Quantifying Coloring Skills Among Preschoolers.

IMPORTANCE: Coloring is popular with preschool children and reveals their developmental state. However, interpreting coloring performances is challenging because descriptive and subjective evaluations are commonly used with large variations. OBJECTIVE: To develop a scoring method to objectively quantify children's coloring skills. DESIGN: Colored blank train templates were analyzed using four indicators (entropy, complexity, coloring outside the lines, and unexpected blank areas) to form a summed score. SETTING: Kindergarten in a urban city (Tainan, Taiwan). PARTICIPANTS: Two hundred thirty-nine typically developing children ages 3 to 6 yr. OUTCOME AND MEASURES: A newly developed method to assess coloring skill on the basis of a colored picture of a train. RESULTS: The summed score exhibited good internal consistency (Cronbach's α = .80), discriminative validity (p = .04), convergent validity (rs = .66 and .59 with age and visual-motor integration), and acceptable factorial validity (comparative fit index = .99, standardized root-mean-square residual = .04, and root-mean-square error of approximation = .13). Moreover, three coloring patterns (mature, transitional, and immature) were identified. CONCLUSIONS AND RELEVANCE: The new method provides objective, reliable, and valid scores representing coloring skills in typically developing children. In addition, the coloring patterns can be recognized. This method can be used to facilitate comparisons of children's coloring skills with peers and provide valuable insight into children's development. Plain-Language Summary: This study proposes a new method to objectively quantify children's coloring skills with sound reliability and validity in typically developing children. The method can be used to evaluate children's coloring skills and patterns to shed light on their developmental stages.

Validation of the Machine Learning-Based Stroke Impact Scale With a Cross-Cultural Sample.

IMPORTANCE: The machine learning-based Stroke Impact Scale (ML-SIS) is an efficient short-form measure that uses 28 items to provide domain scores comparable to those of the original 59-item Stroke Impact Scale-Third Edition (SIS 3.0). However, its utility is largely unknown because it has not been cross-validated with an independent sample. OBJECTIVE: To examine the ML-SIS's comparability and test-retest reliability with that of the original SIS 3.0 in an independent sample of people with stroke. DESIGN: Comparability was examined with the coefficient of determination (R2), mean absolute error, and root-mean-square error (RMSE). Test-retest reliability was examined using the intraclass correlation coefficient (ICC). SETTING: Five hospitals in Taiwan. PARTICIPANTS: Data of 263 persons with stroke were extracted from a previous study; 144 completed repeated assessments after a 2-wk interval. RESULTS: High R2 (.87-.95) and low mean absolute error or RMSE (about 2.4 and 3.3) of the domain scores, except for the Emotion scores (R2 = .08), supported the comparability of the two measures. Similar ICC values (.39-.87 vs. .46-.87) were found between the two measures, suggesting that the ML-SIS is as reliable as the SIS 3.0. CONCLUSIONS AND RELEVANCE: The ML-SIS provides scores mostly identical to those of the original measure, with similar test-retest reliability, except for the Emotion domain. Thus, it is a promising alternative that can be used to lessen the burden of routine assessments and provide scores comparable to those of the original SIS 3.0. Plain-Language Summary: The machine learning-based Stroke Impact Scale (ML-SIS) is as reliable as the original Stroke Impact Scale-Third Edition, except for the Emotion domain. Thus, the ML-SIS can be used to improve the efficiency of clinical assessments and also relieve the burden on people with stroke who are completing the assessments.

Development of a Berg Balance Scale Short-Form Using a Machine Learning Approach in Patients With Stroke.

