Latent Class Analysis to Identify Parental Involvement Styles in Chinese Children's Learning at Home.

BACKGROUND: Parental involvement is one of the most important factors affecting students' academic learning. Different families seem to show similar parental involvement patterns. This study employed a representative sample of 12,575 seventh- and eighth-grade Chinese students' parents to explore the patterns of parental involvement. (2) Methods: Latent class analysis (LCA) was used to identify different parental involvement styles in children's studies at home. Discriminant analysis, MANOVA, post-hoc tests, and effect size were used to verify the LCA results. (3) Results: Four distinctive latent class groups were identified and named: supportive (20%), permissive (54%), restrictive (8%), and neglectful (18%). A discriminant analysis supported the LCA group classification results. The MANOVA results indicated statistically significant differences between the four latent classes using the set of predictor variables. The post-hoc test results and effect sizes showed that the predictor variables had substantial differences among the four latent class groups. Parental education and family income showed statistically significant links to these four parental involvement styles, which, in turn, were linked to students' academic achievement according to the MANOVA, effect sizes, and post-hoc test results. (4) Conclusions: Parental involvement styles in children's learning at home can be identified and categorized into four different latent class styles.

Exploring the Impact of Missing Data on Residual-Based Dimensionality Analysis for Measurement Models.

Researchers frequently use Rasch models to analyze survey responses because these models provide accurate parameter estimates for items and examinees when there are missing data. However, researchers have not fully considered how missing data affect the accuracy of dimensionality assessment in Rasch analyses such as principal components analysis (PCA) of standardized residuals. Because adherence to unidimensionality is a prerequisite for the appropriate interpretation and use of Rasch model results, insight into the impact of missing data on the accuracy of this approach is critical. We used a simulation study to examine the accuracy of standardized residual PCA with various proportions of missing data and multidimensionality. We also explored an adaptation of modified parallel analysis in combination with standardized residual PCA as a source of additional information about dimensionality when missing data are present. Our results suggested that missing data impact the accuracy of PCA on standardized residuals, and that the adaptation of modified parallel analysis provides useful supplementary information about dimensionality when there are missing data.

Exploring Within-Rater Category Ordering: A Simulation Study Using Adjacent-Categories Mokken Scale Analysis.

The interpretation of ratings from educational performance assessments assumes that rating scale categories are ordered as expected (i.e., higher ratings correspond to higher levels of judged student achievement). However, this assumption must be verified empirically using measurement models that do not impose ordering constraints on the rating scale category thresholds, such as item response theory models based on adjacent-categories probabilities. This study considers the application of an adjacent-categories formulation of polytomous Mokken scale analysis (ac-MSA) models as a method for evaluating the degree to which rating scale categories are ordered as expected for individual raters in performance assessments. Using simulated data, this study builds on the preliminary application of ac-MSA models to rater-mediated performance assessments, in which a real data analysis suggested that these models can be used to identify disordered rating scale categories. The results suggested that ac-MSA models are sensitive to disordered categories within individual raters. Implications are discussed as they relate to research, theory, and practice for rater-mediated educational performance assessments.

Social Desirability Amongst Chinese Teachers.

Research has suggested that self-reported responses on surveys can be affected by a participant's tendency toward social desirability, which would prevent them from revealing their true feelings or behaviors. Researchers should provide evidence that their results have not been affected by socially desirable responses using the Marlowe-Crowne Social Desirability Scale (MC-SDS). Past research has used the 33-item original form and 13-item short form of the MC-SDS, although a few researchers have found questionable validation of the 13 item MC-SDS in several populations. Traditional factor analysis failed to converge on a factor structure. Therefore, the current research was conducted using a Rasch dichotomous model analysis on the original 33-item MC-SDS, a 20-item MC-SDS, and the 13-item MC-SDS. Findings indicated that the 33-item MC-SDS had several overlapping items, the 20-item MC-SDS provided a somewhat meaningful measure of social desirability, and the 13-item MC-SDS did not provide sufficient item distribution or separation to produce a meaningful measure. A researcher should check on the factor structure of the MC-SDS when using it in their research, especially with different cultural populations.

Impact of Measured vs. Predicted Residual Lung Volume on Body Fat Percentage Using Underwater Weighing and 4-Compartment Model.

