Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.026
Grace Mausisa , Annick de Bruin , Devon Chenette , Susan Gorky , Tiffany Chow
Introduction
Caregivers or care partners often experience challenges while caring for persons diagnosed with FTD. We surveyed caregivers to better understand their specific challenges and identify gaps in existing services.
Methods
Alector developed the FTD Caregiver Survey, an online self-administered questionnaire, consisting of informed consent, eligibility screening, and questions regarding caregiver burden and strains. The survey was distributed with support from patient groups, individual advocates and an FTD website community. Eligible responders were adults who could read and write in English, reside in the United States, and who have been an unpaid primary caregiver for a person diagnosed with FTD. The first 90 surveys, completed from May to June 2024, were analyzed.
Results
Of all respondents, 47% self-identified as a sole caregiver. Over one third of all respondents spent over 40 hours per week providing direct care. Many respondents (41%) also provided care for other family members, with a majority (92%) reporting difficulty managing those responsibilities. Most caregivers reported difficulty attending to their own healthcare.
Respite services, in-home care, or adult day care were identified as the most needed and the most difficult to access amongst a list of services. Care planning and symptom management were highlighted as areas of need. FTD-specific websites or organizations were identified as being the most helpful source of assistance and information.
Conclusions
Patient organizations and healthcare professionals can help address the need for strategies to overcome barriers and expand on FTD-specific support, ranging from caregiver support groups to financial assistance and additional support in the day-to-day caregiving at home.
{"title":"24. CHALLENGES FACING CAREGIVERS OF INDIVIDUALS DIAGNOSED WITH FRONTOTEMPORAL DEMENTIA IN THE UNITED STATES","authors":"Grace Mausisa , Annick de Bruin , Devon Chenette , Susan Gorky , Tiffany Chow","doi":"10.1016/j.jagp.2025.04.026","DOIUrl":"10.1016/j.jagp.2025.04.026","url":null,"abstract":"<div><h3>Introduction</h3><div>Caregivers or care partners often experience challenges while caring for persons diagnosed with FTD. We surveyed caregivers to better understand their specific challenges and identify gaps in existing services.</div></div><div><h3>Methods</h3><div>Alector developed the FTD Caregiver Survey, an online self-administered questionnaire, consisting of informed consent, eligibility screening, and questions regarding caregiver burden and strains. The survey was distributed with support from patient groups, individual advocates and an FTD website community. Eligible responders were adults who could read and write in English, reside in the United States, and who have been an unpaid primary caregiver for a person diagnosed with FTD. The first 90 surveys, completed from May to June 2024, were analyzed.</div></div><div><h3>Results</h3><div>Of all respondents, 47% self-identified as a sole caregiver. Over one third of all respondents spent over 40 hours per week providing direct care. Many respondents (41%) also provided care for other family members, with a majority (92%) reporting difficulty managing those responsibilities. Most caregivers reported difficulty attending to their own healthcare.</div><div>Respite services, in-home care, or adult day care were identified as the most needed and the most difficult to access amongst a list of services. Care planning and symptom management were highlighted as areas of need. FTD-specific websites or organizations were identified as being the most helpful source of assistance and information.</div></div><div><h3>Conclusions</h3><div>Patient organizations and healthcare professionals can help address the need for strategies to overcome barriers and expand on FTD-specific support, ranging from caregiver support groups to financial assistance and additional support in the day-to-day caregiving at home.</div></div>","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Page S18"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144613981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.033
Morgan Bron , Gideon Aweh , Darlene Salas , Eric Jen , Amita Patel
<div><h3>Introduction</h3><div>Tardive dyskinesia (TD), a persistent movement disorder associated with antipsychotic exposure, can have disabling impacts on social, physical, and emotional functioning. Older adults have a higher risk for TD and may be particularly vulnerable to its physical impacts (e.g., difficulty swallowing), potentially complicating clinical management in long-term care (LTC) settings. However, data on the prevalence and burden of TD in LTC settings are limited. Therefore, a real-world study was conducted using United States (US) claims data to characterize patients with TD in LTC settings.</div></div><div><h3>Methods</h3><div>The STATinMED Real-World Data Insights Database, which captures 80% of US claims data, was used for analysis. The study period was defined as Jan 2016-Dec 2022 (inclusive). Patients with ≥1 LTC stay and an ICD-10 code indicative of TD (G24.01) during the study period were identified and analyzed descriptively by LTC setting for each LTC stay during the study period. Additional analyses related to comorbidities, medication use, and healthcare visits were analyzed descriptively in a subpopulation of patients who met a more stringent set of inclusion criteria: ≥1 LTC stay from Jan 2017 to Dec 2021 (identification period), with “index stay” defined as the first LTC stay; ICD-10 code of G24.01 on or before the index stay; and continuous capture of medical and pharmacy benefits for 1 year pre-index stay and 1 year post-index stay.</div></div><div><h3>Results</h3><div>20,183 patients had an ICD-10 code indicative of TD and ≥1 LTC stay during the study period. Skilled nursing facilities were the most common type of LTC stay, with 14,235 (70.5%) patients having ≥1 skilled nursing facility stay during the study period. LTC stays in nursing homes (55.2%) and assisted living facilities (20.4%) were also common. Among 2,294 patients who met the criteria for additional analysis, 1,483 (64.6%) were ≥65 years and 1,544 (67.3%) were female. The mean (±SD) Charlson Comorbidity Index (CCI) score was 3.72 (±4.2), and 753 (32.8%) had a CCI score ≥4, indicating high comorbidity burden and increased mortality risk. Common comorbidities included mood disorders (66.1%), schizophrenia (38.8%), sleep disorders (35.0%), substance abuse (28.4%), urinary tract infections (26.7%), and dysphagia (18.5%). The use of antidepressants (56.1%), anticonvulsants (52.3%), antipsychotics (50.4%), and anticholinergics (50.0%) was common. Moreover, polypharmacy was common, with 47.9% of patients being prescribed ≥3 medications that may increase risk of falls or cognitive impairment in elderly adults (e.g., anticholinergics, anticonvulsants, antihistamines, benzodiazepines, sedative-hypnotics). Within 1 year after the index LTC stay, 1,085 (47.3%) patients had ≥1 emergency department (ED) visit, with a median of 2 visits/patient and median time to first visit of 143 days. Additional longitudinal real-world analyses on anticholinergic use, the pre