BACKGROUND AND PURPOSE: The Berg Balance Scale (BBS) is frequently used in routine clinical care and research settings and has good psychometric properties. This study was conducted to develop a short form of the BBS using a machine learning approach (BBS-ML). METHODS: Data of 408 individuals poststroke were extracted from a published database. The initial (ie, 4-, 5-, 6-, 7-, and 8-item) versions were constructed by selecting top-ranked items based on the feature selection algorithm in the artificial neural network model. The final version of the BBS-ML was chosen by selecting the short form that used a smaller number of items to achieve a higher predictive power R2 , a lower 95% limit of agreement (LoA), and an adequate possible scoring point (PSP). An independent sample of 226 persons with stroke was used for external validation. RESULTS: The R2 values for the initial 4-, 5-, 6-, 7-, and 8-item short forms were 0.93, 0.95, 0.97, 0.97, and 0.97, respectively. The 95% LoAs were 14.2, 12.2, 9.7, 9.6, and 8.9, respectively. The PSPs were 25, 35, 34, 35, and 36, respectively. The 6-item version was selected as the final BBS-ML. Preliminary external validation supported its performance in an independent sample of persons with stroke ( R2 = 0.99, LoA = 10.6, PSP = 37). DISCUSSION AND CONCLUSIONS: The BBS-ML seems to be a promising short-form alternative to improve administrative efficiency. Future research is needed to examine the psychometric properties and clinical usage of the 6-item BBS-ML in various settings and samples.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A402 ).

Development of a 13-item Short Form for Fugl-Meyer Assessment of Upper Extremity Scale Using a Machine Learning Approach.

OBJECTIVE: To develop and validate a short form of the Fugl-Meyer Assessment of Upper Extremity Scale (FMA-UE) using a machine learning approach (FMA-UE-ML). In addition, scores of items not included in the FMA-UE-ML were predicted. DESIGN: Secondary data from a previous study, which assessed individuals post-stroke using the FMA-UE at 4 time points: 5-30 days post-stroke screen, 2-month post-stroke baseline assessment, 6-month post-stroke assessment, and 12-month post-stroke assessment. SETTING: Rehabilitation units in hospitals. PARTICIPANTS: A total of 408 individuals post-stroke (N=408). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The 30-item FMA-UE. RESULTS: We established 29 candidate versions of the FMA-UE-ML with different numbers of items, from 1 to 29, and examined their concurrent validity and responsiveness. We found that the responsiveness of the candidate versions obviously declined when the number of items was less than 13. Thus, the 13-item version was selected as the FMA-UE-ML. The concurrent validity was good (intra-class correlation coefficients ≥0.99). The standardized response means of the FMA-UE-ML and FMA-UE were 0.54-0.88 and 0.52-0.91, respectively. The Pearson's rs between the change scores of the FMA-UE-ML and those of the FMA-UE were 0.96-0.98. The predicted item scores had acceptable to good accuracy (Kappa=0.50-0.92). CONCLUSIONS: The FMA-UE-ML seems a promising short form to improve administrative efficiency while retaining good concurrent validity and responsiveness. In addition, the FAM-UE-ML can provide all item scores of the FMA-UE for users.

Test-Retest Reliability and Responsiveness of the Computerized Adaptive Test of Social Functioning in Persons With Stroke.

OBJECTIVE: To examine the test-retest reliability, minimal detectable change (MDC), responsiveness, and efficiency of the Computerized Adaptive Test of Social Functioning (Social-CAT) in patients with stroke. DESIGN: Repeated-assessments design. SETTING: A department of rehabilitation of a medical center. PARTICIPANTS: In total, 31 patients with chronic stroke and 65 patients with subacute stroke were recruited. INTERVENTION: Not available. MAIN OUTCOME MEASURE: Social-CAT. RESULTS: The Social-CAT showed acceptable test-retest reliability (intraclass correlation coefficient, 0.80) and small random measurement error (MDC%: 18.0%). However, heteroscedasticity was found (r between the means and the absolute change scores: 0.32), so the MDC% adjusted cut-off score is recommended for determining real improvement. Regarding responsiveness, the Social-CAT showed large differences (Kazis' effect size and standardized mean response: 1.15 and 1.09, respectively) in subacute patients. Regarding efficiency, the Social-CAT required an average of 5 items and less than 2 minutes for completion. CONCLUSIONS: Our findings indicate that the Social-CAT is a reliable and efficient measure with good test-retest reliability, small random measurement error, and good responsiveness. Thus, the Social-CAT is a useful outcome measure for routine monitoring of the changes in social function of patients with stroke.

