Developing the communicative participation item bank: Rasch analysis results from a spasmodic dysphonia sample

Abstract

Purpose: The purpose of this study was to conduct the initial psychometric analyses of the Communicative Participation Item Bank-a new self-report instrument designed to measure the extent to which communication disorders interfere with communicative participation. This item bank is intended for community-dwelling adults across a range of communication disorders.

Method: A set of 141 candidate items was administered to 208 adults with spasmodic dysphonia. Participants rated the extent to which their condition interfered with participation in various speaking communication situations. Questionnaires were administered online or in a paper version per participant preference. Participants also completed the Voice Handicap Index (B. H. Jacobson et al., 1997) and a demographic questionnaire. Rasch analyses were conducted using Winsteps software (J. M. Linacre, 1991).

Results: The results show that items functioned better when the 5-category response format was recoded to a 4-category format. After removing 8 items that did not fit the Rasch model, the remaining 133 items demonstrated strong evidence of sufficient unidimensionality, with the model accounting for 89.3% of variance. Item location values ranged from -2.73 to 2.20 logits.

Conclusions: Preliminary Rasch analyses of the Communicative Participation Item Bank show strong psychometric properties. Further testing in populations with other communication disorders is needed.

Figure 1

Sample item. SD = spasmodic dysphonia.

Figure 2

A: Category response curves for a sample item using the original five-category response structure. Note that the curves for quite a bit and not at all are not distinctly separated from neighboring categories. B: Category response curves for the same item as in 2A using the recoded four-category response structure. Note that each of the four categories now presents a curve with a peak distinctly separate from neighboring categories.

Figure 3

Scree plot for exploratory factor analysis of the original 141 items. The plot demonstrates the presence of one dominant factor by the steep slope between the first and second factor, and the minimal change in slope between subsequent factors.

Figure 4

Distribution of 133 items along the logit scale according to item location. Each horizontal line represents one item. Sample items are provided to illustrate item content at different item location levels. Example participants are provided to illustrate the relationship between participants’ scores (theta values) and items that are calibrated on the same logit scale. Participants are more likely to report interference on items located higher than their theta values, and they are less likely to report interference on items located lower than their theta values. Participant 2 has a more favorable score than Participant 1 (higher scores are better).

Figure 5

The curve is the test information function for the final 133-item set. Measurement is most precise for trait regions under the highest regions of the curve. The horizontal line indicates an information level of 10, which corresponds approximately to a reliability coefficient of 0.90 (Embretson & Reise, 2000). Below the test information curve, the distribution of participants’ theta values (scores) across the same logit scale is presented. Each vertical tick mark represents 1 participant. Comparison of the distribution of participants’ scores with the test information curve reveals those participants for whom measurement was more precise.

Figure 6

The standard error of measurement curve calculated as the inverse of the square root of the test information function.