Life Satisfaction Among Persons with Spinal Cord Injuries

Journal of Rehabilitation, July-Sept, 2000 by Brent W. Chase, Thomas A. Cornille, R. William English

The Personal Assistance Satisfaction Index (Nosek, Quan, & Potter, 1992) was used to measure satisfaction with personal care assistance services. A higher score suggested greater satisfaction. Of our respondents, approximately 30% of the sample did not complete the Personal Assistance Satisfaction Index. A cross tabulation revealed that persons with a missing score tended to be those who were married (n = 28) or persons with an injury level (e.g. C5-8 quadriplegia incomplete and paraplegia) that may have allowed for greater independence (n = 23).

The fourth independent variable, marital status, was coded from the demographic information provided by each participant. Choices included: never married, married, separated, divorced, and widowed.

The fifth independent variable, handicap, is described as a disadvantage that limits or prevents fulfillment of a role that is typical, depending on age, sex, and social and cultural factors (World Health Organization, 1980). Whiteneck, Charlifue, Gerhart, Overholster, & Richardson (1992) developed the Craig Handicap Assessment & Reporting Technique (CHART) as a way of quantifying the degree to which persons with a spinal cord injury in a community setting are handicapped. A higher score implied less handicap. A total handicap score on the CHART cannot be computed without the presence of all five subscale scores. The CHART was given as part of the questionnaire to the respondents of this study. Seventy-seven respondents (48.7%) had scores for all the five subscales, 65 persons (41.1%) had scores for four subscales, and 16 (10.1%) had scores for three or fewer subscales. Due to the loss of data in excluding those respondents answers on only four subscales, in these cases, missing subscale scores were replaced with the subscale mean for the sample for any person reporting a score on four CHART subscales. This conservative approach to estimating responses from incomplete data has been recommended as one approach to this dilemma in social sciences (SPSS, 1997). All respondents with three or fewer subscale scores were removed from the analysis (n = 16).

The sixth independent variable, years since injury, is included in the demographic information provided by participants. As described earlier, participants on the average were 12 years post-injury.

The seventh variable, health, is addressed through two questions. First, participants were asked to rate their overall physical health during the past year on a scale of 1 to 5, with 1 being poor and 5 being very good. All participants responded to this question. The mean overall physical health during the past year was 4.01 with 76% indicating their health was either good or very good. Second, participants were asked to indicate the number of times they had been hospitalized during the past year. All participants responded to this question. The number of hospitalizations reported included 0 (n = 118, 75%), 1 (n = 30, 19.0%), or at least 2 (n = 10, 6%).

Results

Measurement scores, frequencies, means, and standard deviations were initially computed. The data were analyzed using multiple regression analysis. An alpha level for all statistical testing of significance was preset at the .05 level.