https://www.jmir.org/issue/feedJournal of Medical Internet Research2023-01-03T13:00:05-05:00JMIR Publicationseditor@jmir.orgOpen Journal Systems The leading peer-reviewed journal for digital medicine and health and health care in the internet age. https://www.jmir.org/2024/1/e50330/ Weight Gain Prevention Outcomes From a Pragmatic Digital Health Intervention With Community Health Center Patients: Randomized Controlled Trial2024-03-28T10:45:24-04:00Hailey N MillerJohn A GallisMiriam B BergerSandy AskewJoseph R EggerMelissa C KayEric Andrew FinkelsteinMia de LeonAbigail DeVriesAshley BrewerMarni Gwyther HolderGary G Bennett<strong>Background:</strong> The prevalence of obesity and its associated comorbidities continue to rise in the United States. Populations who are uninsured and from racial and ethnic minority groups continue to be disproportionately affected. These populations also experience fewer clinically meaningful outcomes in most weight loss trials. Weight gain prevention presents a useful strategy for individuals who experience barriers to weight loss. Given the often-limited weight management resources available to patients in primary care settings serving vulnerable patients, evaluating interventions with pragmatic designs may help inform the design of comprehensive obesity care delivered in primary care. <strong>Objective:</strong> This study aims to evaluate the effectiveness of Balance, a 2-arm, 12-month pragmatic randomized controlled trial of a digital weight gain prevention intervention, delivered to patients receiving primary care within federally qualified community health centers. <strong>Methods:</strong> Balance was a 2-arm, 12-month pragmatic randomized controlled trial of a digital weight gain prevention intervention delivered to individuals who had a BMI of 25-40 kg/m<sup>2</sup>, spoke English or Spanish, and were receiving primary care within a network of federally qualified community health centers in North Carolina. The Balance intervention was designed to encourage behavioral changes that result in a slight energy deficit. Intervention participants received tailored goal setting and tracking, skills training, self-monitoring, and responsive health coaching from registered dietitians. Weight was measured at regular primary care visits and documented in the electronic health record. We compared the percentage of ≤3% weight gain in each arm at 24 months after randomization—our primary outcome—using individual empirical best linear unbiased predictors from the linear mixed-effects model. We used individual empirical best linear unbiased predictors from participants with at least 1 electronic health record weight documented within a 6-month window centered on the 24-month time point. <strong>Results:</strong> We randomized 443 participants, of which 223 (50.3%) participants were allocated to the intervention arm. At baseline, participants had a mean BMI of 32.6 kg/m<sup>2</sup>. Most participants were Latino or Hispanic (n=200, 45.1%) or non–Latino or Hispanic White (n=115, 26%). In total, 53% (n=235) of participants had at least 1 visit with weight measured in the primary time window. The intervention group had a higher proportion with ≤3% weight gain at 6 months (risk ratio=1.12, 95% CI 0.94-1.28; risk difference=9.5, 95% CI –4.5 to 16.4 percentage points). This difference attenuated to the null by 24 months (risk ratio=1.00, 95% CI 0.82-1.20; risk difference=0.2, 95% CI –12.1 to 11.0 percentage points). <strong>Conclusions:</strong> In adults with overweight or obesity receiving primary care at a community health center, we did not find long-term evidence to support the dissemination of a digital health intervention for weight gain prevention. <strong>Trial Registration:</strong> ClinicalTrials.gov NCT03003403; https://clinicaltrials.gov/study/NCT03003403 2024-03-28T10:45:24-04:00 https://www.jmir.org/2024/1/e46287/ Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial2024-03-28T10:30:04-04:00Yiyang ShengRaymond BondRajesh JaiswalJohn DinsmoreJulie Doyle<strong>Background:</strong> Multiple chronic conditions (multimorbidity) are becoming more prevalent among aging populations. Digital health technologies have the potential to assist in the self-management of multimorbidity, improving the awareness and monitoring of health and well-being, supporting a better understanding of the disease, and encouraging behavior change. <strong>Objective:</strong> The aim of this study was to analyze how 60 older adults (mean age 74, SD 6.4; range 65-92 years) with multimorbidity engaged with digital symptom and well-being monitoring when using a digital health platform over a period of approximately 12 months. <strong>Methods:</strong> Principal component analysis and clustering analysis were used to group participants based on their levels of