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Record W4361000302 · doi:10.1002/ejp.2115

Authors' reply to the comment ‘The importance of measurement content and study design’ by Veirman et al. (2023)

2023· letter· en· W4361000302 on OpenAlexaboutno aff
Mojtaba Habibi, Pardis Salehi Yegaei, Saber Azami‐Aghdash, Mark A. Lumley

Bibliographic record

VenueEuropean Journal of Pain · 2023
Typeletter
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyFacet (psychology)Toronto Alexithymia ScaleFibromyalgiaReliability (semiconductor)Scale (ratio)Clinical psychologySocial psychologyPersonalityBig Five personality traitsPsychiatry

Abstract

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We read with interest the issues raised by Veirman et al. (2023) about our article, ‘The Relationship of Alexithymia to Pain and Other Symptoms in Fibromyalgia: A Systematic Review and Meta-analysis’ (Habibi Asgarabad et al., 2023). Here, we reflect on some of the points they raised—agreeing with some and challenging others. Regarding the assessment of alexithymia with the TAS, we agree that self-report scales have their limitations, and various criticisms have long been made about the self-report of alexithymia generally and of the TAS specifically. Although a few non-self-report measures of alexithymia and emotional awareness exist, the vast majority of studies have used the TAS for assessing alexithymia, as noted in a larger review and meta-analysis of the role of alexithymia in chronic pain (i.e., Aaron et al., 2019). Also, there are long-discussed concerns about the reliability and validity of the externally oriented thinking facet of the TAS, although the scale developers have advocated for interpreting only the full scale rather than the separate facets. Importantly, we noted all of these concerns about the TAS in our article's discussion, appropriately reporting the limitations and pointing to alterative interpretations, including the recommendation that future studies assess alexithymia using observer-rated measures or structured interviews. But our larger goal was to review and meta-analyse the literature as it currently exists, despite its measurement limitations. Veirman et al. (2023) remind us to be mindful of the fact that validity of a measure may vary across populations and contexts, that we should be cautious when using the TAS in people with medical conditions and that some of its items might better reflect constructs other than alexithymia. We generally agree with these concerns, although we find it ironic that they justify these points by referring to their own research (Veirman et al., 2021), which was conducted on a small sample of healthy college students, not people with pain or health problems, which was the focus of our review. Nonetheless, it is noteworthy that Veirman et al. (2021) found support for the validity of two facets of the TAS (difficulty identifying feeling and difficulty describing feelings) in their sample of students. We also agree with the need for caution regarding the interpretation of the observed cross-sectional associations as indicating that alexithymia is a risk factor for FM, and we noted in our discussion that there are alternative interpretations (third-variable and reverse causality). We agree that prospective studies are desirable, and there exist prospective studies that support the view that various emotionally salient problems or emotionally dysregulating events predict later widespread pain and FM. More generally, there is evidence for the role of traumatic events, post-traumatic stress disorder and other emotion dysregulations as contributing to FM and related centralized problems. We consider alexithymia to be one common manifestation of emotional dysregulation; thus, although prospective research on alexithymia per se as a risk for FM may be lacking, there is substantial research on related processes. Furthermore, there are several valuable integrative models of the development of FM, and disturbed emotional processes such as alexithymia play a role in such models—albeit certainly not the only role (Pinto et al., 2023). Yet, even prospective studies are limited. Not only are they difficult to conduct well and require years to complete, but they remain correlational and susceptible to uncontrolled variables, competing constructs and complex iterative processes. Prospective studies commonly yield continued questions and debate, which can lead to the usual recommendation of ‘more research is needed’. Rather than waiting for decades for a sufficient number of prospective studies of alexithymia and FM to be conducted, we recommend another approach to test possible causality of a risk factor for a health problem: one can experimentally reduce or eliminate the risk factor and determine the effects on the health problem. Indeed, our recommendation for using emotion-focused therapies for FM follows this logic. It also has the advantage of actually trying to help people with FM now, rather than wait for the slow accretion of supportive correlational evidence before (possibly) intervening. Intervention research can and should be conducted both to test hypotheses and help people in need—sooner rather than later. Finally, we challenge the authors' core thesis: ‘Extraordinary claims require extraordinary evidence’. Did we make an ‘extraordinary claim’? Such a charge would fit if we claimed the validity of supernatural cures, extrasensory perception or alien abduction. Few scholars, however, find ‘extraordinary’ the claim that problematic emotional processes, often stemming from difficult developmental experiences, contribute to many cases of FM and related centralized problems, and research should test interventions to address these problems. All authors declare no conflict of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.055
metaresearch head score (Gemma)0.318
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.055
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.318
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0030.003
Science and technology studies0.0050.008
Scholarly communication0.0070.009
Open science0.0060.006
Research integrity0.0410.059
Insufficient payload (model declined to judge)0.0110.011

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 head0.111
GPT teacher head0.303
Teacher spread0.191 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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