Nickerson, BS, Esco, MR, Bishop, PA, Schumacker, RE, Richardson, MT, Fedewa, MV, Wingo, JE, and Welborn, BA. Impact of measured vs. predicted residual lung volume on body fat percentage using underwater weighing and 4-compartment model. J Strength Cond Res 31(9): 2519-2527, 2017-The purpose of this study was to compare underwater weighing (UWW) and 4-compartment (4C) model body fat percentage (BF%) for predicted vs. simultaneously measured residual lung volume (RLV). Forty-seven women and 33 men (age = 22 ± 5 years) had UWW and 4C model BF% determined using Boren et al. (RLVBOREN), Goldman and Becklake (RLVGB), and Miller et al. (RLVMILLER) RLV prediction equations. Criterion UWW BF% included body density (BD) values with simultaneous RLV. Criterion 4C model BF% included BD through UWW with simultaneous RLV, total body water through bioimpedance spectroscopy, and bone mineral content through dual-energy x-ray absorptiometry. The standard error of estimate (SEE) for UWW and 4C model BF% determined through RLV prediction equations varied from 2.0 to 2.6% and from 1.3 to 1.5%, respectively. The constant error (CE) was significantly different for UWW BF% when using RLVBOREN, RLVGB, and RLVMILLER (all p < 0.016; CE = 0.7, -2.0, 1.0%, respectively). However, the CEs for RLVBOREN and RLVMILLER were not significant in the 4C model (p = 0.73 and 0.11; CE = 0.1 and 0.2%, respectively), whereas RLVGB remained significantly different (p < 0.001; CE = -1.5%). The 95% limits of agreement were less than ±5.2% for UWW BF% and less than ±3.1% for the 4C model when using the 3 RLV equations. When used in a 4C model, the RLV equations yielded a smaller CE, SEE, and 95% limits of agreement than UWW BF% results. However, because of the range of individual error shown in the current study, caution should be employed when using the 4C model as a criterion method with predicted RLV.

Validity of Selected Bioimpedance Equations for Estimating Body Composition in Men and Women: A Four-Compartment Model Comparison.

Nickerson, BS, Esco, MR, Bishop, PA, Schumacker, RE, Richardson, MT, Fedewa, MV, Wingo, JE, and Welborn, BA. Validity of selected bioimpedance equations for estimating body composition in men and women: a four-compartment model comparison. J Strength Cond Res 31(7): 1963-1972, 2017-The purpose of this study was to compare body fat percentage (BF%) and fat-free mass (FFM) values from bioelectrical impedance analysis (BIA) equations to values determined from a 4-compartment (4C) model. Eighty-two adults (42 men and 40 women) volunteered to participate (age = 23 ± 5 years). Body fat percentage and FFM were estimated from previously developed BIA equations by Chumlea et al. (BIACH), Deurenberg et al. (BIADE), Kyle et al. (BIAKYLE), and Sun et al. (BIASUN). Four-compartment model body composition was derived from underwater weighing for body density, dual-energy X-ray absorptiometry for bone mineral content, and bioimpedance spectroscopy for total body water. The standard error of estimate (SEE) for group BF% and FFM ranged from 3.0 to 3.8% and 2.1 to 2.7 kg, respectively. The constant error (CE) was significantly higher and lower for BF% and FFM (p < 0.001), respectively, for 3 BIA equations (BIACH, CE = 3.1% and -2.2 kg; BIADE, CE = 3.7% and -2.9 kg; BIAKYLE, CE = 2.3% and -1.9 kg), but was not significant for BF% (p = 0.702) and FFM (p = 0.677) for BIASUN (CE = -0.1% and 0.1 kg). The 95% limits of agreement were narrowest for BIACH (±5.9%; ±4.2 kg) and largest for BIADE (±7.4%; ±6.2 kg). The significant CE yielded by BIACH, BIADE, and BIAKYLE indicates these equations tend to overpredict group BF% and underestimate group FFM. However, all BIA equations produced low SEEs and fairly narrow limits of agreement. When the use of a 4C model is not available, practitioners might consider using one of the selected BIA equations, but should consider the associated CE.

Detecting measurement disturbance effects: the graphical display of item characteristics.

