scholarly journals Using experience sampling to link software repositories with emotions and work well-being

2018 ◽  
Author(s):  
Miikka Kuutila ◽  
Mika V. Mäntylä ◽  
Maëlick Claes ◽  
Marko Elovainio ◽  
Bram Adams
Keyword(s):  
Experience Sampling ◽  
Well Being ◽  
Software Repositories

Psychometric Properties of the Spontaneous and Deliberate Mind Wandering Scales

2019 ◽  
Vol 35 (6) ◽  
pp. 878-890 ◽  
Author(s):  
David Marcusson-Clavertz ◽  
Oscar N. E. Kjell
Keyword(s):  
Anxiety Disorder ◽  
Psychometric Properties ◽  
Generalized Anxiety Disorder ◽  
Social Desirability ◽  
Cognitive Task ◽  
Experience Sampling ◽  
Well Being ◽  
Mind Wandering ◽  
Generalized Anxiety ◽  
Psychological Variables

Abstract. Thinking about task-unrelated matters (mind wandering) is related to cognition and well-being. However, the relations between mind wandering and other psychological variables may depend on whether the former commence spontaneously or deliberately. The current two studies investigated the psychometric properties of the Spontaneous and Deliberate Mind Wandering Scales (SDMWS; Carriere, Seli, & Smilek, 2013 ). Study 1 evaluated the stability of the scales over 2 weeks ( N = 284 at Time 1), whereas Study 2 ( N = 323) evaluated their relations to Generalized anxiety disorder symptoms, Openness, Social desirability, and experience-sampling reports of intentional and unintentional mind wandering during an online cognitive task. The results indicated that the SDMWS were better fitted with a two-factor than a one-factor solution, although the fit was improved with the exclusion of one item. The scales exhibited strong measurement invariance across gender and time, and moderately high test-retest reliability. Spontaneous mind wandering predicted Generalized anxiety disorder and experience-sampling reports of unintentional mind wandering, whereas Deliberate mind wandering predicted Openness and experience-sampling reports of intentional mind wandering. Furthermore, Spontaneous mind wandering showed a negative association with social desirability of weak-to-medium strength. In sum, the scales generally showed favorable psychometric properties.

scholarly journals Individual differences limit predicting well-being and productivity using software repositories: a longitudinal industrial study

2021 ◽  
Vol 26 (5) ◽  
Author(s):  
Miikka Kuutila ◽  
Mika Mäntylä ◽  
Maëlick Claes ◽  
Marko Elovainio ◽  
Bram Adams
Keyword(s):  
Individual Differences ◽  
Fixed Effects ◽  
Prediction Models ◽  
Well Being ◽  
Software Project ◽  
Structured Interviews ◽  
Software Developers ◽  
Software Repositories ◽  
Generalized Linear Mixed Effects ◽  
Individualized Prediction

AbstractReports of poor work well-being and fluctuating productivity in software engineering have been reported in both academic and popular sources. Understanding and predicting these issues through repository analysis might help manage software developers’ well-being. Our objective is to link data from software repositories, that is commit activity, communication, expressed sentiments, and job events, with measures of well-being obtained with a daily experience sampling questionnaire. To achieve our objective, we studied a single software project team for eight months in the software industry. Additionally, we performed semi-structured interviews to explain our results. The acquired quantitative data are analyzed with generalized linear mixed-effects models with autocorrelation structure. We find that individual variance accounts for most of the R2 values in models predicting developers’ experienced well-being and productivity. In other words, using software repository variables to predict developers’ well-being or productivity is challenging due to individual differences. Prediction models developed for each developer individually work better, with fixed effects R2 value of up to 0.24. The semi-structured interviews give insights into the well-being of software developers and the benefits of chat interaction. Our study suggests that individualized prediction models are needed for well-being and productivity prediction in software development.

Authentic leadership and leaders' mental well-being: An experience sampling study

2018 ◽  
Vol 29 (2) ◽  
pp. 309-321 ◽  
Author(s):  
Matthias Weiss ◽  
Stefan Razinskas ◽  
Julia Backmann ◽  
Martin Hoegl
Keyword(s):  
Authentic Leadership ◽  
Experience Sampling ◽  
Well Being ◽  
Mental Well Being

Differentiate to Regulate: Low Negative Emotion Differentiation Is Associated With Ineffective Use but Not Selection of Emotion-Regulation Strategies

