MedElevator
Войти в исследования International journal of ophthalmology · 2025
Navigating decisional conflict: laser peripheral iridotomy for primary angle-closure glaucoma prevention.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chen Yi-Jie, Dai Jing-Yao, Le Rong-Rong, Zhang Xiao-Xian, Huang Jia-Li, Lu Hu-Jie, Sun Yi-Wen, Liang Yuan-Bo, Chen Yan-Yan, Zhou Wen-Zhe
Аннотация
AIM: To investigate decisional conflict among patients diagnosed with primary angle-closure suspect (PACS) or primary angle-closure (PAC) who are considering laser peripheral iridotomy (LPI) treatment.
METHODS: A total of 111 individuals diagnosed with PACS or PAC were selected through convenient sampling from March 2023 to December 2023. These participants then completed a general information questionnaire and the Decision Conflict Scale. Data analysis was performed using multiple linear regression to reveal factors influencing decisional conflict.
RESULTS: The mean Decisional Conflict Score among patients with PACS or PAC was 48.58±10.01, with 99.1% of these individuals reporting experiencing decisional conflict. Multiple linear regression analysis revealed that females (P=0.002) and patients with a shorter duration of the disease (P=0.006) had higher levels of decisional conflict. Additionally, patients diagnosed during medical visits (P=0.049), those who refused LPI treatment (P=0.032), and individuals facing significant economic burdens related to medical expenses (P=0.005) exhibited higher levels of decisional conflict. Furthermore, patients who preferred to make medical decisions independently (P=0.023) and those who favored involving family members in decision-making (P=0.005) experienced increased levels of decisional conflict.
CONCLUSION: Patients with PACS or PAC who undergo LPI treatment often encounter significant decisional conflict. Healthcare professionals should thoroughly assess a range of factors that influence this conflict, including gender, duration of disease, method of diagnosis acquisition, LPI treatment, economic burden of medical expenses, and patient preferences regarding medical decision-making. By considering these variables, tailored decision support can be developed to address individual patient needs, ultimately reducing decisional conflict and optimizing the quality of decisions made regarding treatment options.
METHODS: A total of 111 individuals diagnosed with PACS or PAC were selected through convenient sampling from March 2023 to December 2023. These participants then completed a general information questionnaire and the Decision Conflict Scale. Data analysis was performed using multiple linear regression to reveal factors influencing decisional conflict.
RESULTS: The mean Decisional Conflict Score among patients with PACS or PAC was 48.58±10.01, with 99.1% of these individuals reporting experiencing decisional conflict. Multiple linear regression analysis revealed that females (P=0.002) and patients with a shorter duration of the disease (P=0.006) had higher levels of decisional conflict. Additionally, patients diagnosed during medical visits (P=0.049), those who refused LPI treatment (P=0.032), and individuals facing significant economic burdens related to medical expenses (P=0.005) exhibited higher levels of decisional conflict. Furthermore, patients who preferred to make medical decisions independently (P=0.023) and those who favored involving family members in decision-making (P=0.005) experienced increased levels of decisional conflict.
CONCLUSION: Patients with PACS or PAC who undergo LPI treatment often encounter significant decisional conflict. Healthcare professionals should thoroughly assess a range of factors that influence this conflict, including gender, duration of disease, method of diagnosis acquisition, LPI treatment, economic burden of medical expenses, and patient preferences regarding medical decision-making. By considering these variables, tailored decision support can be developed to address individual patient needs, ultimately reducing decisional conflict and optimizing the quality of decisions made regarding treatment options.