engagement, and the data analysis focused on characteristics (eg, age, sex, and chronic health conditions), engagement outcomes, and symptom outcomes of the different clusters that were discovered. <strong>Results:</strong> Three clusters were identified: the typical user group, the least engaged user group, and the highly engaged user group. Our findings show that age, sex, and the types of chronic health conditions do not influence engagement. The 3 primary factors influencing engagement were whether the same device was used to submit different health and well-being parameters, the number of manual operations required to take a reading, and the daily routine of the participants. The findings also indicate that higher levels of engagement may improve the participants’ outcomes (eg, reduce symptom exacerbation and increase physical activity). <strong>Conclusions:</strong> The findings indicate potential factors that influence older adult engagement with digital health technologies for home-based multimorbidity self-management. The least engaged user groups showed decreased health and well-being outcomes related to multimorbidity self-management. Addressing the factors highlighted in this study in the design and implementation of home-based digital health technologies may improve symptom management and physical activity outcomes for older adults self-managing multimorbidity. 2024-03-28T10:30:04-04:00 https://www.jmir.org/2024/1/e41065/ Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites2024-03-28T10:15:04-04:00Feng HeClarissa Ng Yin LingSimon NusinoviciChing-Yu ChengTien Yin WongJialiang LiCharumathi Sabanayagam<strong>Background:</strong> Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes. <strong>Objective:</strong> This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors. <strong>Methods:</strong> We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m<sup>2</sup>) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A<sub>1c</sub>, systolic blood pressure, and BMI. <strong>Results:</strong> Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A<sub>1c</sub>, blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR). <strong>Conclusions:</strong> This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors. 2024-03-28T10:15:04-04:00 https://www.jmir.org/2024/1/e46412/ Evaluation of Telehealth Services that are Clinically Appropriate for Reimbursement in the US Medicaid Population: Mixed Methods Study2024-03-28T10:00:05-04:00Sanjeev SaravanakumarAndrey Ostrovsky<strong>Background:</strong> When the US Department of Health and Human Services instituted a State of Public Health Emergency (PHE) during the COVID-19 pandemic, many telehealth flexibilities were fast-tracked to allow state Medicaid agencies to reimburse new specialty services, sites of care, and mediums such as FaceTime to communicate with patients.. This resulted in expanded access to care for financially vulnerable Medicaid patients, as evidenced by an uptick in telehealth use. Research has mostly focused on telehealth reimbursement for limited use cases such as rural primary care, without broader consideration for how telehealth can be appropriately mainstreamed and maintained. <strong>Objective:</strong> This study sought to (1) evaluate the continuation of flexible telehealth reimbursement broadly, beyond the COVID-19 pandemic; (2) analyze the clinical effectiveness of the new telehealth services; and (3) offer code-by-code reimbursement guidance to state Medicaid leaders. <strong>Methods:</strong> We surveyed 10 state Medicaid medical directors (MMDs) who are responsible for the scientific and clinical appropriateness of Medicaid policies in their respective states. Participants were asked to complete an internet-based survey with a list of medical billing codes, grouped by service type, and asked if they believed they should be reimbursed by Medicaid on a permanent basis. Additional questions covered more detailed recommendations, such as reimbursing video with audio versus audio-only, guardrails for certain specialty services, and motivations behind responses. <strong>Results:</strong> The MMDs felt that the majority of services should be reimbursed via some modality of telehealth after the PHE, with the most support for video combined with audio compared to audio-only. There were exceptions on both ends of the spectrum, where services such as pulmonary diagnostics were not recommended to be reimbursed in any form and services such as psychotherapy for mental health had the most support for audio-only. The vast majority of MMDs were supportive of reimbursement for remote monitoring services, but some preferred to have some reimbursement guardrails. We found that 90% (n=9) of MMDs were supportive of reimbursement for telehealth interprofessional services, while half (n=5) of the respondents