Eating attitudes in a group of 11-year-old urban South African girls

No Abstract. South African Journal of Clinical Nutrition Vol. 19(2) 2006: 80-8

A Smartwatch Step-Counting App for Older Adults: Development and Evaluation Study

Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have been shown to be inaccurate in clinical settings. Step-counting algorithms have been developed for smartwatches, but only using data from younger adults and, often, were only validated in controlled laboratory settings. Objective: We sought to develop and validate a smartwatch step-counting app for older adults and evaluate the algorithm in free-living settings over a long period of time. Methods: We developed and evaluated a step-counting app for older adults on an open-source wrist-worn device (Amulet). The app includes algorithms to infer the level of physical activity and to count steps. We validated the step-counting algorithm in the lab (counting steps from a video recording, n=20) and in free-living conditions—one 2-day field study (n=6) and two 12-week field studies (using the Fitbit as ground truth, n=16). During app system development, we evaluated 4 walking patterns: normal, fast, up and down a staircase, and intermittent speed. For the field studies, we evaluated 5 different cut-off values for the algorithm, using correlation and error rate as the evaluation metrics. Results: The step-counting algorithm performed well. In the lab study, for normal walking (R2=0.5), there was a stronger correlation between the Amulet steps and the video-validated steps; for all activities, the Amulet’s count was on average 3.2 (2.1%) steps lower (SD 25.9) than the video-validated count. For the 2-day field study, the best parameter settings led to an association between Amulet and Fitbit (R2=0.989) and 3.1% (SD 25.1) steps lower than Fitbit, respectively. For the 12-week field study, the best parameter setting led to an R2 value of 0.669. Conclusions: Our findings demonstrate the importance of an iterative process in algorithm development before field-based deployment. This work highlights various challenges and insights involved in developing and validating monitoring systems in real-world settings. Nonetheless, our step-counting app for older adults had good performance relative to the ground truth (a commercial Fitbit step counter). Our app could potentially be used to help improve physical activity among older adults

Waldo Lake Research in 2003

This report summarizes the first year of an effort to develop a more complete understanding of the physical, chemical, and biological characteristics that drive the ecological processes of Waldo Lake. Modern limnology recognizes the importance of watershed processes as well as in- lake processes in lake ecosystem functioning. Therefore, the approach included consideration of watershed hydrology and forcing functions that determine hydrodynamics of the system as well physical and chemical factors that may be important in regulating primary production in the lake. Data collected since 1998 was summarized and bathymetry of the basin was mapped using state-of-the-art digital depth sounding and GPS technology. A hypothesis that UV light may play an important role in regulating phytoplankton efficiency was examined in an effort to move toward more hypothesis-driven investigations to elucidate the factors controlling productivity. A Quality Assurance/Quality Control Plan was developed to guide data collection for long-term monitoring of the lake. Lastly, initial steps were made in the development of a model of lake hydrodynamics and primary production to aid in integration of the physical, chemical, and biological data that has been collected on the lake

IgG Responses to Tissue-Associated Antigens as Biomarkers of Immunological Treatment Efficacy

We previously demonstrated that IgG responses to a panel of 126 prostate tissue-associated antigens are common in patients with prostate cancer. In the current report we questioned whether changes in IgG responses to this panel might be used as a measure of immune response, and potentially antigen spread, following prostate cancer-directed immune-active therapies. Sera were obtained from prostate cancer patients prior to and three months following treatment with androgen deprivation therapy (n = 34), a poxviral vaccine (n = 31), and a DNA vaccine (n = 21). Changes in IgG responses to individual antigens were identified by phage immunoblot. Patterns of IgG recognition following three months of treatment were evaluated using a machine-learned Bayesian Belief Network (ML-BBN). We found that different antigens were recognized following androgen deprivation compared with vaccine therapies. While the number of clinical responders was low in the vaccine-treated populations, we demonstrate that ML-BBN can be used to develop potentially predictive models

Feasibility of using the Automated Self-Administered 24-hour (ASA-24) dietary assessment tool in older adults

