Background and Purpose. To improve the utility of the Berg Balance Scale (BBS), the aim of this study was to develop a short form of the BBS (SFBBS) that was psychometrically similar (including test reliability, validity, and responsiveness) to the original BBS for people with stroke. Subjects and Methods. A total of 226 subjects with stroke participated in this prospective study at 14 days after their stroke; 167 of these subjects also were examined at 90 days after their stroke. The BBS, Barthel Index, and Fugl-Meyer Motor Test were administered at these 2 time points. By reducing the number of tested items by more than half the number of items in the original BBS (ie, making 4-, 5-, 6-, and 7-item tests) and simplifying the scoring system of the original BBS (ie, collapsing the 5-level scale into a 3-level scale [BBS-3P]), we generated a total of 8 SFBBSs. Results. The distributions of scores for all 8 SFBBSs were acceptable but featured notable floor effects. The 4-item BBS, 5-item BBS, 5-item BBS-3P, and 7-item BBS-3P demonstrated good reliability. The subjects' scores on the 6-item BBS, 6-item BBS-3P, 7-item BBS, and 7-item BBS-3P showed excellent agreement with those on the original BBS. The 6-item BBS-3P and 7-item BBS-3P exhibited great responsiveness. Only the 7-item BBS-3P demonstrated both satisfactory and psychometric properties similar to those of the original BBS. Discussion and Conclusion. The 7-item BBS-3P was found to be psychometrically similar to the original BBS. The 7-item BBS-3P, compared with the original BBS, is simpler and faster to complete in either a clinical or a research setting and is recommended. [Chou CY, Chien CW, Hsueh IP, et al. Developing a short form of the Berg Balance Scale for people with stroke. Phys Ther. 2006;86:195-204.]
Four measures showed acceptable psychometric properties with some domains slightly less satisfactory. Overall, use of 8-domain SSQoL and SIS 3.0 are feasible for clinical practice to monitor HRQoL of stroke survivors.
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.
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.
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