Facilitating the recall of biographical data: Alternatives to life history calendars

Reporting life course data is challenging for survey respondents since they need to search their memory for information. Traditional life history calendars where the interviewer guides the respondent through the process are not suitable for web surveys and are not displayable on smaller screens such as smartphones, which are increasingly used to participate in a web survey. Alternative instruments are required that utilize elements of life history calendars to collect life course data in self-administered surveys. To investigate which aspects of life history calendars that are both easy to implement for survey practitioners and easy to utilize for respondents have the potential to enhance the quality of life course data and are perceived as beneficial by respondents, I conducted a short web survey consisting of two waves conducted three months apart covering the respondents' occupational trajectory over the last two years. Herein I experimentally tested two simplified measures derived from life history calendars: (1) the graphical presentation of the time horizon by displaying information in a tabular format and (2) adding temporal bounding cues in terms of information about the respondents' previous response behavior. The results show that providing the respondents with recall aids such as using a table format when collecting occupational data leads to better data quality compared to using question lists, even if respondents use their smartphones to complete the survey. Displaying information from previous surveys has the potential to help respondents retrieve biographical data but might as well lead to poorer data quality when respondents are not provided with the date of the previous survey.

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Publication Details

Journal
Advances in Life Course Research
Published
2025-05-24
DOI
https://doi.org/10.1016/j.alcr.2025.100677
Primary Topic
Data Analysis and Archiving
Type
article
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article

Facilitating the recall of biographical data: Alternatives to life history calendars

Irina Bauer
Advances in Life Course Research
Data Analysis and Archiving
article

Facilitating the recall of biographical data: Alternatives to life history calendars

Irina Bauer
article en

Abstract

Reporting life course data is challenging for survey respondents since they need to search their memory for information. Traditional life history calendars where the interviewer guides the respondent through the process are not suitable for web surveys and are not displayable on smaller screens such as smartphones, which are increasingly used to participate in a web survey. Alternative instruments are required that utilize elements of life history calendars to collect life course data in self-administered surveys. To investigate which aspects of life history calendars that are both easy to implement for survey practitioners and easy to utilize for respondents have the potential to enhance the quality of life course data and are perceived as beneficial by respondents, I conducted a short web survey consisting of two waves conducted three months apart covering the respondents' occupational trajectory over the last two years. Herein I experimentally tested two simplified measures derived from life history calendars: (1) the graphical presentation of the time horizon by displaying information in a tabular format and (2) adding temporal bounding cues in terms of information about the respondents' previous response behavior. The results show that providing the respondents with recall aids such as using a table format when collecting occupational data leads to better data quality compared to using question lists, even if respondents use their smartphones to complete the survey. Displaying information from previous surveys has the potential to help respondents retrieve biographical data but might as well lead to poorer data quality when respondents are not provided with the date of the previous survey.

Advances in Life Course ResearchVol. 65
GESIS - Leibniz Institute for the Social Sciences (DE)
Openalex Percentile: Top 85%
Data Analysis and Archiving
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