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Biomedical subjects

Susan McMillan

Publications and source records attributed to Susan McMillan.

4 recordsLinked to original sources
PubMed2003

Dyspnea and quality of life indicators in hospice patients and their caregivers.

This study describe the assessment of dyspnea, symptom distress, and quality of life measures in 163 hospice patients with cancer who reported dyspnea. Mean age of the hospice patient sample was 70.22 years and 61.86 for caregivers (65% were spouses). The majority of patients and caregivers were white: 87%, 63% of the patients were male while 78% of caregivers were female. Mean dyspnea intensity as reported by patients was 4.52 (SD 2.29) and caregivers, 4.39 (SD 2.93). Patients' and caregivers' ratings of the patient's dyspnea intensity revealed no significant differences in ratings thus verifying that caregivers can assess dyspnea severity accurately. Patients' perceived quality of life ratings were not significantly correlated with ratings of their caregivers' perceived quality of life. For patients, symptom distress and education were significant predictors of variance in quality of life (R2 =.35, p =.04). However, mastery, symptom distress, age, and education were found to be significant predictors of variance in quality of life of caregivers (R2 =.40, p =.02).

Adult↗
PubMedDate not supplied

Maintaining data integrity in randomized clinical trials.

BACKGROUND: The process of attaining and maintaining data integrity is critical to ensure a successful randomized clinical trial. Methodologic strategies to achieve data integrity when repeated measures are used has not been discussed in detail in the literature. The National Institutes of Health requires that data integrity and safety monitoring boards or plans be established for randomized clinical trials. OBJECTIVES: The objectives of this paper are to (a) examine important data collection issues nurse scientists often encounter in randomized clinical trials and (b) present a process that researchers can apply to achieve data integrity. METHODS: The process to achieve data integrity is based on strategies that were developed by an interdisciplinary hospice research team involved in an ongoing National Institutes of Health-funded clinical trial. The process and key issues are illustrated with methodologic examples from the randomized clinical trial and supporting literature. RESULTS: The process of achieving data integrity involves developing protocols in three key areas: data collection, training of data collectors, and data monitoring. The use of these protocols will increase the rigor of the clinical trial and assist in maintaining study validity. CONCLUSIONS: Investigators conducting clinical trials need to consider all issues involved in achieving data integrity and have tested protocols in place throughout the study. These approaches will not only help maintain study validity but also help ensure data of sufficient quantity and quality to achieve the desired statistical power.

Bias↗