{"title":"31. THE BURDEN OF TARDIVE DYSKINESIA IN LONG-TERM CARE SETTINGS: RESULTS FROM A REAL-WORLD STUDY OF UNITED STATES CLAIMS DATA","authors":"Morgan Bron , Gideon Aweh , Darlene Salas , Eric Jen , Amita Patel","doi":"10.1016/j.jagp.2025.04.033","DOIUrl":"10.1016/j.jagp.2025.04.033","url":null,"abstract":"<div><h3>Introduction</h3><div>Tardive dyskinesia (TD), a persistent movement disorder associated with antipsychotic exposure, can have disabling impacts on social, physical, and emotional functioning. Older adults have a higher risk for TD and may be particularly vulnerable to its physical impacts (e.g., difficulty swallowing), potentially complicating clinical management in long-term care (LTC) settings. However, data on the prevalence and burden of TD in LTC settings are limited. Therefore, a real-world study was conducted using United States (US) claims data to characterize patients with TD in LTC settings.</div></div><div><h3>Methods</h3><div>The STATinMED Real-World Data Insights Database, which captures 80% of US claims data, was used for analysis. The study period was defined as Jan 2016-Dec 2022 (inclusive). Patients with ≥1 LTC stay and an ICD-10 code indicative of TD (G24.01) during the study period were identified and analyzed descriptively by LTC setting for each LTC stay during the study period. Additional analyses related to comorbidities, medication use, and healthcare visits were analyzed descriptively in a subpopulation of patients who met a more stringent set of inclusion criteria: ≥1 LTC stay from Jan 2017 to Dec 2021 (identification period), with “index stay” defined as the first LTC stay; ICD-10 code of G24.01 on or before the index stay; and continuous capture of medical and pharmacy benefits for 1 year pre-index stay and 1 year post-index stay.</div></div><div><h3>Results</h3><div>20,183 patients had an ICD-10 code indicative of TD and ≥1 LTC stay during the study period. Skilled nursing facilities were the most common type of LTC stay, with 14,235 (70.5%) patients having ≥1 skilled nursing facility stay during the study period. LTC stays in nursing homes (55.2%) and assisted living facilities (20.4%) were also common. Among 2,294 patients who met the criteria for additional analysis, 1,483 (64.6%) were ≥65 years and 1,544 (67.3%) were female. The mean (±SD) Charlson Comorbidity Index (CCI) score was 3.72 (±4.2), and 753 (32.8%) had a CCI score ≥4, indicating high comorbidity burden and increased mortality risk. Common comorbidities included mood disorders (66.1%), schizophrenia (38.8%), sleep disorders (35.0%), substance abuse (28.4%), urinary tract infections (26.7%), and dysphagia (18.5%). The use of antidepressants (56.1%), anticonvulsants (52.3%), antipsychotics (50.4%), and anticholinergics (50.0%) was common. Moreover, polypharmacy was common, with 47.9% of patients being prescribed ≥3 medications that may increase risk of falls or cognitive impairment in elderly adults (e.g., anticholinergics, anticonvulsants, antihistamines, benzodiazepines, sedative-hypnotics). Within 1 year after the index LTC stay, 1,085 (47.3%) patients had ≥1 emergency department (ED) visit, with a median of 2 visits/patient and median time to first visit of 143 days. Additional longitudinal real-world analyses on anticholinergic use, the pre","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Page S22"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144613996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.035
Parhesh Kumar , Joohyun Kang , Jordan Serrano-Guedea , Faith Gunning , Oded Bein , Nili Solomonov
<div><h3>Introduction</h3><div>Late-life depression is common, debilitating, and linked with poor mental health and medical outcomes. Individuals with depression experience high baseline heart rates and sleep disturbances, including fluctuations in circadian rhythm and sleep cycles. Depression is typically measured using weekly or periodic interviewer-rated or self-reported measures. These scales are limited by recall bias and low time sensitivity and accuracy, especially among older adults. Novel wearable devices and real-time mood scales measured multiple times a day (ecological momentary assessments; EMAs) can improve the precision and accuracy of depression severity measurement. There is little work on the application of these methods in the aging population, with only a few studies examining changes during treatment for late-life depression. We aimed to examine whether wearables and EMAs are feasible and can track precisely the changes across multiple domains during psychotherapy for late-life depression</div></div><div><h3>Methods</h3><div>We implemented a novel wearable biometric ring (Oura Ring) and EMAs (measured twice daily) in an ongoing randomized controlled trial of psychotherapies for late-life suicidality. Three patients with major depression and suicidality completed 9 weeks of psychotherapy while wearing the Oura Ring and completing two EMA surveys a day (afternoon and evening surveys). Oura Ring data collected daily measures of average heart rate (beats per minute), heart rate variability, and hours of sleep. EMAs measured number of hours they slept, negative affect (stress, anxiety, irritability, depression, and loneliness), and positive affect (energy, motivation, excitement, interest, and satisfaction).</div></div><div><h3>Results</h3><div>Our preliminary results show that all three participants experienced a reduction in negative affect and an increase in positive affect during psychotherapy. There was variability in trajectories of positive affect: Patients A and C showed a pronounced increase in positive affect, while Patient B showed an initial increase followed by a decrease. Further, for all three participants, hours slept (measured by Oura Ring) and self-reported hours slept followed a similar pattern over time, indicating these two measures may be linked. Finally, Patients A and C showed a consistent increase in heart rate variability, while patient B experienced a decrease over time.</div></div><div><h3>Conclusions</h3><div>Our preliminary case studies suggest that integrating wearables with daily EMA self-reports can provide a feasible, precise, and granular assessment of daily changes in affect and biometrics, such as sleep and heart rate, during psychotherapy for late-life depression. The strong alignment between wearable-measured and self-reported sleep data, along with observable trends in heart rate variability and negative valence mood responses, highlights the powerful potential of these methods. This potenti
{"title":"33. USING NOVEL WEARABLES AND ECOLOGICAL MOMENTARY ASSESSMENT TO TRACK PHYSIOLOGICAL BIOMARKERS IN PSYCHOTHERAPY FOR LATE-LIFE DEPRESSION","authors":"Parhesh Kumar , Joohyun Kang , Jordan Serrano-Guedea , Faith Gunning , Oded Bein , Nili Solomonov","doi":"10.1016/j.jagp.2025.04.035","DOIUrl":"10.1016/j.jagp.2025.04.035","url":null,"abstract":"<div><h3>Introduction</h3><div>Late-life depression is common, debilitating, and linked with poor mental health and medical outcomes. Individuals with depression experience high baseline heart rates and sleep disturbances, including fluctuations in circadian rhythm and sleep cycles. Depression is typically measured using weekly or periodic interviewer-rated or self-reported measures. These scales are limited by recall bias and low time sensitivity and accuracy, especially among older adults. Novel wearable devices and real-time mood scales measured multiple times a day (ecological momentary assessments; EMAs) can improve the precision and accuracy of depression severity measurement. There is little work on the application of these methods in the aging population, with only a few studies examining changes during treatment for late-life depression. We aimed to examine whether wearables and EMAs are feasible and can track precisely the changes across multiple domains during psychotherapy for late-life depression</div></div><div><h3>Methods</h3><div>We implemented a novel wearable biometric ring (Oura Ring) and EMAs (measured twice daily) in an ongoing randomized controlled trial of psychotherapies for late-life suicidality. Three patients with major depression and suicidality completed 9 weeks of psychotherapy while wearing the Oura Ring and completing two EMA surveys a day (afternoon and evening surveys). Oura Ring data collected daily measures of average heart rate (beats per minute), heart rate variability, and hours of sleep. EMAs measured number of hours they slept, negative affect (stress, anxiety, irritability, depression, and loneliness), and positive affect (energy, motivation, excitement, interest, and satisfaction).