Marilyn Rantz

Grey Literature in Meta-Analyses

BackgroundIn meta-analysis, researchers combine the results of individual studies to arrive at cumulative conclusions. Meta-analysts sometimes include “grey literature” in their evidential base, which includes unpublished studies and studies published outside widely available journals. Because grey literature is a source of data that might not employ peer review, critics have questioned the validity of its data and the results of meta-analyses that include it. ObjectiveTo examine evidence regarding whether grey literature should be included in meta-analyses and strategies to manage grey literature in quantitative synthesis. MethodsThis article reviews evidence on whether the results of studies published in peer-reviewed journals are representative of results from broader samplings of research on a topic as a rationale for inclusion of grey literature. Strategies to enhance access to grey literature are addressed. ResultsThe most consistent and robust difference between published and grey literature is that published research is more likely to contain results that are statistically significant. Effect size estimates of published research are about one-third larger than those of unpublished studies. Unfunded and small sample studies are less likely to be published. Yet, importantly, methodological rigor does not differ between published and grey literature. ConclusionsMeta-analyses that exclude grey literature likely (a) over-represent studies with statistically significant findings, (b) inflate effect size estimates, and (c) provide less precise effect size estimates than meta-analyses including grey literature. Meta-analyses should include grey literature to fully reflect the existing evidential base and should assess the impact of methodological variations through moderator analysis.

A smart home application to eldercare: Current status and lessons learned

To address an aging population, we have been investigating sensor networks for monitoring older adults in their homes. In this paper, we report ongoing work in which passive sensor networks have been installed in 17 apartments in an aging in place eldercare facility. The network under development includes simple motion sensors, video sensors, and a bed sensor that captures sleep restlessness and pulse and respiration levels. Data collection has been ongoing for over two years in some apartments. This longevity in sensor data collection is allowing us to study the data and develop algorithms for identifying alert conditions such as falls, as well as extracting typical daily activity patterns for an individual. The goal is to capture patterns representing physical and cognitive health conditions and then recognize when activity patterns begin to deviate from the norm. In doing so, we strive to provide early detection of potential problems which may lead to serious health events if left unattended. We describe the components of the network and show examples of logged sensor data with correlated references to health events. A summary is also included on the challenges encountered and the lessons learned as a result of our experiences in monitoring aging adults in their homes.

Linguistic summarization of video for fall detection using voxel person and fuzzy logic

In this paper, we present a method for recognizing human activity from linguistic summarizations of temporal fuzzy inference curves representing the states of a three-dimensional object called voxel person. A hierarchy of fuzzy logic is used, where the output from each level is summarized and fed into the next level. We present a two level model for fall detection. The first level infers the states of the person at each image. The second level operates on linguistic summarizations of voxel persons states and inference regarding activity is performed. The rules used for fall detection were designed under the supervision of nurses to ensure that they reflect the manner in which elders perform these activities. The proposed framework is extremely flexible. Rules can be modified, added, or removed, allowing for per-resident customization based on knowledge about their cognitive and physical ability.

Integrative Review of Physical Activity Intervention Research with Aging Adults

This paper reviews randomized, controlled trials (RCTs) that have attempted to increase physical activity behavior by aging adults. A systematic review was necessary because numerous studies target older adults, and previous reviews have addressed a limited range of primary studies. Computerized database, ancestry, and extensive search strategies by authors of research reported in English between 1960 and 2000 located diverse intervention trials. RCTs reporting endurance physical activity or exercise behavioral outcomes for at least five subjects were included. Integrative review methods were used to summarize extant research. Forty‐two studies were retrieved. Seventeen RCTs with 6,391 subjects were reviewed. A wide variety of intervention strategies were reported. The most common interventions were self‐monitoring, general health education, goal setting, supervised center‐based exercise, problem solving, feedback, reinforcement, and relapse prevention education. Few studies individually adapted motivational interventions, used mediated intervention delivery, or integrated multiple theoretical frameworks into the intervention. Links between individual intervention components and effectiveness were not clear. Common methodological weaknesses included small samples, untested outcome measures, and time‐limited longitudinal designs. Significant numbers of aging adults increased their physical activity in response to experimental interventions. The amount of increased activity rarely equaled accepted behavior standards to achieve positive health outcomes. Further work is essential to identify successful strategies to increase activity by larger numbers of elders and to accelerate the increase in activity by those who change activity behaviors. Sex and ethnic differences need further investigation. There is a vital need for rigorously designed studies to contribute to this science.

An acoustic fall detector system that uses sound height information to reduce the false alarm rate

More than one third of about 38 million adults 65 and older fall each year in the United States. To address the above problem we propose to develop an acoustic fall detection system (FADE) that will automatically signal a fall to the monitoring caregiver. As opposed to many existent fall detection systems that require the monitored person to wear devices such as accelerometers or gyroscopes at all times, our system is completely unobtrusive by not requiring any wearable devices. To reduce the false alarm rate we employ an array of acoustic sensors to obtain sound source height information. The sound is considered a false alarm if it comes from a source located at a height higher than 2 feet. We tested our system in a pilot study that consisted of a set of 23 falls performed by a stunt actor during six sessions of about 15 minutes each (1.3 hours in total). The actor was previously trained by our nursing collaborators to fall like an elderly person. The use of height information reduced the false alarm hourly rate from 32 to 5 at a 100% fall detection rate.