Background Dietary patterns can impact the trajectories of healthy aging. However, dietary assessment tools can be challenging to use. With the increased use of technology in older adults, we aimed to evaluate the feasibility of older adults completing the online, Automated Self-Administered 24-h (ASA-24) dietary assessment tool. Methods We conducted a randomized, two-period, two-sequence, crossover design of twenty community-dwelling older adults (≥65 years) comparing their preference for completing the ASA-24 alone versus with a research assistant (RA). Participants were recruited via ResearchMatch.com and randomly allocated 1:1 to a sequence of completing both an ASA-24 alone or with an RA, separated by one week. After each session, participants completed an online 11-item feasibility survey (Likert-scale range of 1–5, strongly disagree to strongly agree). Mean and standard deviations were reported for each question. Results Mean age was 69 ± 3.5 years (90% females), with no differences were observed for sex, age, race, ethnicity, education, or income. Neither group felt a need for RA assistance (p = 0.34). However, both groups felt the system was easier to follow with the help of an RA (RA: 4.4 ± 1.3, vs. SA 4.6 ± 0.5, p = 0.65), particularly when they completed the ASA-24 alone, first (p = 0.04). When conducting the ASA-24 alone, there was less confidence the system could be learned quickly (SA 4.5 ± 0.5→3.4 ± 1.0 vs RA 3.4 ± 1.0→3.4 ± 0.7, p = 0.001). The ASA-24 was thought to be less cumbersome after repeated exposure in those concluding with the RA. Conclusion While older adults were able to complete the ASA-24 independently, the use of an RA led to improved confidence. Enhancing the sample diversity in a larger number of participants could provide helpful data to improve the science of dietary assessment

Biochar has positive but distinct impacts on root, shoot, and fruit production in beans, tomatoes, and willows

Positive relationships have been documented between the amount of biochar added to soils and various aspects of plant growth and fertility such as root, shoot, and fruit production. However, these effects depend on biochar source materials, soil characteristics and species of plant examined. This makes it impossible to systematically compare and generalize findings across previous studies that have used different soils and biochar. We conducted a novel investigation to assess the effects of a single source of biochar (hazelnut wood), in a constructed organic soil, on the different plant tissues in three functionally distinct species: tomatoes (Solanum lycopersicon), green beans (Phaseolus vulgaris), and willow (Salix sp.). Five levels of biochar soil amendment were assessed: 0% (control), 3, 9, and 26% by dry weight. We found a highly significant positive relationship between biochar concentration and total plant biomass (roots + shoots + fruits) in all species, with no significant difference in total biomass response among species. Fruit production increased with increased biochar in both beans and tomatoes. However, tomatoes exhibited significant differences in response among plant tissues; fruit production and shoot biomass increased significantly with biochar, but root tissue did not. Bean germination success increased significantly with biochar concentration. Date of first flowering was earlier with increasing soil biochar in beans but not in tomatoes. Control over both sources of biochar and soil composition in this experiment enables us to conclude that biochar addition can have different impacts on different plants and, in some cases, species-specific impacts on different plant tissues and other measures of fertility. Our results are contrary to prior research that found inhibiting effects of biochar at levels comparable to our 26% treatment. Biochar impacts on soil properties such as CEC and percent base cation saturation do not explain our findings, leading us to conclude that microbial interaction with biochar is an important factor that may explain the positive impacts of soil biochar on plant fertility observed. Further research that repeats this experiment in other soil types, with other biochar sources, and with other plant species is necessary to determine the generalizability of these important findings

Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study

Background: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process. Objective: This study aims to develop a mobile app for a novel device through a user-centered design process with both older adults and clinicians while exploring whether data collected through this process can be used in NLP and sentiment analysis. Methods: Through a user-centered design process, we conducted semistructured interviews during the development of a geriatric-friendly Bluetooth-connected resistance exercise band app. We interviewed patients and clinicians at weeks 0, 5, and 10 of the app development. Each semistructured interview consisted of heuristic evaluations, cognitive walkthroughs, and observations. We used the Bing sentiment library for a sentiment analysis of interview transcripts and then applied NLP-based latent Dirichlet allocation (LDA) topic modeling to identify differences and similarities in patient and clinician participant interviews. Sentiment was defined as the sum of positive and negative words (each word with a +1 or −1 value). To assess utility, we used quantitative assessment questionnaires—System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE). Finally, we used multivariate linear models—adjusting for age, sex, subject group (clinician vs patient), and development—to explore the association between sentiment analysis and SUS and USE outcomes. Results: The mean age of the 22 participants was 68 (SD 14) years, and 17 (77%) were female. The overall mean SUS and USE scores were 66.4 (SD 13.6) and 41.3 (SD 15.2), respectively. Both patients and clinicians provided valuable insights into the needs of older adults when designing and building an app. The mean positive-negative sentiment per sentence was 0.19 (SD 0.21) and 0.47 (SD 0.21) for patient and clinician interviews, respectively. We found a positive association with positive sentiment in an interview and SUS score (ß=1.38; 95% CI 0.37 to 2.39; P=.01). There was no significant association between sentiment and the USE score. The LDA analysis found no overlap between patients and clinicians in the 8 identified topics. Conclusions: Involving patients and clinicians allowed us to design and build an app that is user friendly for older adults while supporting compliance. This is the first analysis using NLP and usability questionnaires in the quantification of user-centered design of technology for older adults