Fabla: A voice-based ecological assessment method for securely collecting spoken responses to researcher questions

This article reports on the validation of Fabla, a researcher-developed and university-hosted smartphone app that facilitates naturalistic and secure collection of participants' spoken responses to researcher questions. Fabla was developed to meet the need for tools that (a) collect longitudinal qualitative data and (b) capture speech biomarkers from participants' natural environments. This study put Fabla to its first empirical test using a repeated-measures experimental design in which participants (n = 87) completed a 1-week voice daily diary via the Fabla app, and an identical 1-week text-entry daily diary administered via Qualtrics, with diary method order counterbalanced and randomized. A preregistered analysis plan investigated (1) adherence, usability, and acceptability of Fabla, (2) concurrent validity of voice diaries (vs. text-entry diaries) by comparing linguistic features obtained via each diary method, and (3) differences in the strength of the association between linguistic features and their known psychological correlates when assessed by voice versus text-entry diary. Voice diaries yielded more than double the mean daily language volume (word count) compared to text-entry diaries and received high usability and acceptability ratings. Linguistic markers consistently associated with depression in prior research were significantly associated with depression symptoms when assessed via voice but not text-entry diaries, and the difference in correlation magnitude was significant. Word-count-adjusted linguistic patterns were highly correlated between diary methods, with statistically significant mean differences observed for some linguistic dimensions in the presence of these associations. Fabla is a promising tool for collecting high-quality speech data from participants' naturalistic environments, overcoming multiple limitations of text-entry responding.

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Publication Details

Journal
Behavior Research Methods
Published
2025-08-12
DOI
https://doi.org/10.3758/s13428-025-02777-1
Citations
1
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
2.44

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Fabla: A voice-based ecological assessment method for securely collecting spoken responses to researcher questions

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Behavior Research Methods
Mental Health via Writing
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article

Fabla: A voice-based ecological assessment method for securely collecting spoken responses to researcher questions

George H. Grant, Jennifer S. Mascaro, Ali John Zarrabi, Charles L. Raison, Barbara O. Rothbaum, Santiago J Arconada Alvarez, Gari D. Clifford, Leslie M. Johnson, Boadie W. Dunlop, Holly Frances Levin-Aspenson, Wilbur Aaron Lam, Morgan N. Greenleaf, Roman Palitsky, Jessica L. Maples‐Keller, Deanna M. Kaplan, Nicole S. Pozzo, Hyoann Choi, Ariel McDowall, Melese Crozier
article en
1 citations

Abstract

This article reports on the validation of Fabla, a researcher-developed and university-hosted smartphone app that facilitates naturalistic and secure collection of participants' spoken responses to researcher questions. Fabla was developed to meet the need for tools that (a) collect longitudinal qualitative data and (b) capture speech biomarkers from participants' natural environments. This study put Fabla to its first empirical test using a repeated-measures experimental design in which participants (n = 87) completed a 1-week voice daily diary via the Fabla app, and an identical 1-week text-entry daily diary administered via Qualtrics, with diary method order counterbalanced and randomized. A preregistered analysis plan investigated (1) adherence, usability, and acceptability of Fabla, (2) concurrent validity of voice diaries (vs. text-entry diaries) by comparing linguistic features obtained via each diary method, and (3) differences in the strength of the association between linguistic features and their known psychological correlates when assessed by voice versus text-entry diary. Voice diaries yielded more than double the mean daily language volume (word count) compared to text-entry diaries and received high usability and acceptability ratings. Linguistic markers consistently associated with depression in prior research were significantly associated with depression symptoms when assessed via voice but not text-entry diaries, and the difference in correlation magnitude was significant. Word-count-adjusted linguistic patterns were highly correlated between diary methods, with statistically significant mean differences observed for some linguistic dimensions in the presence of these associations. Fabla is a promising tool for collecting high-quality speech data from participants' naturalistic environments, overcoming multiple limitations of text-entry responding.

Behavior Research MethodsVol. 57(9)
University of North Texas (US), Georgia Institute of Technology (US), University of Wisconsin–Madison (US), Emory University (US), The Wallace H. Coulter Department of Biomedical Engineering (US), Woodruff Health Sciences Center (US)
National Institutes of Health
Quality Education
Openalex Percentile: Top 11%
Mental Health via Writing
2.44
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