</div></div><div><h3>Results</h3><div>Our preliminary results show that all three participants experienced a reduction in negative affect and an increase in positive affect during psychotherapy. There was variability in trajectories of positive affect: Patients A and C showed a pronounced increase in positive affect, while Patient B showed an initial increase followed by a decrease. Further, for all three participants, hours slept (measured by Oura Ring) and self-reported hours slept followed a similar pattern over time, indicating these two measures may be linked. Finally, Patients A and C showed a consistent increase in heart rate variability, while patient B experienced a decrease over time.</div></div><div><h3>Conclusions</h3><div>Our preliminary case studies suggest that integrating wearables with daily EMA self-reports can provide a feasible, precise, and granular assessment of daily changes in affect and biometrics, such as sleep and heart rate, during psychotherapy for late-life depression. The strong alignment between wearable-measured and self-reported sleep data, along with observable trends in heart rate variability and negative valence mood responses, highlights the powerful potential of these methods. This potenti","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Page S23"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.044
Nikki Bloch , Stephanie Ibrahim , Elizabeth W. Twamley , Colin Depp , Ellen Lee
<div><h3>Introduction</h3><div>While successful aging remains nebulously defined, research definitions commonly include domains of mental health, physical health, cognitive health, and social functioning. Positive psychological factors such as self-compassion and resilience have been shown to be important predictors of these same successful aging domains. However, the literature is mixed regarding which predictors impact which successful aging domains. Discerning the specific positive psychological factors that influence certain domains may allow for more targeted, individualized interventions. Our study aimed to understand the associations of positive psychological factors (e.g., resilience, self-compassion) with successful aging domains. We hypothesized that self-compassion and resilience would be associated with better mental health outcomes, physical health outcomes, social functioning, and cognitive functioning.</div></div><div><h3>Methods</h3><div>This was a cross-sectional, retrospective study of prospectively collected registry data of independent-living older adults in a continuing care senior housing community in San Diego County. Inclusion criteria were: English speaking, age ³65, no known diagnosis of dementia or disabling illness, and ability to complete study assessments. Positive psychological factors were assessed using validated scales: Neff Self-Compassion Scale and Connor-Davidson Resilience Scale. Outcome measures were assessed through validated self-administered and clinician administered instruments for: depression (Patient Health Questionnaire); physical health: frailty (Fried Frailty Index), comorbidities (Cumulative Illness Rating Scale), mobility (Timed Up and Go test), subjective physical well-being (Medical Outcomes Survey); cognitive health: overall (Montreal Cognitive Assessment), executive functioning (Delis-Kaplan Executive Function System); social functioning: social support (Social Support Index), Emotional Support (Perceived Support Scale, PSS), Instrumental Support (PSS), negative social interactions (PSS), loneliness (UCLA Loneliness Scale 8-item); and overall successful aging (Self Rated Successful Aging Scale, SRSA).</div><div>The dataset was limited to the first visit from individuals who completed the SRSA. Statistical analyses were conducted using SPSS software. Descriptive statistics characterizing the sample were calculated with means and standard deviations for numerical variables and percentages for categorical variables. General Linear Models were used to assess associations of positive psychological factors to successful aging domains and covaried for age, sex, years of education, and relationship status.</div></div><div><h3>Results</h3><div>The sample included 118 participants with mean age of 82.92 (range 66-98). The majority were female (66.9%), white (90.7%), and unpartnered (59.3%). Self-compassion was positively associated with better mental health (p < 0.05) and was not associated with phy
虽然成功老龄化的定义仍然模糊不清，但研究定义通常包括心理健康、身体健康、认知健康和社会功能等领域。积极的心理因素，如自我同情和弹性，已被证明是这些成功的老龄化领域的重要预测因素。然而，关于哪些预测因素影响哪些成功的衰老域，文献是混合的。识别影响某些领域的具体积极心理因素，可能会使干预措施更有针对性和个体化。本研究旨在了解积极心理因素（如弹性、自我同情）与成功老龄化领域的关系。我们假设自我同情和弹性与更好的心理健康结果、身体健康结果、社会功能和认知功能有关。方法本研究是一项横断面、回顾性研究，前瞻性地收集了圣地亚哥县一个持续护理高级住房社区中独立生活的老年人的登记数据。纳入标准为：会说英语，年龄65岁，无已知痴呆或致残疾病诊断，有能力完成研究评估。积极心理因素采用Neff自我同情量表和Connor-Davidson弹性量表进行评估。结果测量通过有效的自我管理和临床管理的工具进行评估：抑郁症（患者健康问卷）；身体健康：虚弱（Fried虚弱指数）、合并症（累积疾病评定量表）、活动能力（Timed Up and Go测试）、主观身体健康（医疗结果调查）；认知健康：总体（蒙特利尔认知评估），执行功能（Delis-Kaplan执行功能系统）；社会功能：社会支持（社会支持指数）、情感支持（感知支持量表，PSS）、工具支持（PSS）、负性社会互动（PSS）、孤独感（UCLA孤独感量表8项）；总体成功老龄化（自评成功老龄化量表，SRSA）该数据集仅限于完成SRSA的个人的第一次访问。采用SPSS软件进行统计分析。描述样本特征的统计数据是用数值变量的平均值和标准差以及分类变量的百分比来计算的。使用一般线性模型来评估积极心理因素与成功老龄化领域的关联，并与年龄、性别、受教育年限和关系状况共变。结果118名参与者，平均年龄82.92岁（66 ~ 98岁）。大多数是女性（66.9%）、白人（90.7%）和单身（59.3%）。自我同情与心理健康呈正相关(p <；0.05)，与身体功能无关。心理弹性与更好的主观身体功能呈正相关(p <；0.05)，但与心理健康或身体功能的客观测量无关。两种积极的心理因素都与认知健康无关。两者均与SRSA呈正相关(p值<；0.05)。结论在独立生活老年人中，弹性和自我同情的积极心理因素与成功老龄化的领域有不同的关系，而与认知健康无关。因此，成功的老龄化干预可能需要整合心理因素。
{"title":"42. POSITIVE PSYCHOLOGICAL CORRELATES OF SUCCESSFUL AGING: A CROSS-SECTIONAL STUDY OF MENTAL, PHYSICAL, COGNITIVE, AND SOCIAL FUNCTIONING AMONG COMMUNITY-DWELLING OLDER ADULTS.","authors":"Nikki Bloch , Stephanie Ibrahim , Elizabeth W. Twamley , Colin Depp , Ellen Lee","doi":"10.1016/j.jagp.2025.04.044","DOIUrl":"10.1016/j.jagp.2025.04.044","url":null,"abstract":"<div><h3>Introduction</h3><div>While successful aging remains nebulously defined, research definitions commonly include domains of mental health, physical health, cognitive health, and social functioning. Positive psychological factors such as self-compassion and resilience have been shown to be important predictors of these same successful aging domains. However, the literature is mixed regarding which predictors impact which successful aging domains. Discerning the specific positive psychological factors that influence certain domains may allow for more targeted, individualized interventions. Our study aimed to understand the associations of positive psychological factors (e.g., resilience, self-compassion) with successful aging domains. We hypothesized that self-compassion and resilience would be associated with better mental health outcomes, physical health outcomes, social functioning, and cognitive functioning.