2019 ◽  
Vol 30 (6) ◽  
pp. 863-879 ◽  
Author(s):  
Elise K. Kalokerinos ◽  
Yasemin Erbas ◽  
Eva Ceulemans ◽  
Peter Kuppens
Keyword(s):  
Emotion Regulation ◽  
Negative Emotion ◽  
Experience Sampling ◽  
Well Being ◽  
Emotion Regulation Strategies ◽  
Emotion Differentiation ◽  
Sampling Studies ◽  
Regulation Strategies ◽  
Selection Of

Emotion differentiation, which involves experiencing and labeling emotions in a granular way, has been linked with well-being. It has been theorized that differentiating between emotions facilitates effective emotion regulation, but this link has yet to be comprehensively tested. In two experience-sampling studies, we examined how negative emotion differentiation was related to (a) the selection of emotion-regulation strategies and (b) the effectiveness of these strategies in downregulating negative emotion ( Ns = 200 and 101 participants and 34,660 and 6,282 measurements, respectively). Unexpectedly, we found few relationships between differentiation and the selection of putatively adaptive or maladaptive strategies. Instead, we found interactions between differentiation and strategies in predicting negative emotion. Among low differentiators, all strategies (Study 1) and four of six strategies (Study 2) were more strongly associated with increased negative emotion than they were among high differentiators. This suggests that low differentiation may hinder successful emotion regulation, which in turn supports the idea that effective regulation may underlie differentiation benefits.

scholarly journals Well-being, Smartphone Sensors, and Data from Open-access Databases: A Mobile Experience Sampling Study

Field Methods ◽  
2019 ◽  
Vol 31 (3) ◽  
pp. 277-291 ◽  
Author(s):  
Stefan Stieger ◽  
Ulf-Dietrich Reips
Keyword(s):  
Open Access ◽  
Sampling Method ◽  
Experience Sampling ◽  
Past Research ◽  
Well Being ◽  
Multiple Time ◽  
Multiple Time Point ◽  
Smartphone Sensors ◽  
Internet Databases ◽  
Time Point

We investigated fluctuations of well-being by using a smartphone-based mobile experience sampling method (real-time and multiple time point measurements in the field using smartphones). Moreover, temperature, longitude, latitude, altitude, wind speed, rainfall, and further environment-based indicators were included as predictors either from smartphone sensors or from open-access Internet databases. Overall, a total of 213 participants reported on their well-being (over 14 days; three measurements per day; 8,000+ well-being judgments). We were able to replicate and refine past research about the dynamics of well-being fluctuations during the day (low in the morning, high in the evening) and over the course of a week (low just before the beginning of the week, highest near the end of the week). We also show what kind of benefits empirical researchers can gain for their research using smartphones and their built-in sensors by combining these measures with data from open-access databases.

scholarly journals Recommendations for Developing Support Tools With People Suffering From Chronic Obstructive Pulmonary Disease: Co-Design and Pilot Testing of a Mobile Health Prototype

10.2196/16289 ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. e16289
Author(s):  
Alan Davies ◽  
Julia Mueller ◽  
Jean Hennings ◽  
Ann-Louise Caress ◽  
Caroline Jay
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Health Care Professionals ◽  
Experience Sampling ◽  
Well Being ◽  
Mobile App ◽  
Lessons Learned ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
App Development

Background Gaps exist between developers, commissioners, and end users in terms of the perceived desirability of different features and functionalities of mobile apps. Objective The objective of this study was to co-design a prototype mobile app for people with chronic obstructive pulmonary disease (COPD). We present lessons learned and recommendations from working on a large project with various stakeholders to develop a mobile app for patients with COPD. Methods We adopted a user-centered, participatory approach to app development. Following a series of focus groups and interviews to capture requirements, we developed a prototype app designed to enable daily symptom recording (experience sampling). The prototype was tested in a usability study applying the think aloud protocol with people with COPD. It was then released via the Android app store, and experience sampling data and event data were captured to gather further usability data. Results A total of 5 people with COPD participated in the pilot study. Identified themes include familiarity with technology, appropriate levels for feeding back information, and usability issues such as manual dexterity. Moreover, 37 participants used the app over a 4-month period (median age 47 years). The symptoms most correlated to perceived well-being were tiredness (r=0.61; P<.001) and breathlessness (r=0.59; P<.001). Conclusions Design implications for COPD apps include the need for clearly labeled features (rather than relying on colors or symbols that require experience using smartphones), providing weather information, and using the same terminology as health care professionals (rather than simply lay terms). Target users, researchers, and developers should be involved at every stage of app development, using an iterative approach to build a prototype app, which should then be tested in controlled settings as well as in the wild (ie, when deployed and used in real-world settings) over longer periods.

Sign in / Sign up

Export Citation Format

Share Document