Determinants of satisfactory patient communication and shared decision making in patients with multiple myeloma

Objective: To identify determinants of shared decision making in patients withmultiple myeloma (MM) to facilitate the design of a program to maximize the effects of shared decision making. Methods: This prospective longitudinal study recruited 276 adult patients (52%male, mean age 62.86 y, SD 15.45). Each patient completed the eHealth Literacy Scale (eHEALS), Multidimensional Trust in Health Care Systems Scale (MTHCSS), Patient Communication Pattern Scale (PCPS), and 9‐Item Shared Decision‐Making Questionnaire (SDM‐Q‐9) at baseline and the SDM‐Q‐9 again 6 months later. One family member of the patient completed the Family Decision‐Making Self‐Efficacy (FDMSE) at baseline. Structural equation modeling (SEM) was used to investigate the associations between eHealth literacy (eHEALS), trust in the health care system (MTHCSS), self‐efficacy in family decision making (FDMSE), patient communication pattern (PCPS), and shared decision making (SDM‐Q‐9).Results: SEM showed satisfactory fit (comparative fit index = 0.988) and significant correlations between the following: eHealth literacy and trust in the health care system (β = 0.723, P < 0.001); eHealth literacy and patient communication pattern (β = 0.242, P < 0.001); trust in the health care system and patient communication pattern (β = 0.397, P < 0.001); self‐efficacy in family decision making and patient communication pattern (β = 0.264, P < 0.001); eHealth literacy and shared decision making (β = 0.267, P < 0.001); and patient communication pattern and shared decision making (β = 0.349, P < 0.001).Conclusions: Patient communication and eHealth literacy were found to be important determinants of shared decision making. These factors should be taken into consideration when developing strategies to enhance the level of shared decision making

کلیدواژه ها:

cancer ، multiple myeloma ، oncology ، patient communication ، shared decision making ، structural equation modeling