</div></div><div><h3>Methods</h3><div>This was a cross-sectional, retrospective study of prospectively collected registry data of independent-living older adults in a continuing care senior housing community in San Diego County. Inclusion criteria were: English speaking, age ³65, no known diagnosis of dementia or disabling illness, and ability to complete study assessments. Positive psychological factors were assessed using validated scales: Neff Self-Compassion Scale and Connor-Davidson Resilience Scale. Outcome measures were assessed through validated self-administered and clinician administered instruments for: depression (Patient Health Questionnaire); physical health: frailty (Fried Frailty Index), comorbidities (Cumulative Illness Rating Scale), mobility (Timed Up and Go test), subjective physical well-being (Medical Outcomes Survey); cognitive health: overall (Montreal Cognitive Assessment), executive functioning (Delis-Kaplan Executive Function System); social functioning: social support (Social Support Index), Emotional Support (Perceived Support Scale, PSS), Instrumental Support (PSS), negative social interactions (PSS), loneliness (UCLA Loneliness Scale 8-item); and overall successful aging (Self Rated Successful Aging Scale, SRSA).</div><div>The dataset was limited to the first visit from individuals who completed the SRSA. Statistical analyses were conducted using SPSS software. Descriptive statistics characterizing the sample were calculated with means and standard deviations for numerical variables and percentages for categorical variables. General Linear Models were used to assess associations of positive psychological factors to successful aging domains and covaried for age, sex, years of education, and relationship status.</div></div><div><h3>Results</h3><div>The sample included 118 participants with mean age of 82.92 (range 66-98). The majority were female (66.9%), white (90.7%), and unpartnered (59.3%). Self-compassion was positively associated with better mental health (p < 0.05) and was not associated with phy","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Pages S30-S31"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.093
Christian Schmutz , Julia Mikevitch
<div><h3>Introduction</h3><div>In February 2022 the Russian Federation invaded Ukraine. The ongoing conflict, including 1682 verified attacks on healthcare infrastructure, strained the Ukrainian healthcare system. TeleHelp Ukraine (THU), a nonprofit organization based in the United States, intervened to provide free telemedicine services to individuals living in Ukraine, including areas of active conflict and occupied territories. This paper addresses how age, gender, geographic location, and significant wartime events affect psychiatric symptoms and mental healthcare utilization in older adults.</div></div><div><h3>Methods</h3><div>Data extraction:</div><div>Data was extracted from Cliniko, a secure telemedicine platform utilized by THU. 618 patient visits for all medical specialties were extracted from 8/12/2022-6/27/2023 containing the following variables: date of visit, geographic location, age, sex, chief complaint. A subset of 394 mental health visits with recorded patient ages was isolated. These visits were divided into 2 groups for comparison, patients age 50 or older (31 visits) and patients younger than age 49 or younger (363 visits).</div><div>Data analysis:</div><div>The Wilcoxon rank sum test was used to compare median ages between older and younger patients. Fisher exact test was used to compare reported sexes. Simple statistics described the geographic distribution of older adult visits.</div><div>The number of psychiatric symptoms or “chief complaints” (CCs) recorded for each visit ranged from 0 to 6. 628 and 53 CCs were reported for the younger and older age groups respectively. The large number of unique CCs made meaningful comparisons unrealistic, so CCs were reclassified into categories for comparison: depressive, anxious, PTSD, nonspecific symptoms, psychosocial stress, and other. CCs were compared between groups for each individual category using a Chi Square test. The resulting p-values were adjusted using a Benjamini-Yakutieli correction for multiple testing.</div><div>Significant war events were identified using sources from government and news media. These events were mapped onto the number of patient visits each week over time.</div></div><div><h3>Results</h3><div>Demographics: The median age of the younger and older groups was 33 and 68, respectively (p < 0.0001). Only 3% of visits in the older group were for male-identifying patients, versus 39% in the younger group (p < 0.0001). Geographically, visits in the older adult group were approximately evenly distributed between Kyiv, the occupied territories, and undisclosed locations (35%, 32%, and 29% respectively).</div><div>Chief complaint: Non-specific mood symptoms were more likely in older patient visits than in younger patient visits (26% and 8% respectively; p = 0.001).</div><div>War Events: There was an apparent increase in telemental health utilization around the time of the Russian Bakhmut offensive. There was an apparent decrease in utilization around th
{"title":"91. TELEHEALTH IN WAR: THE STATE OF GERIATRIC MENTAL HEALTH IN UKRAINE","authors":"Christian Schmutz , Julia Mikevitch","doi":"10.1016/j.jagp.2025.04.093","DOIUrl":"10.1016/j.jagp.2025.04.093","url":null,"abstract":"<div><h3>Introduction</h3><div>In February 2022 the Russian Federation invaded Ukraine. The ongoing conflict, including 1682 verified attacks on healthcare infrastructure, strained the Ukrainian healthcare system. TeleHelp Ukraine (THU), a nonprofit organization based in the United States, intervened to provide free telemedicine services to individuals living in Ukraine, including areas of active conflict and occupied territories. This paper addresses how age, gender, geographic location, and significant wartime events affect psychiatric symptoms and mental healthcare utilization in older adults.</div></div><div><h3>Methods</h3><div>Data extraction:</div><div>Data was extracted from Cliniko, a secure telemedicine platform utilized by THU. 618 patient visits for all medical specialties were extracted from 8/12/2022-6/27/2023 containing the following variables: date of visit, geographic location, age, sex, chief complaint. A subset of 394 mental health visits with recorded patient ages was isolated. These visits were divided into 2 groups for comparison, patients age 50 or older (31 visits) and patients younger than age 49 or younger (363 visits).</div><div>Data analysis:</div><div>The Wilcoxon rank sum test was used to compare median ages between older and younger patients. Fisher exact test was used to compare reported sexes. Simple statistics described the geographic distribution of older adult visits.</div><div>The number of psychiatric symptoms or “chief complaints” (CCs) recorded for each visit ranged from 0 to 6. 628 and 53 CCs were reported for the younger and older age groups respectively. The large number of unique CCs made meaningful comparisons unrealistic, so CCs were reclassified into categories for comparison: depressive, anxious, PTSD, nonspecific symptoms, psychosocial stress, and other. CCs were compared between groups for each individual category using a Chi Square test. The resulting p-values were adjusted using a Benjamini-Yakutieli correction for multiple testing.</div><div>Significant war events were identified using sources from government and news media. These events were mapped onto the number of patient visits each week over time.</div></div><div><h3>Results</h3><div>Demographics: The median age of the younger and older groups was 33 and 68, respectively (p < 0.0001). Only 3% of visits in the older group were for male-identifying patients, versus 39% in the younger group (p < 0.0001). Geographically, visits in the older adult group were approximately evenly distributed between Kyiv, the occupied territories, and undisclosed locations (35%, 32%, and 29% respectively).</div><div>Chief complaint: Non-specific mood symptoms were more likely in older patient visits than in younger patient visits (26% and 8% respectively; p = 0.001).</div><div>War Events: There was an apparent increase in telemental health utilization around the time of the Russian Bakhmut offensive. There was an apparent decrease in utilization around th","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Pages S67-S68"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.085
