This study investigated the role of the family in career development and postschool employment outcomes for young adults with learning disabilities. Using a multiple-case study design, the authors examined a set of family structural and process variables. Fifty-nine in-depth interviews were conducted with young adults, parents, and school staff. Family structure was not directly linked to employment outcomes, but family socioeconomic status was related to initial career decision making and vocational identity development. Family process variables, including family relationships, involvement, support and advocacy, career aspirations, and intentional career-related activities worked in combination to form 3 patterns of family interaction labeled (a) advocates, (b) protectors, and (c) removed. Implications for practice and future research are discussed.

Transportation agencies' motor vehicle count programs tend to be well established and robust with clear guidelines to collect short-term count data, to analyze data, develop annual average daily traffic (AADT) adjustment factors, and to estimate AADT volumes. In contrast, bicycle and pedestrian traffic monitoring is an area of work for most transportation agencies. In most agencies, there are a low numbers of counting sites and limited agency experience to manage a city-wide or state-wide system of collecting, processing, and using nonmotorized data. Short duration counts are used to estimate longer duration volumes such as AADT. Because bicycle or pedestrian shortterm counts vary dramatically over time and significantly more than motorized vehicle counts, the direct application of motorized vehicle AADT estimation methods may be inadequate. The goal of this paper is to present a methodology that will enhance, if needed, existing AADT estimation methods widely employed for motorized vehicle counts. The proposed methodology is based on the analysis of AADT estimation errors using regression models to estimate a correcting function that accounts for weather and activity factors. The methodology can be applied to any type of traffic with high volume variability but in this research is applied to a permanent bicycle counting station in Portland, Oregon. The results indicate that the proposed methodology is simple and useful for finding ideal short-term counting conditions and improving AADT estimation accuracy.

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Objectives A community engagement service‐learning experience was planned to provide health services for the homeless during a local 1‐day event. The objectives were to (a) determine the feasibility of a service‐learning experience, and to (b) examine the effects on students’ attitudes toward persons experiencing homelessness. Methods A quasi‐experimental, institutional review board approved study, including health‐related students enrolled in a local university or community college, was planned. The attitudes toward the homeless survey was administered before and after participation in the service‐learning experience. Qualitative data were through student reflections of the experience. Results Participants (n = 106) completed a pre and post questionnaire and a self‐reflection. A statistically significant t(26) = −2.2, p = .04 change in attitudes toward the homeless were found. Three themes were revealed from the reflections: inherent bias, individualized care, and the societal context of people experiencing homelessness. Conclusion Both quantitative and qualitative findings may help students reflect on preconceived stereotypes; therefore, affecting their attitudes toward the homelessness.

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