Using Machine Learning to Develop a Short-Form Measure Assessing 5 Functions in Patients With Stroke.

OBJECTIVE: This study aimed to develop and validate a machine learning-based short measure to assess 5 functions (the ML-5F) (activities of daily living [ADL], balance, upper extremity [UE] and lower extremity [LE] motor function, and mobility) in patients with stroke. DESIGN: Secondary data from a previous study. A follow-up study assessed patients with stroke using the Barthel Index (BI), Postural Assessment Scale for Stroke (PASS), and Stroke Rehabilitation Assessment of Movement (STREAM) at hospital admission and discharge. SETTING: A rehabilitation unit in a medical center. PARTICIPANTS: Patients (N=307) with stroke. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The BI, PASS, and STREAM. RESULTS: A machine learning algorithm, Extreme Gradient Boosting, was used to select 15 items from the BI, PASS, and STREAM, and transformed the raw scores of the selected items into the scores of the ML-5F. The ML-5F demonstrated good concurrent validity (Pearson's r, 0.88-0.98) and responsiveness (standardized response mean, 0.28-1.01). CONCLUSIONS: The ML-5F comprises only 15 items but demonstrates sufficient concurrent validity and responsiveness to assess ADL, balance, UE and LE functions, and mobility in patients with stroke. The ML-5F shows great potential as an efficient outcome measure in clinical settings.

High levels of screen time were associated with increased probabilities of lagged development in 3-year-old children.

AIM: This study determined whether higher screen time was associated with the development of 3-year-old children in Taiwan. It also examined whether differences would be found between television and other screen-based media in the probability of lagged development. METHODS: We examined 2139 children aged 3 years and their parents. The association between daily screen time was assessed using multiple logistic regression analysis. All the odds ratios (ORs) were calculated using the rates of lagged developmental achievement, with the group who used screens for less than 1 h a day as the reference category. Screen time comprised television and other screen-based media, such as smartphones, touch screens, computers and laptops. RESULTS: Children who used screens for more than 3 h per day had the lowest developmental scores and highest probabilities of lagged development. The children who used other screen-based media for more than 1 h per day had greater probabilities of lagged developmental achievements (ORs 1.85-4.98, all p < 0.05) than those who watched television for the same amount of time (OR 1.41-2.77, all p < 0.05). CONCLUSION: Increased screen time was associated with higher probabilities of lagged developmental achievement in multiple development domains in 3-year-old children, particularly other screen-based media.

Development of a Rasch-Calibrated Test for Assessing Implied Meaning in Patients With Schizophrenia.

IMPORTANCE: Patients with schizophrenia tend to have severe deficits in theory of mind, which may limit their interpretation of others' behaviors and thereby hamper social participation. Commonly used measures of theory of mind assess the ability to understand various social situations (e.g., implied meaning or hinting, faux pas), but these measures do not yield valid, reliable, and gender unbiased results to inform interventions for managing theory-of-mind deficits. We used understanding of implied meaning, which appears to be a unidimensional construct highly correlated with social competence, as a promising starting point to develop a theory-of-mind assessment. OBJECTIVE: To develop a Rasch-calibrated computerized test of implied meaning. DESIGN: Cross-sectional design. SETTING: Psychiatric hospitals and community. PARTICIPANTS: 344 participants (240 patients with schizophrenia and 104 healthy adults). RESULTS: We initially developed 27 items for the Computerized Implied Meaning Test. After inappropriate items (12 misfit items and 1 gender-biased item) were removed, the remaining 14 items showed acceptable model fit to the Rasch model (infit = 0.84-1.16; outfit = 0.65-1.34) and the one-factor model (comparative fit index = .91, standardized root mean square residual = .05, root-mean-square error of approximation = .08). Most patients (81.7%) achieved individual Rasch reliability of ≥.90. Healthy participants performed significantly better on the test than patients with schizophrenia (Cohen's d = 2.5, p < .001). CONCLUSIONS AND RELEVANCE: Our preliminary findings suggest that the Computerized Implied Meaning Test may provide reliable, valid, and gender-unbiased results for patients with schizophrenia. What This Article Adds: We developed a new measure for assessing theory-of-mind ability in patients with schizophrenia that consists of items targeting the understanding of implied meaning. Preliminary findings suggest that the Computerized Implied Meaning Test is reliable, valid, and gender unbiased and may be used in evaluating patients' theory-of-mind deficits and relevant factors.

