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Record W6943847307 · doi:10.17605/osf.io/wf28d

Intolerance of uncertainty – the rise and spread of a measure to a construct: A protocol for a systematic bibliometric review

2023· other· en· W6943847307 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2023
Typeother
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
Fundersnot available
KeywordsWorryAnxietyVariance (accounting)PsychometricsScale (ratio)Eating disordersProtocol (science)Self-report study

Abstract

fetched live from OpenAlex

The Intolerance of Uncertainty Scale (IUS, Freeston et al., 1994) was developed by a team at Université Laval (Québec, Canada) in order to develop an understanding of worry and GAD. The original 27-item scale has been translated into several different languages, briefer versions have been developed (e.g., Carleton et al., 2007), and adapted for use with children and young people (see Shihata et al., 2016). Although the IUS has been the most widely used scale, other similar measures exist. In a study of three measures, Fergus (2013) found significant overlap, although each measure also accounted for unique variance in measures of distress. In terms of key reviews, Carleton (2012) reviewed the changing definitions of IU up until that point, indicating perhaps that IU was a measure in search of a construct. Birrell et al. (2011) reviewed the different factor analytic studies up until that point and conclude there appear to be two factors consistently measured by the IUS, namely, prospective IU (also described as desire for predictability) and inhibitory IU (also known as behavioral paralysis). The replicated relationships of IU with other disorders have been subject to meta-analysis, namely for anxiety disorders and depression (McEvoy, Hyett et al., 2019), eating disorders (Brown et al., 2017), and anxiety and worry in young people (Osmanağaoğlu, 2018). Importantly, McEvoy, Hyett et al. (2019) also considered a range of moderators (e.g., age, gender, clinical status, etc.) and conclude that these generally do not affect these relationships to any great extent. Other reviews address IU in relation to neural and psychophysiological correlates (Tanovic et al., 2018) and threat extinction training (Morriss et al., 2021), while Rosser (2019) reviews research on IU and temporal precedence and causality. Carleton (2016) reviews models of uncertainty while Milne et al., (2019) review the relationship between threat and uncertainty in anxiety. Broader treatment implications are considered by Einstein (2014) and Jacoby (2020), while Wilson et al. (2023) review evidence for change in IU in psychosocial treatments for GAD. Finally, McEvoy, Carleton et al. (2019) consider an agenda for research into IU as a transdiagnostic construct in terms of the Research Domain Criteria (RDoC, Insel et al., 2010). The IU construct is essentially defined by the initial measure and later variants and developments. Although the original focus was GAD, the interest then spread to other forms of anxiety and OCD, and then other mental health problems (e.g., depression, psychosis, eating disorders) and more recently to PTSD so it is clearly a transdiagnostic construct in mental health. It has also been increasingly implicated in neuro-divergency (ADHD and especially autism). Further, IU has been implicated in adaptation among informal carers, to physical health problems, as well as racism and discrimination, medical training, tourism, gun purchases, the H1N1 pandemic, climate change, etc. Thus, IU has increasingly been shown to have trans-situational relevance. Further, while the bulk of the research in the first 25-years was mostly in English-speaking and Northern and Western European countries (Sullivan et al., 2023), in the last few years, and especially during the pandemic, the construct has been increasingly researched in many parts of Asia, Eastern and Southern Europe, South America and Africa. The aim of this review is to take a historical bibliometric perspective (Donthu et al., 2021) and systematically track the rise and spread of IU from a putative specific factor in one of several models of a single disorder, namely, GAD (Behar et al. 2009; Freeston, 2022) to a transdiagnostic, trans-situational and increasingly relevant construct in international and cross-cultural contexts

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.076
metaresearch head score (Gemma)0.142
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.963
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.142
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0190.017
Bibliometrics0.0370.039
Science and technology studies0.0040.004
Scholarly communication0.0080.008
Open science0.0050.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0560.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.088
GPT teacher head0.467
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainMethods
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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