The study proposes a definition of organizational humanization as the affirmation of autonomy, individuality and dignity within an organization. This framing distinguishes humanization from the absence of dehumanization. An organization might avoid overtly disrespectful treatment while remaining impersonal or inattentive, but a lack of denial does not establish that employees’ agency, distinctiveness or worth has been actively recognized. Autonomy in the OHS means meaningful influence over how, when and by what criteria organizational activities are performed, rather than complete freedom from the constraints of a role. Individuality concerns whether a person’s uniqueness is valued, embraced and allowed to be expressed. Dignity concerns self- and other-recognized worth through respectful interaction, recognition of contributions and equal treatment.

The OHS was not created as an unrelated theoretical domain. Its items were adapted from established instruments measuring work autonomy, work-group inclusion and workplace dignity, with three items assigned to each dimension. Autonomy items addressed influence over methods, scheduling and evaluation. Individuality items concerned the valuing and embracing of uniqueness and its permitted expression, drawing primarily on the Work Group Inclusion Measure. Dignity items covered respectful interaction, respect for contribution and equal respect, corresponding to components of the Workplace Dignity Scale. Wording was broadened from “work” to “activities” to permit potential use in non-work organizations, and factor-specific stems were introduced. The researchers did not obtain formal ratings from an independent expert panel, leaving further work needed on the adapted items’ relevance, clarity and coverage.

Participants were recruited through the Prolific crowdsourcing platform, with the survey administered through Qualtrics. Eligibility required full-time employment in the United States and at least one year in the current organization, a criterion intended to ensure sustained exposure to organizational practices and interactions. The questionnaire contained 57 items across six measures, five demographic questions and six attention checks; researchers randomized the order of measures and items. Of 501 completed responses, 54 were excluded for straightlining across three or more scales and six more for failing an attention check, leaving 441 participants in the primary analysis. This sample included 255 men, 183 women and three participants who selected “prefer not to say,” with representation across age groups, job levels, industries and organization sizes.

Confirmatory factor analysis supported the proposed higher-order structure. A one-factor model fit poorly, producing a comparative fit index of 0.82. The correlated three-factor and second-order models had identical fit because they are mathematically equivalent when a second-order factor contains exactly three first-order factors; both produced a comparative fit index of 0.99, a Tucker-Lewis index of 0.98, a root mean square error of approximation of 0.05 and a standardized root mean square residual of 0.03. A bifactor model also fit well. Standardized loadings for the nine individual items ranged from 0.79 to 0.93, while second-order loadings were 0.83 for autonomy, 0.93 for individuality and 0.80 for dignity. The bifactor analysis yielded explained common variance of 0.73 and omega hierarchical of 0.85, supporting interpretation of a general humanization score alongside the three subscales.

Internal consistency was strong across the instrument. For the full nine-item OHS, Cronbach’s alpha and McDonald’s omega were both 0.93; for the autonomy, individuality and dignity subscales, both estimates ranged from 0.86 to 0.93. Convergent validity also appeared. The OHS autonomy subscale correlated most strongly with the Work Autonomy Scales, at r = 0.79, while OHS dignity correlated most strongly with the Workplace Dignity Scale, at r = 0.85. The Work Group Inclusion Measure correlated equally with OHS individuality and OHS dignity, at r = 0.76 for each, indicating substantial convergence with the intended dimension without complete separation from related content. Average variance extracted was 0.67 for autonomy, 0.81 for individuality and 0.73 for dignity. Heterotrait-monotrait ratios of 0.66 to 0.78 remained below the 0.85 criterion, providing evidence that the subscales were empirically distinguishable while sharing a broader structure.

Structural equation models examined associations with workplace social capital, which includes networks, norms and trust that facilitate coordination and cooperation, and work engagement, measured through vigor, dedication and absorption. In the primary second-order model, the humanization factor was associated with social capital at a standardized beta of 0.87 and with engagement at beta = 0.69, both with p < 0.001. The model accounted for 75% of the variance in social capital and 47% of the variance in engagement. When the general humanization factor was modeled alongside autonomy, individuality and dignity, their shared component remained strongly associated with both outcomes. Dignity retained an additional association with social capital at beta = 0.37, while unique paths for autonomy and individuality were not significant in that specification. These cross-sectional self-report results do not establish causal direction or rule out reciprocal relationships among the constructs.

Measurement appeared comparable across several broad demographic and organizational divisions. Configural, metric and scalar invariance models supported item-level comparability across age groups, sex, management versus non-management positions, and organizations with 1,000 or fewer versus more than 1,000 employees. Industry-level invariance was not tested because group sizes were too small to combine defensibly, and equality of second-order loadings was not assessed. A sensitivity analysis that retained the 54 responses excluded for straightlining, producing a sample of 494, preserved the principal factor, reliability, validity and association results. The scale was administered only once, however, so its temporal stability and test-retest reliability remain unknown.

