Logit Scores Research Articles

Enhancing English abstract quality for non-English speaking authors using ChatGPT: A comparative study of Taiwan, Japan, China, and South Korea with slope graphs.

A clear and proficient English abstract is crucial for disseminating research findings to a global audience, significantly impacting the accessibility and visibility of research from non-English speaking countries. Despite the adoption of ChatGPT since November 30, 2022, a comprehensive analysis of improvements in English abstracts in scholarly journals has not been conducted. This study aims to identify which authors from Taiwan, Japan, China, and South Korea (TJCS) have shown the most improvement in English abstracts. Article abstracts published in Medicine (Baltimore) sourced from the Web of Science Core Collection from 2020 to 2023 were downloaded. A mixed-methods approach was employed, combining quantitative analysis of linguistic quality indicators and qualitative assessments of coherence and engagement using the Rasch model. Ten quality indicators were determined by prompting ChatGPT. Two scenarios were analyzed: (1) generative pretrained transformer (GPT) versus non-GPT (each with 30 abstracts from 2021) and (2) TJCS in comparison (each with 100 abstracts from 2021 and 2023, respectively). Standardized mean differences were compared using paired samples t test. Visuals including forest plots, Rasch Wright Map, the slope graph, and scatter plot with 95% control lines were used to examine the 2 scenarios. (1) No significant difference was found between GPT and non-GPT abstracts with Rasch logit scores of 3.31 and 3.17, respectively (P = .42), likely due to small sample size (n = 30); (2) significant difference exists between 2020 and 2023 in each country, and between South Korea and Taiwan in 2020. Among TJCS, Taiwan showed the greatest improvement in English abstract quality post-ChatGPT implementation, followed by Japan, China, and South Korea. The English abstracts in Medicine (Baltimore) have improved, reflecting the tool's positive impact on enhancing technical language. This study demonstrates that ChatGPT can enhance the quality of English abstracts for authors from non-English speaking regions, although the assumption that all authors use ChatGPT is invalid and impractical. The findings underscore the value of artificial intelligence tools in academic writing and recommend further investigation into the long-term implications of artificial intelligence integration in scholarly communication.

Behavioral Problems and Self-Feeding Independence Among Patients With Acute Stroke: A Single-Center Study.

Self-feeding independence is often the first goal in acute stroke rehabilitation. Attention deficits appear frequently after stroke, but neuropsychological tests may be difficult to perform in the acute phase, and the effect on self-feeding activities may be difficult to detect. Therefore, we aimed to clarify behavioral problems with self-feeding using the Moss Attention Rating Scale (MARS), a behavioral observational rating scale of attentional function, for a better understanding of the effects of self-feeding. To identify behavioral problems caused by attention deficits among patients with acute stroke who need assistance in self-feeding, using the MARS. Cross-sectional single-center study. St. Marianna University Yokohama Seibu Hospital, Kanagawa, Japan. A total of 96 patients (42 women and 54 men) were admitted to the hospital for stroke treatment. Patients' median age was 75.0 yr. The date of evaluation was a median of 3.0 days from admission. The primary outcome was the FIM® eating subscore. The secondary outcome was the MARS score. Significant differences were noted in the total raw MARS, logit, and three-factor scores for self-feeding independence (p < .01). The effect size of the consistent or sustained factor on independence was large (r = .83). Behavioral problems related to self-feeding dependence include the inability for sustained attention. Our results suggest that sustained concentration during self-feeding is necessary for eating independence. Rehabilitation focused on sustained attention is important for independent self-feeding. Plain-Language Summary: A patient's self-feeding independence is often the first goal in acute stroke rehabilitation. Patients frequently experience attention deficits after a stroke, but neuropsychological tests may be difficult to perform in the acute phase of rehabilitation, and the effect of attention deficits on self-feeding may be difficult to identify. To have a better understanding of the effects on self-feeding, this study aimed to identify behavioral problems using the Moss Attention Rating Scale (MARS). The study found that the MARS can be used to identify behavioral problems related to self-feeding independence, which can help occupational therapists to develop rehabilitation programs for their clients who have experienced a stroke.

