U.S. Social Work Students and Social Media: A Descriptive Analysis of Survey Items across Four Time-Points.

Between fall 2018 and spring 2023, the author conducted four survey studies on social work students' use, attitudes, and knowledge regarding social media: (1) a pilot study in fall 2018 (N = 57), (2) a comparative study in spring 2019 (N = 42), (3) a national survey study in fall 2019 (N = 430), and (4) a national replication survey study in spring 2023 (N = 287). The purpose of this article is to describe general observed trends across these four studies. Findings included persistent and pervasive use of social media, decreased knowledge of the impact of social media in undermining democratic processes, students' inverted concern for others' use of social media when compared with concern over their own use, diminished agreement with the importance of protecting personal data and treating data protection as a civil/human right, overall agreement that law enforcement should be able to use social media in the apprehension of people accused of committing a crime, decreased agreement that disinformation is a problem on social media, ambivalence toward social media's positive impact on society, and increased strong disagreement that students wish to delete their accounts but feel unable to do so.

Racial Disparity in Social Work Professional Licensure Exam Pass Rates: Examining Institutional Characteristics and State Licensure Policy as Predictors.

Purpose: The Association of Social Work Boards (2022a) released a report evidencing test-taker demographics as the strongest predictor of professional licensure exam pass-rates. The purpose of this study was to examine statistical predictors of social work professional licensure exam pass rate disparities between first-time Black/African American and White test-takers.

Materials And Methods: The study addressed the following research question: To what extent do institutional and state licensure characteristics predict race-based disparities in social work licensure exam pass rates? To answer this question, the authors built a data set in an Excel spreadsheet comprised of institutional and state licensure variables using publicly available and reliable sources.