The most important caution concerns shared response method. The same participants completed the humanization, social-capital and engagement measures, using five-point agreement scales for the OHS and social capital and a seven-point frequency scale for engagement. A supplementary model allowing an added factor to load freely on all 20 indicators produced the best global fit and sharply reduced the humanization–social-capital path from beta = 0.866 to 0.041, with a 95% confidence interval of −0.259 to 0.341. A more constrained model, allowing the added factor to operate only across the 17 agreement-format indicators, preserved the primary estimates, including beta = 0.859 for social capital and beta = 0.687 for engagement. Neither specification proves that the added factor is purely methodological, and overlapping content between humanization and social capital may contribute substantively to their association. The magnitude of the relationship therefore remains unresolved.

For researchers, the OHS offers a compact starting point for studying whether employees perceive their autonomy, individuality and dignity as affirmed, including in settings involving restructuring, growth or artificial-intelligence adoption. The study itself did not measure AI implementation or organizational resilience, and its findings cannot show that a particular policy raises humanization, social capital or engagement. The scale records individual perceptions rather than independently observed practices, so its scores should not be interpreted as a direct organizational audit. Future studies should replicate the factor structure across countries, industries and employment arrangements, test the scale in non-work organizations, compare it directly with established dehumanization measures, obtain expert ratings of its items and use longitudinal, multimethod designs to examine change and temporal stability. The central scientific advance is a testable framework for examining whether organizations affirm people as autonomous, distinct and dignified, rather than merely avoiding obvious mistreatment.

Subject of Research: Initial validation of a nine-item measure of perceived organizational humanization

Article Title: Organizational humanization: definition and measurement

Article References: Stroop, K. D. (2026). Organizational humanization: definition and measurement. Frontiers in Psychology, 17, Article 1906924. https://doi.org/10.3389/fpsyg.2026.1906924

Image Credits: AI Generated

DOI: 10.3389/fpsyg.2026.1906924

Keywords: organizational psychology, workplace humanization, measurement, autonomy, individuality, workplace dignity, psychometrics, work engagement, social capital, employee perceptions, Organizational, humanization

Such instruments assess a wider range of emotional, behavioral and social functioning, but their ADHD-related subscales cannot be assumed to perform as well as the overall scale. The authors therefore evaluated each relevant subscale separately, consistent with version 2.0 of the COSMIN guidelines. Following PRISMA 2020 guidance, researchers searched PubMed, Web of Science, Scopus and ProQuest from each database’s inception through December 1, 2025.

The search was supplemented by citation tracking and reference chaining. Two reviewers independently screened records, extracted data, evaluated risk of bias, rated measurement properties and synthesized evidence, resolving discrepancies by consensus. Methodological quality was assessed with the COSMIN Risk of Bias Checklist, measurement results were judged against updated criteria for good measurement properties, and evidence quality was graded using an adapted GRADE approach.

The original PROSPERO protocol, registered as CRD420250655032, evaluated broad-band scales as whole instruments. During the review, the unit of analysis was changed to individual ADHD-related subscales in line with updated COSMIN guidance, with no other substantive protocol change reported. The protocol change was documented to preserve methodological transparency and reproducibility.

For the SDQ Hyperactivity-Inattention subscale, structural validity and internal consistency received sufficient ratings supported by moderate-quality evidence. Cross-cultural validity or measurement invariance, reliability, and convergent and discriminant validity also received sufficient ratings supported by high-quality evidence. Content validity was supported only by low-quality evidence, while measurement error and responsiveness were not evaluated.

The reviewers described this profile as comparatively favorable but cautioned that it did not establish the SDQ’s overall superiority for ADHD assessment. The Child and Adolescent Disruptive Behavior Inventory (CADBI) Inattention and Hyperactivity/Impulsivity subscales showed sufficient results for structural and cross-cultural validity with high-quality evidence and for internal consistency with moderate-quality evidence. The Five to Fifteen (FTF) Attention and Hyperactive/Impulsive subscales had sufficient structural validity and internal consistency results supported by moderate-quality evidence.

Single studies also reported sufficient test–retest reliability and convergent validity for the FTF subscales. The Child and Adolescent Behavior Inventory (CABI) Attention Deficit and Hyperactivity subscale had high-quality evidence for reliability, whereas its structural validity and internal consistency findings were supported by low-quality evidence. For the CBCL Attention Problems subscale, two studies with very good methodological quality found insufficient measurement invariance between US and Australian populations and between Dutch and Israeli populations.

The cross-cultural evidence was graded high quality. Under COSMIN criteria, this insufficient performance supported a recommendation against use. The authors advised caution for users outside North America while noting that the review evaluated the CBCL Attention Problems syndrome scale rather than its separate DSM-oriented ADHD scale.

Evidence for several other instruments was limited or unsatisfactory. ANSER-PQ, CBAI, YI-4 and DSMD were each represented by one study that did not meet the minimum methodological threshold for evidence synthesis, so their results were described separately. The ECI-4 was supported by multiple studies examining internal consistency and convergent and discriminant validity.

Its content-validity evidence was low quality because no relevant development or content-validity studies were identified, while its internal-consistency evidence was downgraded because structural-validity studies were lacking. The ABC and CSI-4 were each represented by two studies conducted by the same research group. Across the 36 included studies, internal consistency was examined in 28, structural validity and convergent validity in 16 each, discriminant validity in 13, cross-cultural validity or measurement invariance in nine, and test–retest reliability in eight.