Development of a Short-Form Stroke Impact Scale Using a Machine Learning Algorithm for Patients at the Subacute Stage.

IMPORTANCE: Several short forms of the Stroke Impact Scale Version 3.0 (SIS 3.0) have been proposed in order to decrease its administration time of about 20 min. However, none of the short-form scores are comparable to those of the original measure. OBJECTIVE: To develop a short-form SIS 3.0 using a machine learning algorithm (ML-SIS). DESIGN: We developed the ML-SIS in three stages. First, we calculated the frequencies of items having the highest contribution to predicting the original domain scores across 50 deep neural networks. Second, we iteratively selected the items showing the highest frequency until the coefficient of determination (R2) of each domain was ≥.90. Third, we examined the comparability and concurrent and convergent validity of the ML-SIS. SETTING: Hospitals. PARTICIPANTS: We extracted complete data for 1,010 patients from an existing data set. RESULTS: Twenty-eight items were selected for the ML-SIS. High average R2s (.90-.96) and small average residuals (mean absolute errors and root-mean-square errors = 0.49-2.84) indicate good comparability. High correlations (rs = .95-.98) between the eight domain scores of the ML-SIS and the SIS 3.0 indicate sufficient concurrent validity. Similar interdomain correlations between the two measures indicate satisfactory convergent validity. CONCLUSIONS AND RELEVANCE: The ML-SIS uses about half of the items in the SIS 3.0, has an estimated administration time of 10 min, and provides valid scores comparable to those of the original measure. Thus, the ML-SIS may be an efficient alternative to the SIS 3.0. What This Article Adds: The ML-SIS, a short form of the SIS 3.0 developed using a machine learning algorithm, shows good potential to be an efficient and informative measure for clinical settings, providing scores that are valid and comparable to those of the original measure.

Development of the CAT-FER: A Computerized Adaptive Test of Facial Emotion Recognition for Adults With Schizophrenia.

IMPORTANCE: The most frequently used measures of facial emotion recognition (FER) are insufficiently comprehensive, reliable, valid, and efficient; moreover, the impact of gender on scoring has not been controlled. OBJECTIVE: To develop a computerized adaptive test of FER for adults with schizophrenia. DESIGN: First, we selected photographs from a published database. Second, items that fitted well to a Rasch model were used to form the item bank. Third and last, we determined the best administration mode for prospective users to achieve both high reliability and efficiency. SETTING: Psychiatric hospitals and the community. PARTICIPANTS: Adults living with schizophrenia (n = 351) and adults without diagnosed mental illness (n = 101). RESULTS: After removal of misfit items (infit or outfit ≥1.4), the remaining 165 items were selected to form an item bank. Among them, 39 showed severe gender bias, so the item difficulties were adjusted accordingly. On the basis of the item bank, two administration modes were recommended for prospective users. The reliable mode required approximately 128 items (nearly 20 min) to achieve reliability (.72-.81), similar to that of the entire item bank. The efficient mode required approximately 73 items (approximate 11 min) to provide acceptable reliability (.69-.73) for the seven domain scores. CONCLUSIONS AND RELEVANCE: Our newly developed measure provides comprehensive, valid, and unbiased (to examinees' gender) assessments of FER in adults living with schizophrenia. In addition, the administration modes can be flexibly changed to optimize the reliability or efficiency for prospective users. WHAT THIS ARTICLE ADDS: This newly developed FER measure can help occupational therapists identify deficits in recognizing specific basic emotions and plan corresponding interventions to manage the impact on their clients' social functions.

Cross-Validation of the Factorial Validity of the Stroke Impact Scale 3.0 in Patients With Stroke.