Alexandra Fortunato , Alison O'Donnell , Brittany Spitznogle , Naveen Reddy , Shaye Kerper , Steven Handler
<div><h3>Introduction</h3><div>Aging United States Military Veterans are at an increased risk of developing dementia compared to the general population due to both military and non-military-related risk factors. With the Food and Drug Administration (FDA) approval of lecanemab (Leqembi ®), a monoclonal antibody therapy (mAb) directed against amyloid beta, Veterans now have access to disease modifying treatment for Alzheimer’s Disease (AD). The implementation of this novel treatment at the VA has uncovered significant education gaps and safety challenges. Specifically, there was a lack of both Veteran and clinician-facing materials for implementation and monitoring lecanemab. Thus, a variety of materials were developed by this project's authors from January 4, 2024 through August 9, 2024 and were distributed via the national VA SharePoint site. Veteran-facing materials prioritized education and safety and included information about lecanemab and its potential adverse effects. A wallet card was also developed to highlight the need for emergent evaluation and MRI brain scan if certain side effects occurred. Clinician-facing documents focused on the potential adverse effects of lecanemab, Veteran inclusion/exclusion criteria, and diagnosis of AD. To better understand the impact that these new materials have had at a national level, we developed and distributed a survey to select VA healthcare professionals. The objective of this project was to perform a gap analysis, obtain broad feedback on currently available educational materials for lecanemab, and set priorities for the development and dissemination of additional materials to support the safe use of lecanemab within the VA.</div></div><div><h3>Methods</h3><div>We conducted a cross-sectional survey of healthcare professionals who actively participate in the national Veteran’s Health Administration (VHA) Novel AD Therapeutics Community of Practice (CoP) Workgroup. The survey was sent out on September 17, 2024 and remained open until October 4, 2024. The primary outcome was the awareness of existing lecanemab educational materials, as described above, among healthcare professionals in the CoP Workgroup involved in lecanemab implementation. Only lecanemab was evaluated since the second mAb, donanemab (Kisunla®) was not commercially available at the time of the study. Secondary outcomes focused on evaluating the effectiveness of resources necessary to: identify Veterans eligible for lecanemab, educate Veterans and caregivers on its use, determine the appropriate dosing schedule, establish monitoring protocols, and manage potential side effects effectively. Outcomes were measured using Microsoft Forms web-based survey software and were reported on a 5-point Likert scale, ranging from “strongly disagree” to “strongly agree”. The two positive responses (“agree” and “strongly agree”) and the two negative responses (“disagree” and “strongly disagree”) were combined to make positive and negative response gr
{"title":"83. SUPPORTING THE SAFETY OF ANTI-AMYLOID MONOCLONAL ANTIBODY THERAPY FOR EARLY ALZHEIMER'S DISEASE IN UNITED STATES VETERANS","authors":"Alexandra Fortunato , Alison O'Donnell , Brittany Spitznogle , Naveen Reddy , Shaye Kerper , Steven Handler","doi":"10.1016/j.jagp.2025.04.085","DOIUrl":"10.1016/j.jagp.2025.04.085","url":null,"abstract":"<div><h3>Introduction</h3><div>Aging United States Military Veterans are at an increased risk of developing dementia compared to the general population due to both military and non-military-related risk factors. With the Food and Drug Administration (FDA) approval of lecanemab (Leqembi ®), a monoclonal antibody therapy (mAb) directed against amyloid beta, Veterans now have access to disease modifying treatment for Alzheimer’s Disease (AD). The implementation of this novel treatment at the VA has uncovered significant education gaps and safety challenges. Specifically, there was a lack of both Veteran and clinician-facing materials for implementation and monitoring lecanemab. Thus, a variety of materials were developed by this project's authors from January 4, 2024 through August 9, 2024 and were distributed via the national VA SharePoint site. Veteran-facing materials prioritized education and safety and included information about lecanemab and its potential adverse effects. A wallet card was also developed to highlight the need for emergent evaluation and MRI brain scan if certain side effects occurred. Clinician-facing documents focused on the potential adverse effects of lecanemab, Veteran inclusion/exclusion criteria, and diagnosis of AD. To better understand the impact that these new materials have had at a national level, we developed and distributed a survey to select VA healthcare professionals. The objective of this project was to perform a gap analysis, obtain broad feedback on currently available educational materials for lecanemab, and set priorities for the development and dissemination of additional materials to support the safe use of lecanemab within the VA.</div></div><div><h3>Methods</h3><div>We conducted a cross-sectional survey of healthcare professionals who actively participate in the national Veteran’s Health Administration (VHA) Novel AD Therapeutics Community of Practice (CoP) Workgroup. The survey was sent out on September 17, 2024 and remained open until October 4, 2024. The primary outcome was the awareness of existing lecanemab educational materials, as described above, among healthcare professionals in the CoP Workgroup involved in lecanemab implementation. Only lecanemab was evaluated since the second mAb, donanemab (Kisunla®) was not commercially available at the time of the study. Secondary outcomes focused on evaluating the effectiveness of resources necessary to: identify Veterans eligible for lecanemab, educate Veterans and caregivers on its use, determine the appropriate dosing schedule, establish monitoring protocols, and manage potential side effects effectively. Outcomes were measured using Microsoft Forms web-based survey software and were reported on a 5-point Likert scale, ranging from “strongly disagree” to “strongly agree”. The two positive responses (“agree” and “strongly agree”) and the two negative responses (“disagree” and “strongly disagree”) were combined to make positive and negative response gr","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Page S61"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<div><h3>Introduction</h3><div>Mirtazapine, first sold in the United States as Remeron in 1996, is a noradrenergic and specific serotonergic antidepressant FDA-approved for major depressive disorder. Its mechanism of action is referred to as NaSSA due to its alpha-2, 5-HT2, and 5-HT3 antagonism. It has also been used off-label as a third-line treatment option for akathisia, appetite stimulation, and SSRI-induced sexual dysfunction. Incidents of hyperkinetic movement disorders caused by mirtazapine have been reported, but even more infrequent for cases involving tardive dyskinesia (TD). The aim of this presentation is to highlight a case of TD with the use of mirtazapine in an older adult and search for more literature involving mirtazapine-induced tardive dyskinesia.