Objectives: To describe the communication behaviors of patients and physicians and patient par-ticipation in communication about treatment decision-making during consultation visits for local-ized prostate cancer (LPC...Objectives: To describe the communication behaviors of patients and physicians and patient par-ticipation in communication about treatment decision-making during consultation visits for local-ized prostate cancer (LPCa). Methods: This is a secondary analysis of data from 52 men enrolled in the usual care control group of a randomized trial that focused on decision-making for newly diagnosed men with LPCa. We analyzed the patient-physician communication using the transcribed audio-recordings of real-time treatment consultations and a researcher-developed coding tool, including codes for communication behaviors (information giving, seeking, and clarifying/ verifying) and contents of clinical consultations (health histories, survival/mortality, treatment options, treatment impact, and treatment preferences). After qualitative content analysis, we categorized patient participation in communication about treatment-related clinical content, including “none” (content not discussed);“low” (patient listening only);“moderate” (patient providing information or asking questions);and “high” (patient providing information and asking questions). Results: Physicians mainly provided information during treatment decision consultations and patients frequently were not active participants in communication. The participation of patients with low and moderate cancer risk typically was: 1) “moderate and high” in discussing health histories;2) “low” in discussing survival/mortality;3) “low and moderate” in discussing treatment options;4) “none and low” in discussing treatment impacts;and 5) “low” in discussing treatment preferences. Conclusions: Findings suggest opportunities for increasing patient participation in communication about treatment decision-making for LPCa during clinical consultations.展开更多
BACKGROUND Pediatric functional gastrointestinal disorders(FGIDs)are common and wellaccepted to be etiologically complex in terms of the contribution of biological,psychological,and social factors to symptom presentat...BACKGROUND Pediatric functional gastrointestinal disorders(FGIDs)are common and wellaccepted to be etiologically complex in terms of the contribution of biological,psychological,and social factors to symptom presentations.Nonetheless,despite its documented benefits,interdisciplinary treatment,designed to address all of these factors,for pediatric FGIDs remains rare.The current study hypothesized that the majority of pediatric patients seen in an interdisciplinary abdominal pain clinic(APC)would demonstrate clinical resolution of symptoms during the study period and that specific psychosocial variables would be significantly predictive of GI symptom improvement.AIM To evaluate outcomes with interdisciplinary treatment in pediatric patients with pain-related FGIDs and identify patient characteristics that predicted clinical outcomes.METHODS Participants were 392 children,ages 8-18[M=13.8;standard deviation(SD)=2.7],seen between August 1,2013 and June 15,2016 in an interdisciplinary APC housed within the Division of Gastroenterology in a medium-sized Midwestern children's hospital.To be eligible,patients had to be 8 years of age or older and have had abdominal pain for≥8 wk at the time of initial evaluation.Medical and psychosocial data collected as part of standard of care were retrospectively reviewed and analyzed in the context of the observational study.Logistic regression was used to model odds of reporting vs never reporting improvement,as well as to differentiate rapid from slower improvers.RESULTS Nearly 70%of patients followed during the study period achieved resolution on at least one of the employed outcome indices.Among those who achieved resolution during follow up,43%to 49%did so by the first follow up(i.e.,within roughly 2 mo after initial evaluation and initiation of interdisciplinary treatment).Patient age,sleep,ease of relaxation,and depression all significantly predicted the likelihood of resolution.More specifically,the odds of clinical resolution were 14%to 16%lower per additional year of patient age(P<0.001 to P=0.016).The odds of resolution were 28%to 42%lower per 1-standard deviation(SD)increase on a pediatric sleep measure(P=0.006 to P<0.040).Additionally,odds of clinical resolution were 58%lower per 1-SD increase on parent-reported measure of depression(P=0.006),and doubled in cases where parents agreed that their children found it easy to relax(P=0.045).Furthermore,sleep predicted the rapidity of clinical resolution;that is,the odds of achieving resolution by the first follow up visit were 47%to 60%lower per 1-SD increase on the pediatric sleep measure(P=0.002).CONCLUSION Outcomes for youth with FGIDs may be significantly improved by paying specific attention to sleep,ensuring adequate skills for relaxation,and screening of and referral for treatment of comorbid depression.展开更多
