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.

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.

Developing a machine learning-based short form of the positive and negative syndrome scale.

BACKGROUND AND HYPOTHESIS: The Positive and Negative Syndrome Scale (PANSS) consists of 30 items and takes up to 50 minutes to administer and score. Therefore, this study aimed to develop and validate a machine learning-based short form of the PANSS (PANSS-MLSF) that reproduces the PANSS scores. Moreover, the PANSS-MLSF estimated the removed-item scores. STUDY DESIGN: The PANSS-MLSF was developed using an artificial neural network, and the removed-item scores were estimated using the eXtreme Gradient Boosting classifier algorithm. The reliability of the PANSS-MLSF was examined using Cronbach's alpha. The concurrent validity was examined by the association (Pearson's r) between the PANSS-MLSF and the PANSS. The convergent validity was examined by the association (Pearson's r) between the PANSS-MLSF and the Clinical Global Impression-Severity, Mini-Mental State Examination, and Lawton Instrumental Activities of Daily Living Scale. The agreement of the estimated removed-item scores with their original scores was examined using Cohen's kappa. STUDY RESULTS: Our analysis included data from 573 patients with moderate severity. The two versions of the PANSS-MLSF comprised 15 items and 9 items were proposed. The PANSS-MLSF scores were similar to the PANSS scores (mean squared error=2.6-24.4 points). The reliability, concurrent validity, and convergent validity of the PANSS-MLSF were good. Moderate to good agreement between the estimated removed-item scores and the original item scores was found in 60% of the removed items. CONCLUSION: The PANSS-MLSF offers a viable way to reduce PANSS administration time, maintain score comparability, uphold reliability and validity, and even estimate scores for the removed items.

Leisure Participation for Mental Health Promotion in Later Life: A Six-Year Longitudinal Study.

Engaging in leisure activities is essential for mental health in older adults. This longitudinal study (n = 1,101, mean age = 69.20 ± 6.23 years at baseline) examined the associations between leisure participation and mental health over 6 years in three waves: 2016, 2018, and 2020. Pearson's correlation analyses and generalized estimating equations were performed for data analyses. The frequency of participation in physical and social activities was significantly positively associated with happiness, life satisfaction, and self-rated health, and significantly negatively associated with depression. Passive activities were significantly positively associated with happiness, life satisfaction, and self-rated health but not with depression. The time effect had no significant association with any mental health outcomes. These findings highlight the importance of leisure activities in promoting mental health among older adults. Policy makers should encourage older adults to engage in physical and social leisure activities.

Using Artificial Intelligence to Identify the Associations of Children's Performance of Coloring, Origami, and Copying Activities With Visual-Motor Integration.

IMPORTANCE: Performance of coloring, origami, and copying activities reflects children's visual-motor integration (VMI), but the levels of association remain unclear. OBJECTIVE: To use artificial intelligence (AI) to investigate associations of performance of coloring, origami, and copying activities with VMI. DESIGN: Cross-sectional study. SETTING: Kindergartens. PARTICIPANTS: A sample of 370 children (182 boys and 188 girls) in the second and third years of kindergarten. OUTCOMES AND MEASURES: Beery-Buktenica Developmental Test of Visual-Motor Integration, 6th Edition (VMI-6). RESULTS: Data for preschool children from an ongoing project were retrieved. AI models were trained to use photographs of activity products to predict total score on the VMI-6. R2 values were used to identify the variance in VMI-6 standardized scores explained by predicted scores from the activities. That is, R2 values reflected associations between activity performance and VMI. The R2 values for the combination of origami and copying were the largest (.390-.577). These R2 values were larger than those for each individual activity (.340-.473) and similar to those for the combination of all three activities (.400-.550). CONCLUSIONS AND RELEVANCE: Because moderate R2 values were found between performance of the three activity products and VMI, the three activities have high potential for use in identifying children's level of VMI or as teaching materials to facilitate the development of children's VMI. Furthermore, combining origami and copying activities is recommended for teachers and clinicians who need to address VMI. What This Article Adds: A combination of origami and copying activities had the strongest associations with children's VMI. Teachers and clinicians can use these two activities when addressing VMI development among preschool children.