Relative complexity in a model of word difficulty: The role of loanwords in vocabulary size tests

Recent studies have shown that the frequency effect, although long used as a guide to word difficulty, fails to explain all variance in learner word knowledge. As such, a “more than frequency” conclusion has been offered to explain how lexical sophistication accounts for word difficulty. This study presents a multiple regression model of word-learning difficulty from a data set of monolingual Japanese first language (L1) learners. Vocabulary Size Test (VST) scores of 2,999 L1 Japanese university students were converted to logit scores to determine the word-learning difficulty of 80 target words. Five lexical sophistication variables were found to correlate with word-learning difficulty (frequency, cognate status, age of acquisition, prevalence, and polysemy) above a practical significance threshold. These were subsequently entered into a regression model with the logit scores as the dependent variable. The model (R2 = .55) indicates that three lexical sophistication variables significantly predicted VST scores: frequency (ß = -.28, p = .029), cognateness (ß = -.24, p = .005), and prevalence (ß = 0.22, p = .040). Despite suggestions that complexity studies be interpreted considering what is understood about the construct of linguistic complexity, researchers have rarely made explicit the differences between absolute and relative complexity variables. As some variables can be shown to vary in complexity according to the L1 population, these must be considered in discussions of test generalizability. Although frequency will continue to be the primary criterion for the selection of lexical items for teaching and testing, the cognate status of words can be used to predict the potential learning burden of the word more precisely for learners of different L1 backgrounds.

Revisiting the transient-evoked otoacoustic emissions passing criteria used for newborn hearing screening

Objective To assess transient-evoked otoacoustic emissions (TEOAE) data from 15 years of a newborn hearing screening program and evaluate how well various criteria separate ears with and without hearing loss. Design Retrospective review of TEOAE data using logistic regression, receiver operating characteristic curves, and cumulative percentage graphs. Study sample: Children with hearing loss who passed TEOAE screening as a newborn were compared to children who failed TEOAE screening and normal hearing children who either passed or failed. Exclusions were applied for acquired hearing loss or auditory neuropathy. Results Ears with hearing loss that passed screening had significantly lower TEOAE response levels compared to ears with normal hearing. Noise levels, test times, and number of sweeps were also lower. Most of these ears had mild hearing loss. Logistic regression results showed that high-frequency TEOAE response level is the best predictor of hearing loss. A multivariate “logit” score calculated from the regression was the best indicator for separating ears with hearing loss from ears with normal hearing. Conclusions TEOAE response levels or an algorithm which incorporates logit scores should be considered as a minimum passing criterion to increase the sensitivity of the TEOAE screening.

Influence of Natural Risks and Non-Agricultural Income on Agricultural Trusteeship Decisions in Northeast China.

As the main service mode and management mode of socialized service, agricultural production trusteeship services (APTS) are an important way to realize the tight link between farmers and modern agricultural development, which is highly important for ensuring national food security. By constructing a utility model of farmers, this paper deduces the decision-making mechanism of farmers' APTS from the dual mechanism of natural risk and non-agricultural employment income (NAEI) and uses the survey data of 956 farmers in the three northeastern provinces to verify the empirical results by using multivariate logit (Mlogit) and propensity score matching (PSM) methods. The research shows that natural risk hinders farmers' choice of the APTS; NAEI has a positive impact on APST, and an increase in NAEI weakens the negative effect of natural risk on the choice of the APTS, and has an enhanced moderating effect. In addition, the scale heterogeneity analysis revealed that the impacts of natural risk and NAEI on farmers of different scales are significantly different. The NAEI adjustment effect has the greatest impact on small-scale farmers, followed by medium-scale farmers. In view of this, the government should stabilize the nonagricultural employment market and improve the nonagricultural employment opportunities of farmers. APTS organizations should transfer natural risks and improve the agricultural insurance system. According to the differences of different scales of farmers, different promotion policies are formulated, and the expansion of management and deepening services is proposed to further promote the development of APTS and consolidate the foundation of food security in China.

