.ConclusionsThe PS presented favorable psychometric characteristics in older people, which can be used as a valid tool for assessing older people’s positive solitude.

Construct validity and reliability of Amharic version of DASS-21 scale among Ethiopian Defense University College of Health Science students

BackgroundDASS-21 is the common and widely used tool for assessing depression, anxiety and stress. However, its validity and Reliability in Ethiopian Amharic language is not assessed.ObjectiveTo translate the DASS-21 and assess its validity and reliability among Ethiopian Defense University college of health science students in Bishoftu, Ethiopia.MethodAn institutional based cross-sectional study was conducted using a self-administered questionnaire. A total of 435 students from different departments in accordance with their proportional size were participated in this study. As to the sampling technique, the study units were selected from each department and year of study using simple random sampling proportional to size. Confirmatory factor analyses were employed to assess the factor structure and construct validity of Amharic version of the DASS-21. Cronbach alpha coefficient and corrected item total correlation was calculated to assess the internal consistency of Amharic version of DASS-21.ResultAmong 435 undergraduate students who participated in the study, 246(56.6%) were the age of 18–25 year and majority 347(79.8%) were males. Regarding their year of study; 200 (46.0%) were first year students. Confirmatory factor analysis indicates a good model fit of the three correlated factors (Comparative fit index (CFI) = 0.92 with root mean square error of approximation (RMSEA) = 0.059[0.052–0.066] and standardize root mean residual SRMR = 0.045). The internal consistency of overall DASS-21 and each sub scale were in acceptable range (0.91, 0.82, 0.77 and 0.77) respectively.ConclusionAmharic version of DASS-21 was found to be a valid and reliable instrument to measure the mental problem especially, Depression, Anxiety and Stress among university students.

Evaluating the Construct Validity of the Charité Alarm Fatigue Questionnaire using Confirmatory Factor Analysis.

The Charité Alarm Fatigue Questionnaire (CAFQa) is a 9-item questionnaire that aims to standardize how alarm fatigue in nurses and physicians is measured. We previously hypothesized that it has 2 correlated scales, one on the psychosomatic effects of alarm fatigue and the other on staff's coping strategies in working with alarms. We aimed to validate the hypothesized structure of the CAFQa and thus underpin the instrument's construct validity. We conducted 2 independent studies with nurses and physicians from intensive care units in Germany (study 1: n=265; study 2: n=1212). Responses to the questionnaire were analyzed using confirmatory factor analysis with the unweighted least-squares algorithm based on polychoric covariances. Convergent validity was assessed by participants' estimation of their own alarm fatigue and exposure to false alarms as a percentage. In both studies, the χ2 test reached statistical significance (study 1: χ226=44.9; P=.01; study 2: χ226=92.4; P<.001). Other fit indices suggested a good model fit (in both studies: root mean square error of approximation <0.05, standardized root mean squared residual <0.08, relative noncentrality index >0.95, Tucker-Lewis index >0.95, and comparative fit index >0.995). Participants' mean scores correlated moderately with self-reported alarm fatigue (study 1: r=0.45; study 2: r=0.53) and weakly with self-perceived exposure to false alarms (study 1: r=0.3; study 2: r=0.33). The questionnaire measures the construct of alarm fatigue as proposed in our previous study. Researchers and clinicians can rely on the CAFQa to measure the alarm fatigue of nurses and physicians.

Carbonization of golden shower pods to high surface area biochar for decontamination of cationic dyes and regeneration study by gamma radiations