Content validity, criterion validity, measurement error and responsiveness remained important gaps. The limited quantity of research and heterogeneous methodological quality prevented any instrument from being assessed across all COSMIN properties. Restriction to English-language publications may also have constrained the assessment of cross-cultural validity and measurement invariance.

Other limitations concerned the COSMIN framework’s treatment of some analytical choices, including rotation methods and eigenvalue criteria in exploratory factor analyses, and the need for reviewer judgment when development evidence was incomplete. For several older instruments, unavailable manuals or sparse original reports also required greater reviewer judgment for content-validity ratings.

Subject of Research: COSMIN-based evaluation of ADHD-related subscales in broad-band behavioral rating instruments for children

Article Title: How do the measurement properties of the broad-band scales for attention-deficit/hyperactivity disorder in children perform based on the COSMIN guidelines?

Article References: Chen, Y., Cai, Q., Hu, S., Zhao, Z., Wang, J., & Niu, L. (2026). How do the measurement properties of the broad-band scales for attention-deficit/hyperactivity disorder in children perform based on the COSMIN guidelines?. BMC Pediatrics, 26(1), Article 907. https://doi.org/10.1186/s12887-026-07661-1

Image Credits: AI Generated

DOI: 10.1186/s12887-026-07661-1

Keywords: ADHD, children, behavioral rating scales, COSMIN, measurement properties, psychometrics, SDQ, CBCL, systematic review, cross-cultural validity, measurement, properties

Researchers used baseline data from the FLOURISH Phase 2 trial. Participants were recruited with their caregivers in Moldova and North Macedonia, and the WHO-5 was administered in local languages using culturally adapted versions. Confirmatory factor analysis tested a one-factor, five-item model in the combined sample and separately in each country. Model fit was evaluated with CFI, TLI, RMSEA and SRMR. Multi-group ordinal confirmatory factor analysis assessed configural, threshold, metric and scalar invariance across the countries, while McDonald’s ω estimated internal consistency.

The one-factor model showed appropriate fit in the combined sample, with CFI = 0.995, TLI = 0.990, RMSEA = 0.069 and SRMR = 0.019. Country-specific analyses also supported the one-factor structure. Standardized factor loadings ranged from 0.698 to 0.811, and residual variances ranged from 0.343 to 0.513. McDonald’s ω was 0.84. The cross-country analyses supported configural, threshold, metric and scalar invariance.

Based on the abstract, these results support using the WHO-5 to assess and compare adolescent well-being within the two program settings and add evidence for the validation of an open-access, culturally adapted instrument in middle-income and prevention contexts. The findings are limited to the study population, age range, program setting and baseline psychometric scope. Results from these two countries do not by themselves establish the measure’s validity in other adolescent populations, countries or intervention contexts, nor do they demonstrate preventive-program effects. The supplied evidence comes from the abstract of an open-access BMC Psychology article published as an early-access version that is subject to further edits, so this report is limited to the methods, estimates and conclusions stated in the abstract.

Subject of Research: Psychometric validation of the WHO-5 among adolescents in Moldova and North Macedonia

Article Title: Structural validity and measurement invariance of the WHO-5 Well-Being Index among young adolescents in a family-focused prevention context in Southeastern Europe

Article References: Piolanti, A., Waller, F., Kunovski, I., Shenderovich, Y., Mueller, J., Wienand, D., Simon, J., Heinrichs, N., Sampathkumar, S., Moore, G., & Foran, H. M. (2026). Structural validity and measurement invariance of the WHO-5 Well-Being Index among young adolescents in a family-focused prevention context in Southeastern Europe. BMC Psychology. https://doi.org/10.1186/s40359-026-05624-w

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05624-w

Keywords: WHO-5, adolescent well-being, measurement invariance, confirmatory factor analysis, Moldova, North Macedonia, psychometrics, FLOURISH trial, cross-cultural validation, Structural, validity, measurement

The theoretical foundation of the research rests on a distinction that many healthcare administrators conflate. Performance measurement refers to the technical apparatus of quantifying organizational activity: indicators, dashboards, benchmarking systems, and scorecards that capture how efficiently beds are occupied, how quickly patients move through emergency departments, and how outcomes compare across units. Performance management, by contrast, is the managerial process that surrounds those numbers: the conversations, target-setting exercises, incentive structures, and strategic reviews that determine whether measurement data actually changes behavior. Smith and Bititci’s framework argues that value creation emerges only when these two layers interact effectively, so that measurement feeds management and management, in turn, refines what gets measured. The Italian researchers set out to test how that interaction plays out in a national health service, a setting where profit motives are absent but accountability to taxpayers and patients is paramount.

The methodological approach was deliberately exploratory. Rather than deploying large-scale surveys, the researchers conducted an in-depth case study within a leading national health service, gathering qualitative evidence through interviews with professionals embedded in the organization. The case study design is well suited to questions where theory has not yet been fully tested in practice, allowing the investigators to trace the mechanisms linking measurement systems to managerial action and, ultimately, to value creation. The study was non-interventional, involving only adult professionals, with informed consent obtained from all participants and data treated confidentially and anonymously. No patients, patient data, or biological materials were involved, and participation was voluntary, reflecting the study’s focus on organizational and managerial dynamics rather than clinical outcomes.