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.

Machine learning-based brief version of the Caregiver-Teacher Report Form for preschoolers.

BACKGROUND: The Caregiver-Teacher Report Form of the Child Behavior Checklist for Ages 1½-5 (C-TRF) is a widely used checklist to identify emotional and behavioral problems in preschoolers. However, the 100-item C-TRF restricts its utility. AIMS: This study aimed to develop a machine learning-based short-form of the C-TRF (C-TRF-ML). METHODS AND PROCEDURES: Three steps were executed. First, we split the data into three datasets in a ratio of 3:1:1 for training, validation, and cross-validation, respectively. Second, we selected a shortened item set and trained a scoring algorithm using joint learning for classification and regression using the training dataset. Then, we evaluated the similarity of scores between the C-TRF-ML and the C-TRF by r-squared and weighted kappa values using the validation dataset. Third, we cross-validated the C-TRF-ML by calculating the r-squared and weighted kappa values using the cross-validation dataset. OUTCOMES AND RESULTS: Data of 363 children were analyzed. Thirty-six items of the C-TRF were retained. The r-squared values of C-TRF-ML scores were 0.86-0.96 in the cross-validation dataset. Weighted kappa values of the syndrome/problem grading were 0.72-0.94 in the cross-validation dataset. CONCLUSIONS AND IMPLICATIONS: The C-TRF-ML had about 60 % fewer items than the C-TRF but yielded comparable scores with the C-TRF.

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.

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.

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.

Error patterns of facial emotion recognition in patients with schizophrenia.

Error patterns of facial emotion recognition (FER) indicate how individuals misinterpret others' facial expressions, which helps clinicians to manage related deficits. However, previous investigations are limited and may have been biased due to methodological issues (e.g., no consideration of response bias). This study aimed to propose a detectability index (d') for adjusting response bias and examine the error patterns of FER in patients with schizophrenia. Responses to 168 photos showing seven basic emotions, obtained from 351 patients with schizophrenia and 101 healthy adults, were extracted from a previous study. The differences in the d's between the two groups (Δd') were calculated to examine the error patterns of FER among the seven emotions. The findings were generally overlapped with those identified by the traditional confusion matrix. Four error patterns were found. First, the patients were insensitive to some negative emotions (i.e., sadness [Δd' = 0.83] and fear [Δd' = 0.72]). Second, they misrecognized happy faces as showing negative emotions (e.g., disgust [Δd' = 0.43] and sadness [Δd' = 0.37]). Third, they misinterpreted surprised faces as all the other emotions (Δd' = 0.41-0.87), except neutral. Fourth, they confused some negative emotions (e.g., misrecognizing fear as anger [Δd' = 0.87]). Our findings suggest that patients with schizophrenia show four error patterns of FER compared to healthy adults. Accordingly, interventions could be selected to improve their sensitivity to faces with negative emotions, differentiation of faces among positive and negative emotions, understanding of surprised faces, and discrimination of faces with negative emotions.

Improving the utility of the European Health Literacy Survey Questionnaire: a computerized adaptive test for patients with stroke.

