A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality

Microtask crowdsourcing is increasingly critical to the creation of extremely large datasets. As a result, crowd workers spend weeks or months repeating the exact same tasks, making it necessary to understand their behavior over these long periods of time. We utilize three large, longitudinal datasets of nine million annotations collected from Amazon Mechanical Turk to examine claims that workers fatigue or satisfice over these long periods, producing lower quality work. We find that, contrary to these claims, workers are extremely stable in their quality over the entire period. To understand whether workers set their quality based on the task's requirements for acceptance, we then perform an experiment where we vary the required quality for a large crowdsourcing task. Workers did not adjust their quality based on the acceptance threshold: workers who were above the threshold continued working at their usual quality level, and workers below the threshold self-selected themselves out of the task. Capitalizing on this consistency, we demonstrate that it is possible to predict workers' long-term quality using just a glimpse of their quality on the first five tasks.Comment: 10 pages, 11 figures, accepted CSCW 201

The sound of stress recovery:an exploratory study of self-selected music listening after stress

Background: Empirical support for the notion that music listening is beneficial for stress recovery is inconclusive, potentially due to the methodological diversity with which the effects of music on stress recovery have been investigated. Little is presently known about which recovery activities are chosen by individuals for the purpose of stress recovery, and whether audio feature commonalities exist between different songs that are selected by individuals for the purpose of stress recovery. The current pre-registered study investigated whether audio feature commonalities can be extracted from self-selected songs for the purpose of stress recovery. Furthermore, the present study exploratorily examined the relationship between audio features and participants’ desired recovery-related emotions while listening and after listening to self-selected music. Methods: Participants (N = 470) completed an online survey in which they described what music they would listen to unwind from a hypothetical stressful event. Data analysis was conducted using a split-sample procedure. A k-medoid cluster analysis was conducted to identify audio feature commonalities between self-selected songs. Multiple regression analyses were conducted to examine the relationship between audio features and desired recovery emotions. Results: Participants valued music listening as a recovery activity to a similar extent as watching TV, sleeping, or talking to a significant other. Cluster analyses revealed that self-selected songs for the purpose of stress recovery can be grouped into two distinct categories. The two categories of songs shared similarities in key, loudness, speechiness, acousticness, instrumentalness, liveness, musical valence, tempo, duration, and time signature, and were distinguished by danceability, energy, and mode. No audio features were significantly associated with participants’ desired recovery emotions. Conclusions: Although a comprehensive portrait of the relationship between audio features and stress recovery still warrants further research, the present study provides a starting point for future enquiries into the nuanced effects of musical audio features on stress recovery.</p

Sedentary work and participation in leisure–time physical activity

Objective: Demanding psychosocial work characteristics, such as high job demands, can have a detrimental impact on leisure–time physical activity (LTPA), with adverse consequences for employee health and well-being. However, the mechanisms and moderators of this crossover effect are still largely unknown. We therefore aimed to identify and test potential mediating and moderating factors from within and outside the work environment. Based on the previous research, we expected job demands to be negatively related to LTPA through fatigue. In addition, we expected that job control and worktime control would attenuate the relationship between job demands and fatigue. Furthermore, we hypothesized that autonomous exercise motivation and spontaneous action planning would attenuate the relationship between fatigue and LTPA. In addition to these cross-sectional hypotheses, we expected the same effects to predict a change in LTPA in the following year. Methods: To investigate these assumptions, a preregistered longitudinal survey study was conducted among a large sample of Dutch employees in sedentary jobs. Participants reported on the constructs of interest in 2017 and 2018 (N = 1189 and 665 respectively) and the resulting data were analyzed using path analyses. Results: Our cross-sectional analyses confirm a weak indirect, negative association between job demands and LTPA, via fatigue. However, this finding was not observed in our longitudinal analyses and none of the other hypotheses were confirmed. Conclusion: This study shows that, among employees with relatively healthy psychosocial work characteristics (i.e., high job control), the evidence for an impact of these work characteristics on participation in LTPA is limited

The Impact of Cognitive and Physical Effort Exertion on Physical Effort Decisions : A Pilot Experiment

Research suggests that cognitive fatigue has a negative impact on physical activity participation. However, the mechanisms underlying this effect are yet unclear. Using an effort-based decision-making paradigm, we examined whether individuals weigh physical effort-costs more strongly when they are cognitively or physically fatigued. Twenty university students visited the lab on three occasions. On each visit, participants underwent a manipulation that was designed to either induce cognitive fatigue (i.e., 2-back task), physical fatigue (i.e., handgrip exercise), or served as a control condition (i.e., documentary watching). After the manipulations, participants performed an effort-based decision-making task in which they decided for 125 offers whether they accepted the offer to exert the required level of physical effort to obtain rewards that varied in value. The probability to accept offers declined with increasing effort requirements whereas the general probability to accept offers was not reduced by any of the experimental conditions. As expected, the decline in accepted offers with increasing effort requirements was stronger after prolonged exertion of physical effort compared to the control condition. Unexpectedly, this effect was not found after exerting cognitive effort, and exploratory analyses revealed that the impact of physical effort exertion on physical effort-based decisions was stronger than that of cognitive effort exertion. These findings suggest that people weight future physical effort-costs more strongly after exerting physical effort, whereas we could not find any evidence for this after exerting cognitive effort. We discuss multiple explanations for this discrepancy, and outline possibilities for future research

The Impact of Cognitive Work Demands on Subsequent Physical Activity Behavior

After cognitively demanding work, individuals tend to be less physically active. However, the psychological mechanisms underlying this effect have not been thoroughly tested. The aim of this article was to experimentally investigate the impact of cognitive work demands on subsequent physical activity behavior. Across two preregistered experiments, participants were exposed to high or low levels of cognitive work demands, operationalized as workload in Experiment 1 and as working-memory load in Experiment 2. In a subsequent choice task, participants made binary consequential choices between leisure nonphysical activities (e.g., drawing) and effortful physical activities (e.g., cycling). Choice alternatives were matched on attractiveness rankings. Additionally, physical endurance performance was measured using a standardized cycling protocol in Experiment 1. In contrast to the hypotheses, after performing work with high cognitive demands, participants were not more likely to choose nonphysical over physical activities nor did they perform significantly worse on the physical endurance task. Exploratory analyses suggest that preexisting preferences for either physical or nonphysical activities explained physical activity behavior above and beyond exposure to cognitively demanding work. These experiments question the impact of cognitively demanding work on subsequent cognitive fatigue and physical activity behavior. Implications for theory, practice, and future directions are discusse