The Effect of Medical Insurance on the Physical Function Health of the Elderly under Different Marital Status

In order to further improve China's medical insurance system and better protect the health rights and interests of the elderly under different marital status, this paper combines the data of China Health and Pension Tracking Survey (CHARLS), uses Logit regression analysis and propensity score matching method to analyze the medical insurance system implemented since 1998. Whether it has an impact on the physical function health of the elderly in different marital states. In this paper, the marital status of the elderly aged 65 and above in 2018 is divided into married and unmarried states, in which the married and surviving spouse means married, and married widows, divorces and lifelong single are all classified as unmarried. The self-rated health of the elderly reflects their physical function health, so as to conduct an empirical study. It is concluded that medical insurance has a positive effect on the physical function health of the elderly under different marital status, and the effect on unmarried elderly is greater than that on married elderly. To this end, this paper puts the following suggestions.

Deep learning for 4D modeling of glioblastoma multiforme with tumor treating fields (TTFields) therapy.

e14032 Background: Prediction of future tumor growth and recurrence are critical in the management of patients with glioblastoma multiforme (GBM). This study develops a deep learning method for estimating future areas of GBM spread across multiple timepoints using MRI in patients receiving tumor treating fields (TTFields) therapy. Methods: A single institutional database was queried to identify adult patients with histologically confirmed newly diagnosed and/or recurrent GBM undergoing TTFields therapy. For newly diagnosed GBM, patients received TTFields with temozolomide after maximal debulking surgery and chemoradiation therapy. For recurrent GBM, patients received TTFields as monotherapy. For each patient, all serial follow-up MRI exams were obtained, including T1 (pre-/post-contrast), T2, and T2/FLAIR sequences. On each exam, all regions of enhancing tumor core (excluding peritumoral edema, necrotic core, or resection cavity) were delineated and aligned across time points using nonlinear deformable registration. For any given pair of serial exams, a convolutional neural network (CNN) was designed to predict future GBM tumor on the follow-up exam given the precursor exam and time interval between the studies. The model is implemented as a 3D encoder-decoder architecture yielding a dense per-voxel prediction of future tumor probability optimized using a binary cross-entropy loss function. Class weights were used to develop high sensitivity and high positive predictive value (PPV) model variants. To generate final logit scores, time information is concatenated to the penultimate feature map as an additional feature channel, allowing the model to calibrate each estimate based on elapsed time between any pair of exams. Upon convergence, a 4D learned representation allows for prediction of spatial distribution of GBM tumor at any future time point. Results: A total of 123 patients (1112 total MR exams) were identified. For any given single patient, a median of 6 follow-up exams (IQR 2.5-12.5) at a median interval follow-up time of 46 days (IQR 15.75-63 days) between exams was observed. Upon five-fold cross-validation, the model demonstrated a 0.44 Dice score overlap between predicted and true areas of future GBM tumor growth. The high sensitivity model yielded a per-voxel sensitivity of 0.91 (IQR 0.77-0.99) and PPV of 0.26 (IQR 0.17 to 0.32), while the high PPV model yielded a per-voxel sensitivity of 0.14 (IQR 0.00 to 0.46) and PPV of 0.75 (IQR 0.56 to 0.94). Upon visual confirmation, model predictions across incremental time values for any given exam yielded expected gradual growth of tumor over time. Conclusions: A deep learning model can accurately predict future areas of GBM tumor growth in patients receiving TTFields therapy, with optimal performance that may be calibrated for high sensitivity or high PPV based on clinical use case.