Nursing home care quality: a multidimensional theoretical model integrating the views of consumers and providers.

This exploratory study was undertaken to discover the defining dimensions of nursing home care quality from the viewpoint of consumers of nursing home care. Eleven focus groups were conducted in five Missouri communities. The seven dimensions of the consumer multidimensional model of nursing home care quality are: staff, care, family involvement, communication, environment, home, and cost. The views of consumers and families are compared with the results of a previous study of providers of nursing home services. An integrated, multidimensional theoretical model is presented for testing and evaluation. An instrument based on the model is being tested to observe and score the dimensions of nursing home care quality.

Modeling Human Activity From Voxel Person Using Fuzzy Logic

As part of an interdisciplinary collaboration on elder-care monitoring, a sensor suite for the home has been augmented with video cameras. Multiple cameras are used to view the same environment and the world is quantized into nonoverlapping volume elements (voxels). Through the use of silhouettes, a privacy protected image representation of the human acquired from multiple cameras, a 3-D representation of the human is built in real time, called voxel person. Features are extracted from voxel person and fuzzy logic is used to reason about the membership degree of a predetermined number of states at each frame. Fuzzy logic enables human activity, which is inherently fuzzy and case-based, to be reliably modeled. Membership values provide the foundation for rejecting unknown activities, something that nearly all current approaches are insufficient in doing. We discuss temporal fuzzy confidence curves for the common elderly abnormal activity of falling. The automated system is also compared to a ground truth acquired by a human. The proposed soft computing activity analysis framework is extremely flexible. Rules can be modified, added, or removed, allowing per-resident customization based on knowledge about their cognitive and functionality ability. To the best of our knowledge, this is a new application of fuzzy logic in a novel approach to modeling and monitoring human activity, in particular, the well-being of an elderly resident, from video.

Clinical Outcomes of Aging in Place

BackgroundPrograms such as Medicaid Home and Community-based Services (HCBS) have provided an alternative to institutionalization through community-based, long-term care services; however, there are limited studies on the clinical outcomes of participants in these programs as compared to nursing home (NH) residents. ObjectiveTo compare clinical outcomes of individuals in a community-based, long-term care program to individuals of similar case mix in institutional-based, long-term care. MethodsA program called Aging in Place (AIP) was developed by the Sinclair School of Nursing in cooperation with the state of Missouris HCBS program. The AIP intervention consisted of nurse coordination of the HCBS program and Medicare home health services. A total of 78 AIP participants were matched with 78 NH residents on admission period, activities of daily living (ADLs), cognitive status, and age. The Minimum Data Set (MDS) was collected on the AIP group at admission and every 6 months over a 30-month period. Cognition was measured by the MDS Cognitive Performance Scale (CPS), ADLs by the sum of 5 MDS ADL items, depression by the MDS-Depression Rating Scale, and incontinence by rating on 2 MDS items related to urinary continence. The Cochran–Mantel–Haenszel method was used to test the association between the AIP intervention and clinical outcomes. ResultsThe AIP group clinical outcomes were better at a statistically significant level (less than .05) for the following outcomes: (a) cognition at 6, 12, and 18 months (p = .00); (b) depression at 6 and 12 months (p = .00); (c) ADL at 6 (p = .02), 12 (p = .04), and 24 (p = .00) months; and (d) incontinence at 24 (p = .02) months. In all 4 outcome measures, the AIP group stabilized or improved outcome scores whereas the NH groups outcome scores deteriorated. DiscussionStudy results suggest that community-based care with nurse coordination enhances clinical outcomes of long-term care participants.

Aging in Place: A New Model for Long-Term Care

It is expected that at least 40 percent of the population over 75 will need extensive health care services late in their lives. The public has a negative view of nursing home placement that has, to some extent, been confirmed by research finding that the health of a frail older person deteriorates each time he or she is moved. The Aging in Place model of care for the elderly offers care coordination (case management) and health care services to older adults so they will not have to move from one level of care delivery to another as their health care needs increase. University Nurses Senior Care (UNSC) is the service entity of this project and provides as its core service care coordination with a variety of service options. These options include care packages or services at an hourly rate to meet individual client needs. The Aging in Place project will be evaluated by comparing project clients to residents of similar acuity in nursing homes and to similar clients receiving standard community support services. Data from this project will be important to consumers, researchers, providers, insurers, and policy makers.

International Survey of Nursing Home Research Priorities

This article reports the findings of a policy survey designed to establish research priorities to inform future research strategy and advance nursing home practice. The survey was administered in 2 rounds during 2013, and involved a combination of open questions and ranking exercises to move toward consensus on the research priorities. A key finding was the prioritization of research to underpin the care of people with cognitive impairment/dementia and of the management of the behavioral and psychological symptoms of dementia within the nursing home. Other important areas were end-of-life care, nutrition, polypharmacy, and developing new approaches to putting evidence-based practices into routine practice in nursing homes. It explores possible innovative educational approaches, reasons why best practices are difficult to implement, and challenges faced in developing high-quality nursing home research.