Using Apple’s Screen Time application to obtain reported actual iPhone and social media (SM) use, we examined the accuracy of retrospective estimates of usage, how inaccuracies bias associations between use and psychosocial well-being (depression, loneliness, and life satisfaction), and the degree to which inaccuracies were predicted by levels of well-being. Among a sample of 325 iPhone users, we found that (a) participants misestimated their weekly overall iPhone and SM use by 19.1 and 12.2 hours, respectively; (b) correlations between estimated use and well-being variables were consistently stronger than the correlations between reported actual use and well-being variables; and (c) the degree of inaccuracy in estimated use was associated with levels of participant well-being and amount of use. These findings suggest that retrospective estimates of digital technology use may be systematically biased by factors that are fundamental to the associations under investigation. We propose that retrospective estimates of digital technology use may be capturing the construct of perceived use rather than actual use, and discuss how the antecedents, correlates, and consequences of perceived use may be distinct from those of actual use. Implications of these findings are discussed in view of the ongoing debate surrounding the effects of digital technology use on well-being.

Background. Disparities in breast and cervical cancer screening by socioeconomic status persist in the United States. It has been suggested that social support may facilitate screening, especially among women of low socioeconomic status. However, at present, it is unclear whether social support enables mammogram and Pap test compliance. Purpose. This study examines the association between social support and compliance with mammogram and Pap test screening guidelines, and whether social support provides added value for women of low education. Method. Data were from a countywide 2009-2010 population-based survey, which included records of 2,588 women 40 years and older (mammogram) and 2,123 women 21 to 65 years old (Pap test). Compliance was determined using the guidelines in effect at the time of data collection. Results. Social support was significantly related to mammogram (adjusted odds ratio = 1.43; 95% confidence interval [1.16, 1.77]) and Pap test (adjusted odds ratio = 1.71; 95% confidence interval [1.27, 2.29]) compliance after controlling for age, race, having a regular health care provider, and insurance status. The interaction between social support and education had a significant effect on Pap test compliance only among women younger than 40; the effect was not significant for mammogram compliance. Conclusion. Social support is associated with breast and cervical cancer screening compliance. The association between education and cancer screening behavior may be moderated by social support; however, results hold only for Pap tests among younger women. Practitioners and researchers should focus on interventions that activate social support networks as they may help increase both breast and cervical cancer screening compliance among women with low educational attainment.

Paid leave, telework, and work attendance

Objectives. To characterize the conflict of sex and gender identity variables in the 2014 Behavioral Risk Factor Surveillance System (BRFSS) sample and examine how this may affect the administration of sex-related health behavior items to transgender participants. Methods. We conducted a secondary analysis of the 2014 BRFSS gender identity, sex, and sex-related health behavior variables. Twenty states administered the gender-identity variables (n = 154 062), and 691 respondents identified as transgender in the survey (0.4%). We examined conflict among sex, gender identity, and gender-related variables, and compared conflicting and nonconflicting groups across 4 sociodemographic characteristics. Results. Nearly one third of respondents (27.8%; n = 171) who identified as transgender received sex-specific items that conflicted with their natal sex, thereby reducing the already small subsample of valid responses. There were no significant differences between conflicting and nonconflicting groups on the basis of region, age, race/ethnicity, or type of interview. Conclusions. Public health surveys should ask respondents to self-identify their sex and gender identity. Interviewer assumptions of respondents’ sex may lead to erroneous collection of sex- and gender-based items, inhibit survey administration, and create problems in data quality.

Fatigue is a common complaint and shares many risk factors with falls, yet the independent contribution of fatigue on fall risk is unclear. This study’s primary aim was to assess the association between fatigue and prospective fall risk in 5642 men aged 64–100 enrolled in the Osteoporotic Fractures in Men Study (MrOS). The secondary aim was to examine the association between fatigue and recurrent fall risk. Fatigue was measured at baseline using the Medical Outcomes Study (short form) single-item question “During the past four weeks, how much of the time did you feel energetic?” Responses were then classified: higher fatigue = “none,” “a little,” or “some” of the time and lower fatigue = “a good bit,” “most,” or “all” of the time. We assessed falls using triannual questionnaires. Fall risk was examined prospectively over 3 years; recurrent falling was defined as at least 2 falls within the first year. Generalized estimating equations and multinomial logistic regression modeled prospective and recurrent fall risk as a function of baseline fatigue status, adjusted for demographics, medications, physical activity, and gait speed. Men with higher (26%) versus lower baseline fatigue were older (75.1 ± 6.2 vs 73.2 ± 5.7 years), 24% less active, and had worse physical function (gait speed = 1.09 ± 0.24 vs 1.24 ± 0.21 m/s), all p < .0001. Within 1 year, 25.4% (n = 1409) had fallen at least once, of which 47.4% (n = 668) were recurrent fallers. Men with higher versus lower fatigue had 25% increased fall risk (relative risk = 1.25, 95% CI: 1.14–1.36) over 3 years follow-up, but had 50% increased odds of recurrent falling (odds ratio = 1.50, 95% CI: 1.22–1.85) within the first year. Fatigue is an important risk factor of falling independent of established risk factors. Reductions in fatigue (ie, increased energy) may lessen the burden of falls in older men and provide a novel avenue for fall risk intervention.