Who is ‘on-call’ in Australia? A new classification approach for on-call employment in future population-level studies

Background On-call research and guidance materials typically focus on ‘traditional’ on-call work (e.g., emergency services, healthcare). However, given the increasing prevalence of non-standard employment arrangements (e.g., gig work and casualisation), it is likely that a proportion of individuals who describe themselves as being on-call are not included in current on-call literature. This study therefore aimed to describe the current sociodemographic and work characteristics of Australian on-call workers. Methods A survey of 2044 adults assessed sociodemographic and work arrangements. Of this population, 1057 individuals were workforce participants, who were asked to provide information regarding any on-call work they performed over the last three months, occupation type, weekly work hours, and the presence or absence of non-standard work conditions. Results Of respondents who were working, 45.5% reported working at least one day on-call in the previous month. There was a high prevalence of on-call work in younger respondents (63.1% of participants aged 18–24 years), and those who worked multiple jobs and more weekly work hours. Additionally, high prevalence rates of on-call work were reported by machinery operators, drivers, community and personal service workers, sales workers, and high-level managers. Conclusions These data suggest that on-call work is more prevalent than previously recorded and is likely to refer to a broad set of employment arrangements. Current classification systems may therefore be inadequate for population-level research. A taxonomy for the classification of on-call work is proposed, incorporating traditional on-call work, gig economy work, relief, or unscheduled work, and out of hours work.

Relationship between financial well-being and Burnout Syndrome in anesthesiologists

Burnout syndrome and problems in personal financial life can have negative effects on mental health. Given this similarity between the two, the question is whether there is a correlation between financial well-being and the risk of developing the syndrome. In this study a questionnaire was applied to analyze this relationship. The results show that the lower the financial well-being, the higher the risk of Burnout. The prevalence of the syndrome in the sample was 28.6%. Furthermore, age and time in the job market showed a negative correlation with this risk, while the weekly work load showed a positive correlation. Despite not demonstrating causality between the variables, this study presents new data in the literature. Future studies in the area are necessary to aid in the prevention and treatment of Burnout Syndrome.

Automating Measurement of Trainee Work Hours

BACKGROUND: Medical training programs across the country are bound to a set of work hour regulations, generally monitored via self-report. OBJECTIVE: We developed a computational method to automate measurement of intern and resident work hours, which we validated against self-report. DESIGN, SETTING, AND PARTICIPANTS: We included all electronic health record (EHR) access log data between July 1, 2018, and June 30, 2019, for trainees enrolled in the internal medicine training program. We inferred the duration of continuous in-hospital work hours by linking EHR sessions that occurred within 5 hours as “on-campus” work and further accounted for “out-of-hospital” work which might be taking place at home. MAIN OUTCOMES AND MEASURES: We compared daily work hours estimated through the computational method with self-report and calculated the mean absolute error between the two groups. We used the computational method to estimate average weekly work hours across the rotation and the percentage of rotations where average work hours exceed the 80-hour workweek. RESULTS: The mean absolute error between self-reported and EHR-derived daily work hours for first- (PGY-1), second- (PGY-2), and third- (PGY-3) year trainees were 1.27, 1.51, and 1.51 hours, respectively. Using this computational method, we estimated average (SD) weekly work hours of 57.0 (21.7), 69.9 (12.2), and 64.1 (16.3) for PGY-1, PGY-2, and PGY-3 residents. CONCLUSION: EHR log data can be used to accurately approximate self-report of work hours, accounting for both in-hospital and out-of-hospital work. Automation will reduce trainees’ clerical work, improve consistency and comparability of data, and provide more complete and timely data that training programs need.

P156 Myositis flares are associated with reduced work productivity and fewer hours worked: illustration of the future potential of digital healthcare solutions in rheumatic diseases