The findings reveal a nuanced picture. On one hand, the case organization demonstrated a moderate level of democratic and participative performance management, meaning that staff across different levels had some degree of involvement in how performance was defined, discussed, and acted upon. This participative dimension matters because research in organizational behavior has long suggested that performance systems imposed from above tend to generate compliance rather than commitment, while systems co-created with frontline professionals tend to produce genuine engagement. On the other hand, the study identified significant limitations in the organization’s ability to capture value creation, suggesting that the measurement apparatus, however sophisticated, was not fully translating into a documented understanding of the value generated for patients, communities, and the broader health system.

Value creation in healthcare is a notoriously slippery concept. Unlike private-sector firms, where value can often be proxied by revenue, market share, or shareholder returns, public healthcare organizations generate value across multiple dimensions simultaneously: improved health outcomes, patient satisfaction, equity of access, system resilience, and efficient use of public funds. The study’s finding that value creation was difficult to capture points to a structural gap in how performance frameworks have been designed for the public sector. Many health systems have imported measurement tools from private-sector management accounting, where financial metrics dominate, without adapting them to the multidimensional nature of public value. The result is often a paradox in which organizations measure intensively but struggle to articulate what all that measurement has actually created.

From the interviews, four areas for managerial improvement emerged, and these constitute the study’s most actionable contribution. The first is enhancing organizational alignment, ensuring that strategic objectives cascade coherently from national health policy down to individual departments and that frontline staff understand how their daily work connects to institutional goals. Misalignment between top-level strategy and operational practice is a well-documented failure mode in large public organizations, where performance indicators may be collected diligently at the unit level without ever informing strategic decisions at the system level. The second area is optimizing efficiency and effectiveness, a pairing that requires health managers to look beyond cost containment toward the broader question of whether resources are deployed in ways that maximize health outcomes per unit of expenditure.

The third improvement area is fostering stakeholder engagement, extending the circle of participation beyond internal staff to include patients, communities, and partner organizations. In public healthcare, stakeholders are not merely customers but co-producers of health, and their involvement in defining what counts as valuable performance can reshape the entire measurement architecture. The fourth area is increasing investments in technology, infrastructure, and human capital, reflecting the recognition that measurement systems and managerial processes cannot function in isolation from the material and human resources that underpin service delivery. Digital health tools, modernized facilities, and continuous professional development are not peripheral concerns but prerequisites for any performance system that aspires to capture and create value in a modern health service.

The study’s contribution to the academic literature lies in addressing a gap in the application of Smith and Bititci’s 2017 conceptual framework within a complex and challenging public sector context, namely national health services. By testing the framework in an environment characterized by political oversight, funding uncertainty, and competing stakeholder demands, the researchers have extended its reach beyond the private-sector settings where it was originally developed. The identification of four managerial improvement areas also carries practical implications for health administrators seeking to strengthen the interaction between performance measurement and performance management, with potential downstream effects on value creation. The findings suggest that the pathway from measurement to value is neither automatic nor straightforward, but can be cultivated through deliberate managerial attention to alignment, efficiency, engagement, and investment.

The broader context of this research is a healthcare landscape where performance measurement and management have become increasingly important for the efficient allocation of resources in public health services. Healthcare systems face multiple simultaneous challenges, including technological change, pandemics, and uncertain macroeconomic and political environments, all of which complicate the implementation of performance frameworks. In Italy, where the study’s authors are based, the national health service operates within a fiscal framework shaped by gross domestic product constraints and monitored by the Italian National Institute of Statistics, adding layers of accountability that make performance management both more necessary and more complex. The tension between fiscal discipline and service quality is a defining feature of contemporary public healthcare, and performance measurement systems sit precisely at that intersection.

For health systems worldwide, the study offers a sobering but constructive message. The apparatus of performance measurement, however technically refined, does not by itself create value. Value emerges when measurement systems are embedded in participative management processes, when organizational alignment connects strategy to practice, when efficiency gains are pursued alongside effectiveness in health outcomes, when stakeholders are engaged as partners rather than subjects of measurement, and when investments in technology, infrastructure, and people provide the material foundation for improvement. The four managerial improvement areas identified in this case study provide a roadmap for administrators willing to move beyond the checkbox culture of performance reporting toward a genuine culture of value creation. As health systems continue to navigate an era of constrained budgets and rising demand, the distinction between measuring performance and managing it toward value may prove to be one of the most consequential ideas in modern healthcare management.

Subject of Research: From performance measurement and management to value creation: an explorative case study in public healthcare

Article Title: From performance measurement and management to value creation: an explorative case study in public healthcare

Article References: Sardi, A., & Sorano, E. (2026). From performance measurement and management to value creation: an explorative case study in public healthcare. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15675-9

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15675-9

Keywords: performance, measurement, management, value, creation, explorative, case, public, healthcare, scientific research

The instrument at the center of the analysis is the Learning Management of University Students Scale, known as GAEU-1, a 19-item self-report questionnaire developed for undergraduates in Chile and Ecuador. Students rate statements about planning, motivation, and study techniques on a five-point agreement scale. Earlier validation work had retained three of the scale’s dimensions: a self-regulated learning factor covering study preparation and time management, a dimension of conscious motivational strategies, and a dimension of deep learning techniques. The new study, led by Xinglong Pang, Lin Zhou, and Jin-Ho Cho, asked whether these three retained dimensions produce measurement parameters that are statistically comparable across the two countries.

