Nancy Fugate Woods1, Rita Ismail, Lauri A Linder, Catherine Fiona Macpherson. 1. 1Biobehavioral Nursing and Health Systems, School of Nursing, University of Washington, Seattle, WA 2Ministry of Health, Jakarta, Republic of Indonesia 3University of Utah College of Nursing, Salt Lake City, UT 4Primary Children's Hospital, Salt Lake City, UT 5Seattle Children's Hospital, Seattle, WA 6Family and Child Nursing, University of Washington, Seattle, WA.
Abstract
OBJECTIVE: This study aims to elicit midlife women's heuristics about symptom clusters they were experiencing, as identified by the Computerized Symptom Capture Tool for Menopause (C-SCAT M). METHODS: Women aged 40 to 60 years who were experiencing symptoms that they associated with menopause were recruited through flyers posted on campus and in clinics. Women completed the C-SCAT M application (app), using an iPad, by identifying and drawing symptom clusters they experienced during the last 24 hours, indicating relationships among symptoms, prioritizing the clusters and symptoms within them, making causal attributions, and identifying exacerbating and ameliorating factors. They were asked to prioritize the clusters and a symptom within each cluster. While women were completing the app, they were asked to "think aloud" about their experience using the app. Data generated from the C-SCAT M app were transmitted securely to an Amazon Web Services account and saved as screen images and Excel files to preserve both graphical images and text elicited from the app. Qualitative data were saved in verbatim phrases. Conventional content analysis was used to analyze qualitative data. RESULTS: Thirty women completed the app. Most women (77%) stated that the final diagrams were very/extremely accurate in depicting their symptoms and their connections. Women reported between 1 and 22 symptoms (median, 11). Hot flashes, waking up during the night, night sweats, and early morning awakening were the most commonly reported symptoms. Women rated hot flashes as their most bothersome symptom, followed by waking up during the night and fatigue. They reported more than 300 different bivariate relationships between their symptoms and more than 150 unique causal paths. They believed that hot flashes caused several symptoms, especially sleep disruption, and most could describe the time order of their symptoms. Women reported clusters consisting of 2 to 18 symptoms. Women also named each cluster based on their response to their symptoms ("really annoying"), time of occurrence ("night problem"), and symptoms included in the cluster ("hot flash"). They attributed their clusters to menopause, life demands, and other symptoms, among other causes. Management strategies that women used included over-the-counter preparations, sleep, rest, and other lifestyle changes. Some women requested for a copy of their final symptom cluster diagram to discuss with their healthcare providers. CONCLUSIONS: Use of the C-SCAT M affords women an opportunity to depict their symptoms and clusters and the relationships between them and to provide narrative data about their heuristics. Women's unsolicited comments about using the cluster diagram to facilitate conversations (about their symptoms) with their healthcare providers suggest the potential value of modifying the C-SCAT M and evaluating its use in a healthcare setting.
OBJECTIVE: This study aims to elicit midlife women's heuristics about symptom clusters they were experiencing, as identified by the Computerized Symptom Capture Tool for Menopause (C-SCAT M). METHODS:Women aged 40 to 60 years who were experiencing symptoms that they associated with menopause were recruited through flyers posted on campus and in clinics. Women completed the C-SCAT M application (app), using an iPad, by identifying and drawing symptom clusters they experienced during the last 24 hours, indicating relationships among symptoms, prioritizing the clusters and symptoms within them, making causal attributions, and identifying exacerbating and ameliorating factors. They were asked to prioritize the clusters and a symptom within each cluster. While women were completing the app, they were asked to "think aloud" about their experience using the app. Data generated from the C-SCAT M app were transmitted securely to an Amazon Web Services account and saved as screen images and Excel files to preserve both graphical images and text elicited from the app. Qualitative data were saved in verbatim phrases. Conventional content analysis was used to analyze qualitative data. RESULTS: Thirty women completed the app. Most women (77%) stated that the final diagrams were very/extremely accurate in depicting their symptoms and their connections. Women reported between 1 and 22 symptoms (median, 11). Hot flashes, waking up during the night, night sweats, and early morning awakening were the most commonly reported symptoms. Women rated hot flashes as their most bothersome symptom, followed by waking up during the night and fatigue. They reported more than 300 different bivariate relationships between their symptoms and more than 150 unique causal paths. They believed that hot flashes caused several symptoms, especially sleep disruption, and most could describe the time order of their symptoms. Women reported clusters consisting of 2 to 18 symptoms. Women also named each cluster based on their response to their symptoms ("really annoying"), time of occurrence ("night problem"), and symptoms included in the cluster ("hot flash"). They attributed their clusters to menopause, life demands, and other symptoms, among other causes. Management strategies that women used included over-the-counter preparations, sleep, rest, and other lifestyle changes. Some women requested for a copy of their final symptom cluster diagram to discuss with their healthcare providers. CONCLUSIONS: Use of the C-SCAT M affords women an opportunity to depict their symptoms and clusters and the relationships between them and to provide narrative data about their heuristics. Women's unsolicited comments about using the cluster diagram to facilitate conversations (about their symptoms) with their healthcare providers suggest the potential value of modifying the C-SCAT M and evaluating its use in a healthcare setting.