Detoxification of water resources is the need of the hour and a number of environment friendly materials are proposed by scientist to deal with water pollution issues. The present study deals with preparation and characterization of porous activated carbon from golden shower pods, a waste ligno-cellulosic biomass, for the removal of dye contaminants from aqueous solution. The synthesized material, golden shower biochar (GSBC) was characterized using various analytical techniques to confirm the presence of active sites. The BET analysis of GSBC revealed high surface area of 1120 m2/g with total pore volume of 1.099 cm3/g and average pore radius 19.618 Å. Operational parameters were optimized using batch studies by taking GSBC dose of 50 mg which showed complete removal of target dyes with an initial dye concentration of 200 mg/L with just 60 min interaction time; based on these results, a fixed bed column of GSBC was designed and column studies were performed. Adsorption isotherm studies were carried out using Langmuir and Freundlich models, of which Langmuir model was found to be best-fit with maximum adsorption capacities of 208.86 mg/g, 284.35 mg/g and 327.56 mg/g for Crystal violet, Brilliant green and Methylene blue dyes respectively. Analysis of kinetics and thermodynamics revealed that the best-fit model was pseudo second-order with spontaneous reaction course and exothermic nature. Regeneration was carried out using gamma irradiation of dye loaded GSBC, followed by leaching in alcohol. It was observed that a 30 KGy dose was just sufficient to completely degrade the dye on the adsorbent surface. GSBC has shown immense potential for eradication of dyes from water effluents and it is easily recovered with negligible loss in efficacy.

Effects of Entrepreneurship Education Components on Entrepreneurial Intentions in Oman

Despite the many studies on entrepreneurship education programs to date, their findings have mainly reported on the changes in attitudes and intentions toward entrepreneurship without answering the questions of what precisely caused these changes. Little has been written and elaborated on the specific effects of entrepreneurship education components. This study integrates Johannisson’s four components of entrepreneurship education into Azjen’s Theory of Planned Behavior model. The model was conveniently tested among undergraduate students in higher education institutions in Oman through an online survey. The results show that the best-fit structural model supports the notion that the systematic entrepreneurship education components are interrelated, and they in fact drive the three antecedent variables of the TPB and entrepreneurial intentions. In addition, the findings also support the assertion that students’ entrepreneurship education (i.e., know-what) solely influences their entrepreneurial intentions. Practical implications of the findings and suggestions for future research are also discussed.

Latent trajectories of anxiety and depression among women during subsequent pregnancy following pregnancy loss.

To determine the longitudinal trajectories of anxiety and depression among pregnant women who have experienced pregnancy loss, and to explore the association between post-traumatic stress symptoms (PTSS) related to pregnancy loss and these trajectories. A prospective longitudinal study. Between October 2022 and August 2023, pregnant women with a history of pregnancy loss were recruited from four hospitals in Guangdong Province, China. Eligible participants were screened for PTSS related to pregnancy loss upon enrolment. Anxiety and depression symptoms were assessed in early, mid and late pregnancy using the Pregnancy-related Anxiety Questionnaire-Revised 2 and the Patient Health Questionnaire-9, respectively. Latent class growth analysis was employed to categorize anxiety and depression trajectories, and multinomial logistic regression analysis was conducted to examine the association between PTSS and these trajectories. Of the 388 participants included in the analysis, 158 individuals (40.7%) reported high PTSS scores. The best-fitting models identified three trajectories for both anxiety and depression: low (anxiety: 35.6%, depression: 48.7%), moderate (anxiety: 44.8%, depression: 40.5%) and high (anxiety: 19.6%, depression: 10.8%). Pregnant women with high PTSS levels were significantly more likely to experience moderate-to-high trajectories of anxiety and depression compared to those with low PTSS levels. Pregnant women who have experienced pregnancy loss exhibit higher incidences of elevated anxiety and depression trajectories. Screening for PTSS and targeted supportive care are recommended to alleviate anxiety and depressive symptoms in this population. This study underscores the importance of early psychological screening and tailored interventions for pregnant women with a history of pregnancy loss. Trauma-informed care should be prioritized to mitigate anxiety and depression trajectories in this vulnerable population. There was no patient or public involvement.

