PURPOSE: Considerable research has demonstrated the negative psychosocial impact of cancer. Recent work has highlighted positive psychosocial outcomes. Research is now needed to evaluate the relationship between negative and positive impacts. This paper reports the development and validation of a measurement model capturing positive and negative psychosocial illness impacts. METHODS: The sample included 754 cancer patients on- or post-treatment. Item development was informed by literature review, expert input patient interviews and the results of a pilot study of 205 cancer patients, resulting in 43 positive and 46 negative items. Factor analyses were used to evaluate the dimensionality of the item pools. Analysis of variance (ANOVA) was used to examine relationships between psychosocial illness impact and other variables. RESULTS: Unidimensionality was demonstrated within but not across negative and positive impact items. ANOVA results showed differential relationships between negative and positive impacts, respectively, and patient sociodemographic and clinical variables. CONCLUSION: Positive and negative psychosocial illness impacts are best conceptualized and measured as two independent factors. Computerized adaptive tests and short-form measures developed from this comprehensive psychosocial illness impact item bank may benefit future research and clinical applications.
PURPOSE: Considerable research has demonstrated the negative psychosocial impact of cancer. Recent work has highlighted positive psychosocial outcomes. Research is now needed to evaluate the relationship between negative and positive impacts. This paper reports the development and validation of a measurement model capturing positive and negative psychosocial illness impacts. METHODS: The sample included 754 cancerpatients on- or post-treatment. Item development was informed by literature review, expert input patient interviews and the results of a pilot study of 205 cancerpatients, resulting in 43 positive and 46 negative items. Factor analyses were used to evaluate the dimensionality of the item pools. Analysis of variance (ANOVA) was used to examine relationships between psychosocial illness impact and other variables. RESULTS: Unidimensionality was demonstrated within but not across negative and positive impact items. ANOVA results showed differential relationships between negative and positive impacts, respectively, and patient sociodemographic and clinical variables. CONCLUSION: Positive and negative psychosocial illness impacts are best conceptualized and measured as two independent factors. Computerized adaptive tests and short-form measures developed from this comprehensive psychosocial illness impact item bank may benefit future research and clinical applications.
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