The MRAAGILE is a device designed to monitor and reinforce medication consumption as well as promote a healthy daily regimen for those who choose to live independently. The device provides interactive reminder messages to inspire the user to follow directives. The purpose of this is to implement motion detection following a reminder to determine whether the user is responding. The device will receive instructions from the user manually on the device or by using a bluetooth wireless link to transmit the times for which medication is to be taken. After reminders are set, the mobile device will continue to function until the first reminder time is reached. A message will be played. If motion is detected, it will serve as an indicator that the message was acknowledged. If not, it will trigger an alarm to remind the user to complete the action. The alarm will deactivate once motion is detected. This device will be useful for increasing the independence for older adults who live in the community as well as assistive living environments.
To characterize physical activity and physical function by stage of change and age in older adults.One thousand two hundred thirty-four individuals completed The Yale physical activity survey (YPAS), stage of change for exercise, and the Up-and-Go physical function test.Most subjects were in the maintenance (50.4%) or precontemplation stages (21/0%). YPAS scores were higher and Upand-Go scores were lower as exercise stage increased. Physical activity and physical function scores were lower in older age groups.Higher stages were positively associated with physical activity and physical function. Age was a significant moderator variable affecting stage, physical activity, and physical function.
The purpose of this study was to identify the population prevalence across the stages of change (SoC) for regular physical activity and to establish the prevalence of people at risk. With support from the National Institutes of Health, the American Heart Association, and the Robert Wood Johnson Foundation, nine Behavior Change Consortium studies with a common physical activity SoC measure agreed to collaborate and share data. The distribution pattern identified in these predominantly reactively recruited studies was Precontemplation (PC) = 5% (± 10), Contemplation (C) = 10% (± 10), Preparation (P) = 40% (± 10), Action = 10% (± 10), and Maintenance = 35% (± 10). With reactively recruited studies, it can be anticipated that there will be a higher percentage of the sample that is ready to change and a greater percentage of currently active people compared to random representative samples. The at-risk stage distribution (i.e., those not at criteria or PC, C, and P) was approximately 10% PC, 20% C, and 70% P in specific samples and approximately 20% PC, 10% C, and 70% P in the clinical samples. Knowing SoC heuristics can inform public health practitioners and policymakers about the population's motivation for physical activity, help track changes over time, and assist in the allocation of resources.
The number of emergency department (ED) visits in the United States reached 119.2 million visits in 2007. 1 The largest percentage of these visits was for people with injury-related diagnoses (42.4 million visits), with falls accounting for 76% of these among adults age 65 and older. 2 Hospital discharge data for injury-related admissions reflects those patients visiting the ED whose injuries were so severe that they warranted admission. Beginning January 1, 2005, hospitals in Rhode Island have reported patient-level data on visits to EDs to the Rhode Island Department of Health. This report presents summary information for 2005 2009 on hospital ED visits and hospital in-patient discharges in Rhode Island for injuries and poisonings, together referred to as “injuries,” with emphasis on falls.
Owing to the recent success of the Transtheoretical Model of behavior change and the possible relationships between health behaviors, this study investigated the stage distribution of 10 healthy behaviors (seatbelt use, avoidance of high fat food, eating a high-fiber diet, attempting to lose weight, exercising regularly, avoiding sun exposure, sunscreen use, attempting to reduce stress, stopping smoking, and conducting cancer self-exams) and their interrelationships in a representative sample of health maintenance organization (HMO) members. The majority of older adults were found to be in either precontemplation or maintenance, illustrating the need to target interventions to precontemplation. Most older individuals were in precontemplation for losing weight and/ or sunscreen use and exercise, making these behaviors a priority for intervention research. Possible gateway behaviors to general health could be identified; however, these results are preliminary and require longitudinal follow-up.