The question matters because score differences between groups can be deceptive. If an item functions differently in Chile than in Ecuador, an apparent gap in self-regulated learning might partly reflect group-specific item behavior rather than genuine psychological differences. Measurement invariance testing addresses this by progressively constraining model parameters to be equal across groups and checking whether the fit of the model deteriorates meaningfully. For Likert-type items, the technical challenge is sharper still: ordered responses arise from thresholds on underlying response propensities, so procedures designed for continuous indicators cannot simply be transferred. The team therefore used weighted least squares mean- and variance-adjusted estimation, WLSMV, with theta parameterization, treating all 15 retained indicators as ordered categorical variables.

The data came from an openly licensed Version-5 dataset containing 1,316 undergraduates, 631 in Chile and 685 in Ecuador, with a mean age of 20.45 years. All 19 items were complete and within range, and only nine participants, less than one percent, showed zero response variance across the full item set. Internal consistency was adequate for the three analyzed dimensions, with pooled coefficient alpha values of 0.782 for self-regulated learning, 0.793 for conscious motivational strategies, and 0.753 for deep learning techniques, and model-based omega estimates reaching 0.890 for the motivation dimension. A fourth dimension, perceived academic performance, was excluded from the invariance model because it had shown weaker reliability in the original validation.

Country-specific confirmatory factor analysis produced a mixed picture. The comparative fit index and standardized root mean square residual were relatively favorable in both countries, with CFI of 0.947 in Chile and 0.952 in Ecuador and SRMR of 0.059 in both. But the root mean square error of approximation told a different story, reaching 0.094 in Chile and 0.085 in Ecuador, above conventional close-fit values. The researchers did not gloss over this. Analytical power calculations showed the elevated RMSEA could not be attributed to low statistical sensitivity, meaning the baseline models carried genuine residual misspecification. Their conclusion was therefore deliberately conditional: the inherited three-dimensional representation was usable for invariance testing, but it was not a perfectly specified model.

The core of the study was a staged multigroup invariance sequence following the Wu-Estabrook identification framework for ordinal indicators. The sequence moved from a configural model, in which the same factor structure was imposed in both countries, to equality constraints on item thresholds, then on thresholds plus factor loadings, and finally on the intercept-related parameters required by the identified ordinal model. The decision guides were prespecified: a decrease in CFI no larger than 0.010 and an increase in RMSEA no larger than 0.015 at each stage. Every planned stage passed. Constraining thresholds changed CFI by only 0.001 while RMSEA actually improved. Adding loading equality improved both indices further, and the intercept-related constraints changed CFI by less than 0.001. No partial invariance was needed, and all 15 indicators retained their cross-group equality constraints through the strong, or scalar, level.

Complementary differential item functioning analyses added an item-level view. Using iterative hybrid ordinal logistic regression procedures with Chile as the reference group, the team found statistically detectable DIF signals for eight items after false discovery rate correction. Yet the largest total change in McFadden pseudo-R-squared was 0.0103, for item GA3, well below the prespecified 0.020 practical-effect criterion. No item therefore required release from the multigroup constraints. The researchers were careful to note that this conclusion depends on the chosen threshold: a sensitivity analysis showed GA3 would be flagged under a more permissive 0.010 rule. The finding supports small rather than absent item-level differences, a distinction the authors argue future work should address with formal equivalence testing rather than simply failing to detect effects.

Post hoc diagnostics sharpened the study’s limitations. The strongest residual dependence was localized to the pair GA7-GA8, both items involving motivational self-talk, in both samples, with residual correlations of 0.174 in Chile and 0.201 in Ecuador. A deliberately parsimonious one-factor model fit appreciably worse than the retained three-factor representation in both countries, with CFI drops of 0.059 and 0.069, arguing against simple unidimensionality. Discriminant validity evidence was mixed: polychoric HTMT values all fell below the conventional 0.85 heuristic, but Fornell-Larcker diagnostics were not satisfied for factor pairs involving the self-regulated learning factor, whose latent correlations with the other dimensions were substantial, reaching 0.836 in Chile. The factors are not empirically identical, but their separation is criterion-dependent.

After invariance was established, the team estimated latent sample contrasts as a secondary illustration. With effects coded Ecuador minus Chile, the latent contrast for self-regulated learning was small and non-significant, while conscious motivation and deep learning showed significant latent differences favoring Chile, with latent Cohen’s d of 0.225 and 0.284 respectively. The researchers stressed these values are descriptive of these two samples after measurement adjustment, not estimates of national or cultural effects, because the samples differed markedly in gender and university-sector composition. Women made up 46.9 percent of the Chilean sample but 65.7 percent of the Ecuadorian sample, and private-university students represented 57.5 percent in Chile versus 98.4 percent in Ecuador.

