Evidence map›Paper›PMID 35343900›Full record

ArticleJMIR formative research2022

A Novel Experience Sampling Method Tool Integrating Momentary Assessments of Cognitive Biases: Two Compliance, Usability, and Measurement Reactivity Studies.

Teresa Boemo, Angela Socastro, Ivan Blanco, Oscar Martin-Garcia, Ana Mar Pacheco-Romero, Raquel Rodríguez-Carvajal, Alvaro Sanchez-Lopez

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Teresa BoemoComplutense University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0002-5543-2914
Angela SocastroComplutense University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0002-1777-258X
Ivan BlancoAutonoma University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0003-3611-5814
Oscar Martin-GarciaComplutense University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0003-3620-9896
Ana Mar Pacheco-RomeroComplutense University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0001-6164-1918
Raquel Rodríguez-CarvajalAutonoma University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0001-9015-5425
Alvaro Sanchez-LopezComplutense University of Madrid, Madrid, Spain.ORCID https://orcid.org/0000-0003-2815-7803
Universidad Complutense de Madrid · ESUniversidad Autónoma de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExperience sampling methods (ESMs) are increasingly being used to study ecological emotion dynamics in daily functioning through repeated assessments taken over several days. However, most of these ESM approaches are only based on self-report assessments, and therefore, studies on the ecological trajectories of their underlying mechanisms are scarce (ie, cognitive biases) and require evaluation through experimental tasks. We developed a novel ESM tool that integrates self-report measures of emotion and emotion regulation with a previously validated app-based cognitive task that allows for the assessment of underlying mechanisms during daily functioning.

objectiveThe objective of the study is to test this new tool and study its usability and the possible factors related to compliance with it in terms of latency and missing responses. Among the compliance predictors, we considered psychological and time-related variables, as well as usability, measurement reactivity, and participants' satisfaction with the tool.

methodsWe conducted 2 extensive ESM studies-study 1 (N=84; a total of 3 assessments per day for 5 days) and study 2 (N=135; a total of 3 assessments per day for 10 days).

resultsIn both studies, participants found the tool highly usable (average usability score >81). By using mixed regression models, we found both common and specific results for the compliance predictors. In both study 1 and study 2, latency was significantly predicted by the day (P<.001 and P=.003, respectively). Participants showed slower responses to the notification as the days of the study progressed. In study 2 but not in study 1, latency was further predicted by individual differences in overload with the use of the app, and missing responses were accounted for by individual differences in stress reactivity to notifications (P=.04). Thus, by using a more extensive design, participants who experienced higher overload during the study were characterized by slower responses to notifications (P=.01), whereas those who experienced higher stress reactivity to the notification system were characterized by higher missing responses.

conclusionsThe new tool had high levels of usability. Furthermore, the study of compliance is of enormous importance when implementing novel ESM methods, including app-based cognitive tasks. The main predictors of latency and missing responses found across studies, specifically when using extensive ESM protocols (study 2), are methodology-related variables. Future research that integrates cognitive tasks in ESM designs should take these results into consideration by performing accurate estimations of participants' response rates to facilitate the optimal quality of novel eHealth approaches, as in this study.

Indexed as

cognitive biasescomplianceemotionexperience sampling methodmeasurement reactivityusability

Identifiers

PMID35343900
PMCPMC9002591
OpenAlexW4205151746

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.