Traditional identification of misfitting items in Rasch measurement models have interpreted the Infit and Outfit z standardized statistic. A more recent approach made possible by Winsteps is to specify "group = 0" in the control file and subsequently view the item characteristic curve for each item against the true probability curve. The graphical display reveals whether an item follows the true probability curve or deviates substantially, thus indicating measurement disturbance. Probability of item response and logit ability are easily copied into data vectors in R software then graphed. An example control file, output item data, and subsequent preparation of an overlay graph for misfit items are presented using Winsteps and R software. For comparison purposes the data are also analyzed using a multi-dimensional (MD) mapping procedure.

Effects of caffeine and menthol on cognition and mood during simulated firefighting in the heat.

This study examined the separate effects of caffeine and menthol on cognition and mood during simulated firefighting in the heat. Participants (N = 10) performed three trials in a counterbalanced order, either with 400 mg caffeine, menthol lozenges, or placebo. The simulated firefighting consisted of 2 bouts of 20-min treadmill exercise and one bout of 20-min stepping exercise in the heat with two brief 15-min rest periods between each exercise phase. Exercise induced significant dehydration (>3%) and elevated rectal temperature (>38.9 °C), for all three conditions. Neither caffeine nor menthol reduced perceived exertion compared to placebo (p > 0.05). Mood ratings (i.e., alertness, hedonic tone, tension) significantly deteriorated over time (p < 0.05), but there was no difference among the three conditions. Simple reaction time, short-term memory, and retrieval memory did not alter with treatments or repeated evaluations. Reaction accuracy from a math test remained unchanged throughout the experimental period; reaction time from the math test was significantly faster after exposure to the heat (p < 0.05). It is concluded that, exhaustive exercise in the heat severely impacted mood, but minimally impacted cognition. These treatments failed to show ergogenic benefits in a simulated firefighting paradigm in a hot environment.

Fluid balance, thermal stress, and post exercise response in women's Islamic athletic clothing.

This study examined heat stress, heart rate (HR), fluid balance, micro-environment temperature and humidity with Islamic athletic clothing (IC) compared to traditional soccer uniform (SC). Ratings of perceived exertion (RPE), session RPE (S-RPE), comfort, and cooling response were also examined. Female volunteers (N = 8) completed a treadmill [Formula: see text] test and then, in a randomized, counter-balanced order, two intermittent running bouts (45 min total) in a hot environment (30.0°C WBGT) in IC and SC. Thereafter, participants sat for 40 min in the hot ambient environment. Repeated measures ANOVA revealed significantly greater micro-environment temperature (p = 0.02) (IC 33.3 ± 3.2°C, SC 32.0 ± 2.8°C) and humidity (p = 0.04) (IC 48.4 ± 8.1%, SC 42.9 ± 7.9%) in IC during the exercise trial but no difference in the 40-min recovery period for micro-environment temperature (p = 0.25) or humidity (p = 0.18). No significant difference (p > 0.05) was shown for core temperature (T (rec)) (IC 38.3 ± 0.4°C, SC 38.2 ± 0.4°C), HR (IC l54 ± 28 beats min(-1), SC 151 ± 26 beats min(-1)) or RPE (IC 4.7 ± 2.1, SC 3.8 ± 1.7) during the exercise trial or recovery period. Results from a paired t test revealed a significantly greater (p < 0.05) S-RPE (IC 5.8 ± 1.2, SC 4.3 ± 1.9), sweat loss (IC 1.4 ± 0.4 L h(-1), SC 1.2 ± 0.4 L h(-1)) and greater discomfort during the exercise and recovery period for the IC. IC clothing appears to have no detrimental effects on heat storage or heat strain during exercise or recovery.

Evaluating the impact of scenario-based high-fidelity patient simulation on academic metrics of student success.

Despite the ongoing nursing shortage, nurse educators are responsible for preparing students to practice in highly complex health care systems. As nurse educators explore new learning strategies to support an increase in student admissions, they must also evaluate the impact of these strategies on the quality of the educational experience. The study reported here evaluated the impact of scenario-based, high-fidelity patient simulation used to increase student admissions in an associate degree and baccalaureate nursing program in north-central Texas upon students' sense of their own clinical competence, graduating grade point average (GPA), and performance on standardized exit examinations. These are measures commonly used by nurse educators as metrics of success.

A practical approach to monitoring recovery: development of a perceived recovery status scale.

