Increasing Participation in a Mobile App Study: The Effects of a Sequential Mixed-Mode Design and In-Interview Invitation

Jäckle, Annette; Wenz, Alexander; Burton, Jonathan; Couper, Mick P.

doi:10.1093/jssam/smac006

Cited by 16 publications

(33 citation statements)

References 13 publications

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“…Additionally, earlier studies (Keusch et al, 2019;Revilla et al, 2019) found that too low incentives were among the two main reasons for not participating in digital data sharing. 1 In contrast, Jäckle et al (2019) and Beuthner et al (2023) found no effect of incentives on downloading an app or sharing different types of data. Silber et al (2022) also reported that incentives do not necessarily motivate all types of data-sharing (e.g., it does not work in the case of sharing highly sensitive health data).…”

Section: Incentivesmentioning

confidence: 99%

“…Self-assessed smartphone skills in earlier studies, however, show contradictory results: Wenz et al (2019) and Ohme et al (2021)found that participants with higher phone skills were more willing to participate, but in the study of Keusch et al (2019) and Struminskaya et al (2020) these skills were not associated with the willingness to participate. Other research showed that those who use mobile technology and devices intensively have a higher willingness to participate in various data collection tasks (Jäckle et al, 2019;Keusch et al, 2019;Pinter, 2015;Wenz et al, 2019).…”

Section: Respondents' Characteristicsmentioning

confidence: 99%

“…As a contribution to the literature, this study aims to understand the underlying mechanisms of the willingness to participate in academic research as a social media data donor. Earlier research has shown that digital data-sharing behavior in a broader sense can be a function of the offered incentives (Jäckle et al, 2019;Keusch et al, 2019;Ságvári et al, 2021), the type of data (Beuthner et al, 2023;Revilla et al, 2019;Silber et al, 2022;Wenz et al, 2019) (Revilla et al, 2019;Silber et al, 2022;Wenz et al, 2019, Beuthner 2023, the autonomy over data collection or the study's sponsor (Keusch et al, 2019;Struminskaya et al, 2020Struminskaya et al, , 2021, (Keusch et al, 2019;Struminskaya et al, 2020), the respondents' characteristics such as privacy concerns (Struminskaya et al, 2021), and various other factors as well.…”

Section: Introductionmentioning

confidence: 99%

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Determinants of willingness to donate data from social media platforms

Kmetty¹,

Stefkovics²,

Szamely³

et al. 2023

Preprint

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Social media data donation through data download packages (DDPs) is a promising new way of collecting individual-level digital trace data with informed consent. When linked with survey data, data donation is an even more promising tool that helps answer novel research questions. Nevertheless, given the novelty of this approach, little is known about whether and how people would share their data with researchers, although this could seriously affect selection bias and thus, the outer validity of the results. To study the determinants of data-sharing and help future data donation studies with detecting the conditions, under which the willingness is the highest, we pre-registered two vignette experiments and embedded them in two online surveys conducted in Hungary and the U.S. In hypothetical requests for donating social media data via DDPs, we manipulated the amount of the monetary incentives (1), the presence or lack of non-monetary incentives (2), the number of requested platforms (3), the estimated upload/download time (4), and the type of requested data (5). The results revealed that data-sharing attitude is strongly subject to the parameters of the actual study, how the request is framed, and some respondent characteristics. Monetary incentives increased willingness to participate in both countries, while other effects were not consistent between the two countries. Non-monetary incentives and time to download/upload data influenced willingness in the U.S. sample but not in the Hungarian one, whereas the type of data affected the willingness to participate only in the case of the Hungarian respondents. Our findings help design more effective future data donation requests and provide insights into the potential patterns of selection bias in data donation studies.