This paper delves into the intricate interplay between artificial intelligence(AI)systems and the perpetuation of Anti-Black racism within the United States medical industry.Despite the promising potential of AI to en...This paper delves into the intricate interplay between artificial intelligence(AI)systems and the perpetuation of Anti-Black racism within the United States medical industry.Despite the promising potential of AI to enhance healthcare outcomes and reduce disparities,there is a growing concern that these technologies may inadvertently/advertently exacerbate existing racial inequalities.Focusing specifically on the experiences of Black patients,this research investigates how the following AI components:medical algorithms,machine learning,and natural learning processes are contributing to the unequal distribution of medical resources,diagnosis,and health care treatment of those classified as Black.Furthermore,this review employs a multidisciplinary approach,combining insights from computer science,medical ethics,and social justice theory to analyze the mechanisms through which AI systems may encode and reinforce racial biases.By dissecting the three primary components of AI,this paper aims to present a clear understanding of how these technologies work,how they intersect,and how they may inherently perpetuate harmful stereotypes resulting in negligent outcomes for Black patients.Furthermore,this paper explores the ethical implications of deploying AI in healthcare settings and calls for increased transparency,accountability,and diversity in the development and implementation of these technologies.Finally,it is important that I prefer the following paper with a clear and concise definition of what I refer to as Anti-Black racism throughout the text.Therefore,I assert the following:Anti-Black racism refers to prejudice,discrimination,or antagonism directed against individuals or communities of African descent based on their race.It involves the belief in the inherent superiority of one race over another and the systemic and institutional practices that perpetuate inequality and disadvantage for Black people.Furthermore,I proclaim that this form of racism can be manifested in various ways,such as unequal access to opportunities,resources,education,employment,and fair treatment within social,economic,and political systems.It is also pertinent to acknowledge that Anti-Black racism is deeply rooted in historical and societal structures throughout the U.S.borders and beyond,leading to systemic disadvantages and disparities that impact the well-being and life chances of Black individuals and communities.Addressing Anti-Black racism involves recognizing and challenging both individual attitudes and systemic structures that contribute to discrimination and inequality.Efforts to combat Anti-Black racism include promoting awareness,education,advocacy for policy changes,and fostering a culture of inclusivity and equality.展开更多
For cancer patients on Phase I trials, one of the most important physician decisions is whether or not patients are deriving benefit from therapy. With an increasing number of cytostatic treatment agents, the criteria...For cancer patients on Phase I trials, one of the most important physician decisions is whether or not patients are deriving benefit from therapy. With an increasing number of cytostatic treatment agents, the criteria to determine patient response to Phase I treatment has become harder to define. Physicians are increasingly looking to patient-reported outcomes (PROs) such as quality of life (QOL) to help evaluate treatment response. Electronic daily diary (EDD) devices can be used by patients to report their QOL over extended periods of time, thereby providing a more accurate picture of how patients are affected by treatment on a daily basis. However, questions remain about how to integrate this patient-reported information into decisions about Phase I treatment. This study investigated how physicians use patients’ daily QOL reports to evaluate patient response to Phase I treatment. Data were collected over a 4-month period from Phase I patients (N = 30) and physicians (N = 3) in an NCI-designated comprehensive cancer center. Patients completed daily QOL reports using EDD devices and physicians were provided with a summary of patients’ QOL before each visit. After the visit, doctors recorded their treatment decision and also rated the importance of four biomedical factors (Toxicity, Imaging, Labs, and Performance Status) and QOL in their treatment decision for that visit. Although physicians rated QOL as being very important in evaluating treatment response, in practice, when predictors of their decisions were analyzed, results showed they relied exclusively on biomedical data (Toxicity, Imaging) to make Phase I treatment decisions. Questions remain about the utility and effective integration of QOL and biomedical data in clinical decision-making processes in Phase I clinical trials.展开更多
文摘Objectives: To describe the communication behaviors of patients and physicians and patient par-ticipation in communication about treatment decision-making during consultation visits for local-ized prostate cancer (LPCa). Methods: This is a secondary analysis of data from 52 men enrolled in the usual care control group of a randomized trial that focused on decision-making for newly diagnosed men with LPCa. We analyzed the patient-physician communication using the transcribed audio-recordings of real-time treatment consultations and a researcher-developed coding tool, including codes for communication behaviors (information giving, seeking, and clarifying/ verifying) and contents of clinical consultations (health histories, survival/mortality, treatment options, treatment impact, and treatment preferences). After qualitative content analysis, we categorized patient participation in communication about treatment-related clinical content, including “none” (content not discussed);“low” (patient listening only);“moderate” (patient providing information or asking questions);and “high” (patient providing information and asking questions). Results: Physicians mainly provided information during treatment decision consultations and patients frequently were not active participants in communication. The participation of patients with low and moderate cancer risk typically was: 1) “moderate and high” in discussing health histories;2) “low” in discussing survival/mortality;3) “low and moderate” in discussing treatment options;4) “none and low” in discussing treatment impacts;and 5) “low” in discussing treatment preferences. Conclusions: Findings suggest opportunities for increasing patient participation in communication about treatment decision-making for LPCa during clinical consultations.
