Behavioral Research

Table of Contents
1 General Description & Theoretical Background
2 Similar Constructs

Measurement and Methodological Issues

4 Conclusion



Measures Appendix

7 Published Examples

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Other Constructs



Dispositional Optimism




Illness Representations

  Implementation Intentions
  Intention, Expectation, and Willingness
  Normative Beliefs
  Optimistic Bias
  Perceived Benefits
  Perceived Control
  Perceived Severity
  Perceived Vulnerability
  Self-Reported Behavior
  Social Influence
  Social Support

Perceived Benefits
Victoria Champion

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3 Measurement and Methodological Issues

Specificity is critical to the assessment of perceived benefits. For example, development of a scale to measure perceived benefits of sun protection must take into account the specific action being considered (e.g., use of sunscreen vs. wearing a hat), and the specific benefits being considered (e.g., decreasing likelihood of skin cancer vs. delaying the appearance of age spots and wrinkles). Thus, developing appropriate operational definitions of benefits will continue to challenge researchers as the construct is used with new behaviors. This work will undoubtedly build on the development of valid and reliable scales during the past decade to assess perceptions of the benefits of screening for breast cancer and colorectal cancer.

Benefits of breast self-examination and mammography

Assessments of benefits of breast cancer screening have included both the behaviors of breast self-examination (Lauver & Angerame, 1988) and mammography (Champion, 1984; Champion, Foster, & Menon, 1997; Champion, 1999). In general, these scales have good predictive validity. For example, Skinner, Champion, Gonin, Hanna et al., (1997) found that perceived benefits for mammography differentiated between women considering a mammogram and those who were currently adherent for mammography. Specific items that significantly differentiated between these groups included finding lumps early, decreasing chances of dying from cancer, and helping find lumps before they can be felt. In a sample of low-income African American women, perceptions of these benefits were lower for those who had not considered having a mammogram than for those who had considered the test (Champion & Springston, 1999).

A measurement study assessed benefits for mammography screening scale for validity and reliability (Champion, 1999). Items included not worrying about breast cancer, helping to find breast lumps early, and treatment won't be as bad (see Appendix A). Internal consistency reliability of .75 was calculated for the scale. Confirmatory factor analysis identified all items as having a Lambda of .40 or greater. Construct validity was also found through exploratory factor analysis and by determining that differences in benefits did exist for persons in different stages of mammography behavior.

Colorectal cancer (CRC)

The development of benefits scales for colorectal cancer screening has been guided by the same measurement principles as those for mammography and breast self-examination, and they have also demonstrated good validity and reliability (Rawl, et al., 2001). A good example of measurement specificity can be found in a scale developed by Rawl et al. (2001), which included questions about the benefits of finding cancer early and decreasing the chances of dying from colorectal cancer if one had FOBT, sigmoidoscopy, or colonoscopy . Reliability was measured using Cronbach's alpha and was .65 for FOBT, .67 for flexible sigmoidoscopy, and .70 for colonoscopy. Exploratory factor analysis identified dimensions for benefits of FOBT, sigmoidoscopy, and colonoscopy with respective items loading at .54 to .78 for FOBT, .35 to .58 for flexible sigmoidoscopy, and .62 to .72 for colonoscopy. Theoretically consistent differences were found in all benefits scales and screening participation. Wardle developed a benefits scale specific to sigmoidoscopy using a 7-item scale with 5-point Likert-like response scales (Wardle et al., 2003). Items demonstrated construct validity by loading at .4 or above on their respective scale. Internal consistency reliability was .83.


The perceived benefits construct is defined as an individual's belief that specific positive outcomes will result from a specific behavior. Research conducted over the last three decades has demonstrated the use of this construct in predicting behavior, but several measurement issues continue to warrant attention when employing a perceived benefits scale. First, perception of benefit is specific to a behavior and the more specifically the behavior is defined, the higher the predictive validity of the scale. For example, a scale to measure benefits of cancer screening would predictive mammography behavior more poorly than a scale designed specifically to identify benefits of mammography screening per se. Second, because the construct of benefits is most useful when developed as behavior-specific, any attempt to use this construct with a new behavior will necessitate development of items specific to that behavior. Thus, the validity and reliability of measures of the construct will continue to be an important issue as scales are developed to assess the benefits on new health behaviors and health threats. When a new scale is developed, it is important to carefully assess its validity and reliability.

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