Regional brain activity and connectivity associated with childhood trauma in drug-naive patients with obsessive–compulsive disorder

Obsessive–compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive, compulsive behaviors, with childhood trauma recognized as a contributing factor to its pathophysiology. This study aimed to delineate brain functional aberrations in OCD patients and explore the association between these abnormalities and childhood trauma, to gain insights into the neural underpinnings of OCD. Forty-eight drug-naive OCD patients and forty-two healthy controls (HC) underwent resting-state functional magnetic resonance imaging and clinical assessments, including the Yale–Brown Obsessive Compulsive Scale (Y–BOCS) and Childhood Trauma Questionnaire-Short Form (CTQ-SF). Compared to HCs, OCD patients exhibited significantly decreased amplitude of low-frequency fluctuations (ALFF) in the right cerebellum, decreased regional homogeneity (ReHo) in the right cerebellum and right superior occipital lobes (FWE-corrected p < 0.05), which negatively correlated with Y–BOCS scores (p < 0.05). Furthermore, cerebellar ALFF negatively correlated with the CTQ emotional abuse subscale (r = − 0.514, p < 0.01). Mediation analysis revealed that cerebellar ALFF mediated the relationship between CTQ-emotional abuse and Y–BOCS (good model fit: R2 = 0.231, MSE = 14.311, F = 5.721, p < 0.01; direct effect, c′ = 0.153, indirect effect, a*b = 0.191). Findings indicated abnormal spontaneous and regional cerebellar activity in OCD, suggesting childhood trauma impacts OCD symptoms through cerebellar neural remodeling, highlighting its importance for clinical treatment selection.

Assessment of factors influencing fuelwood utilization in Makurdi metropolis, Benue state, Nigeria

The study was conducted to assess the factors influencing the utilization of fuelwood in Makurdi metropolis due to the paucity of information on the factors in the area. Simple random sampling technique was used to select 125 people in 25 houses from five locations in the study area. Data for the study was obtained through a semi-structured questionnaire, interview, and personal observation. Field data was analyzed using descriptive, Likert scale rating and regression models. Results of analysis of field data show that seven tree species were utilized for fuelwood in the study area with Prosopis africana (34%) being the most preferred fuelwood spp utilized while Burkia africana (2.1%) was the least utilized fuelwood spp. The Multilinear regression model was selected as the best-fit model in explaining the factors influencing fuelwood utilization in the study area based on its high r2 value and low standard error estimated compared to the other three regression models. None of the socioeconomic variables investigated had a significant influence on fuelwood utilization (P &gt; 0.05). However, age, income, family size, unit price, and availability of the commodity positively influence fuelwood utilization in the study area. The socioeconomic factors were able to explain 67% of the variation in fuelwood utilization in Makurdi Metropolis. Fuelwood is highly utilized in the area. Therefore, the conservation of the preferred fuelwood tree species in community forests and agroforestry practices should be encouraged by the Government, Non-governmental organizations (NGOs), and private individuals to enhance the sustainability of the resource.

Comparative Analysis of GARCH-Based Volatility Models of Financial Market Volatility: A Case of Nairobi Security Market PLC, Kenya

This paper conducted a comprehensive comparative analysis of various GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models to forecast financial market volatility, with a specific focus on the Nairobi Stock Exchange Market. The examined models include symmetric and asymmetric GARCH types, such as sGARCH, GJR-GARCH, AR (1) GJG-GARCH, among others. The primary objective is to identify the most suitable model for capturing the complex dynamics of financial market volatility. The study employs rigorous evaluation criteria, including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Error (ME), and Root Mean Absolute Error (RMAE), to assess the performance of each model. These criteria facilitate the selection of the optimal model for volatility forecasting. The analysis reveals that the GJR-GARCH (1,1) model emerges as the best-fit model, with AIC and BIC values of −5.5008 and −5.4902, respectively. This selection aligns with the consensus in the literature, highlighting the superiority of asymmetric GARCH models in capturing volatility dynamics. The comparison also involves symmetric GARCH models, such as sGARCH (1,1), and other asymmetric models like AR (1) GJG-GARCH. While these models were considered, the GJR-GARCH (1,1) model demonstrated superior forecasting capabilities. The study emphasizes the importance of accurate model selection and the incorporation of asymmetry in volatility modeling. The research provides essential insights into financial market volatility modeling and forecasting using both asymmetric and symmetric GARCH models. These findings have significant implications for government policymakers, financial institutions, and investors, offering improved tools for risk assessment and decision-making during periods of market turbulence.