IMPORTANCE: The Stroke Impact Scale 3.0 appears to be a promising outcome measure of health-related quality of life (HRQOL) for clients with stroke. However, because the factorial validity of the Stroke Impact Scale 3.0 remains unclear, its validity is limited. OBJECTIVE: To examine the underlying structure of the Stroke Impact Scale 3.0 by comparing the currently available eight- and four-domain structures simultaneously. DESIGN: Secondary data analysis of responses to the Stroke Impact Scale 3.0 from a previous psychometric validation study. SETTING: Five general hospitals in northern and southern Taiwan. PARTICIPANTS: Two hundred sixty-three patients with stroke from rehabilitation wards (inpatients) and neurology and rehabilitation clinics (outpatients). OUTCOMES AND MEASURES: Confirmatory factor analysis was used to examine the eight- and four-domain structures of the Stroke Impact Scale 3.0. Four fit indices were considered simultaneously to examine the model fits of both structures. RESULTS: The eight- and four-domain structures of the Stroke Impact Scale 3.0 were not supported by all four indices (χ²/df = 2.7 and 5.0, comparative fit index = .79 and .86, root mean square error of approximation = .08 and .12, standardized root mean square residual = .08 and .08, respectively). The unidimensionality of each domain in the two structures was not supported. CONCLUSIONS AND RELEVANCE: Neither the eight- nor the four-domain structure of the Stroke Impact Scale 3.0 was supported, suggesting that scores may not provide valid assessments of HRQOL in clients with stroke. Further modification and validation of the Stroke Impact Scale 3.0 are warranted. WHAT THIS ARTICLE ADDS: Our findings suggest that the eight- and four-domain scores of the Stroke Impact Scale 3.0 may not be valid. Therefore, until more supporting evidence is developed, these scores should be interpreted cautiously in regard to clients' HRQOL; alternatively, other measures could be used.

Development of a Computerized Adaptive Testing System for Assessing Social Knowledge in People With Schizophrenia.

IMPORTANCE: A psychometrically sound measure of social knowledge (SK) is necessary to assess people with schizophrenia because they tend to have moderate to severe deficits in SK. OBJECTIVE: To develop a computerized adaptive test (CAT) for assessing SK in people with schizophrenia. DESIGN: Two phases, consisting of (1) development and validation of an SK item bank and (2) determination of the best stopping rules for the CAT. SETTING: Two psychiatric hospitals. PARTICIPANTS: Two hundred thirty-six people diagnosed with schizophrenia through convenience sampling. MEASURE: Computerized Adaptive Test-Social Knowledge (CAT-SK). RESULTS: The SK items were examined using Rasch analysis. A CAT simulation was performed to determine the best set of stopping rules for achieving high reliability and efficiency. After unsuitable items were removed, 71 items remained with acceptable model fit (infit and outfit mean square <1.4) and no gender bias. Two suboptimal alternative sets of rules were identified. The most efficient set used 21 items to achieve acceptable Rasch reliability (.81). The most reliable set used 40 items to achieve satisfactory Rasch reliability (.88). High correlations (r > .93) between CAT-SK scores and scores on the SK item bank support the concurrent validity of the CAT-SK. CONCLUSIONS AND RELEVANCE: The CAT-SK appears to be a valid assessment that can provide reliable or efficient measures of SK. If high reliability is needed, examiners can adopt the most reliable set of 40 items. If efficiency is the primary concern, they can adopt the most efficient set of 21 items. WHAT THIS ARTICLE ADDS: The CAT-SK is a valid measure of SK with flexibility to meet examiners' needs.

Development of a Computerized Adaptive Testing System for Assessing 5 Functions in Patients with Stroke: A Simulation and Validation Study.