</div></div><div><h3>Methods</h3><div>This case involved an older adult with a history of major neurocognitive disorder with behavioral disturbance and stroke in 2012 who was initially seen by geriatric medicine for a chief complaint of worsening memory loss. Prior history was noted for chronic use of amitriptyline and clonazepam, MoCA score of 8/30, medical history of Crohn’s disease (controlled), and psychiatric history of depression and anxiety. Trials of donepezil and memantine were used in the past but were discontinued due to lack of tolerance. Attempts were made to taper off amitriptyline and clonazepam with buspirone and citalopram, but this was unsuccessful. The primary care provider was eventually able to wean off clonazepam to 0.5 mg oral once daily from three times a day while amitriptyline was continued at PTA 250 mg dose at bedtime. Symptoms during that visit were noted for paranoia about strangers damaging the house, poor sleep, and poor appetite; ADLs 5/6 and IADLs 3/8; updated MoCA of 9/30. During consultation and follow-up appointments with geriatric psychiatry, medication adjustments were made, which eventually led to the development of tardive dyskinesia (TD). For this poster presentation, geriatric psychiatry and medicine department notes were chart reviewed along with the patient's profile. Informed consent was obtained for this presentation. Consensus AI, a research assistant tool that has access to millions of academic papers and accurately pulls peer-reviewed papers, was used to generate literature investigating or reporting findings of tardive dyskinesia with mirtazapine use. “Mirtazapine-induced tardive dyskinesia in older adults” was used as a search feature. All study types and countries were included, and no specific timeline was selected with regards to the publishing date.</div></div><div><h3>Results</h3><div>Over the course of 6-7 months after the geriatric psychiatry consultation visit, amitriptyline was tapered off to 50 mg at bedtime while clonazepam was continued at 0.5 mg oral daily. Towards the end of the summer, risperidone was added at 0.25 mg due to worsening psychosis, while clonazepam and amitriptyline were continued. By fall, risperidone wa
当使用Consensus AI时，最初生成了10项研究，其中包括随机对照试验、病例报告、观察性研究和系统评价的组合。在这些研究中，只有一项研究（2017年欧洲精神病学发表的一份病例报告）评论了使用ssrid的迟发性运动障碍。一些研究报告了运动障碍/运动障碍与米氮平的使用，但没有与TD。结论从用药变化的时间轴来看，高剂量米氮平明显会导致口腔疼痛和下颌疼痛的发生。持续使用阿米替林也可能使这一事件更有可能发生。根据FDA的规定，米氮平的剂量范围从7.5毫克到45毫克（最大），但60毫克的剂量用于临床抑郁症。CYP1A2, 2D6和3A4的动力学相互作用被注意到。与文拉法辛（Effexor）联合用于促进5 -羟色胺和去甲肾上腺素的神经传递，STAR-D试验报道其疗效与丙氨嘧啶（parate）相似。在高剂量下，与抗组胺作用相比，其去甲肾上腺素能作用更加突出；因此，它会变得不那么镇静，对食欲的刺激也会减少。在15mg的剂量下，它可以作为治疗静坐症的三线选择，但更高的剂量有可能加剧。正如一份病例报告所指出的那样，米氮平有可能诱发急性运动障碍，并且症状可以不经治疗而消退（S. Konitsiotis等，2005）。据报道，一名澳大利亚中年土著妇女在服用舍曲林和米氮平的试验中出现了罕见的迟发性运动障碍，在16周内将口面部运动障碍评分从22/36降至4/36 （D. Roy et al., 2017）。根据NIH PubChem，在服用米氮平后，去甲肾上腺素能和血清素能的活性都增加了。中枢神经系统突触前α 2-肾上腺素能抑制性自身受体和异源受体均有拮抗活性。总之，尽管有证据表明米氮平可以缓解运动障碍的症状，但在老年人中进行药物调整时应仔细考虑。本病例表现为迟发性运动障碍，而非其他由米氮平引起的多动性运动障碍。这个病例说明了米氮平与运动障碍之间存在复杂的相互作用。为了进一步了解，还需要继续进行研究。目前，临床医生应该继续根据患者的个人情况和需求量身定制精神病学管理，同时权衡风险和收益。
{"title":"11. MIRTAZAPINE INDUCED TARDIVE DYSKINESIA IN AN OLDER ADULT","authors":"Amin Syed , Karishma Soni , Azziza Bankole , Badr Ratnakaran","doi":"10.1016/j.jagp.2025.04.014","DOIUrl":"10.1016/j.jagp.2025.04.014","url":null,"abstract":"<div><h3>Introduction</h3><div>Mirtazapine, first sold in the United States as Remeron in 1996, is a noradrenergic and specific serotonergic antidepressant FDA-approved for major depressive disorder. Its mechanism of action is referred to as NaSSA due to its alpha-2, 5-HT2, and 5-HT3 antagonism. It has also been used off-label as a third-line treatment option for akathisia, appetite stimulation, and SSRI-induced sexual dysfunction. Incidents of hyperkinetic movement disorders caused by mirtazapine have been reported, but even more infrequent for cases involving tardive dyskinesia (TD). The aim of this presentation is to highlight a case of TD with the use of mirtazapine in an older adult and search for more literature involving mirtazapine-induced tardive dyskinesia.</div></div><div><h3>Methods</h3><div>This case involved an older adult with a history of major neurocognitive disorder with behavioral disturbance and stroke in 2012 who was initially seen by geriatric medicine for a chief complaint of worsening memory loss. Prior history was noted for chronic use of amitriptyline and clonazepam, MoCA score of 8/30, medical history of Crohn’s disease (controlled), and psychiatric history of depression and anxiety. Trials of donepezil and memantine were used in the past but were discontinued due to lack of tolerance. Attempts were made to taper off amitriptyline and clonazepam with buspirone and citalopram, but this was unsuccessful. The primary care provider was eventually able to wean off clonazepam to 0.5 mg oral once daily from three times a day while amitriptyline was continued at PTA 250 mg dose at bedtime. Symptoms during that visit were noted for paranoia about strangers damaging the house, poor sleep, and poor appetite; ADLs 5/6 and IADLs 3/8; updated MoCA of 9/30. During consultation and follow-up appointments with geriatric psychiatry, medication adjustments were made, which eventually led to the development of tardive dyskinesia (TD). For this poster presentation, geriatric psychiatry and medicine department notes were chart reviewed along with the patient's profile. Informed consent was obtained for this presentation. Consensus AI, a research assistant tool that has access to millions of academic papers and accurately pulls peer-reviewed papers, was used to generate literature investigating or reporting findings of tardive dyskinesia with mirtazapine use. “Mirtazapine-induced tardive dyskinesia in older adults” was used as a search feature. All study types and countries were included, and no specific timeline was selected with regards to the publishing date.</div></div><div><h3>Results</h3><div>Over the course of 6-7 months after the geriatric psychiatry consultation visit, amitriptyline was tapered off to 50 mg at bedtime while clonazepam was continued at 0.5 mg oral daily. Towards the end of the summer, risperidone was added at 0.25 mg due to worsening psychosis, while clonazepam and amitriptyline were continued. By fall, risperidone wa","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Pages S8-S9"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144613901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.068
Miranda Skurla , Sara Gerke , Weronika Pasciak , Ipsit Vahia , Carmel Shachar
Introduction
Digital phenotyping is quickly gaining traction and more widespread availability. This emerging technology has the potential for collecting large amounts of precise, temporal patient data, ultimately leading to enhanced monitoring, detection, and personalization of healthcare. However, this firehose of data generated by digital phenotyping may create a dilemma for clinicians already inundated with information.
Methods
In this study, we consider the potential risks if actionable data are missed. We provide an overview of the current legal framework for clinician liability and extrapolate its use in digital phenotyping.
Results
With no established best practices in digital phenotyping, we recommend that clinicians create a written notice for each patient that details how the data will be collected and monitored, as well as consider sharing the raw data with the patient when appropriate.
Conclusions
Guidelines for digital phenotyping must be developed now to get ahead of the eventual widespread use of digital phenotyping technology in clinical care. A proactive declaration of best practices will help guide the development of an evidence-driven and ethically sound standard of care for using digital phenotyping in clinical mental health practice and the information that should be provided to patients.