Development of a Brief Assessment Tool to Evaluate Early Low Nutrition Risk in Community Elderly. Creation of the tool and examination of its reliability and criterion-related validity.

To date simple assessment tool to evaluate early low nutrition risk in general older population has not been available. This study aimed to create such tool and examined its reliability and criterion-related validity. 1,192 community elderly with a mean age of 74.7(5.8) years responded to a questionnaire consisting of 48 (Hatoyama) or 34 items (Kusatsu), which have been reported to be associated with nutritional state in older people. Item analysis was conducted on the 34 common items, and items were selected based on the following criteria: adequate pass rates and discriminative power, no gender and regional differences, and a certain level of commonality based on factor analysis. Next, the factor structure of the candidate items was examined through exploratory factor analysis, and confirmatory factor analysis was conducted as the final scale structure. Furthermore, Spearman's partial rank correlation coefficients (sex- and age-adjusted) between the created index and important health indicators were examined to determine the criterion-related validity. Finally, we obtained a semantic coherence of 4 factors (named health beliefs, dietary status, physical activity, and food-related quality of life) totaling 13 items; confirmatory factor analysis of the 4-factor solution yielded good model fit values, χ2 (59) =275.4 (p<0.001), CFI=0.930, and RMSEA=0.056. The factor loadings for each factor ranged from 0.43 to 0.82, indicating adequate loadings. The reliability of the index was shown to be high by Good-Poor analysis and Cronbach's α. The index showed statistically significant correlations with all health indicators. We have developed a simple assessment tool to evaluate early low nutrition risk in general older population.

Evaluating the Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP) Scores Using Principal Components Analysis.

Introduction TheVerbal Behavior Milestones Assessment and Placement Program (VB-MAPP)is an extensive tool used to assess children with autism and other developmental disabilities who have language delays. Applied behavior analysis (ABA) professionals frequently use the VB-MAPP to create personalized intervention programs catering to each child's needs. The lack of studies examining the VB-MAPPat the pretest, posttest, and differential scores using principal components analysis (PCA) suggests an opportunity to conduct PCAs on these different VB-MAPP scores. In doing so, researchers could better understand the VB-MAPP's dimensionality and factor structure at these levels. This, in turn, could inform the development of more effective assessment strategies and intervention plans for individuals with language and social communication challenges. Materials and methods From January 2018 to July 2021, The Oxford Centerin Brighton and Troy, Michigan, treated autistic children using ABAtherapy. A convenience sample of 13 children was retrospectively analyzed using VB-MAPP, which evaluates various behavioral milestones using a pretest-posttest design. Descriptive data analysis and internal consistency reliability estimates (using Cronbach's alpha) were calculated for pretest, posttest, and difference scores. A Wilcoxen signed-rank test was conducted to determine the statistical significance between thepretest and posttest. Correlation matrices were inspected for relevant relationships between VB-MAPP scales, and a PCAwith orthogonal rotation was alsoperformed on this pretest, posttest, and difference scores. Results The mean age for the children was 4.083 years ± 1.083 years, (95%CI 3.64, 4.36). Around 66.6% of the children had an autism severity level of three, 33.3% had a severity level of two, and none were at level one. Cronbach's alpha for internal consistency reliability of the pretest, posttest, and difference scores, indicating excellent reliability with values of 0.948 for the pretest and 0.937 for theposttest, respectively. The difference scores had a lower but acceptable reliability coefficient of 0.752. PCAon the pretest scores identified three factors that explain85.584% of the total variation, indicating that these components capture most of the data's structure. The posttest PCA also identified three factors, accounting for 84.293% of the variance, suggesting a similar complexity and good model fit as the pretest. PCA revealed four factors explaining 82.317% of the variation for the difference scores. The increase in factors suggests that changes between pretest and posttest scores are complex, likely due to the ABA treatment, and require an additional component to represent the data adequately. There is a good model fit; the underlying structure is more complex than the pretest or posttest alone. Conclusions Robust coefficient alphas combined with the shift to a more detailed factor structure post-ABA treatment highlight ABA therapy's diverse and multi-faceted impact on children. The increase from three to four principal components indicates a richer and more nuanced pattern of improvements across different domains of verbal and social behavior. This detailed factor structure is a testament to the comprehensive and individualized nature of ABA treatment, reflecting the therapy's effectiveness in addressing specific needs and fostering broad developmental gains in children.