OBJECTIVE: The authors aimed to develop and validate the Computerized Adaptive Testing System for Assessing 5 Functions in Patients with Stroke (CAT-5F) based on the Barthel Index (BI), Postural Assessment Scale for Stroke patients (PASS), and Stroke Rehabilitation Assessment of Movement (STREAM) to improve the efficiency of assessment. The purposes of the CAT-5F assessment are to describe patients' levels of impairments or disabilities in the 5 functions and to serve as an outcome measure in patients with stroke. DESIGN: This is a data-mining study based on data from a previous study using simulation analysis to develop and validate the CAT-5F. SETTING: One rehabilitation unit in a medical center in Taiwan served as the setting for this study. PARTICIPANTS: Data were retrieved from totals of 540 (initial assessment) and 309 (discharge assessment) participants with stroke assessed in a previous study. The assessment data (N=540) were from the BI, PASS, and STREAM. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The outcome measures for this study were from BI, PASS, and STREAM. RESULTS: The CAT-5F using the optimal stopping rule (limited reliability increased <0.010) had good Rasch reliability across the 5 functions (0.86-0.96) and needed 12.7 items, on average, for the whole administration. The concurrent validity (Pearson product-moment correlation coefficient, r=0.91-0.96) and responsiveness (standardized response mean=0.33-0.91) of the CAT-5F were sufficient in the patients. CONCLUSION: The CAT-5F has sufficient administrative efficiency, reliability, concurrent validity, and responsiveness to simultaneously assess basic activities of daily living, postural control, upper extremity/lower extremity motor functions, and mobility in patients with stroke.

Group- and Individual-Level Responsiveness of the 3-Point Berg Balance Scale and 3-Point Postural Assessment Scale for Stroke Patients.

OBJECTIVES: To examine both group- and individual-level responsiveness of the 3-point Berg Balance Scale (BBS-3P) and 3-point Postural Assessment Scale for Stroke Patients (PASS-3P) in patients with stroke, and to compare the responsiveness of both 3-point measures versus their original measures (Berg Balance Scale [BBS] and Postural Assessment Scale for Stroke Patients [PASS]) and their short forms (short-form Berg Balance Scale [SFBBS] and short-form Postural Assessment Scale for Stroke Patients [SFPASS]) and between the BBS-3P and PASS-3P. DESIGN: Data were retrieved from a previous study wherein 212 patients were assessed at 14 and 30 days after stroke with the BBS and PASS. SETTING: Medical center. PARTICIPANTS: Patients (N=212) with first onset of stroke within 14 days before hospitalization. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Group-level responsiveness was examined by the standardized response mean (SRM), and individual-level responsiveness was examined by the proportion of patients whose change scores exceeded the minimal detectable change of each measure. The responsiveness was compared using the bootstrap approach. RESULTS: The BBS-3P and PASS-3P had good group-level (SRM, .60 and SRM, .56, respectively) and individual-level (48.1% and 44.8% of the patients with significant improvement, respectively) responsiveness. Bootstrap analyses showed that the BBS-3P generally had superior responsiveness to the BBS and SFBBS, and the PASS-3P had similar responsiveness to the PASS and SFPASS. The BBS-3P and PASS-3P were equally responsive to both group and individual change. CONCLUSIONS: The responsiveness of the BBS-3P and PASS-3P was comparable or superior to those of the original and short-form measures. We recommend the BBS-3P and PASS-3P as responsive outcome measures of balance for individuals with stroke.

Development of a Computerized Adaptive Testing System of the Functional Assessment of Stroke.

OBJECTIVE: To develop a computerized adaptive testing system of the Functional Assessment of Stroke (CAT-FAS) to assess upper- and lower-extremity (UE/LE) motor function, postural control, and basic activities of daily living with optimal efficiency and without sacrificing psychometric properties in patients with stroke. DESIGN: Simulation study. SETTING: One rehabilitation unit in a medical center. PARTICIPANTS: Patients with subacute stroke (N=301; mean age, 67.3±10.9; intracranial infarction, 74.5%). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The UE and LE subscales of the Fugl-Meyer Assessment, Postural Assessment Scale for Stroke Patients, and Barthel Index. RESULTS: The CAT-FAS adopting the optimal stopping rule (limited reliability increase of <.010) had good Rasch reliability across the 4 domains (.88-.93) and needed few items for the whole administration (8.5 items on average). The concurrent validity (CAT-FAS vs original tests, Pearson r=.91-.95) and responsiveness (standardized response mean, .65-.76) of the CAT-FAS were good in patients with stroke. CONCLUSIONS: We developed the CAT-FAS, and our results support that the CAT-FAS has sufficient efficiency, reliability, concurrent validity, and responsiveness in patients with stroke. The CAT-FAS can be used to simultaneously assess patients' functions of UE, LE, postural control, and basic activities of daily living using, on average, no more than 10 items; this efficiency is useful in reducing the assessment burdens for both clinicians and patients.