felt that there should be continued guardrails for reimbursement. Motivations for continuing reimbursement flexibility were largely attributed to improving access to care, improving outcomes, and improving equity among the Medicaid patient population. <strong>Conclusions:</strong> There is a strong clinical endorsement to continue the telehealth flexibility enabled by the PHE, primarily for video combined with audio telehealth, with caution against audio-only telehealth in situations where hands-on intervention is necessary for diagnosis or treatment. There is also support for reimbursing remote monitoring services and telehealth interprofessional services, albeit with guardrails. These results are primarily from a perspective of improving access, outcomes, and equity; other state-specific factors such as fiscal impact and technical implementation may need to be taken into account when considering reimbursement decisions on telehealth. 2024-03-28T10:00:05-04:00 https://www.jmir.org/2024/1/e54287/ Effectiveness of the Minder Mobile Mental Health and Substance Use Intervention for University Students: Randomized Controlled Trial2024-03-27T11:00:42-04:00Melissa VereschaginAngel Y WangChris G RichardsonHui XieRichard J MunthaliKristen L HudecCalista LeungKatharine D WojcikLonna MunroPriyanka HalliRonald C KesslerDaniel V Vigo<strong>Background:</strong> University attendance represents a transition period for students that often coincides with the emergence of mental health and substance use challenges. Digital interventions have been identified as a promising means of supporting students due to their scalability, adaptability, and acceptability. <i>Minder</i> is a mental health and substance use mobile app that was codeveloped with university students. <strong>Objective:</strong> This study aims to examine the effectiveness of the <i>Minder</i> mobile app in improving mental health and substance use outcomes in a general population of university students. <strong>Methods:</strong> A 2-arm, parallel-assignment, single-blinded, 30-day randomized controlled trial was used to evaluate <i>Minder</i> using intention-to-treat analysis. In total, 1489 participants were recruited and randomly assigned to the intervention (n=743, 49.9%) or waitlist control (n=746, 50.1%) condition. The <i>Minder</i> app delivers evidence-based content through an automated chatbot and connects participants with services and university social groups. Participants are also assigned a trained peer coach to support them. The primary outcomes were measured through in-app self-assessments and included changes in general anxiety symptomology, depressive symptomology, and alcohol consumption risk measured using the 7-item General Anxiety Disorder scale, 9-item Patient Health Questionnaire, and US Alcohol Use Disorders Identification Test–Consumption Scale, respectively, from baseline to 30-day follow-up. Secondary outcomes included measures related to changes in the frequency of substance use (cannabis, alcohol, opioids, and nonmedical stimulants) and mental well-being. Generalized linear mixed-effects models were used to examine each outcome. <strong>Results:</strong> In total, 79.3% (589/743) of participants in the intervention group and 83% (619/746) of participants in the control group completed the follow-up survey. The intervention group had significantly greater average reductions in anxiety symptoms measured using the 7-item General Anxiety Disorder scale (adjusted group mean difference=−0.85, 95% CI −1.27 to −0.42; <i>P</i><.001; Cohen <i>d</i>=−0.17) and depressive symptoms measured using the 9-item Patient Health Questionnaire (adjusted group mean difference=−0.63, 95% CI −1.08 to −0.17; <i>P</i>=.007; Cohen <i>d</i>=−0.11). A reduction in the US Alcohol Use Disorders Identification Test–Consumption Scale score among intervention participants was also observed, but it was not significant (<i>P</i>=.23). Statistically significant differences in favor of the intervention group were found for mental well-being and reductions in the frequency of cannabis use and typical number of drinks consumed. A total of 77.1% (573/743) of participants in the intervention group accessed at least 1 app component during the study period. <strong>Conclusions:</strong> In a general population sample of university students, the <i>Minder</i> app was effective in reducing symptoms of anxiety and depression, with provisional support for increasing mental well-being and reducing the frequency of cannabis and alcohol use. These findings highlight the potential ability of e-tools focused on prevention and early intervention to be integrated into existing university systems to support students’ needs. <strong>Trial Registration:</strong> ClinicalTrials.gov NCT05606601; https://clinicaltrials.gov/ct2/show/NCT05606601 