RESUMEN
Standard-accented job candidates are perceived as more hireable than non-standard-accented candidates. Two broad perspectives have emerged as to what drives this effect: (a) that it is a pragmatic response to the perception that non-standard accents can impede job-relevant communication (processing fluency explanation) and/or (b) that non-standard accents signal "otherness" and candidates are devalued as a result (prejudice explanation). This meta-analytic integration of 139 effect sizes (N = 4,576) examined these two perspectives. Standard-accented candidates were considered more hireable than non-standard-accented candidates (d = 0.47)-a bias that was stronger for high communication jobs. Other findings, however, are difficult to explain from a processing fluency explanation: candidates' relative comprehensibility was not a significant moderator of hiring bias. Moreover, the degree of accent bias was associated with perceptions of the candidates' social status, and accent bias was particularly pronounced among female candidates and for candidates who spoke in foreign (as compared with regional) accents.
RESUMEN
BACKGROUND: The field of health information management (HIM) focuses on the protection and management of health information from a variety of sources. The American Health Information Management Association (AHIMA) Council for Excellence in Education (CEE) determines the needed skills and competencies for this field. AHIMA's HIM curricula competencies are divided into several domains among the associate, undergraduate, and graduate levels. Moreover, AHIMA's career map displays career paths for HIM professionals. What is not known is whether these competencies and the career map align with industry demands. OBJECTIVE: The primary aim of this study is to analyze HIM job postings on a US national job recruiting website to determine whether the job postings align with recognized HIM domains, while the secondary aim is to evaluate the AHIMA career map to determine whether it aligns with the job postings. METHODS: A national job recruitment website was mined electronically (web scraping) using the search term "health information management." This cross-sectional inquiry evaluated job advertisements during a 2-week period in 2021. After the exclusion criteria, 691 job postings were analyzed. Data were evaluated with descriptive statistics and natural language processing (NLP). Soft cosine measures (SCM) were used to determine correlations between job postings and the AHIMA career map, curricular competencies, and curricular considerations. ANOVA was used to determine statistical significance. RESULTS: Of all the job postings, 29% (140/691) were in the Southeast, followed by the Midwest (140/691, 20%), West (131/691,19%), Northeast (94/691, 14%), and Southwest (73/691, 11%). The educational levels requested were evenly distributed between high school diploma (219/691, 31.7%), associate degree (269/691, 38.6%), or bachelor's degree (225/691, 32.5%). A master's degree was requested in only 8% (52/691) of the postings, with 72% (42/58) preferring one and 28% (16/58) requiring one. A Registered Health Information Technologist (RHIT) credential was the most commonly requested (207/691, 29.9%) in job postings, followed by Registered Health Information Administrator (RHIA; 180/691, 26%) credential. SCM scores were significantly higher in the informatics category compared to the coding and revenue cycle (P=.006) and data analytics categories (P<.001) but not significantly different from the information governance category (P=.85). The coding and revenue cycle category had a significantly higher SCM score compared to the data analytics category (P<.001). Additionally, the information governance category was significantly higher than the data analytics category (P<.001). SCM scores were significantly different between each competency category, except there were no differences in the average SCM score between the information protection and revenue cycle management categories (P=.96) and the information protection and data structure, content, and information governance categories (P=.31). CONCLUSIONS: Industry job postings primarily sought degrees, with a master's degree a distant fourth. NLP analysis of job postings suggested that the correlation between the informatics category and job postings was higher than that of the coding, revenue cycle, and data analytics categories.
RESUMEN
AIM: To propose a theoretical based model approach to address the nursing shortage problem of recruiting qualified applicants. BACKGROUND: Vital industries such as nursing and trucking face a large labour shortage. METHODS: A literature review focusing on recruitment and realistic job previews examines relevant theories and an indication of the focus of similar research. Game theory illustrates cooperative and competitive recruitment strategies in vital industries. RESULTS: Proposition and model development where cooperative or competitive strategies for recruitment can either increase or decrease the employee applicant pool. Institutional theory states that firms within a population become isomorphic in nature. Firms employing cooperative or competitive strategies for recruitment can change organisational practices through isomorphic processes. CONCLUSION: Industries facing a labour market shortage using cooperative strategy will use realistic job previews accurately to disseminate information about industry jobs. Realistic job previews will increase the applicant pool through individuals self-selecting into, rather than out of, the applicant pool. IMPLICATIONS FOR NURSING MANAGEMENT: Recruitment in the nursing industry has been examined at the individual applicant and organisational level, yet the overall industry has been ignored. As nursing shortages continue, viewing recruitment at the macro level (the overall industry) is appropriate. Game theory as proposed provides opportunities for current research at the industry level.