Development of a Social Functioning Assessment Using Computerized Adaptive Testing for Patients With Stroke.

OBJECTIVE: To develop a computerized adaptive test of social functioning (Social-CAT) for patients with stroke. DESIGN: This study contained 2 phases. First, a unidimensional item bank was formed using social-related items with sufficient item fit (ie, infit and outfit mean square [MNSQ]). The social-related items were selected from 3 commonly used patient-reported quality-of-life measures. Items with differential item functioning (DIF) of sex were deleted. Second, we performed simulations to determine the best set of stopping rules with both high reliability and efficiency. The participants' responses to the items were extracted from a previous study. SETTING: Rehabilitation wards and departments of rehabilitation/neurology of 5 general hospitals. PARTICIPANTS: Patients (N=263) with stroke (47.1% were inpatients). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Social-CAT. RESULTS: The unidimensionality of the 24 selected items was supported (infit and outfit MNSQs =0.8-1.2). One item had DIF of sex and was deleted. The item bank was composed of the remaining 23 items. With the best set of stopping rules (person reliability ≥.90 or limited reliability increased ≤.001), the Social-CAT used on average 10 items to achieve sufficient reliability (average person reliability =.88; 81.0% of the patients with reliability ≥.90). CONCLUSIONS: The Social-CAT appears to be a unidimensional measure with acceptable reliability and efficiency, and it could be useful for both clinicians and patients in time-pressed clinical settings.

Peroxisome proliferator-activated receptor activating hypoglycemic effect of Gardenia jasminoides Ellis aqueous extract and improvement of insulin sensitivity in steroid induced insulin resistant rats.

BACKGROUND: The active components of Gardenia (Gardenia jasminoides Ellis, GJ) exhibit a hypoglycemic effect by improving insulin secretion and lowering plasma lipids. In the present study, we fed a water extract of gardenia to steroid-induced insulin-resistant (SIIR) rats and observed changes in signaling proteins in order to elucidate the mechanisms of the insulin-sensitizing effect of GJ and evaluate its possibility as an insulin-sensitizing agent. METHODS: Normal Wistar rats were randomly divided into a control group (i.e., saline) and experimental groups (GJ 100 and 200 mg/kg). Blood samples were taken at 0, 30, and 60 min for plasma glucose assay in order to determine the optimal dose to induce the hypoglycemic effect. SIIR rats were then randomly divided into a control group (i.e., saline) and an experimental group (optimal dose of gardenia extract) to observe the insulin-sensitizing effect of the extract. Finally, western blot analysis was performed to detect intracellular signaling proteins to elucidate the mechanisms of the insulin-sensitization effect of GJ. RESULTS: The normal Wistar rats in the GJ 200 mg/kg group exhibited significant hypoglycemic activity. Meanwhile, the SIIR rats had higher plasma glucose levels than normal rats. There was no obvious change in insulin level, but the insulin sensitivity index and homeostasis model assessment index were significantly elevated. Meanwhile, a significant hypoglycemic effect was observed with GJ 200 mg/kg. In addition, intracellular signaling proteins including insulin receptor substrate-1 (IRS-1) and peroxisome proliferator-activated receptor (PPARγ) were elevated in muscle cells. CONCLUSIONS: The optimal dose of GJ aqueous extract of 200 mg/kg exerts a PPARγ-activating hypoglycemic effect and improves insulin resistance in SIIR rats. Therefore, it is a potential insulin-sensitizing agent in type 2 diabetes mellitus with insulin resistance.

Interpreting the results of explicit and applied theory of mind collectively in autistic children: A solution from Rasch analysis.