2024-03-27T11:00:42-04:00 https://www.jmir.org/2024/1/e50337/ Assessment of the Barriers and Enablers of the Use of mHealth Systems in Sub-Saharan Africa According to the Perceptions of Patients, Physicians, and Health Care Executives in Ethiopia: Qualitative Study2024-03-27T10:45:05-04:00Genet Tadese AboyeGizeaddis Lamesgin SimegnJean-Marie Aerts<strong>Background:</strong> Digital technologies are increasingly being used to deliver health care services and promote public health. Mobile wireless technologies or mobile health (mHealth) technologies are particularly relevant owing to their ease of use, broad reach, and wide acceptance. Unlike developed countries, Sub-Saharan Africa experiences more challenges and obstacles when it comes to deploying, using, and expanding mHealth systems. In addition to barriers, there are enabling factors that could be exploited for the design, implementation, and scaling up of mHealth systems. Sub-Saharan Africa may require tailored solutions that address the specific challenges facing the region. <strong>Objective:</strong> The overall aim of this study was to identify the barriers and enablers for using mHealth systems in Sub-Saharan Africa from the perspectives of patients, physicians, and health care executives. <strong>Methods:</strong> Multi-level and multi-actor in-depth semistructured interviews were employed to qualitatively explore the barriers and enablers of the use of mHealth systems. Data were collected from patients, physicians, and health care executives. The interviews were audio recorded, transcribed verbatim, translated, and coded. Thematic analysis methodology was adopted, and NVivo software was used for the data analysis. <strong>Results:</strong> Through this rigorous study, a total of 137 determinants were identified. Of these determinants, 68 were identified as barriers and 69 were identified as enablers. Perceived barriers in patients included lack of awareness about mHealth systems and language barriers. Perceived enablers in patients included need for automated tools for health monitoring and an increasing literacy level of the society. According to physicians, barriers included lack of available digital health systems in the local context and concern about patients’ mHealth capabilities, while enablers included the perceived usefulness in reducing workload and improving health care service quality, as well as the availability of mobile devices and the internet. As perceived by health care executives, barriers included competing priorities alongside digitalization in the health sector and lack of interoperability and complete digitalization of implemented digital health systems, while enablers included the perceived usefulness of digitalization for the survival of the highly overloaded health care system and the abundance of educated manpower specializing in technology. <strong>Conclusions:</strong> mHealth systems in Sub-Saharan Africa are hindered and facilitated by various factors. Common barriers and enablers were identified by patients, physicians, and health care executives. To promote uptake, all relevant stakeholders must actively mitigate the barriers. This study identified a promising outlook for mHealth in Sub-Saharan Africa, despite the present barriers. Opportunities exist for successful integration into health care systems, and a user-centered design is crucial for maximum uptake. 2024-03-27T10:45:05-04:00 https://www.jmir.org/2024/1/e50552/ Bridging and Bonding Social Capital by Analyzing the Demographics, User Activities, and Social Network Dynamics of Sexual Assault Centers on Twitter: Mixed Methods Study2024-03-27T10:30:24-04:00Jia XueQiaoru ZhangYun ZhangHong ShiChengda ZhengJingchuan FanLinxiao ZhangChen ChenLuye LiMicheal L Shier<strong>Background:</strong> Social media platforms have gained popularity as communication tools for organizations to engage with clients and the public, disseminate information, and raise awareness about social issues. From a social capital perspective, relationship building is seen as an investment, involving a complex interplay of tangible and intangible resources. Social media–based social capital signifies the diverse social networks that organizations can foster through their engagement on social media platforms. Literature underscores the great significance of further investigation into the scope and nature of social media use, particularly within sectors dedicated to service delivery, such as sexual assault organizations. <strong>Objective:</strong> This study aims to fill a research gap by investigating the use of Twitter by sexual assault support agencies in Canada. It seeks to understand the demographics, user activities, and social network structure within these organizations on Twitter, focusing on building social capital. The research questions