Evidence map›Paper›PMID 26510822›Full record

ReviewBMC research notes2015

A critical review of scoring options for clinical measurement tools.

Maria Laura Avila, Jennifer Stinson, Alex Kiss, Leonardo R Brandão, Elizabeth Uleryk, Brian M Feldman

Abstract readReview
In one paragraph

Review in BMC research notes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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

  1. Measuring shared decision making in oncology: Development and first testing of the iSHAREpatient and iSHAREphysician questionnaires.Health expectations : an international journal of public participation in health care and health policy · 2020
    Pooled it
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  3. The COSMIN Clubs initiative: improving health measurement through collaborative learning.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
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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

6 authors.

Maria Laura AvilaDepartment of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. laura.avila@sickkids.ca.
Jennifer StinsonLawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada. jennifer.stinson@sickkids.ca.
Alex KissDepartment of Research Design and Biostatistics, Institute for Clinical Evaluative Sciences, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. alex.kiss@ices.on.ca.
Leonardo R BrandãoDepartment of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. leonardo.brandao@sickkids.ca.
Elizabeth UlerykDepartment of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. jasnagora@rogers.ca.
Brian M FeldmanDepartment of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. brian.feldman@sickkids.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this paper is twofold: (1) to describe the fundamental differences between formative and reflective measurement models, and (2) to review the options proposed in the literature to obtain overall instrument summary scores, with a particular focus on formative models.

methodsAn extensive literature search was conducted using the following databases: MEDLINE, EMBASE, PsycINFO, CINAHL and ABI/INFORM, using "formative" and "reflective" as text words; relevant articles' reference lists were hand searched.

resultsReflective models are most frequently scored by means of simple summation, which is consistent with the theory underlying these models. However, our review suggests that formative models might be better summarized using weighted combinations of indicators, since each indicator captures unique features of the underlying construct. For this purpose, indicator weights have been obtained using choice-based, statistical, researcher-based, and combined approaches.

conclusionWhereas simple summation is a theoretically justified scoring system for reflective measurement models, formative measures likely benefit from the use of weighted scores that preserve the contribution of each of the aspects of the construct.

Indexed as

Health Status IndicatorsLogistic ModelsResearch DesignCausalityHumansPsychometricsSemanticsTerminology as Topic

Identifiers

PMID26510822
PMCPMC4624594

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.