文摘BACKGROUND Pediatric functional gastrointestinal disorders(FGIDs)are common and wellaccepted to be etiologically complex in terms of the contribution of biological,psychological,and social factors to symptom presentations.Nonetheless,despite its documented benefits,interdisciplinary treatment,designed to address all of these factors,for pediatric FGIDs remains rare.The current study hypothesized that the majority of pediatric patients seen in an interdisciplinary abdominal pain clinic(APC)would demonstrate clinical resolution of symptoms during the study period and that specific psychosocial variables would be significantly predictive of GI symptom improvement.AIM To evaluate outcomes with interdisciplinary treatment in pediatric patients with pain-related FGIDs and identify patient characteristics that predicted clinical outcomes.METHODS Participants were 392 children,ages 8-18[M=13.8;standard deviation(SD)=2.7],seen between August 1,2013 and June 15,2016 in an interdisciplinary APC housed within the Division of Gastroenterology in a medium-sized Midwestern children's hospital.To be eligible,patients had to be 8 years of age or older and have had abdominal pain for≥8 wk at the time of initial evaluation.Medical and psychosocial data collected as part of standard of care were retrospectively reviewed and analyzed in the context of the observational study.Logistic regression was used to model odds of reporting vs never reporting improvement,as well as to differentiate rapid from slower improvers.RESULTS Nearly 70%of patients followed during the study period achieved resolution on at least one of the employed outcome indices.Among those who achieved resolution during follow up,43%to 49%did so by the first follow up(i.e.,within roughly 2 mo after initial evaluation and initiation of interdisciplinary treatment).Patient age,sleep,ease of relaxation,and depression all significantly predicted the likelihood of resolution.More specifically,the odds of clinical resolution were 14%to 16%lower per additional year of patient age(P<0.001 to P=0.016).The odds of resolution were 28%to 42%lower per 1-standard deviation(SD)increase on a pediatric sleep measure(P=0.006 to P<0.040).Additionally,odds of clinical resolution were 58%lower per 1-SD increase on parent-reported measure of depression(P=0.006),and doubled in cases where parents agreed that their children found it easy to relax(P=0.045).Furthermore,sleep predicted the rapidity of clinical resolution;that is,the odds of achieving resolution by the first follow up visit were 47%to 60%lower per 1-SD increase on the pediatric sleep measure(P=0.002).CONCLUSION Outcomes for youth with FGIDs may be significantly improved by paying specific attention to sleep,ensuring adequate skills for relaxation,and screening of and referral for treatment of comorbid depression.
文摘This paper delves into the intricate interplay between artificial intelligence(AI)systems and the perpetuation of Anti-Black racism within the United States medical industry.Despite the promising potential of AI to enhance healthcare outcomes and reduce disparities,there is a growing concern that these technologies may inadvertently/advertently exacerbate existing racial inequalities.Focusing specifically on the experiences of Black patients,this research investigates how the following AI components:medical algorithms,machine learning,and natural learning processes are contributing to the unequal distribution of medical resources,diagnosis,and health care treatment of those classified as Black.Furthermore,this review employs a multidisciplinary approach,combining insights from computer science,medical ethics,and social justice theory to analyze the mechanisms through which AI systems may encode and reinforce racial biases.By dissecting the three primary components of AI,this paper aims to present a clear understanding of how these technologies work,how they intersect,and how they may inherently perpetuate harmful stereotypes resulting in negligent outcomes for Black patients.Furthermore,this paper explores the ethical implications of deploying AI in healthcare settings and calls for increased transparency,accountability,and diversity in the development and implementation of these technologies.Finally,it is important that I prefer the following paper with a clear and concise definition of what I refer to as Anti-Black racism throughout the text.Therefore,I assert the following:Anti-Black racism refers to prejudice,discrimination,or antagonism directed against individuals or communities of African descent based on their race.It involves the belief in the inherent superiority of one race over another and the systemic and institutional practices that perpetuate inequality and disadvantage for Black people.Furthermore,I proclaim that this form of racism can be manifested in various ways,such as unequal access to opportunities,resources,education,employment,and fair treatment within social,economic,and political systems.It is also pertinent to acknowledge that Anti-Black racism is deeply rooted in historical and societal structures throughout the U.S.borders and beyond,leading to systemic disadvantages and disparities that impact the well-being and life chances of Black individuals and communities.Addressing Anti-Black racism involves recognizing and challenging both individual attitudes and systemic structures that contribute to discrimination and inequality.Efforts to combat Anti-Black racism include promoting awareness,education,advocacy for policy changes,and fostering a culture of inclusivity and equality.
文摘For cancer patients on Phase I trials, one of the most important physician decisions is whether or not patients are deriving benefit from therapy. With an increasing number of cytostatic treatment agents, the criteria to determine patient response to Phase I treatment has become harder to define. Physicians are increasingly looking to patient-reported outcomes (PROs) such as quality of life (QOL) to help evaluate treatment response. Electronic daily diary (EDD) devices can be used by patients to report their QOL over extended periods of time, thereby providing a more accurate picture of how patients are affected by treatment on a daily basis. However, questions remain about how to integrate this patient-reported information into decisions about Phase I treatment. This study investigated how physicians use patients’ daily QOL reports to evaluate patient response to Phase I treatment. Data were collected over a 4-month period from Phase I patients (N = 30) and physicians (N = 3) in an NCI-designated comprehensive cancer center. Patients completed daily QOL reports using EDD devices and physicians were provided with a summary of patients’ QOL before each visit. After the visit, doctors recorded their treatment decision and also rated the importance of four biomedical factors (Toxicity, Imaging, Labs, and Performance Status) and QOL in their treatment decision for that visit. Although physicians rated QOL as being very important in evaluating treatment response, in practice, when predictors of their decisions were analyzed, results showed they relied exclusively on biomedical data (Toxicity, Imaging) to make Phase I treatment decisions. Questions remain about the utility and effective integration of QOL and biomedical data in clinical decision-making processes in Phase I clinical trials.