{"title":"66. DATA OVERLOAD IN THE DIGITAL AGE: CAN DIGITAL PHENOTYPING CREATE LIABILITY FOR CLINICIANS?","authors":"Miranda Skurla , Sara Gerke , Weronika Pasciak , Ipsit Vahia , Carmel Shachar","doi":"10.1016/j.jagp.2025.04.068","DOIUrl":"10.1016/j.jagp.2025.04.068","url":null,"abstract":"<div><h3>Introduction</h3><div>Digital phenotyping is quickly gaining traction and more widespread availability. This emerging technology has the potential for collecting large amounts of precise, temporal patient data, ultimately leading to enhanced monitoring, detection, and personalization of healthcare. However, this firehose of data generated by digital phenotyping may create a dilemma for clinicians already inundated with information.</div></div><div><h3>Methods</h3><div>In this study, we consider the potential risks if actionable data are missed. We provide an overview of the current legal framework for clinician liability and extrapolate its use in digital phenotyping.</div></div><div><h3>Results</h3><div>With no established best practices in digital phenotyping, we recommend that clinicians create a written notice for each patient that details how the data will be collected and monitored, as well as consider sharing the raw data with the patient when appropriate.</div></div><div><h3>Conclusions</h3><div>Guidelines for digital phenotyping must be developed now to get ahead of the eventual widespread use of digital phenotyping technology in clinical care. A proactive declaration of best practices will help guide the development of an evidence-driven and ethically sound standard of care for using digital phenotyping in clinical mental health practice and the information that should be provided to patients.</div></div>","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Pages S48-S49"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.096
Vanessa Garcia , Mario I. Hernandez , Shannon L. Wilson , Heather Anderson , Jeffrey S. Patterson , Ruohui Chen , Lindsay Dillon , Andrea Z. LaCroix , Rong W. Zablocki , Loki Natarajan , Dorothy D. Sears
Introduction
Fatigue is a prevalent symptom experienced in older adults. Prolonged sitting is associated with increased fatigue and adverse mental health. Emerging evidence shows that breaking up sitting time with light activity breaks or stands may reduce fatigue in sedentary workers and individuals with type 2 diabetes. However, little is known regarding the effect of breaking up sitting time on the acute fatigue levels in postmenopausal women. This study aimed to investigate the effect of interrupting sitting time with different standing interventions on the acute fatigue levels in older postmenopausal women.
Methods
This two-site, three-condition randomized controlled crossover trial, the Rise for Health - Lab study, enrolled postmenopausal women with overweight or obesity (n=79; mean ± SD age 67 ± 7 years and BMI 32.52 ± 5.15 kg/m2). Participants completed three 5-hr conditions in a clinical laboratory setting: frequent sit- to- stands (STS – 2-minute stand every 15 minutes), hourly standing breaks (HSB – 8-minute stand every hour), and prolonged sitting (control) in a randomized order, separated by a minimum 7-day washout period before crossover. The secondary outcome of fatigue was assessed hourly using the 18-item Lee Fatigue Scale, which yields a total fatigue score as well as fatigue and energy subscale scores. The net incremental area under the curve (iAUC) was investigated via linear mixed models to evaluate each interruption modality versus the control condition. The significance level was set as 0.025 to account for multiple comparisons (e.g., 2 intervention conditions vs. control).
Results
Seventy-six participants completed at least one study visit and were included in the analysis. After adjusting for site, STS significantly reduced mean iAUC fatigue subscale scores by 81% (-24.8, SE: 10.8, p=0.02) and mean iAUC total fatigue scores by 93% (-25.3, SE: 9.3, p=0.008) compared to the control. STS improved iAUC energy subscale score by 156% (26.4, SE: 10.6, p=0.01) compared to the control. The HSB condition was not associated with significant differences in the iAUC fatigue subscale score (p=0.26), iAUC energy subscale score (p=0.21), or iAUC total fatigue score (p=0.18) compared to the control condition.
Conclusions
Frequently breaking up prolonged sitting with brief standing breaks may reduce acute fatigue in postmenopausal women with overweight or obesity. These findings may provide geriatric practitioners and caregivers with a practical and feasible non-pharmacological option for the treatment of fatigue in older adults.
疲劳是老年人的普遍症状。久坐会增加疲劳和对心理健康不利。越来越多的证据表明，通过轻度活动或站立来打破坐着的时间可能会减少久坐工作者和2型糖尿病患者的疲劳。然而，关于停止久坐对绝经后妇女急性疲劳程度的影响，我们所知甚少。本研究旨在探讨以不同站立干预措施打断久坐时间对老年绝经后妇女急性疲劳水平的影响。方法这项2点、3条件的随机对照交叉试验，即Rise for Health - Lab研究，纳入了绝经后体重超重或肥胖的妇女(n=79；平均±SD年龄67±7岁，BMI 32.52±5.15 kg/m2)。参与者在临床实验室环境中完成了三个5小时的条件：经常坐到站（STS -每15分钟站立2分钟），每小时站立休息（HSB -每小时站立8分钟）和长时间坐（对照组），随机顺序，在交叉之前至少有7天的洗脱期。疲劳的次要结果使用18项Lee疲劳量表每小时评估一次，该量表产生总疲劳得分以及疲劳和能量子量表得分。通过线性混合模型研究了净增量曲线下面积（iAUC），以评估每种中断方式与控制条件的关系。显著性水平设为0.025，以考虑多重比较（例如，2个干预条件与对照）。结果76名参与者至少完成了一次研究访问，并被纳入分析。经场地调整后，与对照组相比，STS显著降低了iAUC平均疲劳亚量表得分81% (-24.8,SE: 10.8, p=0.02)，平均iAUC总疲劳得分93% （-25.3,SE: 9.3, p=0.008）。与对照组相比，STS使iAUC能量分量量表得分提高了156% （26.4,SE: 10.6, p=0.01）。与对照组相比，HSB状态与iAUC疲劳亚量表评分（p=0.26）、iAUC能量亚量表评分（p=0.21）或iAUC总疲劳评分（p=0.18）均无显著差异。结论经常打破长时间的久坐，短暂的站立休息可以减轻绝经后超重或肥胖妇女的急性疲劳。这些发现可能为老年医生和护理人员提供一个实用可行的非药物治疗老年人疲劳的选择。
{"title":"94. ACUTE FATIGUE LEVELS ARE IMPROVED BY BRIEF STANDING BREAKS IN PROLONGED SITTING AMONG OLDER POSTMENOPAUSAL WOMEN.","authors":"Vanessa Garcia , Mario I. Hernandez , Shannon L. Wilson , Heather Anderson , Jeffrey S. Patterson , Ruohui Chen , Lindsay Dillon , Andrea Z. LaCroix , Rong W. Zablocki , Loki Natarajan , Dorothy D. Sears","doi":"10.1016/j.jagp.2025.04.096","DOIUrl":"10.1016/j.jagp.2025.04.096","url":null,"abstract":"<div><h3>Introduction</h3><div>Fatigue is a prevalent symptom experienced in older adults. Prolonged sitting is associated with increased fatigue and adverse mental health. Emerging evidence shows that breaking up sitting time with light activity breaks or stands may reduce fatigue in sedentary workers and individuals with type 2 diabetes. However, little is known regarding the effect of breaking up sitting time on the acute fatigue levels in postmenopausal women. This study aimed to investigate the effect of interrupting sitting time with different standing interventions on the acute fatigue levels in older postmenopausal women.</div></div><div><h3>Methods</h3><div>This two-site, three-condition randomized controlled crossover trial, the Rise for Health - Lab study, enrolled postmenopausal women with overweight or obesity (n=79; mean ± SD age 67 ± 7 years and BMI 32.52 ± 5.15 kg/m2). Participants completed three 5-hr conditions in a clinical laboratory setting: frequent sit- to- stands (STS – 2-minute stand every 15 minutes), hourly standing breaks (HSB – 8-minute stand every hour), and prolonged sitting (control) in a randomized order, separated by a minimum 7-day washout period before crossover. The secondary outcome of fatigue was assessed hourly using the 18-item Lee Fatigue Scale, which yields a total fatigue score as well as fatigue and energy subscale scores. The net incremental area under the curve (iAUC) was investigated via linear mixed models to evaluate each interruption modality versus the control condition. The significance level was set as 0.025 to account for multiple comparisons (e.g., 2 intervention conditions vs. control).</div></div><div><h3>Results</h3><div>Seventy-six participants completed at least one study visit and were included in the analysis. After adjusting for site, STS significantly reduced mean iAUC fatigue subscale scores by 81% (-24.8, SE: 10.8, p=0.02) and mean iAUC total fatigue scores by 93% (-25.3, SE: 9.3, p=0.008) compared to the control. STS improved iAUC energy subscale score by 156% (26.4, SE: 10.6, p=0.01) compared to the control. The HSB condition was not associated with significant differences in the iAUC fatigue subscale score (p=0.26), iAUC energy subscale score (p=0.21), or iAUC total fatigue score (p=0.18) compared to the control condition.</div></div><div><h3>Conclusions</h3><div>Frequently breaking up prolonged sitting with brief standing breaks may reduce acute fatigue in postmenopausal women with overweight or obesity. These findings may provide geriatric practitioners and caregivers with a practical and feasible non-pharmacological option for the treatment of fatigue in older adults.</div></div>","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Pages S69-S70"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.jagp.2025.04.098