Cross-cultural adaptation, validity and reliability of the Japanese version of ABILHAND-kids for children with cerebral palsy using Rasch measurement model

Purpose The aim of this study was to develop the Japanese version of the ABILHAND-Kids and to examine its psychometric properties for Japanese children with cerebral palsy (CP). Methods The experimental version of 75 items was developed using forward-backward translation method. Parents of 137 children with CP answered it. Their responses were analyzed to successive items, and psychometric properties of the final version were investigated through the Rasch measurement model. Results The Japanese version of the ABILHAND-Kids contained 22 items. It showed valid item-patient targeting, no significant floor and ceiling effects, and no differential item functioning for demographic and clinical subgroups. All items contributed to the definition of one-dimensional measure. For internal consistency, the person separation index was 0.94. For test-retest reliability, the intraclass correlation coefficients were 0.96 (95% CI: 0.92–0.98). The minimal detectable difference was calculated with a logit score of 0.79 and a total raw score of 4.50. The logit score showed a strong correlation with the Manual Ability Classification System level (ρ= −0.70) and the Gross Motor Function Classification System level (ρ= −0.62). Conclusions The Japanese version of the ABILHAND-Kids was found to be valid and reliable. It appears to be a good tool for assessing manual abilities in daily activities in children with CP.

Agricultural value chain and households' livelihood in Africa: The case of Nigeria

One of the critical issues of concern is how African countries can take agriculture as a business that creates wealth which can help transform rural communities, increase income, reduce poverty and help the continent achieve the United Nations (UN) Sustainable Developments Goals (SDGs) of no poverty (SDG-1) and food and nutrition security (SDG-2) by 2030. Hence, this study examines how participation in agriculture through cassava value chain can improve households' livelihood income in Africa using the case of Nigeria. To achieve its objective, the study utilised quantitative analysis approach to address the linkages among economic agents within the agricultural value chain. The logit regression and propensity scores matching technique are used for the quantitative analysis. The result show that, while more significant proportion of male cassava production household heads sell cassava in its fresh form, their female counterparts add value by processing cassava further into finished staple foods. Another key insight is the high involvement of youth and women in cassava production, processing and marketing. Thus, they have greater influence in promoting and improving households’ livelihood income. Therefore, more targeted efforts should be made by all stakeholders to ensure that youth and women have better, less expensive and dependable assess to facilities at lower interest rates to participate in agricultural value chain. This will engender inclusiveness of the vulnerable groups in agricultural value chain.

Does Health Insurance Boost Subjective Well-being? Examining the Link in China through a National Survey

Abstract Drawing on nationwide data from the 2021 China General Social Survey, this study leverages ordered logit regression and propensity score matching to delve into the intricate relationship between commercial health insurance and subjective well-being among Chinese residents. The analysis unveils a robust, positive association between commercial health insurance and subjective well-being, with its impact most evident at intermediate levels of happiness. Notably, the study pinpoints a more pronounced effect among the middle-high income group. However, closer scrutiny of the marginal effects reveals a heightened need for commercial health insurance among low-income individuals, suggesting a potential avenue for policy intervention. In light of these findings, we recommend that the Chinese government actively foster the development of commercial health insurance, aligning it effectively with the existing system, to bolster the subjective well-being of the entire population.

A novel sociodemographically‐neutral speech analysis algorithm to detect cognitive impairment in a Spanish population