Association Between Dominant-Shoulder Internal-Rotation Restriction and Low-Back Pain in Elite Male High School Soft Tennis Players.

The incidence of low-back pain (LBP)is high among elite male high school soft tennis players. A previous report showed that hip internal-rotation (IR) restriction in the non-dominant leg could increase the risk of LBP. Moreover, IR in the dominant shoulder is important for serve and stroke movements, suggesting that IR restriction in the dominant shoulder can contribute to LBP. The simultaneous incidence of non-dominant-hip IR restriction may help in developing a good LBP-related factor model; therefore, this study aimed to investigate the association between dominant-shoulder IR restriction and LBP in elite male high school soft tennis players. This is a single-center cross-sectional study. This study included 176 male high school soft tennis players from 14 elite teams. The main measures were IR and external-rotation range of motion (ROM) in the dominant and non-dominant shoulders and hip, assessed using a goniometer with a bubble attached. Multiple logistic regression analyses were performed with the presence of LBP as a categorical variable (LBP, 1; non-LBP (NLBP), 0). Multiple logistic regression models were created as follows: Model 1 included dominant-shoulder IR restriction (loss of glenohumeral IR (GIRLoss)), Model 2 included non-dominant-hip IR ROM, and Model 3 included both GIRLoss and non-dominant-hip IR ROM as the main explanatory variables to test the association between dominant-shoulder IR restriction and LBP, compare its suitability as an associated factor with non-dominant-hip IR restriction, and determine if either or both should be considered in an LBP association model based on model fit. The significance of each multiple logistic regression model was examined using the model χ2 test, and a model with P<0.05 was judged as a significant model. Model fit was examined using the Hosmer-Lemeshow test, and P≥0.05 was judged as a good model fit. The Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare the goodness-of-fit among multiple logistic regression models. Results: The LBP and non-LBP groups comprised 59 and 117 players, respectively. GIRLoss in the dominant shoulder was a significant independent factor (odds ratio: 1.06, 95% CI: 1.02-1.09; P<0.01) in Model 3, which included hip IR restriction in the non-dominant leg (odds ratio: 0.90, 95% CI: 0.86-0.94; P<0.01).In all models, the explanatory variables fitted were significantly associated with LBP, indicating that the models were significant and fitted well: the AICs (and BICs) for Models 1, 2, and 3 were 198.4 (207.6), 178.6 (187.9), and 168.8 (181.1), respectively, indicating that Model 3 was the best fit. In elite male high school soft tennis players, IR restriction in the dominant shoulder was associated with LBP. IR restriction in the dominant shoulder and non-dominant hip as a significant factor for LBP may contribute to developing an optimal multiple logistic regression model for LBP.

