Qualitative Analysis of Decision to Pursue Electrical Brain Stimulation by Patients With Drug-Resistant Epilepsy and Their Caregivers.

Background and Objectives: To understand why patients with drug-resistant epilepsy (DRE) pursue invasive electrical brain stimulation (EBS). Methods: We interviewed patients with DRE (n = 20) and their caregivers about their experiences in pursuing EBS approximately 1 year post device implant. Inductive analysis was applied to identify key motivating factors. Results: The cohort included participants aged from teens to 50s with deep brain stimulation, vagus nerve stimulation, responsive neurostimulation, and chronic subthreshold cortical stimulation. Patients' motivations included (1) improved quality of life (2) intolerability of antiseizure medications, (3) desperation, and (4) patient-family dynamics. Both patients and caregivers described a desire to alleviate burdens of the other. Patient apprehensions about EBS focused on invasiveness and the presence of electrodes in the brain. Previous experiences with invasive monitoring and the ability to see hardware in person during clinical visits influenced patients' comfort in proceeding with EBS. Despite realistic expectations for modest and delayed benefits, patients held out hope for an exceptionally positive outcome. Discussion: Our findings describe the motivations and decision-making process for patients with DRE who pursue invasive EBS. Patients balance feelings of desperation, personal goals, frustration with medication side effects, fears about surgery, and potential pressure from concerned caregivers. These factors together with the sense that patients have exhausted therapeutic alternatives may explain the limited decisional ambivalence observed in this cohort. These themes highlight opportunities for epilepsy care teams to support patient decision-making processes.

Experiences of individuals receiving a sex chromosome multisomy diagnosis.

Sex chromosome multisomies (SCMs) are genomic conditions with variable phenotypes that range from undetectable to requiring extensive clinical intervention. Currently, many individuals with SCMs are diagnosed in adolescence or adulthood based on physical symptoms related to pubertal development and infertility. Given the expansion of genetic testing in routine clinical practice, the diagnosing clinician is increasingly a primary care or family medicine provider. This study aims to help providers better understand the patient experience of receiving a diagnosis. We conducted a survey of individuals (n = 55) with SCMs using closed and open-ended questions. Open-response questions were qualitatively analyzed and are reported here with the descriptive results of the closed-ended questions. Most participants were diagnosed with 47,XXY (n = 51; 85.0%), identified as White race/ethnicity (n = 46; 88.5%), and were college graduates or higher (n = 29; 54.7%). Many participants reported dissatisfaction with the delivery of the diagnosis, expressing that it was rushed and their provider lacked detailed information about the condition. Participants were frustrated by the general lack of availability of high-quality informational resources from both medical and other sources at the time of diagnosis. Some participants also described the social and psychological impact of the diagnosis and how it was delivered. To the best of our knowledge, this is the largest survey of individuals diagnosed with SCMs, which is notable considering their prevalence and low diagnostic rate. Our findings provide patient-informed insight on how to improve the delivery of SCM diagnoses, especially delivery in a primary care setting, including the provision of up-to-date information and proactive referral to specialty care and counseling services.

A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare.

Background: While use of artificial intelligence (AI) in healthcare is increasing, little is known about how patients view healthcare AI. Characterizing patient attitudes and beliefs about healthcare AI and the factors that lead to these attitudes can help ensure patient values are in close alignment with the implementation of these new technologies. Methods: We conducted 15 focus groups with adult patients who had a recent primary care visit at a large academic health center. Using modified grounded theory, focus-group data was analyzed for themes related to the formation of attitudes and beliefs about healthcare AI. Results: When evaluating AI in healthcare, we found that patients draw on a variety of factors to contextualize these new technologies including previous experiences of illness, interactions with health systems and established health technologies, comfort with other information technology, and other personal experiences. We found that these experiences informed normative and cultural beliefs about the values and goals of healthcare technologies that patients applied when engaging with AI. The results of this study form the basis for a theoretical framework for understanding patient orientation to applications of AI in healthcare, highlighting a number of specific social, health, and technological experiences that will likely shape patient opinions about future healthcare AI applications. Conclusions: Understanding the basis of patient attitudes and beliefs about healthcare AI is a crucial first step in effective patient engagement and education. The theoretical framework we present provides a foundation for future studies examining patient opinions about applications of AI in healthcare.