AbstractBackgroundEarly detection of mild cognitive impairment (MCI) and dementia is crucial for initiation of care. Brief, cost‐effective cognitive screening instruments are needed to identify individuals who require further evaluation. This study presents preliminary data on a new screening technology using automated recordings analysis software in a Spanish population.MethodData were collected from 148 Spanish‐speakings in Spain (MAge = 74.4, MEducation = 12.93, 43.3% males), clinically diagnosed as cognitively normal (CN, n = 78) or impaired (MCI, n = 49; all‐cause dementia, n = 21). Participants were recorded performing four language tasks [Animal fluency, alternating fluency (sports and fruits), phonemic “F” fluency and Cookie Theft Description]. Recordings were processed via text‐transcription and digital‐signal processing techniques to capture neuropsychological variables and audio characteristics. A training sample of 103 subjects with similar demographics (age, sex, education) across groups was used to develop an algorithm to detect cognitive impairment. The features of each task and of speech were used separately to develop five algorithms to compute scores between 0 and 1, and a final algorithm was constructed from these using repeated cross‐validation. Of the 45 remaining original participants, an age‐balanced subset of 28 subjects was used to test the algorithm. General linear modeling was used to quantify demographic biases in the data and in the predicted logistically‐transformed algorithm scores.ResultMean logit algorithm scores were significantly different across groups in both test/training samples (p&lt;1e‐3). Sex‐bias in the test dataset (psex = 1.3e‐5) was reduced by predicted logit scores (psex = 0.01); other demographic variables were not significant across samples (page = 0.31→0.21; peducatiom = 0.69→0.58; pmultilingualism = 0.74→0.32). The final algorithm in test/training samples obtained an AUC of 0.908/0.956, with overall accuracy of 89%/89%, sensitivity of 0.85/0.95, and specificity of 0.92/0.83 in discriminating CN and impaired groups.ConclusionThese findings provide initial support for the utility of this automated speech analysis algorithm as a screening tool for cognitive impairment that does not explicitly use memory tests. Further research is needed to validate algorithm in other languages and cultures.

78 Preliminary Exploration of a Novel Speech Analysis Algorithm to Detect Cognitive Impairment in a Spanish Population

Objective:Early detection of mild cognitive impairment (MCI) and dementia is crucial for initiation of treatment and access to appropriate care. While comprehensive neuropsychological assessment is often an intrinsic part of the diagnostic process, access to services may be limited and cannot be utilized effectively on a large scale. For these reasons, cognitive screening instruments are used as brief and cost-effective methods to identify individuals who require further evaluation. Novel technologies and automated software systems to screen for cognitive changes in older individuals are evolving as new avenues for early detection. The present study presents preliminary data on a new technology that uses automated linguistic analysis software to screen for MCI and dementia.Participants and Methods:Data were collected from 148 Spanish-speaking individuals recruited in Spain (MAge=74.4, MEducation=12.93, 56.7% females) of whom 78 were diagnosed as cognitively normal [CN; Mmmse = 28.51 (1.39)], 49 as MCI [MMMSE = 25.65 (2.94)], and 21 as all-cause dementia [MMMSE = 22.52 (2.06)]. Participants were recorded performing various verbal tasks [Animal fluency, phonemic (F) fluency, Cookie Theft Description, and CERAD list learning task]. Recordings were processed via text-transcription and sound signal processing techniques to capture neuropsychological variables and audio characteristics. Features from each task were used in the development of an algorithm (for that task) to compute a score between 0 or 1 (healthy to more impairment), and a fifth algorithm was constructed using audio characteristics from all tasks. These five classifiers were combined algorithmically to provide the final algorithm. Receiver Operating Characteristic (ROC) analysis was conducted to determine sensitivity and specificity of predicted algorithm performance [CN vs. impaired (MCI or dementia)] against clinical diagnoses, and additional general linear modeling was used to test whether age, sex, education, and multilingualism significantly predicted logistically transformed weighted algorithm scores.Results:Scores were transformed to logit scores, with significant differences in mean logit scores between all groups (p &lt;.001). Logit-inverse transformation of mean logit scores (possible range 0 -1) resulted in values of 0.06 for CN, 0.90 for MCI, and 0.99 for all-cause dementia groups. ROC curve analyses revealed the algorithm obtained a total area under the curve of 0.92, with an overall accuracy of 86.8%, a sensitivity of 0.92, and specificity of 0.82. Age was identified as a significant predictor (beta = 0.22; p &lt;0.01) of algorithm output, whereas years of education (beta = -0.04; p = 0.64), sex (beta = 0.38; p = 0.02, did not survive correction for type-1 error), and multilingualism (beta = -0.24; p = 0.22) were non-significant.Conclusions:These findings provide initial support for the utility of an automated speech analysis algorithm to detect cognitive impairment quickly and efficiently in a Spanish-speaking population. Although sociodemographic variables were not included in the algorithm, age significantly predicted algorithm output, and should be further explored to determine if age-adjusted formulas would improve algorithm accuracy for younger versus older individuals. Additional research is needed to validate this novel methodology in other languages, as this may represent a promising cross-cultural screening method for MCI and dementia detection.

