Personal Health Data Tracking by Blind and Low-Vision People: Survey Study.

BACKGROUND: Personal health technologies, including wearable tracking devices and mobile apps, have great potential to equip the general population with the ability to monitor and manage their health. However, being designed for sighted people, much of their functionality is largely inaccessible to the blind and low-vision (BLV) population, threatening the equitable access to personal health data (PHD) and health care services. OBJECTIVE: This study aims to understand why and how BLV people collect and use their PHD and the obstacles they face in doing so. Such knowledge can inform accessibility researchers and technology companies of the unique self-tracking needs and accessibility challenges that BLV people experience. METHODS: We conducted a web-based and phone survey with 156 BLV people. We reported on quantitative and qualitative findings regarding their PHD tracking practices, needs, accessibility barriers, and work-arounds. RESULTS: BLV respondents had strong desires and needs to track PHD, and many of them were already tracking their data despite many hurdles. Popular tracking items (ie, exercise, weight, sleep, and food) and the reasons for tracking were similar to those of sighted people. BLV people, however, face many accessibility challenges throughout all phases of self-tracking, from identifying tracking tools to reviewing data. The main barriers our respondents experienced included suboptimal tracking experiences and insufficient benefits against the extended burden for BLV people. CONCLUSIONS: We reported the findings that contribute to an in-depth understanding of BLV people's motivations for PHD tracking, tracking practices, challenges, and work-arounds. Our findings suggest that various accessibility challenges hinder BLV individuals from effectively gaining the benefits of self-tracking technologies. On the basis of the findings, we discussed design opportunities and research areas to focus on making PHD tracking technologies accessible for all, including BLV people.

Exposure data for cosmetic products: facial cleanser, hair conditioner, and eye shadow.

Reliable exposure information for cosmetic and other personal care products and ingredients is needed in order to conduct safety assessments. Essential information includes both the amount of product applied, and the frequency of use. To obtain current data, a study to assess consumer use practices was undertaken. Three widely used types of cosmetic products - facial cleanser, hair conditioner, and eye shadow - were included in the study. Three hundred and sixty women, ages 18-69 years, who regularly use the products of interest, were recruited nationwide within the US. Subjects were provided with a new container of the brand of product they normally use and kept diaries and recorded detailed daily usage information over a two week period. Products were weighed at the start and completion of the study in order to determine the total amount of product used. Statistical analyses of the data were conducted to derive summary distributions of use patterns. The mean and median usage per application, respectively, for the three product types were: facial cleanser, 2.57 g and 2.11 g; hair conditioner, 13.13 g and 10.21 g; and eye shadow, 0.03 g and 0.009 g. The mean and median usage per day for the three product types was: facial cleanser, 4.06 g and 3.25 g; hair conditioner, 13.77 g and 10.62 g; and eye shadow, 0.04 g and 0.010 g. The mean number of applications per day for facial cleanser, hair conditioner, and eye shadow was 1.6, 1.1, and 1.2, respectively. This study provides an estimate of current exposure information for commonly used products which will be useful for risk assessment purposes.

Life change and instrumental support as predictors of illness in mothers of 6-month-olds.

The extent to which life change after birth of a baby and instrumental support of parenting predict the occurrence of illness in mothers of 6-month-olds was studied. Mothers (N = 155) were selected from an urban clinic and from the birth records of a suburban hospital. All data were collected with questionnaires and interviews in mothers' homes when infants were 6 months old. Age, race, socioeconomic status, and prior illness were used as control variables in the analyses. Life change and intensity of support were positively related, and size of the support network was negatively related to illness. There was no evidence for the buffering effect of support. Findings confirmed that life change helps predict postpartal illness, and revealed that characteristics of instrumental support differ in their importance as predictors.