An Analytic Strategy for Modeling Multiple-Item Responses

Midlife women's symptom cluster heuristics: evaluation of an iPad application for data collection

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.

Relationship Between Patients' Perceptions of Care Quality and Health Care Errors in 11 Countries: A Secondary Data Analysis

Patients may be the most reliable reporters of some aspects of the health care process; their perspectives should be considered when pursuing changes to improve patient safety. The authors evaluated the association between patients' perceived health care quality and self-reported medical, medication, and laboratory errors in a multinational sample. The analysis was conducted using the 2010 Commonwealth Fund International Health Policy Survey, a multinational consumer survey conducted in 11 countries. Quality of care was measured by a multifaceted construct developed using Rasch techniques. After adjusting for potentially important confounding variables, an increase in respondents' perceptions of care coordination decreased the odds of self-reporting medical errors, medication errors, and laboratory errors (P < .001). As health care stakeholders continue to search for initiatives that improve care experiences and outcomes, this study's results emphasize the importance of guaranteeing integrated care.

Symptoms of hormonal therapy and social support: Is there a connection? Comparison of symptom severity, symptom interference and social support among breast cancer patients receiving and not receiving adjuvant hormonal treatment

BACKGROUND

Although there has been a significant reduction in mortality, breast cancer is the most frequent cancer among women worldwide. This decline in mortality has created a significant survivor population that must manage the post curative treatment phase, in order to have an increased quality of life and well-being. This study examined the relationship between symptom interference and severity with the perception of social support in the lives of women receiving or not receiving, hormonal therapy after initial treatment.

METHODS AND SAMPLE

Participants completed symptom severity and interference questionnaires, (MDASI and BCPT), a social support survey (MSPSS) and demographic and comorbidity questionnaires.

RESULTS

Of the 210 women participants, higher symptom severity correlated with unemployment, living alone or being religious. Participants who were currently taking hormonal treatment (n = 84), reported a significant negative correlation between symptom severity, measured by MDASI, and social support (p = 0.006). Consequently, as symptom severity increased, perceived social support decreased. In the BCPT assessment, decreased cognitive functioning (p < 0.05), pain (p < 0.05), bladder dysfunction (p = 0.001), and reduced self-image (p < 0.01) were significantly negatively correlated with social support for those participants currently taking hormonal therapy. Participants who had not previously received hormonal therapy (n = 64), cognitive dysfunction and bladder dysfunction were negatively correlated with social support. Women with preexisting heart or pulmonary dysfunction and arthritis reported statistically significant higher levels of symptom severity and decreased perceptions of social support.

CONCLUSIONS

Identifying socio-demographic variables and comorbidities that affect hormonal therapy symptom burden is essential for offering adequate support for breast cancer survivors.

Evaluation of time-varying and cumulative effects in nursing in a longitudinal study

BACKGROUND

Traditional statistics in longitudinal data analysis are likely to be insufficient in nursing studies, in which the time varying characteristics of explanatory variables and cumulative effects require additional consideration.

OBJECTIVES

The aims of this study were to introduce alternative longitudinal approaches for incorporating time-varying variables and cumulative effects, to discuss their strengths, and to highlight key issues that nursing researchers should recognize before and while undertaking such analyses.

RESULTS

The three alternative models provide differing analytical outcomes based on the research focus. The baseline tracking model was used to estimate the stability effect of an intervention program, detecting risk factors early. The temporal sequence of potential cause and effect was incorporated further in the time-dependent model. The cumulative model was used to explore whether cumulative intervention effects existed.

CONCLUSION

Nurse researchers should incorporate alternative methods into the longitudinal data analysis tools they commonly use when facing explanatory variables with time variations or cumulative effects on the variable being measured.

Causal symptom attributions in somatoform disorder and chronic pain

OBJECTIVE

Somatoform disorders (SFD) are defined by symptoms that lack medical explanation. This study examined the type and pattern of patients' causal attributions using a new semistructured interview technique

METHODS

The Causal Attributions Interview allows to assess and weigh 15 common explanations of physical symptoms. Attributions given by 79 patients with SFD were compared with those obtained from 187 chronic pain patients.

RESULTS

The test-retest reliabilities of the interview-elicited attributions were satisfactory to good. SFD patients attributed most of their symptoms to mental/emotional problems (46.9%) and somatic disease (41.1%), while the pain sample preferred physical overloading/exhaustion (56.1%), daily hastiness/time pressure (41.7%), somatic disease (39.6%), and weather influence (39.0%). On average, SFD patients chose 2.57 and pain patients 3.86 different attributions for each symptom. These numbers were substantially larger than those of initial spontaneous attributions. Correspondence analysis revealed underlying dimensions with three groups labeled "environmental," somatic," and "psychological/stress." While pure environmental attributions were rare (1.1%), somatic factors were chosen for 28.3% of the symptoms, psychological/stress for 22.1%, and the combination of both for 25.6%. Approximately 10% were attributed in a multicausal sense to all three groups. Depression was found to correlate positively with psychological/stress and negatively with somatic attributions.

CONCLUSION

The results do not support the perspective that SFDs generally result from poor acknowledgement of emotional factors. SFD and chronic pain showed distinguishable attributional patterns.

Is there a biological basis for the clustering of symptoms?

OBJECTIVES

To examine symptom clusters in oncology patients; to determine if these symptom clusters might share a common biologic mechanism; and to describe potential biologic mechanisms that warrant investigation.

DATA SOURCES

Synthesis of the theoretical and research papers on symptom clusters.

CONCLUSION

Definitive conclusions about whether there is a biologic basis for the clustering of symptoms cannot be determined at this time. The animal model of sickness behavior holds promise as a potential biologic mechanism for clustering symptoms.

IMPLICATIONS FOR NURSING PRACTICE

Until more definitive studies of symptom clusters are performed, clinicians need to monitor patients for the co-occurrence of multiple symptoms and develop appropriate management plans.

Symptom experience in the last year of life among individuals with cancer

Individuals with cancer often experience many symptoms that impair their quality of life at the end of life. This study examines symptom experience at end of life among individuals with cancer, and determines if symptom experience changes with proximity to death, or differs by depressive symptomatology, sex, site of cancer, or age. A secondary analysis of data from three prospective, descriptive, longitudinal studies (n=174) was performed, using a three-level hierarchical linear model. Fatigue, weakness, pain, shortness of breath, and cough were the five most prevalent symptoms in the last year of life. The symptom experience in the last year of life was significantly associated with site of cancer, depressive symptomatology, dependencies in activities of daily living, and independent activities of daily living at the start of the study. These findings shed light on the symptom experience in the last year of life for individuals with cancer. With greater understanding of the symptom experience, intervention strategies can be targeted to achieve the desired outcome of increased quality of life at the end of life.