Each round of the study involved community-dwelling older adults who self-reported a cancer diagnosis, whether recent or past. The study sample size per round fluctuated from 1996 (2015) to 1131 (2021). pdgf receptor Digital health technology engagement, within the preceding month, involved online activities such as ordering or refilling prescriptions, communicating with medical practitioners, handling Medicare or other insurance matters, and obtaining health information. The influence of sociodemographics, clinical factors (self-evaluated health, existing conditions, challenges in daily activities, dementia, anxiety, and depression), and physical performance (Short Physical Performance Battery and grip strength) on digital health technology usage was assessed via design-based logistic regression analysis. All statistical analyses considered the intricate nature of the sample design.A significant increase in the adoption of digital health technologies was observed, escalating from 36% usage in 2015 to 45% in 2019. Amidst the global COVID-19 pandemic, the period spanning from 2020 to 2021 witnessed a consistent percentage range of 51% to 52%. In 2015, the predominant use of digital health technologies among older cancer survivors was for health information retrieval (28%), followed by interactions with clinicians (19%), prescription filling (14%), and insurance management (11%). A correlation existed between increased digital health technology use and attributes such as younger age, White ethnicity, higher education levels, higher income, more comorbidities (excluding dementia), and quicker gait speed.The utilization of digital health technologies by older adults battling cancer has risen steadily, especially during the COVID-19 pandemic. Older cancer survivors, unfortunately, show persistent socioeconomic and racial inequities. Digital health engagement patterns in seniors with cancer might exhibit specific characteristics. Their use might be influenced positively by their multiple health issues (i.e., a multitude of healthcare requirements) but negatively by their frailty.The utilization of digital health technologies by older adults battling cancer has experienced a gradual rise, notably during the COVID-19 pandemic. The unfortunate reality is that socioeconomic and racial inequities continue to affect older cancer survivors. In addition, older adults who have cancer may show special patterns when interacting with digital health tools; for instance, their increased use could be driven by the intricacy of their health conditions (e.g., their broad array of health care needs) and simultaneously decreased by their frailty.Despite the abundance of scholarly articles and pathway models detailing quality improvement (QI), evidence-based practice (EBP), research, and innovation, a clear methodology for projects remains elusive. A practical, step-by-step process is indispensable to assist with navigating projects.A model for decision-making pathways, its development and assessment, will be detailed.The INQUIRE Model, developed through an iterative process, was subsequently assessed using feedback from 23 attendees at national conferences. The evaluation protocol featured four Likert-scale questions, allowing for a response scale from 1 (strongly disagree) to 7 (strongly agree).The model guides the project planning process, starting with an identified trigger (a problem, opportunity, or challenge), to determine the suitable project method which conforms to the scope and availability of a solution. Project method identification saw a 14% improvement, solution scanning an 8% increase, missed steps a 36% decrease, and team building a 10% boost, as determined by model evaluation.The research indicates that INQUIRE may strengthen the procedures used in project planning and help select suitable methods, including quality improvement, evidence-based practice, research, and innovative approaches. Model incorporation's potential benefit for organizations can be determined by evaluating the current state of their project planning procedures.INQUIRE, according to the findings, can augment project planning and the selection of approaches, including quality improvement (QI), evidence-based practice (EBP), research, and innovation strategies. Identifying the potential advantages of model incorporation requires organizations to evaluate the current state of their project planning.The use of robots in rehabilitation programs has seen substantial growth in the last two decades. The interdisciplinary nature of rehabilitation robot research greatly complicates the quest for a comprehensive understanding of this multifaceted field.This bibliometric study examined the characteristics of research on rehabilitation robots, along with emerging trends in the field over the past two decades.July 28, 2022, marked the retrieval date of rehabilitation robot reports, taken from the Web of Science Core Collection, published between January 1, 2001, and December 31, 2020. In order to uphold the high validity of our research on the evolution of this body of work over time, only article and meeting documents were