Levels and predictors of distress in home hemodialysis caregivers

The principal objective of this study was to understand the level of distre ss in the home hemodialysis caregiver community. A literature review reveal ed that relativity little attention had been given to this group. Seventy-t wo caregivers of the Sydney Dialysis Center's home hemodialysis population were approached to complete a self-report questionnaire with 64 caregivers responding (89% response rate). This analysis includes 61 caregivers of a p atient of the opposite sex. The questionnaire included a global measure of distress (General Health Questionnaire) and a specific measure of distress (Relatives' Stress Scale). The Relatives' Stress Scale included subscales f or Personal Distress, Life Upsets, and Negative Feelings. Other variables i ncluded were demographic and medical. Descriptive statistics revealed that the specific distress scales were more sensitive measures of caregiver distress than the global distress score. S egmentation modeling (SPSS CHAID decision-tree analysis) was performed to i dentify, caregiver subgroups which reported high distress. Separate segment ation analyses were performed for Personal Distress, Life Upsets, and Negat ive Feelings. The main predictors of high Personal Distress were younger ag e of the caregiver combined with low levels of involvement with the patient . The main predictors of high Life Up-sets were a perception of the patient 's health as "fair" combined with a younger caregiver For caregivers who pe rceived their patient to be in "fair" health,females were also high on Life Up-sets. The main predictor of high Negative Feelings was level of involve ment, with high Negative Feelings associated with both low and high involve ment. Two caregiver subgroups-rural-based caregivers with high involvement; and caregivers, able to fake a break from caring responsibilities, with lo w involvement-were particularly at risk of reporting high Negative Feelings . Interestingly, the age of the caregiver was not associated with Negative Feelings. Overall complete segmentation decision-tree analysis assists in t he identification of caregiver subgroups with specific forms of distress th at may not be identified with global distress measures.