explore the demographic profile, geographic distribution, and Twitter activity of these organizations as well as the social network dynamics of bridging and bonding social capital. <strong>Methods:</strong> This study used purposive sampling to investigate sexual assault centers in Canada with active Twitter accounts, resulting in the identification of 124 centers. The Twitter handles were collected, yielding 113 unique handles, and their corresponding Twitter IDs were obtained and validated. A total of 294,350 tweets were collected from these centers, covering >93.54% of their Twitter activity. Preprocessing was conducted to prepare the data, and descriptive analysis was used to determine the center demographics and age. Furthermore, geolocation mapping was performed to visualize the center locations. Social network analysis was used to explore the intricate relationships within the network of sexual assault center Twitter accounts, using various metrics to assess the network structure and connectivity dynamics. <strong>Results:</strong> The results highlight the substantial presence of sexual assault organizations on Twitter, particularly in provinces such as Ontario, British Columbia, and Quebec, underscoring the importance of tailored engagement strategies considering regional disparities. The analysis of Twitter account creation years shows a peak in 2012, followed by a decline in new account creations in subsequent years. The monthly tweet activity shows November as the most active month, whereas July had the lowest activity. The study also reveals variations in Twitter activity, account creation patterns, and social network dynamics, identifying influential <i>social queens</i> and marginalized entities within the network. <strong>Conclusions:</strong> This study presents a comprehensive landscape of the demographics and activities of sexual assault centers in Canada on Twitter. This study suggests that future research should explore the long-term consequences of social media use and examine stakeholder perceptions, providing valuable insights to improve communication practices within the nonprofit human services sector and further the missions of these organizations. 2024-03-27T10:30:24-04:00 https://www.jmir.org/2024/1/e49058/ Outpatient Video Visits During the COVID-19 Pandemic: Cross-Sectional Survey Study of Patients’ Experiences and Characteristics2024-03-27T10:15:04-04:00Stefanie C van den BoschDemi van DalenMarjan MeindersHarry van GoorStefaan BergéMartijn StommelSandra van Dulmen<strong>Background:</strong> During the first lockdown of the COVID-19 pandemic, an exponential increase in video consultations replacing in-person outpatient visits was observed in hospitals. Insight into patients’ experiences with this type of consultation is helpful for a broad, sustainable, and patient-centered implementation of video consultation. <strong>Objective:</strong> This study aims to examine patients’ experiences with video consultation during the COVID-19 pandemic and identify discriminative patient and consultation characteristics to determine when video consultation is most feasible. <strong>Methods:</strong> A cross-sectional survey study was conducted. Patients aged ≥18 years and scheduled for a video consultation at the outpatient clinic of a Dutch university medical center from August 2020 to December 2020 for all medical specialties were eligible. Patients’ experiences were explored through a study-specific survey using descriptive quantitative statistics. Open-ended questions were qualitatively analyzed and thematically categorized into appreciated aspects and aspects for improvement. Discriminative patient and consultation characteristics were identified using 3 distinctive survey items. Characteristics of patients who scored and those who did not score all 3 items positively were analyzed using binary logistic regression. <strong>Results:</strong> A total of 1054 patients were included in the analysis. Most patients (964/1054, 91.46%) were satisfied with their video consultation, with a mean overall grade of 8.6 (SD 1.3) of 10. In the qualitative analyses, 70.02% (738/1054) of the patients cited aspects they appreciated and 44.97% (474/1054) mentioned aspects for improvement during their consultation. Patients with better self-rated health reported a positive evaluation significantly more often (<i>P=</i>.001), which also held true for other medical specialties (vs surgical and nonsurgical specialties; <i>P</i><.001). <strong>Conclusions:</strong> Video consultation was perceived as highly satisfactory by patients during the COVID-19 pandemic, with the best experience reported by healthy participants and those undergoing their first consultation. Appreciated aspects are mainly at the individual professional level, organizational level, and innovation level itself. The aspects that were mentioned for improvement can be changed for the better. 