Modeling the decision to undergo colorectal cancer screening: insights on patient preventive decision making

Med Care. 2008 Sep;46(9 Suppl 1):S17-22. doi: 10.1097/MLR.0b013e31817eb332.

Abstract

Background: Little is known about how patients decide whether or not to undergo colorectal cancer screening. Although low screening rates evidence the outcome of these decisions, the processes patients use to balance benefits, risks, and costs with their own values and preferences are unclear. To increase screening rates, and ultimately save lives, it is important for providers to be aware of how patients make screening decisions.

Objectives: The purpose of this study was to identify patterns of patient colorectal cancer screening decisions that might be supported by health care providers.

Population: In this study, we focused on people from Central Kentucky--a region with historically low screening rates.

Method: We interviewed patients using a semi-structured format. Three members of the research team independently analyzed each interview transcript for factors that influenced the decision, and a pictorial representation of each decision process, based on Kurt Lewin's theory of decision making, was constructed for each participant. The individual decision processes were compared with identify patterns.

Results: Seventeen women and 13 men made up the sample. We discerned 7 decision patterns.

Conclusions: This research documents 7 patterns and identifies common driving and restraining forces.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Attitude to Health*
  • Colorectal Neoplasms / diagnosis*
  • Colorectal Neoplasms / psychology*
  • Decision Making*
  • Female
  • Humans
  • Kentucky
  • Male
  • Mass Screening / methods
  • Mass Screening / psychology*
  • Middle Aged
  • Outcome Assessment, Health Care
  • Patient Acceptance of Health Care / statistics & numerical data
  • Patient Education as Topic
  • Patient Participation / statistics & numerical data*
  • Patient Satisfaction / statistics & numerical data
  • Physician-Patient Relations
  • Surveys and Questionnaires