Assessing Students Understanding of Chemical Bonds Material by Rasch Modeling

This study aimed to assess high school student’s understanding of Banjarmasin by Rasch modeling, preci-sely the cognitive aspect. The research method was descriptive with a quantitative approach to assess the pattern of reactions and symptoms of Rasch data. According to the research findings, the person reliability (students) was +0.66 based on the Rasch modeling analysis, with the criterion satisfactory, indicating that the students knowledge was adequate. At the same time, Cronbachs’ alpha score had a value of +0.71 and met the criteria of excellent. In addition, the students with the highest level of understanding were coded 127P12B with a logit value (person measure) of 2.52 and average students with logit value of -0.77 or 0. In contrast, the students with low abilities were coded 030P10B and 059L11B (same logit value, -3.27 or 0). Other data were INFIT MNSQ and OUTFIT MNSQ (person) with average values of +0.99 and +1.14 (closer to 1, the better), while the INFIT and OUTFIT ZSTD values were -0.1 and 0.0 respectively (closer to 0, better). The most difficult question was Q16, which had a logit score of 1.96; students’ logit values carried this question. Students were regarded to have appropriate knowledge even though their ability excee-ded the problem ability. In conclusion, the Rasch model-based pre-learning evaluation was found to be useful in measuring students’ cognitive grasp of chemical bonding material. This study could serve as the primary reference for teachers in assessing students’ level of knowledge before they begin learning. In addi-tion to interpreting student knowledge through various Rasch data presentations, a study of the structure of questions with varying difficulty levels could be used to assess the full group of students’ understanding of chemistry.

Impacts of family care for children and the elderly on women's employment: evidence from rural China.

China's traditional culture makes rural women and men take on different family responsibilities. Use "China Family Panel Studies" (CFPS) data and build Logit and propensity score matching models to empirically study the impact of children care and elderly care on rural married women going out to work. And explore the welfare effects of basic education public services in helping rural women take care of their families. The results show that caring for children has a significant hindering effect on rural married women's job hunting. Especially for those in low-income families, the employment inhibition is most significant among women aged 20-30 with multiple children. Contrary to previous cognition, supporting the elderly has a certain weak stimulating effect. The kindergarten public services in rural areas can help women take care of their children and relieve their work pressure. The primary school public services have not played a role in alleviating them. This shows that there are still a large number of female laborers in rural China who are unable to go out to work due to family care. The improvement of rural basic education public services can promote more rural women going out to work. This finding will provide a policy reference for the introduction of a formal care system and the establishment of basic education public services in China.

Adoption of Small-Scale Irrigation and Its impact on Household’s Income in Dugda Districts, East Shewa Zone, Oromia, Ethiopia

The major of this study was to estimate the impact of Adoption of Small-Scale Irrigation in Dugda district. Data were collected from both primary and secondary data sources. Primary data was collected from 384 household heads in four kebeles of the district using structured questionnaire. Descriptive, logit and propensity score matching techniques were used for data analysis. The study finding from the propensity score matching technique revealed that the incomes of adopters of small scale irrigation were increased by 37,696.06ETB per annum. This calls for strengthening the available irrigation facilities and expansion of irrigation sector in the study area.

