Measuring Time Use in Surveys: How Valid Are Time Use Questions in Surveys? Concordance of Survey and Experience Sampling Measures

Since it is still unclear to what extent time allocation retrospectively reported in questionnaires, reflects people's actual behavior, examining the accuracy of responses to time use survey questions is of crucial importance. We analyze the congruence of time use information assessed through retrospective questionnaires and through experience sampling methodology. The sample comprised 433 individuals ranging in age from 14 to 86 years. Participants completed standard survey questions on time allocation. In addition, a mobile-phone based experience sampling technology was used over a period of three weeks to obtain snapshots of, on average, 54 momentary activities in which participants participated while pursuing their normal daily routines. Experience sampling assessments were scheduled six times a day over at least nine days, including workdays, Saturdays, andSundays. Results indicate that the congruence between time allocation assessed with survey questions (i.e. in SOEP) and time allocation assessed with experience sampling methodology depends on the characteristics of the respective activities. Associations between standard survey questions and experience sampling methods are quite substantial for long-lasting and externally structured activities, such as paid work on workdays. Incontrast, associations between survey and experience sampling methods are somewhat weaker, though highly statistically significant, for less externally structured, short-term and infrequent activities, such as errands, housework, and leisure. These moderate and relatively small correlations may indicate either an error-prone estimation of the prevalence of shortterm and infrequent activities by experience sampling or respondents' overrating of sporadic and short activities in survey questions. We conclude that activities with a long duration, such as paid work, can be measured in a satisfactory manner using short survey questions. Futureresearch is necessary to elucidate which method (experience sampling method or survey questions) delivers more reliable and valid measures for shortterm and sporadic activities.Day Reconstruction Methods (DRM) should be included in this future methodological research.Survey methods, experience sampling method, validity, time use, market work, housework, leisure, German Socio-Economic Panel Study, MMAA, SOEP

Experience Sampling

Experience Sampling refers to the repeated sampling of momentary experiences in the individual’s natural environment. Methodological advantages include the minimization of retrospective response biases and the maximization of the validity of the assessment. Conceptual benefits include the provision of insights into shortterm processes and into the daily-life contexts of the phenomena under study. Making use of the benefits of Experience Sampling while taking its methodological challenges into consideration allows addressing important research questions in the social and behavioral sciences with much precision and clarity. Despite this, Experience Sampling information is still rare in the data infrastructure that is publicly available to researchers. This stands in contrast to a current thriving of the methodology in research producing datasets that are not publicly available, as is the case in many psychological investigations. Following a discussion of the benefits and challenges of Experience Sampling, this report outlines its potential uses in social science and economic research and characterizes the status quo of Experience Sampling applications in currently available datasets, focusing primarily on household surveys conducted after 2001. Recommendations are given on how an intensified use of Experience Sampling in large-scale data collections can be facilitated in the future.Experience Sampling in the social and behavioural sciences

Examining Affect in Psychometric Schizotypy Using Behavioral Experience Sampling Methodology

poster abstractIn schizophrenia, patients often experience more negative emotions in the form of anger, sadness, and anxiety when compared to the general population. One unique way of measuring affect outside of the laboratory has been to use Experience Sampling Methods (ESM) to assess how individuals perceive current emotions in their daily life. However, these methods are still subject to self-report bias. In this study, we examined affect using traditional ESM methods while also implementing the Electronically Activated Recorder (EAR), a behaviorally-based ESM measure that provides real-world assessments of speech. To examine the EAR, we evaluated affect in schizotypy and non-schizotypy groups. Research shows that schizophrenia-like experiences, like increased negative affect, run along a continuum. Schizotypy is a category on the healthier end of the schizophrenia-spectrum; it applies to individuals who are thought to have a putative genetic liability for schizophrenia. Using the Linguistic Inquiry and Word Count (LIWC), we compared affective word usage among schizotypy and non-schizotypy groups to provide a real-world, behavioral ESM measure. When traditional ESM measures were used, we found individuals with schizotypy reported less negative emotions compared to the non-schizotypy group, but results did not reach the level of significance. We also observed that non-schizotypy individuals reported slightly higher positive emotions, and the schizotypy group reported slightly higher negative emotions. A similar pattern was observed when examining EAR data. Overall, results suggested that traditional and behavioral ESM measures of affect had significant overlap. In general, those with schizotypy demonstrated slightly more negative emotion and slightly less positive emotion than the non-schizotypy group. Findings did not reach the level of significance. This study demonstrates that the EAR provides behavioral ratings of affect that are on par with traditional ESM ratings. Future work should examine the EAR at different points on the schizophrenia-spectrum

Grounded Theory Investigation into Depression during the Freshman Year of College

