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REVIEW 3 major objections 4 minor 53 references

The influence of diversity on the measurement of functional impairment: An international validation of the Amsterdam IADL Questionnaire in 8 countries

T0 review · 3 major / 4 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read Across 3,571 people in eight Western countries, the Amsterdam IADL Questionnaire shows no indication of clinically relevant item bias for age, gender, education, or culture.

desk verdict Solid large-sample DIF validation of the A-IADL-Q-SV, but the 'no meaningful bias' conclusion rests on a cutoff just above all observed effects, and the paper lacks the sensitivity analysis to make that claim stick. read the letter →

arxiv 1909.01915 v2 pith:XLT7FGL3 submitted 2019-09-04 q-bio.NC stat.AP

Mark A. Dubbelman , Merike Verrijp , David Facal , Gonzalo Sánchez-Benavides , Laura J.E. Brown , Wiesje M. van der Flier , Hanna Jokinen , Athene Lee
show 13 more authors
Iracema Leroi Cristina Lojo-Seoane Vuk Milosevic José Luís Molinuevo Arturo X. Pereiro Rozas Craig Ritchie Stephen Salloway Gemma Stringer Stelios Zygouris Bruno Dubois Stéphane Epelbaum Philip Scheltens Sietske A.M. Sikkes
This is my paper · ORCID
classification q-bio.NCstat.AP
keywords instrumentalactivitiesofdailylivingdementiafunctionalimpairmentdifferentialitemfunctioningbiascross-culturalvalidationAmsterdamIADLQuestionnaireresponsetheory
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper asks whether a widely used informant questionnaire of everyday functioning in dementia, the Amsterdam IADL Questionnaire (A-IADL-Q), measures the same thing across different kinds of people. Using data from 3,571 individuals in eight Western countries, the authors tested whether items function differently by country, age, gender, or education, a form of measurement bias called differential item functioning. They report that although a few items show statistically significant differences (for example, technology-related activities are endorsed less in some Mediterranean countries, and home-repair or washing-machine items split by gender), the effect sizes were uniformly small, with no item reaching the pre-set threshold for practically meaningful bias. The impact on total $T$-scores was minimal, including for the four items in the long version that were flagged for country bias. The paper concludes that the A-IADL-Q, and particularly its short version, yields functional impairment scores that can be compared across these demographic and cultural groups without adjustment.

What carries the argument

The central machinery is differential item functioning (DIF) analysis on item-level responses, using ordinal logistic regression with nested model comparisons, alongside a McFadden pseudo-$R^2$ effect size cutoff of .035 (moderate .035–.070, large > .070) to separate statistical from practically meaningful bias. Monte Carlo simulations under a no-DIF null generated empirical effect-size thresholds, and the authors examined whether DIF materially changed IRT-based $T$-scores, which were calibrated to a mean of 50 with a standard deviation of 10 in a Dutch memory-clinic population.

What would settle it

Re-run the same ordinal logistic regression DIF analysis on the A-IADL-Q-SV in a sample that includes people with fewer than six years of formal education and in non-Western countries; if multiple items exceed $\Delta R^2 = .035$ and correcting for DIF shifts mean $T$-scores by more than 5 points (half a standard deviation), the no-bias conclusion would be contradicted.

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Extended reading notes

Core claim

The paper's central claim is that clinically relevant item bias in the Amsterdam IADL Questionnaire is absent: no indication was found that age, gender, education, or national culture distorts the measurement of functional impairment in a way that would change conclusions drawn from the $T$-score. The evidence is that $\Delta R^2$ effect sizes never exceeded .034 across all items and comparisons in the short version, and the four items with meaningful DIF in the original version (Spanish 'using the washing machine', 'making appointments', 'playing card and board games'; French 'functioning adequately at work') shifted mean scores by no more than 0.16 points on the $T$-scale. The paper therefore argues that the A-IADL-Q-SV $T$-scores need no correction for these diversity factors and supports the instrument as an outcome measure for international dementia research and trials.

Load-bearing premise

The conclusion of no clinically relevant bias rests on a pre-set $\Delta R^2$ cutoff of .035 for meaningful differential item functioning and on trait estimates that come from a Dutch memory-clinic calibration; if that cutoff is too lenient or those trait estimates do not generalize, under-detection of item bias is possible.

