Search PubMed⌕ Search

Biomedical subjects

A Lowe-Strong

Publications and source records attributed to A Lowe-Strong.

2 recordsLinked to original sources

Measuring disability in multiple sclerosis: is the Community Dependency Index an improvement on the Barthel Index?

The Community Dependency Index (CDI) was developed due to concerns that the Barthel Index (BI) was limited as a measure of physical function in community settings. However, no studies have compared the two rating scales within multiple sclerosis (MS). The aim of this study was to determine whether, in a community-based sample of people with MS, the CDI is a better measure than the BI. BI and CDI data were collected from 90 people with MS. Four measurement properties were compared: scaling assumptions (item mean scores, corrected item-total correlations), acceptability (score distributions, floor/ceiling effects), reliability (Cronbach's alpha) and validity (concurrent, discriminant, group differences, relative validity). Both scales satisfied recommended criteria for scaling assumptions (indicating it was legitimate to report a summed score) and internal consistency reliability (alpha > 0.85). The scales were highly correlated (r = 0.96), indicating they measured the same construct. Both scales demonstrated good group differences validity, but the BI was marginally superior. Notable ceiling effects (BI > CDI) were demonstrated for both scales, particularly in those less disabled. This study sample had relatively minor levels of disability, with over 70% still being independently mobile. In this sample of people with MS, the measurement properties of the BI and CDI examined were very similar, suggesting the CDI does not appear to have achieved its goal of better measurement.

Activities of Daily Living↗

Structure data entry using graphical input: recording symptoms for multiple sclerosis.

Structured Data Entry provides flexible and efficient input to the computer-based patient record. We have utilized the SDE approach to build a prototype interface for recording common symptoms associated with Multiple Sclerosis (MS). The software provides both graphical input and output, to facilitate efficient data entry and monitoring of data. Graphical input is transformed to textual information, which is stored in a database in a hierarchical tree structure. Pain management in MS may be achieved by careful monitoring of the symptom in response to treatment. Pain location is selected on a body image and severity and other attributes represented using a graphical visual analog scale, leading to more convenient input and a less ambiguous coding than is achievable with narrative text alone. This approach could provide an objective means of monitoring the progress of the disease and management of the symptoms. The intuitive interface may also facilitate self-monitoring.

Computer Graphics↗