Demonstration of the Yonsei-Social Play Evaluation Tool Keyforms for Occupational Therapy Practice

Play is regarded as a child’s primary occupation and provides valuable information about the child’s abilities. Thus, informative assessment tools of play skills are critical for establishing play-related treatment goals in occupational therapy. The objective of this study is to present a practical method for occupational therapists to develop intervention goals using the Yonsei-Social Play Evaluation Tool (Y-SPET) keyforms. Parent responses (n = 310) for preschool children (three to six years old) who did not have a medical diagnosis were examined. The Rasch measurement model was used to create keyforms for the Y-SPET. All children’s raw scores were converted into individual Rasch-calibrated logit scores and standard errors were estimated to establish logically attainable treatment goals. Results showed use of the keyforms could logically identify the intervention goals of the children’s social play. This suggests that the Y-SPET keyforms are helpful for assessing the level of children’s social play and establishing practical treatment goals.

Catquest-9SF questionnaire: validation of the Portuguese version using the Rasch analysis.

The aim of this study was to validate the Portuguese version of Catquest-9SF through its application in a native Brazilian population with cataracts and to determine the correlation of the questionnaire scores with preoperative visual acuity. A prospective study was conducted to validate the Catquest-9SF questionnaire, which was translated and back-translated, generating a final version in Portuguese. A total of 120 Brazilian patients awaiting cataract surgery were recruited to answer the questionnaire and to document their preoperative data and visual acuity. The Rasch analysis was used to assess the instrument's psychometric properties. The Portuguese version of Catquest-9SF demonstrated an acceptable adjustment of the items (item fit statistics ranging from 0.7 to 1.3), unidimensionality (principal component analysis), and good organization in the item response categories (thresholds of the categories: -2.79, 0.57, and 2.22, respectively). The questionnaire contains items with stable relationships if considered at the same level of visual impairment in the comparison between the two groups (absence of differential item functioning). The separation of people (person separation index, 3.07) was adequate. The visual acuity in the logarithm of the minimum angle of resolution (logMAR) in the best eye with the best optical correction showed a statistically significant correlation with the Catquest-9SF logit score (r=0.282 and p=0.004). The Portuguese version of Catquest-9SF presents evidence of validity and reliability, in addition to being linguistically and culturally understandable for Portuguese-speaking patients born in Brazil. The questionnaire is easy to understand and quick to apply, as it could adequately estimate the subjective visual functioning in patients with cataracts. We found a significant correlation between visual acuity and the questionnaire score.

Catquest-9SF questionnaire: Validation in a Greek-speaking population using Rasch analysis.

The Catquest-9SF questionnaire is a tool measuring visual disability and vision-related limitation in patients' daily activities. The primary objective of this study was the validation of Catquest-9SF in a Greek-speaking cataract population. The questionnaire was translated into Greek and translated back into English. A pre-final Greek version was formed and tested by 10 Greek-English bilingual participants and by the translation team, and the final version was produced. Patients scheduled for cataract surgery completed the questionnaire preoperatively and postoperatively. Rasch analysis was performed for the assessment of the Catquest-9SF psychometric properties, including response category ordering, item fit statistics, principal components analysis, precision, differential item functioning and targeting for preoperative and postoperative data collectively. A total of 100 (55 men, 45 women, mean age = 71.94±6.63) cataract patients completed the Greek version of Catquest-9SF questionnaire preoperatively and postoperatively. Rasch analysis showed a significant improvement in the median person Rasch score from -1.49 preoperatively to -4.71 logits postoperatively, while the effect size was 1.3. Unidimensionality was confirmed since infit and outfit mean square values varied between 0.66 and 1.37. Rasch analysis showed good precision and separation ability (Person Separation Index of 3.28, and Person Reliability of 0.92). Four response categories were found for all items. The item-person means difference was -1.83 logits. The difference between preoperative and postoperative Catquest-9SF logit score was positively correlated with preoperative Catquest-9SF logit score (coeff. = 0.798, p<0.0001) and negatively correlated with postoperative spherical equivalent (coeff. = -0.825, p = 0.011). The Greek version of Catquest-9SF proved to be reliable, valid, unidimensional and responsive to changes after cataract surgery presenting good psychometric properties for cataract patients. Some postoperative mistargeting was found indicating that the tasks were easily performed by respondents after cataract surgery. NCT05323526 -retrospectively registered.