Purpose: In a national study of college students during the fall of 2017, a total of 31,463 students reported feeling hopeless (51.7%), being overwhelmed (86.5%), feeling so depressed it was difficult to function (39.3%), and seriously considered suicide (12.1%) (American College Health Association, 2017). These statistics represent a major concern regarding health care practice because it is a severe mental health crisis that can disrupt students’ daily lives. The purpose of this research is to amplify awareness of freshman student depression to gain knowledge about the mental health of college students using grounded theory methodology. Theoretical/conceptual framework: Attending college for the first time can be a life changing event for many students. Depression, whether formally diagnosed or self-identified, is an increasingly significant problem in emerging adults. Method: Grounded theory methodology will be used to examine the experience of depression during the freshmen year of college. Purposive sampling will be used to recruit sophomore students who identify as having had depression during their freshman year. Recruitment will continue until data saturation occurs. Following informed consent, interviews will begin with one open-ended question of “What was the experience of your freshman year in college?” Interviews will be recorded, transcribed, and constantly compared for emerging themes throughout the data collection process. Data will be analyzed using NVivo software. Results/conclusions: Results will describe the initial categories associated with depression in this population. These preliminary categories will help provide a more in depth understanding of the experience of depression

Reliable online social network data collection

Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users’ behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users’ behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.Postprin

How to Sample Behavior and Emotions of Traders: A Psychological Approach and an Empirical Example

This paper describes an empirical approach based on psychological methodology, which assumes that individual behaviour must be studied within its natural environment. This approach is called experience sampling (ESM). To illustrate the potentials of employing ESM in the stock-trading domain, we report on observations from an explorative pilot study designed to shed light on the following issues: how outcomes of trades are perceived by traders; the reasons traders associate with good and bad trades; and how traders’ moods fluctuate over a trading day.

A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration

Algorithmic composition is the process of creating musical material by means of formal methods. As a consequence of its design, algorithmic composition systems are (explicitly or implicitly) described in terms of parameters. Thus, parameter space exploration plays a key role in learning the system's capabilities. However, in the computer music field, this task has received little attention. This is due in part, because the produced changes on the human perception of the outputs, as a response to changes on the parameters, could be highly nonlinear, therefore models with strongly predictable outputs are needed. The present work describes a methodology for the human perceptual (or aesthetic) exploration of generative systems' parameter spaces. As the systems' outputs are intended to produce an aesthetic experience on humans, audition plays a central role in the process. The methodology starts from a set of parameter combinations which are perceptually evaluated by the user. The sampling process of such combinations depends on the system under study and possible on heuristic considerations. The evaluated set is processed by a compaction algorithm able to generate linguistic rules describing the distinct perceptions (classes) of the user evaluation. The semantic level of the extracted rules allows for interpretability, while showing great potential in describing high and low-level musical entities. As the resulting rules represent discrete points in the parameter space, further possible extensions for interpolation between points are also discussed. Finally, some practical implementations and paths for further research are presented.Peer ReviewedPostprint (author's final draft

Milk Handling in the Supply Chains: The Case of Smallholder Retail Outlets In Nakuru, Kenya

This paper characterises smallholder milk outlets in Nakuru district one of the major milk producing Districts in Kenya, and also analyses factors that influence their current operating and handling capacities. Data comes from four divisions of the district. A sample of 137 smallholder milk retail outlets was made using systematic random sampling methodology. Both descriptive and ordinary regression methods were used in the analysis. A characterisation of the retail outlets is brought out and the factors that affect their current operating capacities presented. Results show that a unit change in education, experience and selling prices leads to 0.29, 0.18 and 0.23 significant changes in milk handling capacities by the retail outlets respectively. These imply that there is an efficiency gain from education and better prices through higher consumer incomes in the industry. Enhancement of milk retailers' value addition through provision of physical facilities such as cooling equipment and stability in prices should be encouraged through policy intervention to promote informal sector investments in the sub-sector.milk supply chain, smallholder retail outlets, Kenya, Industrial Organization, Marketing,

The role of trust in e-government adoption: A systematic literature review

Electronic government (e-government) is a concept that has been adopted in most countries for the purposes of providing government services digitally, improving transparency between government and citizens and enabling additional communication channels with the government. Although e-government readiness in most countries is at a high level, adoption of e-government services is still considered tentative. A critical review of the literature suggests that this may be linked to citizens’ trust in government and e-government. As such, there is a need to investigate the role of trust in e-government adoption. For this purpose, a systematic literature review was conducted in order to observe research design, methodologies and approaches adopted in these studies as well as limitations identified and recommendation for future studies. The findings highlight that quantitative techniques and survey research methods appear to have been much preferred over other available alternatives such as qualitative techniques and interview methods or mixed methods in studies relating to trust in e-government adoption

Faktor Penentu dari Persepsi Nilai Pelanggan dan Implikasinya terhadap Intensi Pembelian

The purpose of this study is to examine the determinants of customer value perception of the purchase intention on the internet consumer services. The methodology of this research was hypothesis testing. Sample in this research is conducted by non-probability method with purposive sampling technique from350 internet subscribers in Jakarta. The result of the research by structural equation modeling analysis in the first model showed that the service quality, experience economy and price fairness have a significant influence to customer value perception. In the second model, the results showed that service quality, experience economic, price fairness and customer value perception have a significant influenceto purchase intention