LAY ABSTRACT: Theory of mind is an ability to infer others' mental states, which is a foundation for generating appropriate social responses. Theory of mind can be conceptually divided into two related but distinguishable constructs: explicit theory of mind (conceptual knowledge/information about others' mental states) and applied theory of mind (the ability to use theory of mind skills in real-life contexts). Although these two theory of mind scores can be described by the percentages of children in the early, basic, and advanced developmental stages, the resulting information may not be sufficient to determine the corresponding relationships between these two theory of mind constructs or identify children with mismatched theory of mind abilities (e.g. children who have difficulty in effectively applying their theory of mind knowledge in real-life contexts). To resolve these limitations, methods for simultaneously interpreting the relationships between the two theory of mind scores are proposed. Based on the findings, each applied theory of mind score can reflect multiple scores of explicit theory of mind. In particular, the results do not take measurement error into consideration, which would make them more ambiguous. Therefore, the scores of applied theory of mind should be interpreted carefully, given that children who have the same applied theory of mind score may actually have high or low explicit theory of mind. Regarding the method for joint interpretation, cutoff scores were selected to identify children who have mismatched theory of mind abilities (high explicit theory of mind with low applied theory of mind or low explicit theory of mind with high applied theory of mind) and determine the priority for interventions.

Enhancing Cordycepin in Functional Porridge through Rice Varietal Fermentation with Cordyceps militaris (Ascomycetes) and Utilizing Non-Targeted Metabolomics for Process Enhancement.

Cordyceps militaris, a medicinal fungus rich in cordycepin, shows promise in treating diseases such as cancer, respiratory issues, and COVID-19. This study examines the impact of different Taiwanese rice varieties on its solid-state fermentation, focusing on optimizing cordycepin production. The results indicated that the cordycepin yield was indeed affected by the type of rice used. In terms of the fruiting bodies, germ rice resulted in the highest yield (13.1 ± 0.36 mg/g), followed by brown rice (11.9 ± 0.26 mg/g). In the rice culture medium (RCM), brown rice led to the highest yield (4.77 ± 0.06 mg/g). Using gas chromatography-mass spectrometry and untargeted metabolomics, the study identifies four key volatile components linked to cordycepin, providing insights into developing functional rice porridge products. These findings are significant for advancing cordycepin mass production and offering dietary options for older individuals.

Developing an Accumulative Assessment System of Upper Extremity Motor Function in Patients With Stroke Using Deep Learning.

OBJECTIVE: The Fugl-Meyer assessment for upper extremity (FMA-UE) is a measure for assessing upper extremity motor function in patients with stroke. However, the considerable administration time of the assessment decreases its feasibility. This study aimed to develop an accumulative assessment system of upper extremity motor function (AAS-UE) based on the FMA-UE to improve administrative efficiency while retaining sufficient psychometric properties. METHODS: The study used secondary data from 3 previous studies having FMA-UE datasets, including 2 follow-up studies for subacute stroke individuals and 1 test-retest study for individuals with chronic stroke. The AAS-UE adopted deep learning algorithms to use patients' prior information (ie, the FMA-UE scores in previous assessments, time interval of adjacent assessments, and chronicity of stroke) to select a short and personalized item set for the following assessment items and reproduce their FMA-UE scores. RESULTS: Our data included a total of 682 patients after stroke. The AAS-UE administered 10 different items for each patient. The AAS-UE demonstrated good concurrent validity (r = 0.97-0.99 with the FMA-UE), high test-retest reliability (intra-class correlation coefficient = 0.96), low random measurement error (percentage of minimal detectable change = 15.6%), good group-level responsiveness (standardized response mean = 0.65-1.07), and good individual-level responsiveness (30.5%-53.2% of patients showed significant improvement). These psychometric properties were comparable to those of the FMA-UE. CONCLUSION: The AAS-UE uses an innovative assessment method, which makes good use of patients' prior information to achieve administrative efficiency with good psychometric properties. IMPACT: This study demonstrates a new assessment method to improve administrative efficiency while retaining psychometric properties, especially individual-level responsiveness and random measurement error, by making good use of patients' basic information and medical records.