The participants were members of the Qualtrics online participant panel. The demographics of the United States Qualtrics panel pool are as follows: median age = 35-44 years old (IQR [interquartile range] = 25 to 54); racial identification is 73.8% White, 10.3% African-American, 6.5% Asian, 1.5% American Indian or Alaska Native, 0.6% Pacific Islander, and 4.6% “some other race ”; median household income = $45,000 to $49,999 (IQR = $25,000 to $89,000); highest level of education is 26.9% High School graduate with 18.4% possessing an undergraduate college degree or better. Of the 2,260 panel members who responded to the invitation and were screened for inclusion, N = 1,372 met study inclusion criteria and consented to participate (Full Study Sample). Inclusion criteria were (a) married or living with a partner, (b) both partners ≥ 18 years old, and (c) cohabiting with the partner for at ≥ 1 year. The Full Study Sample was 51.0% female, 42.3% had a high school diploma, GED, or less, and 29.1% had an undergraduate university degree or better. The modal annual family income range was $50,000 to $99,000 (31.6%), with 24.5% earning ≤ $25,000 and 19% earning ≥ $100,000.

[+]

Identified

Coercive Family Process Theory (Patterson, 1982) is one of the most highly developed and influential interpersonal models of dyadic family conflict. Coercion Theory builds off of Social Learning Theory, the foremost cognitive behavioral approach to behavior. Coercion Theory explains how, despite their unpleasant and destructive qualities, hostile escalation sequences are reinforced for both persons. Patterson posited that people learn coercive behavior through the ways in which conflicts are resolved. Over time, if Person A responds to Person B’s escalating aversive behavior by giving in (thus ceasing his/her own aversive behavior), B learns to escalate to get his/her way. Importantly, both persons’ behaviors are maintained through reinforcement. B is negatively reinforced for escalating (via A shutting up) and may be positively reinforced as well (via A doing what B was asking for in the argument). A is negatively reinforced for giving in (via the termination of B’s aversive behavior). Over time, these conflicts serve as learning trials. Of course, B does not always win. Sometimes, B backs down in response to the A’s aversive escalation. Thus, once a coercive process takes hold, both members of the dyad are faced with an unfortunate choice: (a) give in and lose the battle, or (b) win via out-escalating the other. This process leads to ever darker, bitter battles. In Patterson’s (1976, p. 1) exquisite phrasing, each person is both “victim and architect of a coercive system.”
As noted in a review of the literature by Robles et al., 2014 (a meta-analysis of 126 published empirical articles investigating relationship quality and physical health), a sizable literature links hostile couple relationships to (a) problems with social-cognitive and affective processes, such as self-regulation of emotion and behavior; (b) physiological stress reactivity processes, especially in the neuroendocrine axes and in immune functioning; and (c) poor health outcomes.

[+] PMCID, PUBMED ID, or CITATION

Text Citation: Robles, T. F., Slatcher, R. B., Trombello, J. M., & McGinn, M. M. (2014). Marital quality and health: A meta-analytic review. Psychological Bulletin, 140, 140. doi:10.1037/a0031859

Text Citation: Patterson, G. R. (1982). Coercive family processes. Eugene, OR: Castilla Press.

Measured

Factor analysis indicates that the CCS is reasonably, if not perfectly, unifactorial.
Multigroup CFAs were estimated to investigate possible differences in factor structure by gender. The model that equated women's and men's factor loadings had an acceptable fit, but a significantly worse fit than the model that allowed men's and women's factor loadings to vary freely. Follow-up analyses revealed 3 items that differed for men and women, although the magnitude of these differences was small. Thus, some items are differentially representative of coercion for women and men.
Item response theory analysis indicates that reliability is excellent, exceeding .9 for much of the range of coercion (-.6 SDs below to 2.6 SDs above the mean), and exceeding .7 beginning at 1.4 SDs below the coercion mean. Reliability as calculated by Cronbach's alpha is .93.
The CCS is significantly correlated in the hypothesized direction, with moderate to strong effect sizes, with couple relationship satisfaction (r = -0.35), partner physical (r = 0.34) and emotional abuse (r = 0.32), and dysfunctional couple conflict (r = 0.54).

