The authors analyze bias avoidance behaviors, whereby employees respond to biases against caregiving in the workplace by strategically minimizing or hiding family commitments. They divide bias avoidance behaviors into productive types that improve work performance and unproductive types that are inefficient. Original survey data from 4,188 chemistry and English faculty in 507 U.S. colleges and universities suggest both types of bias avoidance are relatively common and women more often report both types of behavior. Regression analyses show few disciplinary differences, find supportive supervisors associated with reductions in reports of bias avoidance, suggest low levels of bias avoidance for women are linked to institutional gender equity, and support the possibility that there are subjective components to bias avoidance behaviors.

Data from two studies assessed the effects of nonstandard work schedules on perceived family well-being and daily stressors. Study 1, using a sample of employed, married adults aged 25 – 74 (n = 1,166) from the National Survey of Midlife in the United States, showed that night work was associated with perceptions of greater marital instability, negative family-work, and work-family spillover than weekend or daytime work. In Study 2, with a subsample of adults (n = 458) who participated in the National Study of Daily Experiences, weekend workers reported more daily work stressors than weekday workers. Several sociodemographic variables were tested as moderators. Both studies demonstrated that nonstandard work schedules place a strain on working, married adults at the global and daily level.

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Work–family conflict, Fertility intentions, Dual-earner couples,

Abstract:We introduce family researchers to the Occupational Information Network, or O*Net, an electronic database on the work characteristics of over 950 occupations. The paper here is a practical primer that covers data collection, selecting occupational characteristics, coding occupations, scale creation, and construct validity, with empirical illustrations from the Family Life Project, a study of almost 1,300 families with infants born in 6 lowincome, nonmetro counties in North Carolina and Pennsylvania. We factor analyzed parents' occupations on 35 O*Net characteristics and identified 5 factors: occupational self-direction, physical hazards, physical activity, care work, and automation/repetition, variables that supplement data collected from parents directly. Applied researchers can use the O*Net to expand their knowledge of participants' work circumstances with objective data.

for valuable advice along the way. Many of the arguments below were developed jointly with Lotte Bailyn and Tom Kochan for the Sloan Work/Family Policy Network, funded by the Alfred P. Sloan Foundation. We would also like to particularly thank the Department of Family and Community Services for funding this research. The views expressed in this paper are those of the authors and do not represent the views of the Minister for Family and Community Services, the Department of Family and Community Services or the Commonwealth Government.

OBJECTIVES: To determine if clinicians and staff from 21 diverse primary care practice settings could implement the 2008 Bright Futures Guidelines for Health Supervision of Infants, Children, and Adolescents, 3rd edition recommendations, at the 9-and 24-month preventive services visits.METHODS: Twenty-two practice settings from 15 states were selected from 51 applicants to participate in the Preventive Services Improvement Project (PreSIP). Practices participated in a 9-month modified Breakthrough Series Collaborative from January to November 2011. Outcome measures reflect whether the 17 components of Bright Futures recommendations were performed at the 9-and 24-month visits for at least 85% of visits. Additional measures identified which office systems were in place before and after the collaborative.RESULTS: There was a statistically significant increase for all 17 measures. Overall participating practices achieved an 85% completion rate for the preventive services measures except for discussion of parental strengths, which was reported in 70% of the charts. The preventive services score, a summary score for all the chart audit measures, increased significantly for both the 9-month (7 measures) and 24-month visits (8 measures).CONCLUSIONS: Clinicians and staff from various practice settings were able to implement the majority of the Bright Futures recommended preventive services at the 9-and 24-month visits at a high level after participation in a 9-month modified Breakthrough Series collaborative.

Public health practitioners have increasingly leveraged technology-based communication to get health information into the hands of hard-to-reach populations; however, best practices for outreach and enrollment into mobile health (mHealth) programs are lacking. This article describes enrollment results from campaigns focused on enrolling underserved pregnant women and mothers in Text4baby-a free, mHealth service-to inform outreach strategies for mHealth programs. Text4baby participants receive health and safety information, interactive surveys, alerts, and appointment reminders through at least three weekly texts and a free app-timed to users' due date or babies' birth date. Text4baby worked with partners to implement national, state, and community-based enrollment campaigns. Descriptive statistics were used to compare baseline enrollment prior to a campaign with enrollment during a campaign to generate enrollment estimates. Enrollment rates were calculated for campaigns for which the number targeted/reached was available. National television campaigns resulted in more than 10,000 estimated enrollments. Campaigns that were integrated with an existing program and text-based recruitment had the highest enrollment rates, ranging from 7% to 24%. Facebook advertisements and traditional media targeting providers and consumers were least effective. mHealth programs should consider text-based recruitment and outreach via existing programs; additional research is needed on return on investment for different outreach strategies and on the effectiveness of different outreach strategies at reaching and enrolling specific target populations.