Two planned sensitivity analyses, one removing zero-variance respondents and one allowing residual covariances for the data-informed item pairs, preserved the main comparability result, as did a post hoc private-university-only analysis of 1,037 respondents. The overall conclusion is bounded but useful: the three retained GAEU-1 dimensions showed approximately stable thresholds, loadings, and intercept-related parameters across these Chilean and Ecuadorian university samples, conditional on the inherited scoring representation. For researchers using the scale in similar Latin American university settings, that is meaningful evidence for model-based cross-sample comparison, while broader structural, equivalence, and country-level claims remain outside what was actually tested.

Subject of Research: Ordinal measurement invariance testing of the GAEU-1 learning-management scale across Chilean and Ecuadorian university students

Article Title: Ordinal measurement invariance of three retained GAEU-1 dimensions in Chilean and Ecuadorian university samples

Article References: Pang, X., Zhou, L., & Cho, J.-H. (2026). Ordinal measurement invariance of three retained GAEU-1 dimensions in Chilean and Ecuadorian university samples. Frontiers in Psychology, 17, Article 1990515. https://doi.org/10.3389/fpsyg.2026.1990515

Image Credits: AI Generated

DOI: 10.3389/fpsyg.2026.1990515

Keywords: measurement invariance, self-regulated learning, GAEU-1, Chile, Ecuador, higher education, psychometrics, differential item functioning, Ordinal, measurement, invariance, three

The review, led by Joshua M. Lovett of the University of Illinois Chicago alongside colleagues including Kimberly A. Schonert-Reichl of the University of British Columbia, systematically examined 531 intervention studies published between 2000 and 2025. The team screened more than 12,000 records and distilled them into a comprehensive map of the measures used to assess prosocial behavior across interventions. What emerged was a portrait of remarkable diversity—and remarkable imprecision.

The numbers tell the story. The 531 studies collectively employed 427 distinct measures of prosocial behavior, meaning that on average, each new study introduced a slightly different instrument than the last. Only a small fraction of measures appeared more than once. The most frequently used tool was the Strengths and Difficulties Questionnaire, a brief behavioral screening instrument whose prosocial subscale appeared in 75 studies. Informant reports from teachers and parents dominated the landscape, followed by self-report questionnaires and economic allocation games such as the trust game and dictator game.

This fragmentation is not merely an academic curiosity. When each study uses a different measure, results cannot be meaningfully compared across interventions. Meta-analyses struggle to pool findings. Practitioners cannot determine which programs actually work. And the field’s cumulative knowledge—its ability to build on prior discoveries—is undermined at a fundamental level.

The review also uncovered a deeper conceptual problem: researchers rarely specify what they mean by prosocial behavior. Some studies treat it as a broad disposition, others as a specific act like sharing or helping, and still others as an outcome of empathy or compassion. Without a shared definition, the construct being measured varies from study to study in ways that are often invisible to both researchers and readers.

Psychometric reporting proved equally inconsistent. Among the 427 measures, 30 percent did not report any reliability index, and 79 percent did not report validity evidence. Even when reliability was reported, it was most often internal consistency—Cronbach’s alpha—rather than test-retest stability or inter-rater agreement. This means that many of the instruments at the center of prosocial behavior research have never been rigorously evaluated for the properties that would justify their use.

The consequences ripple outward. In intervention research, unclear constructs and unvalidated measures threaten the internal validity of studies. When researchers cannot demonstrate that their measure actually captures the construct they intend to assess, observed changes in prosocial behavior may reflect measurement artifacts rather than genuine behavioral change. Replication efforts, already strained in psychology, become even more difficult when the original instruments are never fully documented.

The review’s authors argue that the field needs a coordinated effort to establish shared definitions and validated measures. They point to the heterogeneity of the 531 studies—spanning 63 countries, 301 journals, and populations from early childhood through adulthood—as evidence that no single measure can serve all contexts. Instead, they call for researchers to be more precise about the specific facet of prosocial behavior they intend to assess, and to select instruments with documented psychometric properties appropriate for their population and setting.

The timing of this review is significant. Interest in prosocial behavior has surged in recent years, driven partly by research linking it to mental health, well-being, and social cohesion. School-based social and emotional learning programs, mindfulness interventions, and digital prosocial games have all expanded rapidly. As the field grows, the review suggests, so does the risk that its foundational measurement practices will drift further from scientific rigor.

For now, the review offers a sobering baseline. The field’s enthusiasm for cultivating kindness, generosity, and cooperation has outpaced its ability to measure these constructs consistently. Until researchers agree on what prosocial behavior means and how best to assess it, the review concludes, the science of promoting it will remain fragmented—one study, one measure, one definition at a time.

The distinction between the different families of measures identified in the review carries practical weight beyond simple frequency counts. Informant-report measures, which accounted for roughly a quarter of all extracted instruments, typically rely on teachers, parents, or other observers who know the target individual well. Their popularity in intervention research stems largely from convenience: a single adult can rate a child’s behavior across many situations and over extended periods, capturing the kind of naturally occurring helping, sharing, and cooperating that laboratory tasks often miss. Yet informant reports are also vulnerable to halo effects, in which a rater’s general impression of a person colors judgments of specific behaviors, and to reference-group effects, in which ratings depend on the comparison group the rater implicitly uses. Self-report questionnaires, the second most common category, introduce their own complications, since people may overstate their own generosity or interpret questionnaire items in idiosyncratic ways. Economic allocation games, the third major family, offer behavioral observation with real stakes, but a single decision in a one-shot game may not generalize to the sustained, context-dependent prosociality that interventions aim to cultivate.

