Our study highlights important issues for cancer prevention and control research and contributes to the scant cancer screening literature of published scales with defined psychometric properties. Our study is one of very few published reports of POC construct validation using confirmatory factor analysis (O’Connor, Carbonari, & DiClemente, 1996
) and, to our knowledge, the only study examining POC invariance across stage. As a critical element of the TTM, and the primary construct reflecting how
shifts in behavior occur, both the psychometrics and the role of POC in behavior change deserve greater attention in the cancer screening literature. Because psychometric and intervention research studies using the TTM often neglect POC, much remains to be known about the validity, reliability, and utility of POC as mechanisms of change across multiple and varied cancer prevention behaviors. Although we took the first step in exploring the construct validity and invariance across stage of change for one mammography POC scale, continued psychometric research is needed on the multiple existing POC scales for diverse health behaviors and during the development phase of new POC scales.
Our results provide additional support for the construct validity of this previously published scale. We replicated the factor structure and provided evidence of factorial validity in our full sample and among women in the maintenance stage, the largest subsample. We found evidence of full and partial measurement invariance across adjacent stages of change. Examination of mean POC use by stage confirmed the expected pattern of associations and replicated earlier work supporting the concurrent validity of this scale (Rakowski, Ehrich, et al., 1996
). Lastly, internal consistency coefficients were adequate to good for each subscale and were higher than previously reported (Rakowski, Ehrich, et al., 1996
Although the use of MANOVA to support the concurrent validity of POC scales is common in the TTM literature (DiClemente, et al., 1991
; Fava, et al., 1995
; Rakowski, Ehrich, et al., 1996
; Wadsworth & Hallam, 2007
), conclusions about observed mean differences are based on an assumption of measurement invariance by stage. Our replication of expected differences in factor means by stage groups (concurrent validity analyses) is supportive, but cannot be accepted as completely unequivocal support for construct validity given the differences in model fit by stage group and only partial measurement invariance in 2 of the 3 adjacent stage comparisons; one of which required the free estimation of factor loadings. There is no consensus regarding the number or percent of items with invariant loadings that are necessary to support measurement invariance across groups nor a single recommended approach for dealing with invariant items. Approaches for dealing with scales lacking invariance include restricting group comparisons to items with equivalent factor loadings and variances or exploring the qualitative meaning of the item or factor to understand meaningful group differences (Gregorich, 2006
). Closer examination of the estimates differing by stage indicated that they did not differ qualitatively; that is, they were all positive coefficients and only differed modestly by degree (magnitude). Upon examination of the three factor loadings that were not invariant in the PC-Con comparison, one item (I5) was comparatively longer and more complex than the others and therefore may be a reasonable item to drop from the scale. Four of the items in the Thinking
POC referred to women, friends, and people generally, and only the 2 items referring to doctor recommendation (T3, T6) were not invariant in the PC-Con comparison. These items could be considered for deletion because they may be less relevant for women in precontemplation; women in this stage may have less contact with physicians and are therefore less likely to discuss or be offered mammography. However, because this is only the second study to examine this scale, we believe it would be premature to suggest dropping these items prior to analysis of the POC in other samples.
We also found very large factor correlations (r ≥.91) between 3 of the POC suggesting that at a measurement level it is not clear that women perceive these constructs as different. However, alternative models, including a correlated two-factor model combining these three factors and a second-order factor model grouping these three factors into one second-order factor, did not demonstrate improvement in fit compared with the a priori model. Therefore, although the presence of high correlations among factors is not desirable, the a priori model provided the best fit to the data and was selected as the final model.
