Evidence map›Paper›PMID 32104971›Full record

ArticleResearch synthesis methods2020

Quantitizing findings from qualitative studies for integration in mixed methods reviewing.

Leonie van Grootel, Lakshmi Balachandran Nair, Irene Klugkist, Floryt van Wesel

Abstract read
In one paragraph

Article in Research synthesis methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Leonie van GrootelDepartment of Methodology and Statistics, School of Social and Behavioral Sciences, Tilburg University, Tilburg, Netherlands.ORCID https://orcid.org/0000-0001-6675-9018
Lakshmi Balachandran NairDepartment of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Tilburg, Netherlands.
Irene KlugkistDepartment of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Tilburg, Netherlands.
Floryt van WeselDepartment of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Tilburg, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In mixed methods reviewing, data from quantitative and qualitative studies are combined at the review level. One possible way to combine findings of quantitative and qualitative studies is to quantitize qualitative findings prior to their incorporation in a quantitative review. There are only a few examples of the quantification of qualitative findings within this context. This study adds to current research on mixed methods review methodology by reporting the pilot implementation of a new four-step quantitizing approach. We report how we extract and quantitize the strength of relationships found in qualitative studies by assigning correlations to vague quantifiers in text fragments. This article describes (a) how the analysis is prepared; (b) how vague quantifiers in text fragments are organized and transformed to numerical values; (c) how qualitative studies as a whole are assigned effect sizes; and (d) how the overall mean effects size and variance can be calculated. The pilot implementation shows how findings from 26 primary qualitative studies are transformed into mean effect sizes and corresponding variances.

Indexed as

Qualitative ResearchResearch DesignBayes TheoremData Interpretation, StatisticalHumansModels, StatisticalModels, TheoreticalPilot Projectsmixed methods reviewingquantitizingsystematic review methodologyvague quantifiers

Identifiers

PMID32104971
PMCPMC7317911

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.