Julia Kimball , Ashley Abi Chaker , Alp Canbulat , Ipsit Vahia
Introduction
There is an urgent need for novel approaches that may facilitate early detection of Alzheimer's disease and thus, create targets for effective intervention and management. Current diagnostic methods often rely on expensive and/or time-consuming procedures such as brain imaging and cognitive assessments. A novel approach proposes leveraging AI/ML models to detect AD early through the analysis of spontaneous speech and language use. This method holds the potential to advance the process of AD diagnosis by offering a non-invasive, cost-effective, and easily accessible screening tool that may identify subtle variations in linguistic (and by extension, neurocognitive) function that may not yet be identified by standard screening tools. Here, we explore the range of deep learning models that have been applied to language and cognition. We also compare their analytic approaches and available results, with a view to identifying which approach may translate most readily to clinical care.
Methods
We used a multi-faceted approach that included a literature review, brainstorming sessions with an interdisciplinary team and field experts, and targeted internet searches for relevant web-based resources. The focus of our search was to compile studies that explored the development and application of AI algorithms to identify subtle changes in speech patterns, linguistic features, and acoustic properties associated with the early stages of AD. We considered, but did not apply a traditional biomedical search algorithm, since the literature in this space is often found outside of the biomedical literature, and because this is an exploratory project. We noted that by analyzing extensive datasets of speech samples from both healthy individuals and those with AD, all the identified studies sought to establish robust predictive models for early detection. We further examined whether confounding variables present in current linguistic AD models, such as those arising from language barriers, are also present in trained deep learning models.
Results
Our investigation demonstrated the consistent application across the literature, of a multimodal system, encompassing both neural networks and traditional analysis models, which were fine-tuned for the early detection of Alzheimer's disease. Among these, the ADReSS dataset emerged as the most effective, with the ensemble method achieving the highest accuracy in predicting Alzheimer’s disease based on speech patterns. However, we noted a crucial limitation: the model’s training relied solely on English speech data. This restriction introduces bias and hinders generalizability. Languages exhibit distinct phonetic structures, accents, and rhythms, potentially causing a model trained exclusively on English to misinterpret speech from other languages. Furthermore, while deep neural networks excel at discerning complex patterns, their internal wo
{"title":"96. USING MACHINE LEARNING MODELS TO DETECT EARLY ALZHEIMER’S DISEASE THROUGH SPEECH ANALYSIS","authors":"Julia Kimball , Ashley Abi Chaker , Alp Canbulat , Ipsit Vahia","doi":"10.1016/j.jagp.2025.04.098","DOIUrl":"10.1016/j.jagp.2025.04.098","url":null,"abstract":"<div><h3>Introduction</h3><div>There is an urgent need for novel approaches that may facilitate early detection of Alzheimer's disease and thus, create targets for effective intervention and management. Current diagnostic methods often rely on expensive and/or time-consuming procedures such as brain imaging and cognitive assessments. A novel approach proposes leveraging AI/ML models to detect AD early through the analysis of spontaneous speech and language use. This method holds the potential to advance the process of AD diagnosis by offering a non-invasive, cost-effective, and easily accessible screening tool that may identify subtle variations in linguistic (and by extension, neurocognitive) function that may not yet be identified by standard screening tools. Here, we explore the range of deep learning models that have been applied to language and cognition. We also compare their analytic approaches and available results, with a view to identifying which approach may translate most readily to clinical care.</div></div><div><h3>Methods</h3><div>We used a multi-faceted approach that included a literature review, brainstorming sessions with an interdisciplinary team and field experts, and targeted internet searches for relevant web-based resources. The focus of our search was to compile studies that explored the development and application of AI algorithms to identify subtle changes in speech patterns, linguistic features, and acoustic properties associated with the early stages of AD. We considered, but did not apply a traditional biomedical search algorithm, since the literature in this space is often found outside of the biomedical literature, and because this is an exploratory project. We noted that by analyzing extensive datasets of speech samples from both healthy individuals and those with AD, all the identified studies sought to establish robust predictive models for early detection. We further examined whether confounding variables present in current linguistic AD models, such as those arising from language barriers, are also present in trained deep learning models.</div></div><div><h3>Results</h3><div>Our investigation demonstrated the consistent application across the literature, of a multimodal system, encompassing both neural networks and traditional analysis models, which were fine-tuned for the early detection of Alzheimer's disease. Among these, the ADReSS dataset emerged as the most effective, with the ensemble method achieving the highest accuracy in predicting Alzheimer’s disease based on speech patterns. However, we noted a crucial limitation: the model’s training relied solely on English speech data. This restriction introduces bias and hinders generalizability. Languages exhibit distinct phonetic structures, accents, and rhythms, potentially causing a model trained exclusively on English to misinterpret speech from other languages. Furthermore, while deep neural networks excel at discerning complex patterns, their internal wo","PeriodicalId":55534,"journal":{"name":"American Journal of Geriatric Psychiatry","volume":"33 10","pages":"Page S71"},"PeriodicalIF":4.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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