Assessing Bilateral Upper Extremity Integration using the Bilateral Task Assessment

<h3>Research Objectives</h3> To investigate the validity and reliability of the Bilateral Task Assessment (BTA) in the inpatient rehabilitation (IP rehab) setting. <h3>Design</h3> Study on psychometric properties. <h3>Setting</h3> An urban, inpatient rehabilitation facility. <h3>Participants</h3> Inpatient rehabilitation consumers assessment results. <h3>Interventions</h3> The BTA was administered by occupational therapists to 3,962 individuals in IP rehab. Psychometric analysis consisted of Cronbach's alpha and item-to-total correlations to determine internal consistency, a correlation analysis to assess concurrent validity, factor analysis to determine dimensionality, and item response theory to compute scores and assess test difficulty. <h3>Main Outcome Measures</h3> Validity, inter-rater/test-retest reliability, and internal consistency of the Bilateral Task Assessment. <h3>Results</h3> The scoring standard (.93) and times score (.86) indicates that both variables have good internal consistency. Factor analysis indicates a large effect size for BTA task scores and moderate effect size for BTA times. The additional analyses of the rating scale data confirmed the high internal consistency (.93) and high ITT correlations ranging from .86 - .90. The concurrent validity analysis found significant correlations with seven other measures of upper extremity function. Confirmatory factor analysis indicated that the BTA is a unidimensional measure (1-factor RMSEA = .06, CFI = .99). IRT analysis determined that the measure is most accurate for logit scores around -.40. <h3>Conclusions</h3> This study determined that the BTA demonstrated strong psychometric qualities and that it can be more widely used within occupational therapy practice to assess bilateral integration in stroke survivors. The BTA is a valid and consistent measure that can support BUE integration in occupational performance through assessment in a more functional context. <h3>Author(s) Disclosures</h3> The authors have nothing to disclose.

The Vision Correction Questionnaire: an electronic patient-reported outcome measure for refractive surgery.

To develop a psychometrically robust electronic patient reported outcome measure (ePROM) for refractive surgery. Moorfields Eye Hospital, London, United Kingdom. Questionnaire development study. Items were derived in 6 domains (spectacle dependence, visual quality, eye comfort, functional freedom, emotional wellbeing, and satisfaction with treatment) from existing Rasch adjusted instruments, patient and surgeon feedback, and refinement in semistructured interviews before administration to a field test cohort (n = 360) of patients undergoing routine refractive surgery. Spectacle dependence and satisfaction with treatment items were used to provide descriptive statistical information only. Contemporary criteria for item reduction and Rasch modeling were applied to the remaining domains. The finalized questionnaire was then administered to a second patient cohort (n = 120) before and after surgery to assess sensitivity to change. A 5-item scale derived for emotional wellbeing was unidimensional and a good fit to the Rasch model with ordered category response profiles, adequate precision (person separation 2.22 logits, reliability coefficient 0.83), and no misfitting items. Mean logit scores were 0.91 higher after treatment (effect size 1.26) suggesting a positive impact on emotional wellbeing. Functional scales could not be derived for visual quality, eye comfort, or functional freedom. Single-item ratings for visual quality and eye comfort were retained in our final 11-item questionnaire. This short ePROM should integrate well with routine clinical care and clinical trials in refractive surgery. The Rasch adjusted emotional wellbeing scale may help quantify the way patients feel about refractive surgery, with the remaining items providing useful descriptive information.