Interpersonal positive reframing in the daily lives of couples coping with breast cancer

Abstract

Objectives: This study examined word use as an indicator of interpersonal positive reframing in daily conversations of couples coping with breast cancer and as a predictor of stress.

Design: The Electronically Activated Recorder (EAR) and Linguistic Inquiry and Word Count (LIWC) were used to examine naturally occurring word use conceptually linked to positive reframing (positive emotion, negative emotion, and cognitive processing words).

Sample: Fifty-two couples coping with breast cancer.

Methods: Couples wore the EAR, a device participants wear, that audio-recorded over one weekend (>16,000 sound files), and completed self-reports of positive reframing (COPE) and stress (Perceived Stress Scale). LIWC, a software program, measured word use.

Findings: Both partners’ word use (i.e., positive emotion and cognitive processing words) was associated with their own reported positive reframing, and spouses’ word use was also indicative of patients’ positive reframing. Results also revealed that, in general, words indicating positive reframing predicted lower levels of stress.

Conclusions: Findings supported the hypothesis that partners—and particularly spouses of breast cancer patients—may assist each other’s coping by positively reframing the cancer experience and other negative experiences in conversation.     

From Braxton Hicks to preterm labour: the constitution of risk in pregnancy.

With the recent introduction of preterm birth prevention programs there has been a shift in our understanding of what the presence of contractions during pregnancy means and a reconstituting of risk in ways that position increasing numbers of women at risk for preterm birth. This paper highlights the findings of a study exploring the influences of risk discourses on women's experiences of preterm labour. The primary goals of this institutional ethnographic study were to describe the effects of societal discourses, institutional structures, and nursing work processes on the everyday lives of childbearing women experiencing preterm labour. The findings suggest that risk discourses exert social control over pregnant women and result in fear, guilt, feelings of being judged or punished, and an overwhelming sense of personal responsibility for preventing preterm birth.The study also exposes ways in which biomedical constructions of risk and preterm labour affect the organization of health services, including nursing practice.     

Influenza vaccination: incidence of symptoms and resulting absenteeism in hospital employees.

A convenience sample of hospital workers, those receiving influenza vaccine and those not receiving vaccine, were asked to complete questionnaires delineating the occurrence of symptoms (e.g., fever, headache, extreme tiredness, dry cough, sore throat, runny nose, stuffy nose, muscle aches) and absenteeism in the 7-day period post-vaccination if vaccinated. Those unvaccinated completed the questionnaire in a self-selected 7 consecutive day period during the study conducted from November 2004 to February 2005. Those receiving either Fluzone or FluMist reported significantly fewer symptoms and related absenteeism than the unvaccinated group (p < .05). Administration of influenza vaccine did not result in higher rates of post-vaccination symptoms as compared to an unvaccinated group. Further, vaccinated employees did not experience higher absenteeism rates as a result of receiving either influenza vaccine. However, for those reporting absenteeism as a result of symptoms, mean absenteeism days were highest in the FluMist group (4.5 days) compared to the unvaccinated group (2.1 days) and the Fluzone group (1.9 days).     

Statistical clues to postoperative blood loss: Moving averages applied to medical data

With the advent of computerized databases, medical data has become easy to accumulate; however, effective use of this data continues to pose significant problems. In other circumstances, smoothing algorithms have been used to uncover non-obvious correlations, trends and relationships in noisy data. We have applied four such algorithms to a large dataset of postoperative blood replacement in cardiopulmonary bypass patients. When applied to this dataset, one of the algorithms proved surprisingly effective. It confirmed several previously observed correlations, and also provided an additional series of counterintuitive and apparently unrelated associations. These associations have been explored in an accompanying paper.