Babak Nejati1, Chien-Chin Lin2,3,4, Neil K Aaronson5, Andy S K Cheng6, Maria Browall7, Chung-Ying Lin6, Anders Broström7, Amir H Pakpour7,8. 1. Hematology and Oncology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. 2. Department of Laboratory Medicine, National Taiwan University Hospital, Taipei, Taiwan. 3. Division of Hematology and Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan. 4. Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan. 5. Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. 6. Department of Rehabilitation Sciences, Hong Kong Polytechnic University, Hung Hom, Hong Kong. 7. Department of Nursing, School of Health and Welfare, Jönköping University, Jönköping, Sweden. 8. Social Determinants of Health Research Center, Qazvin University of Medical Sciences, Qazvin, Iran.
Abstract
OBJECTIVE: To identify determinants of shared decision making in patients with multiple 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.
OBJECTIVE: To identify determinants of shared decision making in patients with multiple 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.
Authors: Luke X van Rossenberg; David Ring; Xander Jacobs; George Sulkers; Mark van Heijl; Bastiaan T van Hoorn Journal: J Patient Exp Date: 2021-12-08
Authors: Robin L Whitney; Anne Elizabeth Clark White; Aaron S Rosenberg; Richard L Kravitz; Katherine K Kim Journal: Cancer Med Date: 2021-10-05 Impact factor: 4.452