Christopher Antoun
Biographic Data
| ID | 218967 |
|---|---|
| NAME | Christopher Antoun |
| GIVEN NAMES | Christopher |
| FAMILY NAME | Antoun |
| SIGNATURE | ANTOUN C |
| AFFILIATIONS | University of Maryland, College Park |
| ORCID | 0000-0002-2639-340X |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 91 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 5 |
Engaging underserved communities in smartphone-based research
Developing a Modular Survey App Using Co-design Principles
The objective of our project was to develop a smartphone app for administering shorter (“modular”) surveys. Given the paucity of research on this topic, we decided to use “co-design” techniques to generate design solutions. To implement these techniques, we recruited respondents in the survey target population to work in small groups and provide design ideas for the app. In this article, we present their input and examine whether we were successf…
Nonparticipation Bias in Accelerometer-Based Studies and the Use of Propensity Scores
Relatively little attention has been paid to the effects of nonparticipation on data quality in population-based studies that use accelerometers to measure physical activity. We examine these issues using data from the 2013 Longitudinal Internet Studies for the Social Sciences (LISS) panel and 2013-2014 National Health and Nutrition Examination Survey (NHANES) accelerometer studies, both of which collected survey data in advance and therefore per…
Open Questions Self-Administered on the Web versus Interviewer-Administered in Person
Relatively little is known about the performance of open questions in self-administered questionnaires compared to interviewer-administered ones. We examined this issue using the responses to the 2016 American National Election Study’s Web self-administered questionnaires and face-to-face computer-assisted personal interviews (CAPI) from independently drawn samples that asked three sets of open questions: most important problem(s) facing the coun…
Professional Respondents in Opt-in Online Panels
Survey researchers often assume that “professional” respondents, those who complete a large number of surveys in opt-in online panels, are more likely than others to provide low-quality responses because their primary motivation is to earn rewards with minimal effort. However, there is little empirical evidence for this assumption. It could also be that professional respondents are willing to expend effort in order to be compensated. We investiga…
Factors Affecting Completion Times
This article compares the factors affecting completion times (CTs) to web survey questions when they are answered using two different devices: personal computers (PCs) and smartphones. Several studies have reported longer CTs when respondents use smartphones than PCs. This is a concern to survey researchers because longer CTs may increase respondent burden and the risk of breakoff. However, few studies have analyzed the specific reasons for the t…
Willingness to Participate in Passive Mobile Data Collection
The rising penetration of smartphones now gives researchers the chance to collect data from smartphone users through passive mobile data collection via apps. Examples of passively collected data include geolocation, physical movements, online behavior and browser history, and app usage. However, to passively collect data from smartphones, participants need to agree to download a research app to their smartphone. This leads to concerns about nonco…
What Does All This Data Mean for My Future Mood? Actionable Analytics and Targeted Reflection for Emotional Well-Being
We explore the Examined Life, informing the design of reflective systems to promote emotional well-being, a critical health issue. People now have increasingly rich, digital records of highly personal data about what they said, did, and felt in the past. But social science research shows that people have difficulty in tracking and regulating their emotions. New reflective technologies that promote constructive analysis of rich personal data poten…
Design Heuristics for Effective Smartphone Questionnaires
Design principles for survey questionnaires viewed on desktop and laptop computers are increasingly being seen as inadequate for the design of questionnaires viewed on smartphones. Insights gained from empirical research can help those conducting mobile surveys to improve their questionnaires. This article reports on a systematic literature review of research presented or published between 2007 and 2016 that evaluated the effect of smartphone que…
Effects of Mobile versus PC Web on Survey Response Quality
Survey participants are increasingly responding to Web surveys on their smartphones as opposed to their personal computers (PCs), and this change brings with it some potential data-quality issues. This study reports on a randomized crossover experiment to compare the effect of two different devices, smartphones and PCs, on response quality in a Web survey conducted in a probability-based panel. Participants (n = 1,390) were invited to complete an…
Respondent mode choice in a smartphone survey
