Over the last 15 years, numerous self-report health status measures have appeared in the literature. An important parallel development has been the development of numerous strategies for assessing change in health status over time. The purpose of this article is to summarize and critique the more common design and analytic strategies for assessing the meaningfulness of change over time. Five commonly reported designs are presented, critiqued, and depicted using examples from the literature. Methods for analyzing results are reviewed and illustrated using two data sets. Insights into comparing competing health status measures are provided. In summary, the article suggests that some designs and analytic strategies are more adept than others at assessing change and that these methods should be considered when planning sensitivity-to-change studies.
Self-report disability measures are one method of asessing patients' outcomes. Generic, disease-or condition-specific, and patient-specific measures represent three types of self-report meawres (2,5,8,9,13,14,16,23,25,26). Generic measures sample a broad spectrum of health concepts that usually include social, emotional, and physical wellbeing (2,26). These measures usually take much longer to completeoften greater than 20 minutes-than conditionspecific measures. Moreover, generic measures tend to lack the specificity that is present in a welldesigned condition-specific measure (8,13,23). Condition-specific measures consist of items that are most relevant to the condition being measured. They are used to compare the health status among patients at the same point in time and to assess change over time.A potential limitation of generic and conditionspecific measures is that they are designed with group decision-making in mind. Accordingly, when they are applied to individual patients, two shortcomings are often noted: I) a substantial change in a patient over time, relative to the error associated with the measure, is required to be confident that a true change has occurred in a patient and 2) an inability to detect confidently an improvement in persons present-
Important change appears to be dependent on patients' initial RMQ scores. Subsequent inquiry using different hypotheses would add support to the estimates of important change found in this study.
BACKGROUND: The current model of care for individuals with breast cancer focuses on treatment of the disease, followed by ongoing surveillance to detect recurrence. This approach lacks attention to patients' physical and functional well-being. Breast cancer treatment sequelae can lead to physical impairments and functional limitations. Common impairments include pain, fatigue, upper-extremity dysfunction, lymphedema, weakness, joint arthralgia, neuropathy, weight gain, cardiovascular effects, and osteoporosis. Evidence supports prospective surveillance for early identification and treatment as a means to prevent or mitigate many of these concerns. This article proposes a prospective surveillance model for physical rehabilitation and exercise that can be integrated with disease treatment to create a more comprehensive approach to survivorship health care. The goals of the model are to promote surveillance for common physical impairments and functional limitations associated with breast cancer treatment; to provide education to facilitate early identification of impairments; to introduce rehabilitation and exercise intervention when physical impairments are identified; and to promote and support physical activity and exercise behaviors through the trajectory of disease treatment and survivorship. METHODS: The model is the result of a multidisciplinary meeting of research and clinical experts in breast cancer survivorship and representatives of relevant professional and advocacy organizations. RESULTS/CONCLUSIONS: The proposed model identifies time points during breast cancer care for assessment of and education about physical impairments. Ultimately, implementation of the model may influence incidence and severity of breast cancer treatment-related physical impairments. As such, the model seeks to optimize function during and after treatment and positively influence a growing survivorship community.
The magnitude of CSEMs is sufficiently small to detect change in patients with initial scores in the central portion of the scale (4-20 RMQ points); however, the magnitude is too large to detect improvement in patients with scores of less than 4 and deterioration in patients who have scores greater than 20.
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