The aim of this study was to develop and test the practical utility of a perceived recovery status (PRS) scale. Sixteen volunteers (8 men, 8 women) performed 4 bouts of high-intensity intermittent sprint exercise. After completion of the baseline trial, in a repeated-measures design, subjects were given variable counterbalanced recovery periods of 24, 48, and 72 hours whereupon they repeated an identical intermittent exercise protocol. After a warm-up period, but before beginning each subsequent bout of intermittent sprinting, each individual provided their perceived level of recovery with a newly developed PRS scale. Similar to perceived exertion during exercise, PRS was based on subjective feelings. The utility of the PRS scale was assessed by measuring the level of agreement of an individual's perceived recovery relative to their performance during the exercise bout. Perceived recovery status and change (both positive and negative) in sprint performance during multiple bouts of repeated sprint exercise were moderately negative correlated (r = -0.63). Additionally, subjects were able to accurately assess level of recovery using the PRS scale indicated by correspondence with negative and positive changes in total sprint time relative to their previous session. The ability to detect changes in performance using a noninvasive psychobiological tool to identify differences in performance was independent of other psychological and physiological markers measured during testing, because there were no differences (p > 0.05) among ratings of perceived exertion (RPE), heart rate, blood lactate concentration, or session RPE values among any of the performance trials. Although further study is needed, current results indicate a subjective approach may be an effective means for assessing recovery from day to day, at least under similar conditions.

Evaluation of a carbon dioxide personal cooling device for workers in hot environments.

This study tested the effectiveness of a carbon dioxide cooling device in reducing heat strain for workers in a hot and humid environment. Ten participants completed two trials in an environment of 30 degrees C WBGT (75% relative humidity) with a novel liquid carbon dioxide cooling shirt (CC) or no cooling (NC) in a randomized order. Mean time-weighted workload for each individual equaled 465 W (400 Kcals. h(-1)). In the CC condition, the work time was significantly increased by 32% (97 +/- 36 min) compared with NC (74 +/- 26 min) (p < 0.05). There was no significant difference in mean skin temperature over the trials. Rectal temperature (T(re)) was significantly different after 50 min (p < 0.05). Mean heart rate, the delta T(re) increase rate, and heat storage at 55 min (last point with n = 8) were significantly lower in CC (p < 0.05). Overall heat storage was 54 +/- 41 W and 72 +/- 40 W for CC and NC, respectively (p < 0.05). Participants also indicated favorable subjective responses for CC vs. NC (p < 0.05). These findings suggest that this novel cooling device would effectively attenuate heat strain and increase work productivity for personnel working in a hot and humid environment. Practical aspects of use such as cost, convenience, weight, cooling duration, and rise in ambient CO(2) concentration in confined spaces must also be considered.

Rasch measurement using dichotomous scoring.

The Rasch measurement model using dichotomous scoring of item response data from a newly created Mobility Scale administered to elderly independent living individuals is presented. The dichotomous scoring model, item calibration, person calibration, logit scale, normative scale score, reliability, and validity are explained. Results indicated that additional activity statements need to be written and tested to improve the Mobility Scale instrument.

The heterogeneous pain personality: diverse coping styles among sufferers of chronic pain.

The utility of personality assessment in chronic pain populations can be greatly enhanced with the understanding of risk assessment and the heterogeneous nature of at-risk personality types. Simplistic, unidimensional notions of risk have not been useful in assessing psychosocial and functional impairment in those with chronic pain syndromes. Previous literature suggests that certain combinations of psychometric scales, as opposed to individual scales, may be more useful in predicting the multiplicity of factors associated with functional disability among chronic pain patients. A hierarchical cluster analysis was performed on the 8 coping scales of the Millon Behavioral Health Inventory. Analyses revealed 3 distinct groups. The first cluster, termed repressors, exhibited high introversive and cooperative scales, and low forceful scales. The second cluster, termed amplifiers, exhibited high inhibited and sensitive scales. The third cluster, termed social copers, exhibited high confident and social scales. Analyses of these 3 clusters with regard to measures of psychopathology (Minnesota Multiphasic Personality Inventory II), depression (Beck Depression Inventory), functional impairment (Chronic Illness Problem Inventory), and other measures (Multidimensional Pain Inventory) resulted in significantly different levels of psychosocial and functional impairment. These clusters identified those patients who are at risk for nondisclosure of psychosocial dysfunction, those who are most emotionally distressed, and those who are most likely to comply with treatment. Consequently, such classifications identify psychosocial variables that will dictate a differential treatment approach and thus have potentially important clinical applications.