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Facial vascularized composite allotransplantation (fVCA) is a life-enhancing procedure performed to improve quality of life (QOL). Patient-reported outcome measures (PROMs) are tools used to assess QOL from the patients' perspective, and are increasingly recognized as an important clinical metric to assess outcomes of treatment. A systematic literature review was performed to identify and appraise the content of PROMs used in fVCA. We searched PUBMED/Medline, CINAHL, Embase, PsychInfo, and Web of Science from their inception through to June 2020. Included studies used a PROM in candidates and recipients of fVCA of any gender or age. We excluded abstracts, reviews, editorials, and dissertations. Items from each PROM were extracted and coded, using top-level codes and subcodes, to develop a preliminary conceptual framework of QOL concerns in fVCA, and to guide future PROM selection. Title and abstract screening of 6089 publications resulted in 16 studies that met inclusion criteria. Review of the 16 studies identified 38 PROMs, none of which were developed for fVCA. Review of the coded content for each PROM identified six top-level codes (appearance, facial function, physical, psychological and social health, and experience of care) and 16 subcodes, making up the preliminary conceptual framework. There are currently no PROMs designed to measure QOL concerns of fVCA candidates and recipients. Findings from this systematic review will be used to inform an interview guide for use in qualitative interviews to elicit and refine important concepts related to QOL in fVCA. [ABSTRACT FROM AUTHOR]

Computerised adaptive testing (CAT) has the potential to transform plastic surgery outcome measurement by making patient-reported outcome measures (PROMs) shorter, individualised and more accurate than pen-and-paper questionnaires. This paper reports the results of two optimisation studies for the CLEFT-Q CAT, a CAT intended for use in the field of cleft lip and/or palate. Specifically, we aimed to identify the optimal score estimation and item selection methods for using this CAT in clinical practice. These represent two major components of any CAT algorithm. Monte Carlo simulations were performed using simulated data in the R statistical computing environment and incorporated a range of score estimation and item selection techniques. The performance and accuracy of the CAT was assessed by mean items administered, correlation between CAT scores and paired linear assessment scores, and the root mean squared deviation (RMSD) of these score pairs. The accuracy of the CLEFT-Q CAT was not significantly affected by the choice of score estimation or item selection method. Sub-scales which originally contain more items were amenable to greater item reduction with CAT. This study shows that score estimation and item selection methods that need minimal processing power can be used in the CLEFT-Q CAT without compromising accuracy. This means that the CLEFT-Q CAT could be administered quickly and efficiently with basic hardware demands. We recommend the use of less computationally intensive techniques in future CLEFT-Q CAT studies. [ABSTRACT FROM AUTHOR]

The International Consortium for Health Outcome Measurement (ICHOM) has recently agreed upon a core outcome set for the comprehensive appraisal of cleft care, which puts a greater emphasis on patient-reported outcome measures (PROMs) and, in particular, the CLEFT-Q. The CLEFT-Q comprises 12 scales with a total of 110 items, aimed to be answered by children as young as 8 years old. In this study, we aimed to use computerised adaptive testing (CAT) to reduce the number of items needed to predict results for each CLEFT-Q scale. We used an open-source CAT simulation package to run item responses over each of the full-length scales and its CAT counterpart at varying degrees of precision, estimated by standard error (SE). The mean number of items needed to achieve a given SE was recorded for each scale's CAT, and the correlations between results from the full-length scales and those predicted by the CAT versions were calculated. Using CATs for each of the 12 CLEFT-Q scales, we reduced the number of questions that participants needed to answer, that is, from 110 to a mean of 43.1 (range 34–60, SE < 0.55) while maintaining a 97% correlation between scores obtained with CAT and full-length scales. CAT is likely to play a fundamental role in the uptake of PROMs into clinical practice given the high degree of accuracy achievable with substantially fewer items. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Social withdrawal is described as the condition in which an individual experiences a desire to make social contact, but is unable to satisfy that desire. It is an important issue for patients with motor neurone disease who are likely to experience severe physical impairment. This study aims to reassess the psychometric and scaling properties of the MND Social Withdrawal Scale (MND-SWS) domains and examine the feasibility of a summary scale, by applying scale data to the Rasch model. Methods: The MND Social Withdrawal Scale was administered to 298 patients with a diagnosis of MND, alongside the Hospital Anxiety and Depression Scale. The factor structure of the MND Social Withdrawal Scale was assessed using confirmatory factor analysis. Model fit, category threshold analysis, differential item functioning (DIF), dimensionality and local dependency were evaluated. Results: Factor analysis confirmed the suitability of the four-factor solution suggested by the original authors. Mokken scale analysis suggested the removal of item five. Rasch analysis removed a further three items; from the Community (one item) and Emotional (two items) withdrawal subscales. Following item reduction, each scale exhibited excellent fit to the Rasch model. A 14-item Summary scale was shown to fit the Rasch model after subtesting the items into three subtests corresponding to the Community, Family and Emotional subscales, indicating that items from these three subscales could be summed together to create a total measure for social withdrawal. Conclusion: Removal of four items from the Social Withdrawal Scale led to a four factor solution with a 14-item hierarchical Summary scale that were all unidimensional, free for DIF and well fitted to the Rasch model. The scale is reliable and allows clinicians and researchers to measure social withdrawal in MND along a unidimensional construct. [Copyright &y& Elsevier]