Living with colorectal cancer : naturalistic assessment of daily life

Ecological momentary assessment provides a unique way of studying quality of life factors of colorectal cancer patients. It has yet to be used to study the behavioral expression of distress or depression by colorectal cancer patients. The current study utilized the Electronically Activated Recorder (EAR) technology to capture the daily activities and conversations of forty-eight adults with colorectal cancer. The study had two purposes: 1) to test the feasibility of the EAR with colorectal cancer patients; 2) to examine separate (self-report and behavioral) indicators of physical functioning, coping, and social support for their relationship to depression.
Study participants wore the EAR, a portable digital recorder, for two consecutive days as the EAR recorded 30 seconds every 12.5 minutes. The EAR digital data were transcribed and analyzed for behavioral and linguistic indicators of physical functioning, coping, and social support. The acoustic data were analyzed using the standardized coding system Social Environment Coding of Sound Inventory (SECSI) and the Linguistic Inquiry and Word Count (LIWC2007) computer program. The results provided preliminary evidence that the EAR operated as a feasible and non-disruptive tool for gathering naturalistic data about colorectal patients’ lives. The EAR data revealed information about both the colorectal patients’ internal emotional world as well as their external world which was characterized by solitary acts of daily living. Study subjects were more likely to accept and receive tangible support from others than directly discuss their cancer with others. Analysis of language found that personal disclosure to others was associated with coping through emotional support while causation words (e.g., because, effect, hence) were significantly related with self-report cognitive scales. Furthermore, the study found that first-person singular pronouns were associated not only with depression, but with appraisal of social support. Lastly, a predictive model was tested to see whether self-reported tangible and emotional support and behavioral coding of emotional support each contributed uniquely to the prediction of depression. Only self-reported tangible support was found to significantly predict depression.