ExperienceSampler: An open-source scaffold for building smartphone apps for experience sampling.

2018 ◽  
Vol 23 (4) ◽  
pp. 729-739 ◽  
Author(s):  
Sabrina Thai ◽  
Elizabeth Page-Gould
Keyword(s):  
Open Source ◽  
Experience Sampling ◽  
Smartphone Apps

scholarly journals ExperienceSampler: An Open-Source Scaffold for Building Experience Sampling Smartphone Apps

2017 ◽  
Author(s):  
Sabrina Thai ◽  
Elizabeth Page-Gould
Keyword(s):  
Open Source ◽  
Sampling Methods ◽  
Daily Life ◽  
Experience Sampling ◽  
Cost Effective ◽  
Smartphone Apps ◽  
Median Response ◽  
Psychological Study ◽  
Sampling Studies ◽  
Experience Sampling Methods

Experience sampling methods allow researchers to examine phenomena in daily life and provide various advantages that complement traditional laboratory methods. However, existing experience sampling methods may be costly, require constant Internet connectivity, may not be designed specifically for experience sampling studies, or require a custom solution from a computer programming consultant. In this paper, we present ExperienceSampler, an open-source scaffold for creating experience-sampling smartphone apps designed for Android and iOS devices. We designed ExperienceSampler to address the common barriers to using experience sampling methods. First, there is no cost to the user. Second, ExperienceSampler apps make use of local notifications to let participants know when to complete surveys and store the data locally until Internet connection is available. Third, our app scaffold was designed with experience sampling methodological issues in mind. We also demonstrate how researchers can easily customize ExperienceSampler even if they have no programming skills. Furthermore, we evaluate the utility of ExperienceSampler apps with results from one social psychological study conducted using ExperienceSampler (N = 168). Mean response rates averaged 84%, and the median response latency was 10 minutes. Taken together, ExperienceSampler creates cost-effective smartphone apps that can be easily customized by researchers to examine experiences in daily life.

scholarly journals formr: A study framework allowing for automated feedback generation and complex longitudinal experience sampling studies using R

2018 ◽  
Author(s):  
Ruben C. Arslan ◽  
Matthias Walther ◽  
Cyril Tata
Keyword(s):  
Open Source ◽  
Programming Language ◽  
Online Social Network ◽  
Text Message ◽  
Experience Sampling ◽  
Sampling Studies ◽  
Longitudinal Data Collection ◽  
Statistical Programming ◽  
Complex Features ◽  
Automated Feedback

Open source software improves the reproducibility of scientific research. Because existing open source tools often do not offer dedicated support for longitudinal data collection on phones and computers, we built formr, a study framework that enables researchers to conduct both simple surveys and more intricate studies. With automated email and text message reminders according to any schedule, longitudinal and experience sampling studies become easy to implement. By integrating a web-based API for the statistical programming language R via OpenCPU, formr allows researchers to use a familiar programming language to enable complex features. These can range from adaptive testing to graphical and interactive feedback, to integration with non-survey data sources such as self-trackers or online social network data. Here, we showcase three studies created in formr: a study of couples with dyadic feedback; a longitudinal study over months including social networks, peer, and partner ratings; and a diary study with daily invitations by text message and email and extensive feedback on intraindividual patterns.

Open Source

2007 ◽  
Author(s):  
Fadi P. Deek ◽  
James A. M. McHugh
Keyword(s):  
Open Source

Emotional Variability Predicts Tiredness in Daily Life

2016 ◽  
Vol 37 (3) ◽  
pp. 181-193 ◽  
Author(s):  
Aire Mill ◽  
Anu Realo ◽  
Jüri Allik
Keyword(s):  
Sampling Method ◽  
Daily Life ◽  
Emotional Experience ◽  
Experience Sampling ◽  
Experience Sampling Method ◽  
Building Blocks ◽  
Intraindividual Variability ◽  
Unique Role ◽  
Over Time

Abstract. Intraindividual variability, along with the more frequently studied between-person variability, has been argued to be one of the basic building blocks of emotional experience. The aim of the current study is to examine whether intraindividual variability in affect predicts tiredness in daily life. Intraindividual variability in affect was studied with the experience sampling method in a group of 110 participants (aged between 19 and 84 years) during 14 consecutive days on seven randomly determined occasions per day. The results suggest that affect variability is a stable construct over time and situations. Our findings also demonstrate that intraindividual variability in affect has a unique role in predicting increased levels of tiredness at the momentary level as well at the level of individuals.

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.

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