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Section: Incentivesmentioning

confidence: 99%

Section: Respondents' Characteristicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Determinants of willingness to donate data from social media platforms

Kmetty¹,

Stefkovics²,

Szamely³

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…For instance, over 20% of the internet users declined to respond by the web mode in the initial recruitment of the GESIS Panel (Pforr & Dannwolf, 2017), and around 10 percent of Gallop panel members with internet access explicitly asked to send the questionnaires by mail (Rookey et al, 2008). A substantial proportion of internet users also declined to respond online after the web mode had been introduced as the first mode option in ongoing panel studies, instead of choosing an alternative mode (Fitzgerald et al, 2019; Jäckle et al, 2015). Since internet penetration rates are still increasing in most countries, internet-using respondents who are reluctant to participate in web surveys may become more relevant for survey research as a reflection of a new digital divide (Herzing & Blom, 2018).…”

Section: Introductionmentioning

confidence: 99%

How Do Internet-Related Characteristics Affect Whether Members of a German Mixed-Mode Panel Switch from the Mail to the Web Mode?

Bretschi

Weiß

2022

Social Science Computer Review

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In recent years, several longitudinal studies have transitioned from an interviewer-administered to a mixed-mode design, using the internet as one of the modes of data collection. However, a substantial proportion of panelists are reluctant to participate in web surveys when offered a choice in an ongoing mixed-mode panel. We still know little about the characteristics of panel members that drive them to comply with the request to complete surveys via the internet. This study aims to fill this gap by investigating how internet-related characteristics are linked to the willingness of panelists to switch from the mail mode to the web. We use data from multiple waves of the GESIS Panel, a probability-based mixed-mode panel in Germany ( N = 5734). A web-push intervention motivated 28% of 1364 panelists of the mail mode to complete the survey online in a single wave and 70% of these 380 short-term switchers to switch to the web mode permanently. We measured indicators of internet use, internet skills, and attitudes toward the internet as potential mechanisms of this short-term and long-term mode switching in the two waves before the intervention. Our results suggest that internet use and internet skills affect respondents’ willingness to switch modes in a single wave. For these short-term switchers, however, none of the internet-related characteristics could explain mode switching in the long term. We also present self-reported reasons by panelists for not accepting the offer to switch modes that correspond to these findings. The results of this study can be used to develop effective push-to-web methods for longitudinal mixed-mode surveys.

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“…It has received considerable attention in the social sciences and the survey research literature (Bethlehem, 2010;Heckman, 2010). A number of studies have focused on motivational barriers of uptake into studies (in general, not focused on EMA) by examining the relevance of study content for prospective participants , the availability of data collection devices (Jäckle et al, 2019), and by examining appropriate monetary and non-monetary incentives (Yu & Cooper, 1983).…”

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confidence: 99%

A population-based investigation of participation rate and self-selection bias in momentary data capture and survey studies

et al. 2023

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Participant selection bias is of concern to researchers conducting surveys of all types. For momentary data capture studies, such as Ecological Momentary Assessment, the level of burden associated with these techniques and the possibility of low uptake rates makes the concerns especially salient. This study invited 3,000 individuals to participate in a study of health and mood and recorded the uptake rates at various points in the process. Respondents expressing interest in participating in general were randomized into a one-time survey, a low-burden momentary study, or a high-burden momentary study. Overall, 85.9% of the sample did not respond to the study invitation (including confirming non-interest); 6.9% of the sample expressed interest in the study by completing a brief survey; 2.1% agreed to participate in the study when the protocol specifics were described (none of the study protocols were actually run). Whites were more likely to complete the survey. Of those completing the survey, individuals who reported higher income, a more “open” personality, better typing skills, better computer skills, who viewed the research topic as important, and who expressed interest in research on daily feelings more likely consented to being enrolled in the experiment. The number of prior surveys taken had an inverted-U shaped association with participation in this study. Finally, all individuals randomized to the one-time survey group agreed to participate compared to two-thirds of individuals in the momentary groups. These results suggest that participant selection bias may affect both one-time survey and momentary data capture studies, with the caveat that the degree of such bias will be related to a study’s hypotheses.

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Increasing Participation in a Mobile App Study: The Effects of a Sequential Mixed-Mode Design and In-Interview Invitation

Cited by 16 publications

References 13 publications

Determinants of willingness to donate data from social media platforms

Determinants of willingness to donate data from social media platforms

How Do Internet-Related Characteristics Affect Whether Members of a German Mixed-Mode Panel Switch from the Mail to the Web Mode?

A population-based investigation of participation rate and self-selection bias in momentary data capture and survey studies

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