The Family Health Decision-Making Model

Breast cancer is the second most deadly cancer among women (American Cancer Society, 2005). However, women can reduce their chances of surviving this disease if they detect the cancer early on through breast screening. This study will evaluate the Family Health Decision-Making Model (FHDMM) as it relates to partner influence on breast cancer screening adherence. The FHDMM proposes a decision-making process that incorporates the concepts of differentiation, monitoring style, coping, and the interactions between these concepts. Health, a critical component to quality of life, directly influences family functioning and interactions. For this reason, health decisions made by families are a significant predictor of family health. Participants in this study include women from a larger study and their family members. The women attended a presentation about breast cancer awareness, risk factors, and prevention. Data for this study was analyzed using correlations, t-tests, regressions, and a structural equation model with the SPSS 14.0 and LISREL 8.72 software packages. Research hypothesis one examined differentiation and monitoring, and this hypothesis was supported. This suggests that there is a relationship between differentiation and monitoring and that those reporting lower differentiation scores also reported higher monitoring. Findings from research hypothesis two revealed that there was not a significant difference on instrumental coping based on level of differentiation. Results from research hypothesis three revealed that differentiation did not directly influence the family dyad’s decision to engage in breast cancer screening behaviors although it is believed that differentiation has an indirect relationship to breast cancer-screening behaviors. This study did not support the full Family Health Decision Making Model, which stated that differentiation is related to coping, which is related to monitoring, and participant’s adherence to breast cancerscreenings. Due to the large sample size, the model did not have a significant fit to the data. Limitations and clinical implications are further discussed in this paper.

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