Editorial extensions

If this is right

  • The short version's $T$-scores can be compared across the eight countries and across age, gender, and education groups without DIF-based adjustment.
  • The findings support using the A-IADL-Q as an outcome measure in multinational clinical trials where functional impairment is a key endpoint.
  • The four country-flagged items in the original version have a negligible effect on total scores, so historical data from the long version remain usable.
  • Correlations with cognitive and functional measures were similar to the original Dutch validation, reinforcing the instrument's construct validity in new settings.
  • The cross-cultural adaptation process (forward and backward translation, expert review, cognitive interviews) likely contributed to the small number of biased items.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper does not claim that the .035 threshold is a law of nature; its own simulations produced effect-size thresholds up to .018, so a stricter cutoff would flag more items. A user who cares about fine-grained score differences should check whether lowering the threshold in these data changes any clinical decision.
  • The conclusion applies to Western countries with mostly well-educated participants; it does not extend to non-Western cultures, ethnic or racial groups, or people with very little formal education, where other IADL instruments have shown response bias.
  • Because endorsement gaps were largest for technology-related activities (computers, ATMs) and household tasks, the item parameters could drift over time as technology adoption and gender roles change; a future replication using the same DIF procedure would reveal whether the no-bias result is stable across decades.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The paper investigates whether the Amsterdam IADL Questionnaire (A-IADL-Q) and its short version (A-IADL-Q-SV) exhibit item bias due to country, age, gender, and education in a sample of 3,571 participants from eight Western countries. Differential item functioning (DIF) is assessed by ordinal logistic regression, using a McFadden ΔR2 threshold of .035 for practically meaningful DIF, supplemented by Monte Carlo simulations. The authors report SV effect sizes in the range .000–.034, below the threshold, while four items in the original version show moderate DIF for nationality with negligible impact on T-scores. They conclude that there is no indication of clinically relevant bias and that A-IADL-Q scores are comparable across these diversity factors.

Significance. If the conclusion holds, the study provides valuable evidence for the cross-cultural validity of a functional outcome measure used in dementia research, supporting the use of the A-IADL-Q-SV in international trials. The study has notable strengths: a large multi-country sample, a standard DIF methodology, the use of Monte Carlo simulations to estimate null thresholds, and explicit effect-size criteria. However, the central no-bias claim depends on a single cutoff, and the reported analysis does not establish robustness to alternative thresholds. The manuscript also contains an inconsistency in the reported number of DIF comparisons. These issues are addressable and should be resolved before the claim is accepted.

major comments (3)
  1. [Results 3.2 / Methods 2.2] The conclusion that the A-IADL-Q-SV has no practically meaningful item bias is operationalized entirely by the fixed McFadden ΔR2 ≥ .035 cutoff in Methods 2.2. In Results 3.2, the empirical SV ΔR2 values range from .000 to .034, so the main finding is that no item exceeded a threshold set only 0.001 above the largest observed effect. The Monte Carlo simulations produced 99th-percentile null thresholds up to .018, and the text states that lowering the threshold would lead to more items being flagged. The authors do not report how many items would be flagged, for which comparisons, or whether the cumulative effect of those items would shift T-scores by a clinically meaningful amount. Because the empirical distribution is packed against the chosen cutoff, the no-bias conclusion is not invariant to a defensible alternative criterion such as the simulation-based threshold. Please provide the number of items flagged using the simulation-based threshold and an impact analysis for the SV analogous to the original-version analysis in Section 3.2.
  2. [Results 3.2 / Table 1] The reported counts of analyzed item-factor combinations are inconsistent. For the SV, 272 out of 300 comparisons is consistent with 30 items × 10 comparisons (7 countries plus age, gender, and education). For the original version, 437 out of 490 comparisons is consistent with 70 items × 7 country comparisons only, yet the text in Section 3.2 reports effects for age, gender, and education for the original version ('The effects for age, gender and education were again small'). Please clarify which factors were analyzed for each version and provide the total number of comparisons per version so that the denominators can be verified.
  3. [Methods 2.1.1 / Results 3.2] The IRT-based trait estimates used for matching in the DIF analysis were calibrated in a Dutch memory-clinic population. DIF detection depends on this anchor metric; if the latent trait metric is not invariant across national samples or across the diagnostic spectrum included here, DIF could be under- or over-detected. The manuscript does not explicitly discuss this as a limitation of the cross-cultural no-bias claim. Please discuss whether the Dutch calibration could affect the generalizability of the conclusion, and if feasible, perform a sensitivity analysis with an alternative anchor metric, such as recalibration on the combined sample or fixed-item anchoring.
minor comments (4)
  1. [Abstract] The abstract reports an effect-size range of '0–0.03' for the SV, while Results 3.2 reports '.000–.034'; please align these values.
  2. [Discussion, paragraph 6] The sentence 'We used DIF, which is a powerful procedure to detect variance in measurement between groups on an item level and was possible as a result of the IRT scoring method' contains an ungrammatical phrase; 'and was possible' should read 'and which was possible.'
  3. [Results 3.1] The text states 'In Mediterranean countries, it seemed people used computers less often than in Northern European countries and America,' but Serbia, which is included in the analysis, is not typically considered Mediterranean; please rephrase to 'Southern and Eastern European countries' or list the specific countries.
  4. [Methods 2.2] The sentence 'OLR has previously been shown to be superior the Mantel Haenszel procedure' is missing the preposition 'to'; it should read 'superior to the Mantel-Haenszel procedure.'