Background/Aims The digital healthcare revolution provides the opportunity for clinicians and researchers to collect useful data on a frequent and remote basis. Work ability is impacted by many rheumatic diseases, including the idiopathic inflammatory myopathies (IIMs), however, methods to assess the real-time impacts are limited. This study aims to explore the impact of IIM flares and symptoms upon employment using frequently collected data via a smartphone-based app. Methods The Myositis Physical Activity Device Study recruited a UK-based adult IIM cohort who completed weekly employment and flare questions via a specially designed smartphone-based app throughout a 91 day period in 2019/20. Employment-related questions were assessed every week (see Table 1 for details). Flares were reported via a weekly question. Employment variables were compared between flare and non-flare weeks using descriptive statistics. The relationship between flares and work productivity was assessed using multi-level mixed effects logistic regression modelling, adjusted for age and sex. Results Data on 13 (69% female) employed participants was analysed. A median of 5 flares were reported per patient during the three month period (IQR 3, 9). Summary employment results are displayed in Table 1. Participants reported greater impact of IIM upon employment, lower productivity and fewer hours worked during a flare week, compared to a non-flare week. There was a significant association between flares and detrimental impact upon work productivity (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.03, 1.12, p < 0.01). Flares were also significantly associated with an increased number of work hours missed due to IIM (OR 1.04, 95% CI 1.01, 1.08, p = 0.02) P156 Table 1:- Summary employment parameters compared between flare and non-flare weeksEmployment parameterAnswer formatWhole study period (159 weeks)Flare weeks (60 weeks)Non-flare weeks (99 weeks)p-value*Number of weeks’ work productivity affected by IIM (%)Dichotomous - “yes”, “no”54 (34.0)33 (55.0)21 (21.2)<0.01Mean effect of IIM upon work productivity (SD)Visual analogue scale - “Myositis had no effect on work" (0);“Myositis completely prevented me from working” (100)29.8 (28.8)46.2 (33.3)19.9 (20.0)<0.01Mean number of scheduled work hours per week per participant (SD)Numerical33.2 (15.8)36.9 (19.33)31.0 (13.0)<0.01Mean number of hours worked per week per participant (SD)Numerical23.5 (15.1)18.86 (17.1)26.23 (13.2)<0.01Proportion of hours worked per week per participant / % (SD)Calculated by research team73.7 (38.7)55.9 (43.2)84.7 (31.1)<0.01Mean number of hours of weekly work missed due to IIM per participant (SD)Numerical6.6 (16.6)14.9 (23.4)1.5 (6.6)<0.01Proportion of hours of weekly work missed due to IIM per participant / % (SD)Calculated by research team12.7% (29.5)29.2 (41.1)2.6 (10.0)<0.01SD = standard deviation *Categorical variables were compared using the Chi-squared test and continuous variables compared using the student t-test. Conclusion Our study has demonstrated that IIM flares are significantly associated with detrimental impact upon employment ability. On average, patients lost 15 hours of work a week during a flare compared to less than 2 hours outside a flare. The economic and personal impact of flares highlights the need for research in this area, with the aim of allowing early identification and instigation of treatment and possible need for supported work. Smartphone based remote monitoring of flares and other pertinent variables could enhance digital consultations, which may become more common in the post COVID-19 setting. Disclosure J.C. Williams: None. A.G.S. Oldroyd: None. W.G. Dixon: None. H. Chinoy: None.

How and When Job Crafting Relates to Employee Creativity: The Important Roles of Work Engagement and Perceived Work Group Status Diversity

Creative employees are treasured assets for organizations. However, relatively little is known about what specific actions employees can take to manage their own creative process. Taking a motivational perspective, this study examined how job crafting behaviors positively link to employee creative performance through work engagement, and whether perceived work group status diversity moderates this relationship. We conducted a weekly diary study in which 55 employees from a Chinese energy company were asked to fill in diaries over four consecutive weeks (176 observations in total). Results of the multilevel analyses showed that weekly job crafting behaviors were positively related to weekly creative performance through increasing weekly work engagement. In contrast to our expectation, we found that weekly job crafting behaviors were more positively related to weekly creative performance when perceived work group status diversity was high. In summary, our study suggests that job crafting behaviors are effective actions employees can take to manage their creative processes through increasing work engagement. In addition, we stress that status diversity in existing work environments is an important contextual factor that shapes the job crafting process.

Implementing Job Crafting Behaviors: Exploring the Effects of a Job Crafting Intervention Based on the Theory of Planned Behavior

This article presents a combined motivational and volitional intervention based on the theory of planned behavior aimed at promoting expansion-oriented job crafting behaviors. Participants were employees working in different companies, assigned to either an intervention ( n = 53) or a control group ( n = 55). Results of a field study (including premeasure, postmeasure, and weekly diaries) indicated that the intervention enhanced participants’ perceptions of behavioral control referred to job crafting and awareness regarding others’ engagement in job crafting. Latent change growth modeling showed that participation in the intervention led to participants shaping their job crafting intentions during the weeks, which translated into more frequent job crafting behaviors at the end of the study period. Besides, the intervention served to trigger weekly work-related flow experiences in terms of high absorption while working. Findings suggest that job crafting interventions can benefit from the inclusion of self-regulatory strategies complementing goal setting.

Diversification of Customer Shopping Styles as a Result of Changes in the Weekly Work Schedules of Retail Outlets

The article presents the results of three studies conducted by the author concerning the preferences of retail outlet customers with regard to the days of the week on which they most frequently purchase general food and non-food merchandise. This issue has become relevant within the context of the enactment of the Act of 10 January 2018 on limiting trade on Sundays, holidays and certain other days. Previous customer shopping styles as regards weekly shopping schedules must have changed. The aim of the article is to identify consumers’ habits and their changes concerning the weekly shopping schedules before and after the Act implementation. The results are based on direct surveys conducted in 2014, 2016 and 2018 among customers in Podkarpackie Province. A descriptive analysis of the results is supported by the statistical test chi square usage. It may be concluded that both in relation to food and non-food merchandise, the implementation of the Act resulted in a decrease in the number of customers engaging in shopping on Sundays. In the case of food items, the shopping activity moved to Mondays and Tuesdays of the following week, the purpose being to resupply. No increase was identified in the number of customers purchasing food on Fridays or Saturdays preceding non-trading Sundays. The opposite was true for non-food merchandise, where non-trading Sundays resulted primarily in increased sales on Saturdays, with minor increases on Mondays, Tuesdays and Wednesdays as well. The differences in weekly shopping schedules observed between every edition of the study also proved to be more significant than those identified in the individual respondent classification groups used for the purpose of the article.