Now that people on mobile devices can easily choose their mode of communication (e.g., voice, text, video), survey designers can potentially allow respondents to answer questions in whatever mode they find momentarily convenient given their circumstances or that they chronically prefer. We conducted an experiment to explore how mode choice affects response quality, participation, and satisfaction in smartphone interviews. A total of 1,260 iPhone …
Comparisons of Online Recruitment Strategies for Convenience Samples
The rise of social media websites (e.g., Facebook) and online services such as Google AdWords and Amazon Mechanical Turk (MTurk) offers new opportunities for researchers to recruit study participants. Although researchers have started to use these emerging methods, little is known about how they perform in terms of cost efficiency and, more importantly, the types of people that they ultimately recruit. Here, we report findings about the performan…
Willingness to Participate in Passive Mobile Data Collection
The rising penetration of smartphones now gives researchers the chance to collect data from smartphone users through passive mobile data collection via apps. Examples of passively collected data include geolocation, physical movements, online behavior and browser history, and app usage. However, to passively collect data from smartphones, participants need to agree to download a research app to their smartphone. This leads to concerns about nonco…
Effects of Mobile versus PC Web on Survey Response Quality
Survey participants are increasingly responding to Web surveys on their smartphones as opposed to their personal computers (PCs), and this change brings with it some potential data-quality issues. This study reports on a randomized crossover experiment to compare the effect of two different devices, smartphones and PCs, on response quality in a Web survey conducted in a probability-based panel. Participants (n = 1,390) were invited to complete an…
Comparisons of Online Recruitment Strategies for Convenience Samples
The rise of social media websites (e.g., Facebook) and online services such as Google AdWords and Amazon Mechanical Turk (MTurk) offers new opportunities for researchers to recruit study participants. Although researchers have started to use these emerging methods, little is known about how they perform in terms of cost efficiency and, more importantly, the types of people that they ultimately recruit. Here, we report findings about the performan…
Professional Respondents in Opt-in Online Panels
Survey researchers often assume that “professional” respondents, those who complete a large number of surveys in opt-in online panels, are more likely than others to provide low-quality responses because their primary motivation is to earn rewards with minimal effort. However, there is little empirical evidence for this assumption. It could also be that professional respondents are willing to expend effort in order to be compensated. We investiga…
Design Heuristics for Effective Smartphone Questionnaires
Design principles for survey questionnaires viewed on desktop and laptop computers are increasingly being seen as inadequate for the design of questionnaires viewed on smartphones. Insights gained from empirical research can help those conducting mobile surveys to improve their questionnaires. This article reports on a systematic literature review of research presented or published between 2007 and 2016 that evaluated the effect of smartphone que…
Respondent mode choice in a smartphone survey
Now that people on mobile devices can easily choose their mode of communication (e.g., voice, text, video), survey designers can potentially allow respondents to answer questions in whatever mode they find momentarily convenient given their circumstances or that they chronically prefer. We conducted an experiment to explore how mode choice affects response quality, participation, and satisfaction in smartphone interviews. A total of 1,260 iPhone …
Nonparticipation Bias in Accelerometer-Based Studies and the Use of Propensity Scores
Relatively little attention has been paid to the effects of nonparticipation on data quality in population-based studies that use accelerometers to measure physical activity. We examine these issues using data from the 2013 Longitudinal Internet Studies for the Social Sciences (LISS) panel and 2013-2014 National Health and Nutrition Examination Survey (NHANES) accelerometer studies, both of which collected survey data in advance and therefore per…
Comparisons of Online Recruitment Strategies for Convenience Samples
The rise of social media websites (e.g., Facebook) and online services such as Google AdWords and Amazon Mechanical Turk (MTurk) offers new opportunities for researchers to recruit study participants. Although researchers have started to use these emerging methods, little is known about how they perform in terms of cost efficiency and, more importantly, the types of people that they ultimately recruit. Here, we report findings about the performan…
What Does All This Data Mean for My Future Mood? Actionable Analytics and Targeted Reflection for Emotional Well-Being