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the DIF conclusion is an empirical finding from multinational data with a literature-based cutoff, not a reduction of outputs to inputs.

full rationale

This is an empirical validation study. The central claim—that the A-IADL-Q shows no practically meaningful item bias across country, age, gender, and education—is estimated from observed multinational data using ordinal logistic regression implemented in the lordif package, not derived from a fitted parameter that already encodes the conclusion. The McFadden ΔR2 = .035 cutoff is adopted from published DIF effect-size recommendations (refs 43–45) and is not calibrated to the current dataset; the Monte Carlo simulations are used only to characterize null variability, and the authors explicitly concede in the Limitations that lowering the threshold would flag more items, which undercuts any suggestion that the threshold was chosen to force the result. The IRT T-scores calibrated in earlier Dutch work are an input measurement model, but the DIF analysis is exactly an independent check of that model's invariance across groups; no equation in the paper makes the empirical ΔR2 values equal the threshold or makes the T-score impact minimal by construction. Self-citations (refs 29–33) concern questionnaire development, validation, and the short-version rationale; they do not themselves supply the multinational DIF estimates or the conclusion of absent bias. The robustness concern about the cutoff is a statistical/correctness issue, not circularity. No exhibited reduction exists, so the appropriate finding is no significant circularity.

Assumptions & free parameters 0 free parameters · 4 assumptions · 0 invented entities

The study introduces no fitted parameters, invented constructs, or circular derivation. The central claim rests on standard psychometric modeling assumptions, the authors' operationalization of culture as country, the generalizability of the Dutch IRT calibration, and the chosen DIF threshold. None of these are unique to the paper, but the threshold and calibration assumptions are load-bearing and the authors themselves express caution about them.

assumptions (4)
  • domain assumption The A-IADL-Q measures a unidimensional latent trait (IADL functioning) and satisfies IRT assumptions of local independence and monotonicity.
    Invoked implicitly by using IRT-based T-scores and DIF analysis (Methods 2.1.1, 2.2). If the instrument is not unidimensional, DIF results could be spurious.
  • domain assumption Country of residence is a valid proxy for cultural differences.
    The authors operationalize culture as country (Introduction, last paragraph; Discussion limitations: 'we use the term culture to refer to each country's national culture').
  • domain assumption The latent trait estimates from the Dutch-calibrated IRT model are applicable to all groups before DIF correction.
    The T-scores were calibrated in a memory-clinic population (Methods 2.1.1); DIF analysis depends on these estimates, and the conclusion of no bias rests on the trait estimates being comparable.
  • domain assumption A McFadden pseudo-R2 change of .035 is the correct threshold for practically meaningful DIF.
    Taken from Jodoin and Gierl (ref 43); the authors note that Monte Carlo simulations suggest this threshold may be high (Discussion, limitations, third limitation).

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Cite this review

Pith. "Pith review of The influence of diversity on the measurement of functional impairment: An international validation of the Amsterdam IADL Questionnaire in 8 countries." pith.science (2026). https://pith.science/paper/XLT7FGL3

@misc{pith2026190901915,
  author       = {Pith},
  title        = {Pith review of: The influence of diversity on the measurement of functional impairment: An international validation of the Amsterdam IADL Questionnaire in 8 countries},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XLT7FGL3}},
  note         = {Machine review of arXiv:1909.01915}
}
read the original abstract

INTRODUCTION: To understand the potential influence of diversity on the measurement of functional impairment in dementia, we aimed to investigate possible bias caused by age, gender, education, and cultural differences. METHODS: 3,571 individuals (67.1 {\pm} 9.5 years old, 44.7% female) from the Netherlands, Spain, France, United States, United Kingdom, Greece, Serbia and Finland were included. Functional impairment was measured using the Amsterdam IADL Questionnaire. Item bias was assessed using differential item functioning (DIF) analysis. RESULTS: There were some differences in activity endorsement. A few items showed statistically significant DIF. However, there was no evidence of meaningful item bias: effect sizes were low ({\Delta}R2 range 0-0.03). Impact on total scores was minimal. DISCUSSION: The results imply a limited bias for age, gender, education and culture in the measurement of functional impairment. This study provides an important step in recognizing the potential influence of diversity on primary outcomes in dementia research.

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Reference graph

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