Evidence map›Paper›PMID 38869735›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2024

Assessing and accounting for measurement in intensive longitudinal studies: current practices, considerations, and avenues for improvement.

Leonie V D E Vogelsmeier, Joran Jongerling, Esther Maassen

Abstract read
In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Article
  3. Mapping methods and tools for measuring patient experience in oncology settings: a scoping review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  4. A primer on intensive longitudinal psychometrics.Behavior research methods · 2026
    Review
  5. Article
  6. 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

3 authors.

Leonie V D E Vogelsmeier *Department of Methodology and Statistics, Tilburg University, PO Box 90153, 5000 LE, Tilburg, The Netherlands. l.v.d.e.vogelsmeier@tilburguniversity.edu.ORCID http://orcid.org/0000-0002-1666-7112
Joran Jongerling *Department of Methodology and Statistics, Tilburg University, PO Box 90153, 5000 LE, Tilburg, The Netherlands.ORCID http://orcid.org/0000-0001-5697-1381
Esther Maassen *Department of Methodology and Statistics, Tilburg University, PO Box 90153, 5000 LE, Tilburg, The Netherlands.ORCID http://orcid.org/0000-0003-3288-5424

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIntensive longitudinal studies, in which participants complete questionnaires multiple times a day over an extended period, are increasingly popular in the social sciences in general and quality-of-life research in particular. The intensive longitudinal methods allow for studying the dynamics of constructs (e.g., how much patient-reported outcomes vary across time). These methods promise higher ecological validity and lower recall bias than traditional methods that question participants only once, since the high frequency means that participants complete questionnaires in their everyday lives and do not have to retrospectively report about a large time interval. However, to ensure the validity of the results obtained from analyzing the intensive longitudinal data (ILD), greater awareness and understanding of appropriate measurement practices are needed.

methodWe surveyed 42 researchers experienced with ILD regarding their measurement practices and reasons for suboptimal practices.

resultsResults showed that researchers typically do not use measures validated specifically for ILD. Participants assessing the psychometric properties and invariance of measures in their current studies was even less common, as was accounting for these properties when analyzing dynamics. This was mainly because participants did not have the necessary knowledge to conduct these assessments or were unaware of their importance for drawing valid inferences. Open science practices, in contrast, appear reasonably well ingrained in ILD studies.

conclusionMeasurement practices in ILD still need improvement in some key areas; we provide recommendations in order to create a solid foundation for measuring and analyzing psychological constructs.

Indexed as

PsychometricsQuality of LifeFemaleHumansLongitudinal StudiesMaleReproducibility of ResultsResearch DesignSurveys and QuestionnairesExperience sampling methodologyInvarianceMeasurementReliability

Identifiers

PMID38869735
PMCPMC11286633

What OpenQuestion holds

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LicenceCC BY
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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.