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Randomized Controlled Trial
. 2023 Oct 16;57(11):965-977.
doi: 10.1093/abm/kaad048.

Identifying Mediators of Intervention Effects Within a Randomized Controlled Trial to Motivate Cancer Genetic Risk Assessment Among Breast and Ovarian Cancer Survivors

Jinghua An  1 , Shou-En Lu  1   2 , Jean McDougall  3 , Scott T Walters  4 , Yong Lin  1   2 , Emily Heidt  1 , Antoinette Stroup  1   2 , Lisa Paddock  1   2 , Sherry Grumet  1 , Deborah Toppmeyer  1 , Anita Y Kinney  1   2
Affiliations
Randomized Controlled Trial

Identifying Mediators of Intervention Effects Within a Randomized Controlled Trial to Motivate Cancer Genetic Risk Assessment Among Breast and Ovarian Cancer Survivors

Jinghua An et al. Ann Behav Med. .

Abstract

Background: A theory-guided Tailored Counseling and Navigation (TCN) intervention successfully increased cancer genetic risk assessment (CGRA) uptake among cancer survivors at increased risk of hereditary breast and ovarian cancer (HBOC). Understanding the pathways by which interventions motivate behavior change is important for identifying the intervention's active components.

Purpose: We examined whether the TCN intervention exerted effects on CGRA uptake through hypothesized theoretical mediators.

Methods: Cancer survivors at elevated risk for HBOC were recruited from three statewide cancer registries and were randomly assigned to three arms: TCN (n = 212), Targeted Print (TP, n = 216), and Usual Care (UC, n = 213). Theoretical mediators from the Extended Parallel Process Model, Health Action Planning Approach, and Ottawa Decision Support Framework were assessed at baseline and 1-month follow-up; CGRA uptake was assessed at 6 months. Generalized structural equation modeling was used for mediation analysis.

Results: The TCN effects were most strongly mediated by behavioral intention alone (β = 0.49 and 0.31) and by serial mediation through self-efficacy and intention (β = 0.041 and 0.10) when compared with UC and TP, respectively. In addition, compared with UC, the TCN also increased CGRA through increased perceived susceptibility, knowledge of HBOC, and response efficacy.

Conclusions: Risk communication and behavioral change interventions for hereditary cancer should stress a person's increased genetic risk and the potential benefits of genetic counseling and testing, as well as bolster efficacy beliefs by helping remove barriers to CGRA. System-level and policy interventions are needed to further expand access.

Keywords: Cancer genetic risk assessment; Early detection of cancer; Extended Parallel Process Model; Genetic counseling; Hereditary breast and ovarian cancer syndrome; Remote behavioral intervention.

Plain language summary

It is recommended that cancer survivors at increased risk for heredity seek cancer genetic risk assessment (CGRA), which includes cancer genetic counseling and genetic testing. A Tailored Counseling and Navigation (TCN) intervention successfully increased CGRA uptake among women with a history of cancer who enrolled in a randomized controlled trial. Understanding reasons for TCN’s effectiveness can guide future interventions that use risk messages and behavior change techniques. We conducted mediation analyses, which enabled identification of the TCN’s active components. Eligible breast and ovarian cancer survivors (n = 641) were recruited from three statewide cancer registries and were assigned to three groups: TCN, Targeted Print, and Usual Care. Mediator variables drawn from behavioral and risk communication theories were assessed at baseline and 1-month follow-up; CGRA uptake was assessed at 6 months. The strongest mediator was intention to obtain a CGRA, followed by self-efficacy, perceived risk, knowledge of hereditary breast and ovarian cancer, and perceived CGRA benefits. Risk communication and behavioral change interventions for hereditary cancer should stress a person’s increased genetic risk and the potential benefits of genetic counseling and testing, as well as bolster efficacy beliefs by helping remove CGRA barriers. System-level and policy interventions are needed to further expand access.

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Figures

Fig. 1.
Fig. 1.
GRACE study CONSORT diagram. Note. Some participants were found ineligible after randomization and were removed from all analyses. These participants had prior cancer genetic risk assessment, but they did not report it at recruitment due to recall errors.
Fig. 2.
Fig. 2.
A generalized structural equation model (Model 1) linking intervention (Tailored Counseling and Navigation vs. Usual Care), theoretical mediators, and cancer genetic risk assessment uptake. Note. CGRA cancer genetic risk assessment; HBOC hereditary breast and ovarian cancer; TCN Tailored Counseling and Navigation; UC Usual Care. All parameters are standardized effect sizes. All relationships were controlled for age, household income, education attainment, ethnicity, years since diagnosis, health insurance, urban/rural residence, breast or ovarian cancer, health literacy, and whether having at-risk first- or second-degree relatives. Theoretical mediators were assessed at baseline and then 1 month after the intervention; CGRA uptake was assessed 6 months after the intervention. *p < .05; **p < .01. Nonsignificant pathways are shown in dash arrows.
Fig. 3.
Fig. 3.
A generalized structural equation model (Model 2) linking intervention (Tailored Counseling and Navigation vs. Targeted Print), theoretical mediators, and cancer genetic risk assessment uptake. Note. CGRA cancer genetic risk assessment; HBOC hereditary breast and ovarian cancer; TCN Tailored Counseling and Navigation; TP Targeted Print. All parameters are standardized effect sizes. All relationships were controlled for age, household income, education attainment, ethnicity, years since diagnosis, health insurance, urban/rural residence, breast or ovarian cancer, health literacy, and whether having at-risk first- or second-degree relatives. Theoretical mediators were assessed at baseline and then 1 month after the intervention; CGRA uptake was assessed 6 months after the intervention. *p < .05; **p < .01. Nonsignificant pathways are shown in dash arrows. p values are denoted for marginally significant pathways.
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