Breast Cancer Survivors' Intentions of Managing Lymphedema

Mei R. Fu, PhD, RN, CNS


Cancer Nurs. 2005;28(6):446-457. 

In This Article


A qualitative and cross-sectional design was employed. To ensure a deep understanding of uniqueness of each participant's experience and the experience common to all participants, a descriptive phenomenological method consisting of 4 phases was used for developing a bracket, gathering data, and analyzing data.[30,35] Table 1 describes the 4 phases.

The interview guide was developed to guide the semi-structured interviews as well as to provide the opportunity to flexibly ask other situational questions and use probes to elicit more information. Favorable views of its content validity were provided by 6 doctorally prepared expert researchers and an eligible woman who did not participate. The core questions were designed to elicit information on 3 key sources of data concerning the experience of managing lymphedema: (a) participants' perceptions ("Please tell me what it is like for you to have lymphedema?"), (b) their intentions ("Please tell me what makes you take care of your lymphedema."), and (c) their actions ("Please tell me how you take care of your lymphedema.")

Following the approval by the Health Sciences Center Institutional Review Board of Human Subjects, women were recruited in a midwest state of the United States. A purposive sampling technique was employed to ensure that the participants shared certain similarities.[33,34] Participants were 12 breast cancer survivors who met the following inclusion criteria: (a) being 18 years or older; (b) having completed surgical treatment for breast cancer at least 3 months before enrolling in the study; and (c) having had a diagnosis of lymphedema for at least 1 month prior to enrolling in the study. No additional participants were recruited because the saturation of the data was reached. No attrition occurred.

Among the 12 women, 10 were white and 2 were African American. Most of the women were over 50 years of age and only 2 women were in their late 40s; the age of the women ranged from 46 to 74 years with a mean age of 59. Among the 12 women, 2 were having intensive lymphedema therapy for the exacerbations of arm swelling. Among the 12 women, 2 were retired; 7 had jobs that did not require frequent physical use of their affected arms and hands (such as teacher, cytological technologist, or psychologist); 1 woman, a EKG technician, had a job that required her to frequently lift patients; 1 woman's teaching job required her to move heavy tables to set up activities for children; 1 woman's secretary job required her to constantly type. Table 2 provides more information about the participants.

Developing a Phenomenological Bracket. To conduct phenomenological reduction is to set aside or bracket conventional knowledge during data collection and data analysis.[30,35,36] The conventional knowledge about the experience of managing lymphedema in the study were key ideas conveyed repeatedly in scientific and professional literature. These key ideas bracketed were: (a) managing lymphedema is a set of specific treatments;[14,28,37] (b) managing lymphedema is stressful and demanding;[8,15,37] and (c) managing lymphedema requires high-degree compliance.[15,29]

Data Collection. The researcher conducted 3 private, semi-structured, audio-recorded interviews with each woman at intervals of 1 to 3 weeks, a total of 36 interviews with 12 participants. Each interview was about 70 minutes. Multiple interviews for each participant were employed to ensure data reliability (ie, the stability of the data).[32] The emergence of similar data elicited by asking the same or similar questions over time in each interview was considered a strong indicator for the reliability of data.[35]Table 3 provides an example of similar data collected in the first and second interviews. Data validity, that is, accuracy and truthfulness of the data, was ensured by collecting observational data.[30]

Descriptive Data Analysis. Strategies of "description; comparing and distinguishing, collecting and counting, presupposing and inferring"[30 (p93)] were used for data analysis in a reflective and intuitive way. Using such strategies, the researcher carefully analyzed each idea in every transcript, differentiated each participant's actions from relevant perceptions, and identified the participant's intentions of actions and perceptions. The following example is presented to illustrate identification of the intention of an action. As a teacher for the parent-as-teacher program, one of the participants was accustomed to moving heavy tables to set up activities for children. After she had lymphedema, she tried to carry stuff of lightweight, as she described:

I can't carry heavy tables any more. I try certain activities that I don't have to carry heavy stuff. So, when is the time to sign up, I am trying to think [raising her voice a little], "OK, let me see what stuff has lighter weight. Shaving cream! That's not very heavy to hold." So, like last night, I was carrying my package of shaving cream for the children's activities.

From the action of carrying stuff of lightweight, this intention was developed: "lightening my load physically." Using data this way, the researcher developed the essential structures "directly presented in experience."[38 (p9)]

To achieve an accurate, vivid, and truthful description of experience, Husserl[30] suggested that a categorical system of the essential structures from general to mediating to specific be identified. Accordingly, the researcher developed a taxonomy of 3 levels to describe the essential structures of experience, ranging from specific to mediating to general: unit intention (each participant's unique intention), cluster intention (a proposition in general found in most of the participants), and revelatory intention (a general intention found in all the participants).

Appraisal of the Finding. To appraise the credibility of the analysis and ensure the descriptive validity, the researcher engaged in dialogues with each participant and expert researchers. The researcher used the last interview with each participant to validate her understanding of each participant's experience from the previous 2 interviews. The researcher discussed the final data analysis with 6 doctorally prepared expert researchers; these experts considered the data analysis valid. Finally, the researcher discussed the findings from the data analysis by integrating the bracketed key ideas and relevant literature.


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