[+] PMCID, PUBMED ID, or CITATION

Text Citation: Mitnick, D. M., Lorber, M. F., Nichols, S., Slep, A. M. S., Heyman, R. E., Eddy, J. M., Bulling, L. J., & Xu, S. (2017). New self-report measure of coercion in couple relationships. Manuscript in preparation.

[+] Demographics

The participants were members of the Qualtrics online participant panel. The demographics of the United States Qualtrics panel pool are as follows: median age = 35-44 years old (IQR [interquartile range] = 25 to 54); racial identification is 73.8% White, 10.3% African-American, 6.5% Asian, 1.5% American Indian or Alaska Native, 0.6% Pacific Islander, and 4.6% “some other race ”; median household income = $45,000 to $49,999 (IQR = $25,000 to $89,000); highest level of education is 26.9% High School graduate with 18.4% possessing an undergraduate college degree or better. Of the 2,260 panel members who responded to the invitation and were screened for inclusion, N = 1,372 met study inclusion criteria and consented to participate (Full Study Sample). Inclusion criteria were (a) married or living with a partner, (b) both partners ≥ 18 years old, and (c) cohabiting with the partner for at ≥ 1 year. The Full Study Sample was 51.0% female, 42.3% had a high school diploma, GED, or less, and 29.1% had an undergraduate university degree or better. The modal annual family income range was $50,000 to $99,000 (31.6%), with 24.5% earning ≤ $25,000 and 19% earning ≥ $100,000.

Influenced

This measure has not been influenced yet.

Validated

This measure has not been validated yet.

Access Measure

SOBC Validation Process

The Science of Behavior Change (SOBC) program seeks to promote basic research on the initiation, personalization and maintenance of behavior change. By integrating work across disciplines, this effort will lead to an improved understanding of the underlying principles of behavior change. The SOBC program aims to implement a mechanisms-focused, experimental medicine approach to behavior change research and to develop the tools required to implement such an approach. The experimental medicine approach involves: identifying an intervention target, developing measures to permit verification of the target, engaging the target through experimentation or intervention, and testing the degree to which target engagement produces the desired behavior change.

Within the SOBC Measures Repository, researchers have access to measures of mechanistic targets that have been (or are in the processing of being) validated by SOBC Research Network Members and other experts in the field. The SOBC Validation Process includes three important stages of evaluation for each proposed measure: Identification, Measurement, and Influence.

The first stage of validation requires a measure to be Identified within the field; there must be theoretical support for the specific measure of the proposed mechanistic target or potential mechanism of behavior change. This evidence may include references for the proposed measure, or theoretical support for the construct that the proposed measure is intended to assess. The second stage of validation requires demonstration that the level and change in level of the chosen mechanistic target can be Measured with the proposed measure (assay). For example, if the proposed measure is a questionnaire, the score on the measure should indicate the activity of the target process, and it must have strong psychometric properties. The third stage of validation requires demonstration that the measure can be Influenced; there must be evidence that the measured target is malleable and responsive to manipulation. Evidence relating to each stage includes at least one peer-reviewed publication or original data presentation (if no peer-reviewed research is available to support the claim) and is evaluated by SOBC Research Network Members and experts in the field.

Once a measure has gone through these three stages, it will then either be Validated or Not validated according to SOBC Research Network standards. If a measure is Validated, then change in the measured target was reliably associated with Behavior Change. If a measure is Not validated, then change in the measured target was not reliably associated with Behavior Change. Why would we share measures that are not validated? The SOBC Research Network values open, rigorous, and transparent research. Our goal is to make meaningful progress and develop replicable and effective interventions in behavior change science. Therefore, the SOBC sees value in providing other researchers in the field with information regarding measures that work and measures that fall short for specific targets. Further, a measure that is not validated for one target in one population may be validated in another target or population.

Want to learn more? For any questions regarding the SOBC Validation Process or Measures Repository, please email info@scienceofbehaviorchange.org.

Identified

Has the mechanism been identified as a potential target for behavior change? This section summarizes theoretical support for the mechanism.

Measured

Have the psychometric properties of this measure been assessed? This section includes information such as content validity, internal consistency, and test-retest reliability.

Influenced

Has a study manipulation led to change in the mechanism? This section addresses evidence that this measure is modifiable by experimental manipulation or clinical intervention.

Not Validated

Has a change in this mechanism been associated with behavior change? This section addresses empirical evidence that causing change in the measure reliably produces subsequent behavior change.