Patient apprehensions about the use of artificial intelligence in healthcare.

While there is significant enthusiasm in the medical community about the use of artificial intelligence (AI) technologies in healthcare, few research studies have sought to assess patient perspectives on these technologies. We conducted 15 focus groups examining patient views of diverse applications of AI in healthcare. Our results indicate that patients have multiple concerns, including concerns related to the safety of AI, threats to patient choice, potential increases in healthcare costs, data-source bias, and data security. We also found that patient acceptance of AI is contingent on mitigating these possible harms. Our results highlight an array of patient concerns that may limit enthusiasm for applications of AI in healthcare. Proactively addressing these concerns is critical for the flourishing of ethical innovation and ensuring the long-term success of AI applications in healthcare.

The Expert in the Room: Parental Advocacy for Children with Sex Chromosome Aneuploidies.

OBJECTIVE: Owing to fragmentation in the medical system, many parents of children with disabilities report taking on a care coordinator and advocate role. The parental advocacy and care coordination requirements are further amplified in this population because of a lack of awareness about sex chromosome aneuploidies (SCAs) in medical and social services settings, as well as the complex needs of affected children. This burden disproportionately affects mothers and low-resource families as a result of gendered ideas of parenthood and social stratification in resource access. The aim of this study is to understand the unique parental burdens of SCAs and family support needs. METHODS: We conducted 43 interviews with individuals with SCAs and/or their parents and qualitatively coded and analyzed the transcripts for themes relating to parent advocacy, medical services, social and educational services, and coping. RESULTS: Our findings indicate that parents must repeatedly advocate for their concerns about their child to be taken seriously before diagnosis and continue to advocate for services and interventions throughout childhood and adolescence. Parents also report the need to educate health care professionals about their child's medical condition. A majority of the parent participants were women, and single mothers reported high levels of emotional burden. CONCLUSION: Parents of children with SCAs shoulder additional roles of medical advocate and care coordinator. This causes excessive burden on families but also disadvantages families in which parents are unable to act as an advocate for their child.

Magnetic resonance imaging volumetric analysis in patients with Alternating hemiplegia of childhood: A pilot study.

Quantitative MRI is increasingly being used as a biomarker in neurological disorders. Cerebellar atrophy occurs in some Alternating Hemiplegia of Childhood (AHC) patients. However, it is not known if cerebellar atrophy can be a potential biomarker in AHC or if quantitative MRI is a reliable method to address this question. Here we determine the reproducibility of an MRI-volumetrics method to investigate brain volumes in AHC and apply it to a population of 14 consecutive AHC patients (ages 4-11 years). We studied method reproducibility in the first 11 patients and then performed correlation of cerebellar volumes, relative to published normal population means, with age in all 14. We used FreeSurfer 6.0.0 to automatically segment MRI images, then performed manual resegmentation correction by two different observers. No significant differences were observed in any of ten brain regions between the two reviewers: p > .591 and interclass Correlation Coefficient (ICC) ≥0.975 in all comparisons. Additionally, there were no significant differences between the means of the two reviewers and the automatic segmentation values: p ≥ .106 and ICC ≥0.994 in all comparisons. We found a negative correlation between cerebellar volume and age (R = -0.631, p = .037), even though only one patient showed any cerebellar atrophy upon formal readings of the MRIs by neuroradiology. Sample size did not allow us to rule out potential confounding variables. Thus, findings from this cross-sectional study should be considered as exploratory. Our study supports the prospective investigation of quantitative MRI-volumetrics of the cerebellum as a potential biomarker in AHC.