The stanford healthy neighborhood discovery tool: a computerized tool to assess active living environments.
American journal of preventive medicine
2013; 44 (4): e41-7
Harnessing Different Motivational Frames via Mobile Phones to Promote Daily Physical Activity and Reduce Sedentary Behavior in Aging Adults.
2013; 8 (4)
The built environment can influence physical activity, particularly among older populations with impaired mobility. Existing tools to assess environmental features associated with walkability are often cumbersome, require extensive training, and are not readily available for use by community residents.This project aimed to develop and evaluate the utility of a computerized, tablet-based participatory tool designed to engage older residents in identifying neighborhood elements that affect active living opportunities.Following formative testing, the tool was used by older adults (aged ?65 years, in 2011) to record common walking routes (tracked using built-in GPS) and geocoded audio narratives and photographs of the local neighborhood environment. Residents (N=27; 73% women; 77% with some college education; 42% used assistive devices) from three low-income communal senior housing sites used the tool while navigating their usual walking route in their neighborhood. Data were analyzed in 2012.Elements (from 464 audio narratives and photographs) identified as affecting active living were commensurate with the existing literature (e.g., sidewalk features, aesthetics, parks/playgrounds, crosswalks). However, within each housing site, the profile of environmental elements identified was distinct, reflecting the importance of granular-level information collected by the tool. Additionally, consensus among residents was reached regarding which elements affected active living opportunities.This tool serves to complement other assessments and assist decision makers in consensus-building processes for environmental change.
View details for DOI 10.1016/j.amepre.2012.11.028
View details for PubMedID 23498112
A Comparison of Acuity and Treatment Measures of Inmate and Noninmate Hospital Patients With a Diagnosis of Either Heart Disease or Chest Pain
JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION
2011; 103 (2): 109-115
Mobile devices are a promising channel for delivering just-in-time guidance and support for improving key daily health behaviors. Despite an explosion of mobile phone applications aimed at physical activity and other health behaviors, few have been based on theoretically derived constructs and empirical evidence. Eighty adults ages 45 years and older who were insufficiently physically active, engaged in prolonged daily sitting, and were new to smartphone technology, participated in iterative design development and feasibility testing of three daily activity smartphone applications based on motivational frames drawn from behavioral science theory and evidence. An "analytically" framed custom application focused on personalized goal setting, self-monitoring, and active problem solving around barriers to behavior change. A "socially" framed custom application focused on social comparisons, norms, and support. An "affectively" framed custom application focused on operant conditioning principles of reinforcement scheduling and emotional transference to an avatar, whose movements and behaviors reflected the physical activity and sedentary levels of the user. To explore the applications' initial efficacy in changing regular physical activity and leisure-time sitting, behavioral changes were assessed across eight weeks in 68 participants using the CHAMPS physical activity questionnaire and the Australian sedentary behavior questionnaire. User acceptability of and satisfaction with the applications was explored via a post-intervention user survey. The results indicated that the three applications were sufficiently robust to significantly improve regular moderate-to-vigorous intensity physical activity and decrease leisure-time sitting during the 8-week behavioral adoption period. Acceptability of the applications was confirmed in the post-intervention surveys for this sample of midlife and older adults new to smartphone technology. Preliminary data exploring sustained use of the applications across a longer time period yielded promising results. The results support further systematic investigation of the efficacy of the applications for changing these key health-promoting behaviors.
View details for DOI 10.1371/journal.pone.0062613
View details for PubMedID 23638127
This paper used the Healthcare Cost and Utilization Project National Inpatient Survey for the period 1998-2004 to examine whether California male inmate hospital patients with a primary diagnosis of heart disease or chest pain receive poorer quality of care (measures = number and type of procedures and time from admission to first procedure) or are sicker (measures = length of stay, risk of mortality, severity of illness, and number of diagnoses) compared to noninmate patients.Differences between inmates and noninmates were examined using a t test for continuous variables and a chi2 test for categorical variables. Multiple linear regression, logistic regression, and ordered logistic regression were used to investigate relationships between the outcome variables and inmate/noninmate status, controlling for age, race, expected payer, hospital, and total charges.Being an inmate was not statistically significantly associated with acuity or quality of care for patients with chest pain. For patients with heart disease, being an inmate was statistically significantly associated with a decrease in time to first procedure of 0.464 days (standard error = 0.189, p = .015) and an increase in length of stay of 0.81 days (standard error = 0.256, p = .002).The provision of health care to prison inmates is required by law, paid for by taxpayers, and increasing as the inmate population increases. The findings that, on average, inmate patients with heart disease stay in the hospital longer and receive treatment sooner compared to noninmate patients do not indicate that inmates receive poorer quality of care compared to noninmates.
View details for Web of Science ID 000287910000003
View details for PubMedID 21443062