IntroductionDelirium, defined as acute change in consciousness that is accompanied by inattention and either a change in cognition or perceptual disturbance (Delirium Assessment and Management, 2012, p. 79) has been acknowledged internationally to be a significant health problem for older adults. Manifesting its symptoms alone or presenting concurrently with a host of conditions such as heart disease (e.g., Lahariya, Grover, Bagger, & Sharma 2014), cancer (e.g., Boettger, Jenewein, & Breitbart, 2014), stroke (e.g., Miu & Yeung, 2013), dementia (e.g., Morandi et al., 2012), depression (e.g., Givens, Jones, & Inouye, 2009), and hip fractures (e.g., Krogseth, Wyller, Engedal, & Juliebo, 2014), delirium has been studied in heterogeneous settings across the health care spectrum, including emergency departments (e.g., Kennedy et al., 2014), intensive care units (e.g., Kamdar et al., 2015), postoperative wards (e.g., Gani et al., 2012), post-acute (e.g., Kiely et al., 2009) and long-term care facilities (e.g., McCusker et al., 2011), and palliative care settings (e.g., Leonard et al., 2014). Although proven prevention strategies and treatment modalities exist, the bulk of previous investigations have established that delirium remains highly prevalent (56%-88%) in the elderly and those with serious or advanced medical illnesses . . . [leading ]to unnecessary medical interventions, increased hospital admissions, prolonged hospitalizations, increased need for higher levels of care, functional decline, increased mortality, decreased life expectancy, and increased health care utilization and costs (Irwin, Pirrello, Hirst, Buckholz, & Ferris, 2013, p. 423).Given the pervasiveness of delirium in geriatric patients across the health care system, its adverse outcomes, and the potential for effective clinical management, much attention has been devoted to the development of accurate clinical assessment of the condition. A number of patient interview instruments have been verified as reliable in assessing patients (Chun & Leipzig, 2011), although chart review (Saczynski et al., 2014) and family caregiver ratings (Carbone & Gugliucci, 2015; Steis et al., 2012) have shown promise as well. In a review of the Medline database over twenty years to identify the delirium scales in use, Martins, Simoes, and Fernandes (2011) concluded that the most commonly cited instrument is the Confusion Assessment Method (CAM). The CAM algorithm (Inouye et al., 1990) centers on four features found to reliably distinguish between delirium and other types of abnormal mental status (acute onset and fluctuating course, inattention, disorganized thinking, and altered level of consciousness). The CAM was originally designed to assist nonpsychiatric health care providers but has been adapted for the special populations of emergency departments (Phillips, 2013), the intensive care unit (Marcantonio, 2011), and long-term care settings (Saliba et al., 2012). It has been designated an evidencebased clinical tool (Purvis & Brenny-Fitzpatrick, 2010) capable of predicting patient outcomes (Tomasi et al., 2012).Despite the recognized need for delirium care and the availability of validated assessment methods-or arguably because of the overwhelming variety of tools from which practitioners must select (Maclullich et al., 2013), under-detection of delirium is widely reported and screening for it (via the CAM or other measures) has not been universally embedded into routine formal cognitive assessment in general hospitals (Martins & Fernandes, 2012; Stout & Gaveria, 2011). A statewide study of the presence of geriatric inpatient protocols and guidelines in general acute care hospitals confirmed that guidelines for risk factors for delirium before surgery and routine screening for delirium after surgery were the least frequently reported (roughly 20%) compared to other domains of care (Neuman, Speck, Karlawish, Schwartz, & Shea, 2010). …
Abstract A model was developed, using the nursing process, that has been incorporated into a health planning project for a community health nursing course. It is used to assist students to view larger aggregates as the client and to gain knowledge and experience in health planning. Examples of completed projects are presented. Evaluation of the projects by students, faculty, and aggregates supports the use of the model as a framework for nursing intervention within a community for the improvement of client health.
The AAGILE is a device designed to reinforce a healthy daily regimen for those who choose to live independently, especially those with diminishing cognitive or physical functions. The device does so by setting goals, providing personalized interactive reminder messages, and monitoring daily activity in 5-minute increments. The purpose of this study is to minimize the overall device size and footprint of the motherboard, further develop the functions of the AAGILE and test the overall health benefits with respect to different physical and cognitive limitations and in comparison to different commercially available monitoring devices.
Meaning in life has been intimately linked to health, but it has not been explored in an elderly population. The factors that elderly people perceive as being meaningful must be identified, as well as the extent to which they experience fulfillment of meaning in their lives. The majority of study participants indicated that relationships give meaning to their lives; however, nurses must individually assess clients regarding what is most meaningful to them. Clients without meaning or low levels of meaning need to be identified. As nurses become more aware of what is meaningful to older people, they can plan and carry out interventions based on interaction to support or improve areas meaningful to the older person.