PURPOSE: Health literacy among patients is crucial for effective stroke management. The European Health Literacy Survey Questionnaire is a theory-based measure that comprehensively captures 12 domains of health literacy. We aimed to develop a computerized adaptive test of the European Health Literacy Survey Questionnaire to efficiently assess health literacy among patients with stroke. MATERIALS AND METHODS: The European Health Literacy Survey Questionnaire data of 311 patients and item parameters were retrieved from a Rasch validation study. Real data simulations were performed to develop a computerized adaptive test of the European Health Literacy Survey Questionnaire and explore its efficiency and reliability. RESULTS: The computerized adaptive test of the European Health Literacy Survey Questionnaire displayed suitable reliability in all 12 domains (0.72-0.84) with a mean test length of 17 items (36.2% of the 47-item European Health Literacy Survey Questionnaire). CONCLUSIONS: Our findings indicate that the computerized adaptive test of the European Health Literacy Survey Questionnaire, which assesses 12 domains of health literacy among patients with stroke in a timely and precise fashion, is efficient and reliable.Implications for rehabilitationThe computerized adaptive test of the European Health Literacy Survey Questionnaire assesses the subjective fit of personal health literacy competencies to environmental demands, providing insight into patient strengths and weaknesses when dealing with health tasks and interacting with health systems.The computerized adaptive test of the European Health Literacy Survey Questionnaire assesses the 12 domains of health literacy among patients with stroke in a timely and precise manner.Our study has demonstrated the utility of the computerized adaptive test of the European Health Literacy Survey Questionnaire in reducing the assessment burden of patients in clinical practice.Developing of the computerized adaptive test of the European Health Literacy Survey Questionnaire provided findings that may benefit researchers and clinicians interested in developing efficient outcome measures.

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 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.

A 10-item Fugl-Meyer Motor Scale Based on Machine Learning.

OBJECTIVE: The Fugl-Meyer motor scale (FM) is a well-validated measure for assessing upper extremity and lower extremity motor functions in people with stroke. The FM contains numerous items (50), which reduces its clinical usability. The purpose of this study was to develop a short form of the FM for people with stroke using a machine-learning methodology (FM-ML) and compare the efficiency (ie, number of items) and psychometric properties of the FM-ML with those of other FM versions, including the original FM, the 37-item FM, and the 12-item FM. METHODS: This observational study with follow-up used secondary data analysis. For developing the FM-ML, the random lasso method of ML was used to select the 10 most informative items (in terms of index of importance). Next, the scores of the FM-ML were calculated using an artificial neural network. Finally, the concurrent validity, predictive validity, responsiveness, and test-retest reliability of all FM versions were examined. RESULTS: The FM-ML used fewer items (80% fewer than the FM, 73% fewer than the 37-item FM, and 17% fewer than the 12-item FM) to achieve psychometric properties comparable with those of the other FM versions (concurrent validity: Pearson r = 0.95-0.99 vs 0.91-0.97; responsiveness: Pearson r = 0.78-0.91 vs 0.33-0.72; and test-retest reliability: intraclass correlation coefficient = 0.88-0.92 vs 0.93-0.98). CONCLUSION: The findings preliminarily support the efficiency and psychometric properties of the 10-item FM-ML. IMPACT: The FM-ML has potential to substantially improve the efficiency of motor function assessments in patients with stroke.

Practice Effects and Test-Retest Reliability of the Continuous Performance Test, Identical Pairs Version in Patients with Schizophrenia over Four Serial Assessments.

OBJECTIVE: The purposes of this study were to examine the practice effects and test-retest reliability of the Continuous Performance Test, Identical Pairs version (CPT-IP) over four serial assessments in patients with schizophrenia. METHOD: Fifty-six patients with schizophrenia were assessed with the CPT-IP four times, once per week. The CPT-IP contains four indices: "2-digit score," "3-digit score," "4-digit score," and "total score." RESULTS: The four indices showed trivial-to-small practice effects (Cohen's d = -0.13-0.24), good-to-excellent test-retest reliability (ICC = 0.62-0.88), and unacceptable random measurement error (MDC% = 33.8%-110.8%). CONCLUSIONS: The total score had the best reliability among the four indices. Although practice effects of the four indices all appeared cumulative, all four CPT-IP indices reached a plateau after the second assessment. These results indicate that clinicians should interpret the change scores of the CPT-IP conservatively and use the total-score index in their routine repeated assessments.

A Comparison of the Responsiveness of the Postural Assessment Scale for Stroke and the Berg Balance Scale in Patients With Severe Balance Deficits After Stroke.