2024-03-27T10:15:04-04:00 https://www.jmir.org/2024/1/e44574/ Digital Alcohol Interventions Could Be Part of the Societal Response to Harmful Consumption, but We Know Little About Their Long-Term Costs and Health Outcomes2024-03-27T10:00:04-04:00Katarina Ulfsdotter GunnarssonMartin HenrikssonMarcus BendtsenAlcohol consumption causes both physical and psychological harm and is a leading risk factor for noncommunicable diseases. Digital alcohol interventions have been found to support those looking for help by giving them tools for change. However, whether digital interventions can help tackle the long-term societal consequences of harmful alcohol consumption in a cost-effective manner has not been adequately evaluated. In this Viewpoint, we propose that studies of digital alcohol interventions rarely evaluate the consequences of wider dissemination of the intervention under study, and that when they do, they do not take advantage of modeling techniques that allow for appropriately studying consequences over a longer time horizon than the study period when the intervention is tested. We argue that to help decision-makers to prioritize resources for research and dissemination, it is important to model long-term costs and health outcomes. Further, this type of modeling gives important insights into the context in which interventions are studied and highlights where more research is required and where sufficient evidence is available. The viewpoint therefore invites the researcher not only to reflect on which interventions to study but also how to evaluate their long-term consequences.2024-03-27T10:00:04-04:00 https://www.jmir.org/2024/1/e45855/ Youth is Prized in Medicine, Old Age is Valued in Law: Analysis of Media Narratives Over 200 Years2024-03-26T10:30:04-04:00Reuben NgNicole Indran<strong>Background:</strong> This is the first study to explore how age has influenced depictions of doctors and lawyers in the media over the course of 210 years, from 1810 to 2019. The media represents a significant platform for examining age stereotypes and possesses tremendous power to shape public opinion. Insights could be used to improve depictions of older professionals in the media. <strong>Objective:</strong> This study aims to understand how age shapes the portrayals of doctors and lawyers. Specifically, it compares the difference in sentiments toward younger and older doctors as well as younger and older lawyers in the media over 210 years. <strong>Methods:</strong> Leveraging a 600-million-word corpus of American media publications spanning 210 years, we compiled top descriptors (N=478,452) of nouns related to youth × occupation (eg, younger doctor or physician) and old age × occupation (eg, older lawyer or attorney). These descriptors were selected using well-established criteria including co-occurrence frequency and context relevance, and were rated on a Likert scale from 1 (very negative) to 5 (very positive). Sentiment scores were generated for “doctor/physician,” “young(er) doctor/physician,” “old(er) doctor/physician,” “lawyer/attorney,” “young(er) lawyer/attorney,” and “old(er) lawyer/attorney.” The scores were calculated per decade for 21 decades from 1810 to 2019. Topic modeling was conducted on the descriptors of each occupation in both the 1800s and 1900s using latent Dirichlet allocation. <strong>Results:</strong> As hypothesized, the media placed a premium on youth in the medical profession, with portrayals of younger doctors becoming 10% more positive over 210 years, and those of older doctors becoming 1.4% more negative. Meanwhile, a premium was placed on old age in law. Positive portrayals of older lawyers increased by 22.6% over time, while those of younger lawyers experienced a 4.3% decrease. In the 1800s, narratives on younger doctors revolved around their participation in rural health care. In the 1900s, the focus shifted to their mastery of new medical technologies. There was no marked change in narratives surrounding older doctors from the 1800s to the 1900s, though less attention was paid to their skills in the 1900s. Narratives on younger lawyers in the 1800s referenced their limited experience. In the 1900s, there was more focus on courtroom affairs. In both the 1800s and 1900s, narratives on older lawyers emphasized their prestige, especially in the 1900s. <strong>Conclusions:</strong> Depending on the occupation, one’s age may either be seen as an asset or a liability. Efforts must be expended to ensure that older professionals are recognized for their wealth of knowledge and skills. Failing to capitalize on the merits of an older workforce could ultimately be a grave disservice not only to older adults but to society in general. 2024-03-26T10:30:04-04:00