Non-steroidal anti-inflammatory drugs adsorption from aqueous solution by MOFs MIL-100(Fe), ZIF-8 and UiO-66: Synthesis, characterization, and comparative study

Pharmaceutical products such as ibuprofen and naproxen pose a potencial risk to the environment and to the human health. In this context, it is necessary seek and implement new effective and low-cost technologies for water treatment such as adsorption. Metal-organic frameworks (MOFs) emerge as promising adsorbent materials due to their structural diversity and stability. The obtained MOFs were characterized by SEM/EDX, XRD, FTIR, N2 at 77 K, DLS, and PZC. According to the textural parameters, the obtained MOFs have the next surface areas: MIL-100 (Fe) 1359 m2, ZIF-8 357 m2 and UiO-66 1654 m2. Having this differences in surface areas, alongside the different PZC of each materials, affect the adsorption capacity. According to the experimental data UiO-66 and MIL-100(Fe) had the highest ibuprofen adsorption capacity (152.3 mg g-1) and naproxen adsorption capacity (278.3 mg g-1), respectively. On the other hand, ZIF-8 has the lowest adsorption capacity of ibuprofen and naproxen (85.4 and 78.9 mg g-1 respectively). It was found that the best-fitting model according to its R2 for all materials with both adsorbates was the Sips model. Moreover, all materials with all adsorbates, except for UiO-66 with naproxen, reached equilibrium within the first 120 min and fitted the pseudo-second order model. According to thermodynamic parameters and analysis of fitted kinetic models, it was determined that during adsorption, a combination of physical and chemical phenomena occurs, from which the following interactions are proposed as the main adsorption mechanisms: hydrogen bonding, π -π interactions, anion-π interactions, and Lewis’ acid/base interactions.

The PERMA+4 Positive Functioning at Work Scale: Spanish Adaptation and Validation.

Donaldson & Donaldson (2021b) developed a scale to assess Positive Functioning at Work, adding four new blocks to strengthen the original PERMA framework in the workplace. The aim of the present study was to validate this scale in a Spanish sample. 698 Spanish workers participated, 59% were women and 41% were men, 71.6% were employees and 71.2% belonged to the basic worker level. Confirmatory Factor Analysis showed a good fit of the nine-factor model (χ/df = 2.441; RMSEA = .056, 90% IC (.049, .063); SRMR =. 062; CFI = .926; TLI = .916), the bifactor model (χ/df = 1.703; RMSEA = .044, 90% CI [.037, .050]; SRMR = .050; CFI = .959; TLI = .952) and the ESEM model (χ/df = 1.736; RMSEA = .041, 90% CI [.033, .049]; SRMR = .017; CFI = .976; TLI = .942). The adapted scale also demonstrated good internal consistency, with a Cronbach's α of .90 for the scale, and evidence of discriminant, criterion, predictive, and incremental validity with other well-being and performance measures, as well as measurement invariance across educational levels. This scale provides a comprehensive measurement tool that can help in the design of workplace programs and interventions.

CHAOS. VIII. Far-ultraviolet Spectra of M101 and the Impact of Wolf–Rayet Stars* ∗Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the Data Archive at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

We investigate the stellar and nebular properties of nine H ii regions in the spiral galaxy M101 with far-ultraviolet (FUV; ∼900–2000 Å) and optical (∼3200–10,000 Å) spectra. We detect significant C iii] λλ1907,1909 nebular emission in seven regions, but O iii] λ1666 only in the lowest-metallicity region. We produce new analytic functions of the carbon ionization correction factors as a function of metallicity in order to perform a preliminary C/O abundance analysis. The FUV spectra also contain numerous stellar emission and P-Cygni features that we fit with luminosity-weighted combinations of single-burst Starburst99 and BPASS models. We find that the best-fit Starburst99 models closely match the observed very-high-ionization P-Cygni features, requiring very hot, young (≲3 Myr), metal-enriched massive stars. The youngest stellar populations are strongly correlated with broad He ii emission, nitrogen Wolf–Rayet (WR) FUV and optical spectral features, and enhanced N/O gas abundances. Thus, the short-lived WR phase may be driving excess emission in several N P-Cygni wind features (λ955, λ991, λ1720) that bias the stellar continuum fits to higher metallicities relative to the gas-phase metallicities. Accurate characterization of these H ii regions requires additional inclusion of WR stars in the stellar population synthesis models. Our FUV spectra demonstrate that the ∼900–1200 Å FUV can provide a strong test bed for future WR atmosphere and evolution models.