Evidence map›Paper›PMID 40522903›Full record

ArticlePloS one2025

Applying qualitative methods to experimental designs: A tutorial for the behavioral sciences.

Hidde Jelmer Leplaa, Jari A Tönjes, Mariska Bouterse, Karlijn F B Soppe, Irene Klugkist

Abstract read
In one paragraph

Article in PloS one, 2025. 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
–field-weighted citation impact
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.

  1. Reasons for Participating in the EDS-HEART Program: Holistic and Performative Within a Supportive Community.International journal of environmental research and public health · 2025
    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

5 authors.

Hidde Jelmer LeplaaDepartment of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0001-6900-7989
Jari A TönjesDepartment of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.
Mariska BouterseDepartment of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.
Karlijn F B SoppeDepartment of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.
Irene KlugkistDepartment of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies with experimental designs are almost invariably evaluated with quantitative outcomes and methods, both in behavioral sciences and other disciplines. We argue that there can be added value of using qualitative methods for the evaluation of (behavioral) experiments. Incorporating qualitative data can enhance the ecological validity of a study, by acquiring a more holistic understanding of the phenomenon of interest. There is, however, little methodological guidance on how to implement such an approach. In this paper we present the different steps and considerations for a qualitative evaluation of results in experimental designs. Methodological guidelines are offered for each stage of a study, from formulation of the research goals, through data collection and data analysis, to the interpretation of a potential effect of the intervention. In addition, there is ample attention for ensuring the rigor of the research. The presented guidelines are developed and illustrated using an empirical example, in which a constructivist grounded theory approach was applied to evaluate the effect of empathy prompts on the motivation to adhere to COVID-19 regulations.

Indexed as

Behavioral SciencesResearch DesignCOVID-19HumansQualitative ResearchSARS-CoV-2

Identifiers

PMID40522903
PMCPMC12169552

What OpenQuestion holds

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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.