BACKGROUND AND PURPOSE: Previous evidence that the Postural Assessment Scale for Stroke (PASS) and the Berg Balance Scale (BBS) have similar responsiveness is doubtful. Compared with the BBS, the PASS has more items assessing basic balance abilities (such as postural transition during lying and sitting), so it should be more likely to detect changes in patients with severe balance deficits. We aimed to compare the responsiveness of the PASS and the BBS in patients with stroke who have severe balance deficits. METHODS: The PASS and BBS scores of 49 patients with severe balance deficits at 14 and 30 days after stroke were retrieved. The group-level responsiveness was examined with the standardized response mean (SRM). The individual-level responsiveness was examined by the proportion of patients who achieved clinically significant improvements (ie, their pre-post change scores in the PASS/BBS exceeded the minimal detectable change with 95% confidence of each measure). The responsiveness of the 2 measures was compared using the bootstrap approach. RESULTS AND DISCUSSION: The comparisons of responsiveness showed significant differences between the PASS and the BBS at both the group and individual levels. At the group level, the PASS indicated moderate changes in balance function (SRM = 0.79), but the BBS indicated only small changes (SRM = 0.39). At the individual level, the PASS showed that 42.9% of patients had clinically significant improvements, while the BBS showed that only 6.1% of patients had clinically significant improvements. CONCLUSIONS: Compared with the BBS, the PASS was better able to detect balance improvements in patients having severe balance deficits. The PASS is recommended as an outcome measure to detect change in balance in patients with stroke who have severe balance deficits.

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.

Computerized Adaptive Testing System of Functional Assessment of Stroke.

The computerized adaptive testing system of the functional assessment of stroke (CAT-FAS) can simultaneously assess four functions (motor functions of the upper and lower extremities, postural control, and basic activities of daily living) with sufficient reliability and administrative efficiency. CAT, a modern measurement method, aims to provide a reliable estimate of the examinee's level of function rapidly. CAT administers only a few items whose item difficulties match an examinee's level of function and, thus, the administered items of CAT can provide sufficient information to reliably estimate the examinee's level of function in a short time. The CAT-FAS was developed through four steps: (1) determining the item bank, (2) determining the stopping rules, (3) validating the CAT-FAS, and (4) establishing a platform of online administration. The results of this study indicate that the CAT-FAS has sufficient administrative efficiency (average number of items = 8.5) and reliability (group-level Rasch reliability: 0.88 - 0.93; individual-level Rasch reliability: ≥70% of patients had Rasch reliability score ≥0.90) to simultaneously assess four functions in patients with stroke. In addition, because the CAT-FAS is a computer-based test, the CAT-FAS has three additional advantages: the automatic calculation of scores, the immediate storage of data, and the easy exporting of data. These advantages of the CAT-FAS will be beneficial to data management for clinicians and researchers.

Responsiveness and predictive validity of the computerized digit vigilance test in patients with stroke.

Purpose: To investigate the responsiveness and predictive validity of the computerized digit vigilance test (C-DVT) in inpatients receiving rehabilitation following stroke. Methods: Forty-nine patients completed the C-DVT and the Barthel Index (BI) after admission to and before discharge from the rehabilitation ward. The standardized response mean (SRM) was used to examine the responsiveness of the C-DVT. We used a paired t-test to determine the statistical significance of the changes in scores on the C-DVT. We estimated the predictive validity of the C-DVT with the Pearson correlation coefficient (r) to investigate the association between the scores of the C-DVT at admission and the scores of the BI at discharge. Results: Our data showed a small SRM (-0.31) and a significant difference (paired t-test, p = 0.034) between the C-DVT scores at admission and discharge. These findings indicate that the C-DVT can appropriately detect changes in sustained attention. In addition, we found a moderate association (r = 0.48) between the scores of the C-DVT at admission and the scores of the BI at discharge, suggesting the sufficient predictive validity of the C-DVT. Conclusions: Our results showed that the C-DVT had adequate responsiveness and sufficient predictive validity in inpatients receiving rehabilitation following stroke. Implications for rehabilitation The computerized digit vigilance test (C-DVT) had adequate responsiveness to be an outcome measure for assessing the sustained attention in inpatients receiving rehabilitation after stroke. The C-DVT had sufficient predictive validity to predict daily function in inpatients receiving rehabilitation after stroke.