We explore the Examined Life, informing the design of reflective systems to promote emotional well-being, a critical health issue. People now have increasingly rich, digital records of highly personal data about what they said, did, and felt in the past. But social science research shows that people have difficulty in tracking and regulating their emotions. New reflective technologies that promote constructive analysis of rich personal data poten…
Design Heuristics for Effective Smartphone Questionnaires
Design principles for survey questionnaires viewed on desktop and laptop computers are increasingly being seen as inadequate for the design of questionnaires viewed on smartphones. Insights gained from empirical research can help those conducting mobile surveys to improve their questionnaires. This article reports on a systematic literature review of research presented or published between 2007 and 2016 that evaluated the effect of smartphone que…
Effects of Mobile versus PC Web on Survey Response Quality
Survey participants are increasingly responding to Web surveys on their smartphones as opposed to their personal computers (PCs), and this change brings with it some potential data-quality issues. This study reports on a randomized crossover experiment to compare the effect of two different devices, smartphones and PCs, on response quality in a Web survey conducted in a probability-based panel. Participants (n = 1,390) were invited to complete an…
Respondent mode choice in a smartphone survey
Now that people on mobile devices can easily choose their mode of communication (e.g., voice, text, video), survey designers can potentially allow respondents to answer questions in whatever mode they find momentarily convenient given their circumstances or that they chronically prefer. We conducted an experiment to explore how mode choice affects response quality, participation, and satisfaction in smartphone interviews. A total of 1,260 iPhone …
Professional Respondents in Opt-in Online Panels
Survey researchers often assume that “professional” respondents, those who complete a large number of surveys in opt-in online panels, are more likely than others to provide low-quality responses because their primary motivation is to earn rewards with minimal effort. However, there is little empirical evidence for this assumption. It could also be that professional respondents are willing to expend effort in order to be compensated. We investiga…
Factors Affecting Completion Times
This article compares the factors affecting completion times (CTs) to web survey questions when they are answered using two different devices: personal computers (PCs) and smartphones. Several studies have reported longer CTs when respondents use smartphones than PCs. This is a concern to survey researchers because longer CTs may increase respondent burden and the risk of breakoff. However, few studies have analyzed the specific reasons for the t…
Willingness to Participate in Passive Mobile Data Collection
The rising penetration of smartphones now gives researchers the chance to collect data from smartphone users through passive mobile data collection via apps. Examples of passively collected data include geolocation, physical movements, online behavior and browser history, and app usage. However, to passively collect data from smartphones, participants need to agree to download a research app to their smartphone. This leads to concerns about nonco…
Nonparticipation Bias in Accelerometer-Based Studies and the Use of Propensity Scores
Relatively little attention has been paid to the effects of nonparticipation on data quality in population-based studies that use accelerometers to measure physical activity. We examine these issues using data from the 2013 Longitudinal Internet Studies for the Social Sciences (LISS) panel and 2013-2014 National Health and Nutrition Examination Survey (NHANES) accelerometer studies, both of which collected survey data in advance and therefore per…
Open Questions Self-Administered on the Web versus Interviewer-Administered in Person
Relatively little is known about the performance of open questions in self-administered questionnaires compared to interviewer-administered ones. We examined this issue using the responses to the 2016 American National Election Study’s Web self-administered questionnaires and face-to-face computer-assisted personal interviews (CAPI) from independently drawn samples that asked three sets of open questions: most important problem(s) facing the coun…
Engaging underserved communities in smartphone-based research
Developing a Modular Survey App Using Co-design Principles
The objective of our project was to develop a smartphone app for administering shorter (“modular”) surveys. Given the paucity of research on this topic, we decided to use “co-design” techniques to generate design solutions. To implement these techniques, we recruited respondents in the survey target population to work in small groups and provide design ideas for the app. In this article, we present their input and examine whether we were successf…
Psychology (10 works) · Computer Science (9 works) · Focus Groups and Qualitative Methods (7 works) · Survey Methodology and Nonresponse (7 works) · Applied Psychology (5 works) · Human–computer interaction (4 works) · Internet privacy (4 works) · Social Psychology (4 works) · World Wide Web (4 works) · Applied Psychology (3 works)