Ultimately, the relevance of stage-specific model fit and invariance by stage depends on the primary purpose of the POC. If the purpose of using POC scales is to compare mean scores across stage, factorial invariance by stage should be the goal, as it allows for accurate comparisons of true group differences across stage. For this purpose, items should be general enough and relevant to all stages and items lacking equivalence across stage could be candidates for removal. Alternatively, if researchers are using a POC scale to identify stage-specific clinical indicators of change or to develop tailored individual-based behavioral change interventions, then factorial invariance across stages may not be relevant or necessary. Toward this end, within-stage comparisons would be appropriate and stage-specific POC scales may even be useful in the identification and manipulation of processes needed within a particular stage, but they could not be compared across stages as they reflect different POC.
It is not clear whether the mammography POC scales examined in this study are conceptually different from behavioral and cognitive POC or simply a different grouping of these processes. POC are defined as the cognitive and behavioral strategies used by individuals to facilitate behavior change (Prochaska, Velicer, DiClemente, & Fava, 1988
) and are typically measured with 10 cognitive/experiential and 10 behavioral items reflecting five POC per subscale. Future research should examine the factorial validity and invariance of 2-factor POC scales and compare different conceptualizations of the POC. However, to our knowledge, no previously published 2-factor mammography POC scales are available; moreover, the convention of measuring 2-factor POC with 2 items per process limits the utility of construct validity testing; as more items are typically recommended for confirmatory factor analysis (Marsh, Hau, Balla, & Grayson, 1998
It has been suggested that rather than measuring the behaviors and cognitions through which behavior change occurs, these POC may instead represent reactive actions or attitudes that can result from an intervention (Spencer, Pagell, & Adams, 2005
). Moreover, the response scale ranges from strongly agree-strongly disagree, similar to that used in attitudinal measures and not the frequency scale typically used for the measurement of 2-factor POC. However, all POC items have been selected in part because they are potentially modifiable factors that can be influenced by intervention and it could be argued that even reactive actions or attitudes represent processes that could influence future action. In a longitudinal or intervention study, we would expect increasing use of processes (with the exception of the Avoids
subscale which should decrease) across stage of change progression, as seen in this study and other cross-sectional (Rakowski, Ehrich, et al., 1996
) and intervention studies (Rakowski, et al., 1998
) of mammography, and in cross-sectional studies of other behaviors (DiClemente, et al., 1991
; Fava, et al., 1995
; Wadsworth & Hallam, 2007
). It would be worthwhile to explore the conceptual overlap between different conceptualizations of POC along with their inter-relations with other theoretical constructs in both cross-sectional and longitudinal research to help clarify and understand their unique roles in supporting health behavior change.
This study was a secondary analysis of self-report data from a large cross-sectional sample of baseline participants in a repeat mammography intervention trial. The women were predominantly white, well-educated, and in the maintenance stage for mammography, which may reduce the generalizability of our results. However, our sample was large and randomly selected from a national population of U.S. veterans that is similar in demographic characteristics to the U.S. female population (del Junco, et al., 2008
A strength of this study is that it expands on previous research that has applied the TTM to mammography behavior and replicates earlier findings regarding the valid measurement of infrequently measured POC. The results of this study provide some evidence for construct validity, internal consistency reliability, and partial structural and measurement invariance across stages of change for this scale. We have added confidence in our findings because the factor structure was replicated in our full sample, several years after it was first developed and used in a different population. Our study provides a good launching point for additional psychometric and conceptual research on the POC for mammography and other cancer prevention and control behaviors. For example, following recent work on constructs from the Health Behavior Model (Champion, et al., 2008
) future researchers should explore the psychometrics of this and other TTM measures among diverse populations. Importantly, our study also examined previously untested assumptions that mean differences across stage of change reflect true stage differences rather than differences in construct measurement and/or response style. Future researchers should consider employing similar analyses prior to comparing mean differences of TTM constructs across stage of change.
POC are a central construct of the TTM and are important targets for intervention; yet they are frequently overlooked in studies of cancer screening behaviors. The availability of valid and reliable POC scales will improve researchers’ ability to discriminate between stages of change and to target stage-specific POC in the design of interventions, thus improving intervention effectiveness.