The prominence of the Strengths and Difficulties Questionnaire in this literature deserves particular scrutiny. Originally developed as a broad behavioral screening tool for emotional and conduct difficulties, its prosocial subscale consists of a small number of items rated by an informant or, in the self-report version, by the respondent. Its ubiquity across the reviewed studies means that a substantial share of the intervention literature rests on a measure that was not designed primarily as a stand-alone index of prosociality. Whether that subscale is sensitive enough to detect change following an intervention—an essential property for outcome measurement, as opposed to screening—remains an open question that the review’s findings on validity reporting do little to resolve.

The review’s window on the field’s growth also situates prosociality research within a broader historical arc. For much of the twentieth century, psychology and education concentrated on deficit reduction: treating aggression, conduct problems, and psychopathology. The rise of positive psychology at the turn of the millennium reframed the agenda toward cultivating strengths, and the fifteen-year publication trend documented in the review tracks that shift. School-based social and emotional learning programs have been a major driver, with meta-analyses of hundreds of such interventions showing gains not only in academic performance but also in observable positive social behavior. This institutional momentum means that measurement decisions made now will shape a large and growing evidence base for years to come.

The conceptual breadth of prosocial behavior itself compounds the measurement challenge. Helping a stranger carry groceries, donating money anonymously, comforting a distressed friend, and cooperating in a workplace team are all prosocial in the ordinary sense, but they differ in motivation, skill, developmental meaning, and situational demand. The construct’s definition deliberately leaves motivation unspecified: a child may share to win approval or out of genuine other-oriented concern, and both count as prosocial behavior. This definitional openness is philosophically defensible but psychometrically costly, because instruments that aggregate across heterogeneous behaviors may dilute the very signal an intervention targets. Decades of research linking prosocial behavior to empathy show that the strength of that association varies depending on which measure of prosociality is used—evidence that different instruments are, in effect, measuring partly different constructs.

The consequences of weak psychometric reporting extend into policy. School districts, public health agencies, and employers increasingly adopt programs whose evaluations rest on the kinds of measures cataloged in this review. When four in five applicable measures lack reported validity evidence, decision-makers cannot easily judge whether an observed improvement reflects genuine behavioral change or an artifact of the instrument. The authors’ call for greater precision in conceptualizing outcomes and for routine reporting of reliability and validity is therefore not a methodological nicety but a precondition for the field’s findings to accumulate into trustworthy guidance for practice.

Subject of Research: Psychology

Article Title: Assessing prosocial behavior in interventions: a scoping review of existing measures and their psychometric properties

Article References: Lovett, J. M., Galloway, C., Bhanushali, P. D., Sarda, S., Bledsoe, A., Thursby Bourke, K., & Schonert-Reichl, K. A. (2026). Assessing prosocial behavior in interventions: a scoping review of existing measures and their psychometric properties. Frontiers in Social Psychology, 4, Article 1804116. https://doi.org/10.3389/frsps.2026.1804116

Image Credits: AI Generated

DOI: 10.3389/frsps.2026.1804116

Keywords: prosocial behavior, psychometrics, measurement, scoping review, intervention research, psychology, Assessing, prosocial, behavior, interventions, scoping, review

The caverns hosting the four Large Hadron Collider experiments — ATLAS, ALICE, CMS, and LHCb — are among the harshest environments imaginable for robots. They are confined, cluttered with fragile detector hardware, and entirely denied of satellite navigation. Above all, they are permeated by intense stray magnetic fields spilling out of the powerful magnet systems that surround the interaction points. These fringe fields can disturb onboard electronics, corrupt sensor readings, and destabilise the actuators of any robotic platform sent into the space. Characterising them is a prerequisite for deploying robots in the caverns, but it also matters to detector operation itself: anomalous fringe fields extending beyond the detector volume can interfere with surrounding infrastructure and, if severe, compromise particle tracking and momentum reconstruction.

Conventional approaches to mapping these fields have serious limitations. Purpose-built mechanical systems with Hall-probe arrays work well inside the detector bore but cannot reach the cluttered open cavern. Fixed sensors and manual surveys provide only sparse spatial coverage and require significant access coordination. The robotic airship offers a compelling alternative. Buoyant lift from helium enables extended flight endurance while inherently reducing collision risk, making the blimp well suited for safe indoor navigation near fragile detector components. The platform is built entirely from non-ferromagnetic materials — PLA and DEPRON foam — so the field that it measures cannot attract it toward the massive steel flux-return yoke of the L3 solenoid, the dominant magnetic source in the cavern.