used, while review documents were not included. Our co-occurrence and co-citation analysis, using CiteSpace as our tool, served to depict the characteristics and emergent trends within this specific area of research. Using the metrics of betweenness centrality and burst strength, landmark publications were selected.Our process of data collection, purification, and removal of redundant entries resulted in 9287 publications and 110619 citations, focusing on rehabilitation robots, published between 2001 and 2020. The results of the Mann-Kendall test highlight a noteworthy correlation (P<.001; S) in the counts of both publications.Sample size (S = 1750) and citations (P < .001) displayed a profound connection.The adoption of rehabilitation robots demonstrated a consistent increase each year, beginning in 1880. Co-occurrence analysis generated 120 categories relevant to rehabilitation robot research; these categories were used to define the research relationships. Through co-citation analysis, 169 distinct clusters of co-cited publications were discovered, depicting this research area's characteristics and the trends arising within it. Of significant interest in rehabilitative recovery for both upper and lower limbs is soft robotic technology, exhibiting a burst strength of 7907. In current research, task-oriented upper-limb training, strategies for controlling robot-assisted lower limb rehabilitation, and the power output of exoskeleton robots were highly regarded topics.Research into rehabilitation robots, particularly its characteristics and evolving trends over the past two decades, is comprehensively explored in our work, leading to a profound understanding of the field.Our work delves into the realm of rehabilitation robot research, encompassing its properties and the groundbreaking advancements witnessed over the past two decades, ultimately affording a thorough perspective on this area of study.Adolescents and young adults identifying as sexual and gender minorities (SGMs) in the Southern United States are at an increased risk of contracting HIV. Effective biomedical prevention strategies, including pre-exposure prophylaxis (PrEP), are readily available; however, their accessibility and adoption among SGM AYAs remain inadequate. In light of the situation, the Louisiana Department of Health established the LA TelePrEP Program, strategically leveraging telemedicine to connect residents of Louisiana to PrEP. Enrollment in the program is facilitated by a virtual TelePrEP Navigator, which addresses questions, schedules appointments, coordinates lab tests, and manages medication delivery for users. To encourage broader SGM AYA engagement in the TelePrEP program, the program, in conjunction with researchers, developed a chatbot that would improve access and support navigation within the program. Chatbots' capabilities to complete many tasks that reduce employee workloads are evident in both health care and public health settings, though their integration into HIV prevention remains relatively new.Within this paper, we articulate the iterative and community-involved method used to build an SMS chatbot to aid in SGM AYA navigation and to distribute PrEP information.The two phases that made up our process were conceptualization and development. During the conceptualization stage, key elements of navigator duties, programmatic workflows, and user interfaces for chatbot development (e.g., scheduling appointments and responding to inquiries) were determined. In addition, we selected a commercially available chatbot platform suitable for carrying out these functions, which could be programmed with minimal coding proficiency. As part of the developmental phase, we sought input from Department of Health staff and SGM AYAs within our professional and personal networks. To gauge the efficacy of each chatbot iteration, five experimental rounds were conducted with varying participant groups. After every iteration of the testing procedure, a meeting of the research team took place to discuss user feedback, provide direction to the programmer on making necessary adjustments, and re-assess the functionality of the chatbot.Our community-engaged and highly collaborative approach yielded the successful creation of a rule-based chatbot with artificial intelligence capabilities. Important knowledge was obtained that has the potential to greatly accelerate future chatbot development projects in HIV prevention. The PrEPBot's achievement stemmed from the resolution of user experience hurdles, which included problematic practices like posing unnecessary queries, offering prompt answers, and misinterpreting user inputs.With the help of readily available commercial tools, HIV prevention researchers can feasibly and effectively build a rule-based chatbot. The iterative process of obtaining feedback from researchers, program staff, and distinct subgroups of SGM AYAs proved vital for the successful creation of the chatbot. Should the pilot trial demonstrate that the chatbot is both practical and acceptable to SGM AYAs, future HIV researchers and practitioners could incorporate chatbots into their projects.