OBJECTIVES: To examine the effect of enhanced information regarding the risks, benefits, and life-sustaining treatment alternatives on hypothetical medical decisions and decisional conflict in older, community-dwelling Caucasian and African-American adults. DESIGN: Two-group (enhanced information; no information) between-subjects design. SETTING: Community-based dwellings, two assisted living facilities, and one senior citizen center. PARTICIPANTS: Seventy-eight adults (aged 74.5+/-7.18) with a mean Telephone Interview for Cognitive Status--Modified (TICS-m) score of 31.5+/-4.7 were recruited through personal contacts and informational talks held at the recruitment sites. MEASUREMENTS: Measures included the Life Support Preferences/Predictions Questionnaire--modified (LSPQ-m); the Decisional Conflict Scale; and enhanced information, including detailed descriptions of life-sustaining treatment options for each LSPQ-m illness scenario, risks of the treatment, benefits of the treatment, and alternatives for each treatment (called medical information stimuli). RESULTS: Enhanced information (e.g., medical information stimuli) reduced decisional conflict (P=.049, d=0.47) for hypothetical life-sustaining treatment decisions. A mixed analysis of variance with group and race as between-subjects variables and illness and treatment as within-subjects variables revealed significant main effects of race, illness, and treatment, as well as a significant race-by-illness-by-group interaction (Wilk's lambda=0.923, F(2, 73)=3.05, P=.05, partial eta(2)=0.08). Enhanced information produced different patterns of desire for life-sustaining treatments in African Americans and Caucasians. CONCLUSION: Physicians and other healthcare professionals can reduce decisional conflict in patients by providing enhanced information regarding treatment risks, benefits, and alternatives. Such decision aids may provide new information or knowledge and thus reduce desire for treatment in African Americans.
RCT Entities:
OBJECTIVES: To examine the effect of enhanced information regarding the risks, benefits, and life-sustaining treatment alternatives on hypothetical medical decisions and decisional conflict in older, community-dwelling Caucasian and African-American adults. DESIGN: Two-group (enhanced information; no information) between-subjects design. SETTING: Community-based dwellings, two assisted living facilities, and one senior citizen center. PARTICIPANTS: Seventy-eight adults (aged 74.5+/-7.18) with a mean Telephone Interview for Cognitive Status--Modified (TICS-m) score of 31.5+/-4.7 were recruited through personal contacts and informational talks held at the recruitment sites. MEASUREMENTS: Measures included the Life Support Preferences/Predictions Questionnaire--modified (LSPQ-m); the Decisional Conflict Scale; and enhanced information, including detailed descriptions of life-sustaining treatment options for each LSPQ-m illness scenario, risks of the treatment, benefits of the treatment, and alternatives for each treatment (called medical information stimuli). RESULTS: Enhanced information (e.g., medical information stimuli) reduced decisional conflict (P=.049, d=0.47) for hypothetical life-sustaining treatment decisions. A mixed analysis of variance with group and race as between-subjects variables and illness and treatment as within-subjects variables revealed significant main effects of race, illness, and treatment, as well as a significant race-by-illness-by-group interaction (Wilk's lambda=0.923, F(2, 73)=3.05, P=.05, partial eta(2)=0.08). Enhanced information produced different patterns of desire for life-sustaining treatments in African Americans and Caucasians. CONCLUSION: Physicians and other healthcare professionals can reduce decisional conflict in patients by providing enhanced information regarding treatment risks, benefits, and alternatives. Such decision aids may provide new information or knowledge and thus reduce desire for treatment in African Americans.
Authors: Esther R Smith-Howell; Susan E Hickman; Salimah H Meghani; Susan M Perkins; Susan M Rawl Journal: J Palliat Med Date: 2016-02 Impact factor: 2.947
Authors: Chetna Malhotra; Meibo Hu; Rahul Malhotra; David Sim; Fazlur Rehman Jaufeerally; Filipinas G Bundoc; Eric A Finkelstein Journal: J Gen Intern Med Date: 2020-02-26 Impact factor: 5.128