The complementary use of factor analysis, Mokken scaling and Rasch analysis allowed us to conduct a thorough investigation of scaling properties of the SIPSO. The three analyses provided incremental evidence for the validity of the two SIPSO subscales: Factor analysis confirmed the two-factor subscale structures proposed by its originators [8
]; Mokken analysis showed that the two subscales were valid ordinal scales; and Rasch analysis demonstrated that they conformed to the most stringent requirements of measurement and were unidimensional. Therefore, we are confident that the two subscales can be used.
The Mokken scaling showed an acceptable H
-Loevinger Coefficient for the total SIPSO. Mokken scaling determines if an ordinal scale has been constructed but assumes that the scale is unidimensional. Unidimensionality is a requirement for summating any set of items and this is part of the basic science of measurement. Factor analysis and Rasch analysis showed that the 10 SIPSO items did not form a valid, unidimensional scale. The findings from the former found two significant eigenvalues and the latter demonstrated misfit to the Rasch model when all items were tested against the Rasch model. Rasch analysis is strict in terms of satisfying the requirement for transformation to interval scaling [30
]. The iterative process of Rasch analysis requires unidimensionality tests to be done at each stage. Thus, factor analysis and Rasch analysis provide their own hierarchical ordering of scalability with the assumption of unidimensionality and finally the potential for interval scale transformation. Thus, the three analyses provided incremental evidence of the two subscales, but not the total SIPSO.
The Rasch model has specific properties associated with fundamental measurement, specifically, the raw score as a sufficient statistic, and the separation of person and item parameters[15
]. The former is important as clinicians and others add up the set of responses to make a total score and use these to calculate change scores. As ordinal scales do not support such mathematical operations this is inappropriate. The Rasch model is the only Item Response Theory model that provides an interval scale transformation of the data. As our subscale data fit the Rasch model we were able to produce a conversion table. This table will aid clinicians and researchers in the conversion of the raw data into interval level data for the purpose of mathematical procedures such as summing subscale totals, calculating change scores and for parametric statistical analyses.
The SIPSO is relatively new and there are not many publications reporting its use even though it uniquely measures stroke specific physical and social outcome. There are no other measures that enable the evaluation of physical and social outcome in stroke although there are self-reported health related quality of life (HRQOL) scales, which include aspects of these domains. For example, frequently cited [10
] stroke specific HRQOL measures include the Stroke-Specific Quality of Life Scale [32
] and the Stroke Impact Scale[5
]. However, these measures are much longer, contain other domains and do not have this specific focus on physical and social integration. A direct comparison between these longer HRQOL measures and the SIPSO would enable the comparison of their research and clinical utility. In addition, to compare findings in stroke populations with other groups of patients it will be useful to also include a generic measure in research.
The sample size (n = 445) for the study was estimated for the two parallel needs studies [11
]. A retrospective sample size calculation for the Rasch analysis took into account that in order to be able to report the transformation of ordinal to interval scores normally requires a minimum of 250 cases, or 20 times the number of items, whichever is the greater. Therefore, with a ten item scale this requires 200 cases. As our sample included 445 people this was more than sufficient.
This study included only patients aged 18 to 65. Only 25% of people experience a stroke are younger than 65[2
]. Therefore, our study makes no claims about the appropriateness of the SIPSO in older patients although this has been established by others [6
]. The SIPSO does not include items that are only specific to people of a certain age. In addition, a key characteristic of Rasch analysis is that of specific objectivity
. This is the estimation of item difficulty (or endorsability) independent of the distribution of the person estimates (in this case the amount of physical or social integration someone experiences) in the particular group of patients, and vice versa[15
]. In other words, Rasch analysis is said to enable sample-free estimates of item difficulty. We can therefore conclude that the SIPSO subscales are valid and unidimensional for stroke patients, irrespective of their age.
The SIPSO was completed by post and the overall response rate in the two surveys was 53% [11
] despite strategies that have been shown to improve response rates such as follow-up letters together with the questionnaire and the supply of self-reply envelopes [33
]. However, this response rate tends to be in line with other postal surveys[35
]. In a survey of people discharged from UK hospitals after their stroke it was shown that of those who rated their care as very poor to fair immediately following discharge, fewer responded to the follow-up survey one year later than those who had said the care was good to excellent[36
]. Whether or not our surveys incurred this self-selection bias is impossible to say as we did not the opportunity to collect such data. Non-responders in our first survey were similar to responders in terms of their age and gender[11
]. As for the second survey we were unable to record data on non-responders we are not able to comment on differences between responders and non-responders[12
]. For future studies it would be useful to collect more data on non-responders, though the Research Governance Framework for Health and Social Care [37
] and the Data Protection Act pose significant challenges in achieving such ambitions.