The L3 solenoid is a veteran of particle physics. Originally commissioned in 1988 for the L3 experiment at the Large Electron–Positron collider and later adapted for ALICE, it generates a nominal axial field of 0.5 tesla over a volume roughly 12 metres long and 11.8 metres in diameter, driven by 30,000 amperes through 168 turns of an octagonal aluminium coil and storing 150 megajoules of energy. A warm forward dipole magnet, providing 0.67 tesla for the muon spectrometer, sits nearby. The fringe field extending beyond the steel yoke into the cavern — typically in the millitesla range at the measurement locations — was the primary target of the blimp’s campaigns.

The measurement payload is elegantly simple. A TMAG5273 linear three-axis Hall-effect sensor from Texas Instruments, operated in the millitesla range and sampled at 10 hertz, provides the magnetic readings. It is read by an Arduino Portenta H7, which also acquires an inertial measurement unit, environmental sensors, and a time-of-flight proximity sensor. Because every field measurement must be tied to a spatial position, a Raspberry Pi Camera 3 Wide, operated by a dedicated Raspberry Pi Zero 2W, streams images used for localisation. The two data streams are timestamped independently and synchronised via Network Time Protocol, limiting temporal misalignment between field readings and pose estimates during post-processing.

Localisation is the crux of the system, since the cavern offers no satellite navigation. The team deployed 82 ArUco fiducial markers — square binary patterns designed for robust visual detection — printed on continuous paper rolls and arranged in strips along the joint lines between the concrete shielding blocks in front of the L3 solenoid. A JSON vocabulary file associates each marker with its three-dimensional coordinates in the ALICE reference frame, derived from the official detector CAD model. The onboard camera detects visible markers, solves the Perspective-n-Point problem to estimate its pose, and chains transformations through the camera-to-sensor offset to express the Hall sensor’s position and orientation in the ALICE frame. The measured field vector is then rotated into the same frame for direct comparison with the simulation.

Two complementary campaigns were conducted with the magnets at nominal current. The first consisted of static measurements: the Hall sensor was mounted on a 3D-printed platform with the same footprint as an ArUco marker, placed at twenty known positions in two parallel strips, and a 30-second acquisition was triggered at each point. By eliminating localisation uncertainty, this campaign isolated the Hall sensor’s accuracy from the pose-estimation error. The second campaign consisted of four manually piloted flights on two separate days in 2026, during which the blimp acquired measurements continuously while navigating over the same instrumented region, exploring a volume of several cubic metres in front of the A-side shielding blocks.

To compare measurements with the electromagnetic model, the team built a high-fidelity simulation of the ALICE magnet system in CST Studio Suite, including the L3 return yoke and forward dipole yoke with the nonlinear B–H curve of AISI 1050 annealed carbon steel, and generated a field map sampled on a uniform 200-millimetre grid. A dedicated uncertainty-propagation framework then combined the Hall-sensor error budget — sensitivity error, zero-field offset, and intrinsic RMS noise — with the ArUco pose uncertainty, which was characterised in a controlled indoor environment against a Qualisys motion-capture ground truth. The validation campaign yielded a three-dimensional position RMSE of 5.38 centimetres and attitude errors within about 2.6 degrees, with the Hall-sensor contribution dominating the total uncertainty in every flight.

The results are strikingly consistent across both campaigns. The simulation reproduces the transverse field components well: statically, the x-component achieved a coefficient of determination of 0.98 with 100 percent of simulated values falling within the sensor uncertainty bounds, and the y-component reached 0.94 with 90 percent compliance. Dynamically, pooled over 858 valid points across the four flights, the transverse components showed coefficients of determination of 0.86 and 0.93 with compliance of 89.4 and 79.3 percent. The vertical component, however, stood out as the clear outlier in both campaigns, with a lower coefficient of determination of 0.75 to 0.79 and a systematic positive bias of 0.65 to 1.12 millitesla — the measured field consistently higher than the simulation predicted.

Critically, because this vertical bias appears already in the static campaign, where the ArUco localisation contribution is entirely absent, the authors conclude that the discrepancy originates primarily in the electromagnetic model rather than in the measurement pipeline. Two modelling limitations are the most plausible culprits: the actual yoke materials are not documented, introducing systematic uncertainty in the field components most sensitive to the permeability value, and the CST geometry does not include the ferromagnetic concrete shielding blocks adjacent to the solenoid access doors, which may locally perturb the field. A parametric sensitivity study varying the yoke permeability and shielding geometry is planned as future work. The team also notes that the current system depends on marker visibility for absolute localisation, and that the four manually piloted flights demonstrate the methodology within an instrumented test region rather than a complete cavern survey.

The significance of the work extends well beyond ALICE. The High-Luminosity LHC will employ stronger focusing magnets and further restrict human access, and the proposed Future Circular Collider foresees no iron return yoke for the solenoid flux at all — under that assumption, the stray field at the cavern wall is expected to reach approximately 100 millitesla, falling below 5 millitesla only beyond 55 metres from the detector. Such conditions, orders of magnitude more intense than in current LHC caverns, make magnetic compatibility a critical design driver for any future autonomous inspection platform. The next step for the blimp is autonomy: integrating the ArUco localisation pipeline with a closed-loop position controller and a field-aware path planner would allow it to execute pre-programmed survey patterns, repeat missions consistently, and function as a continuous monitoring system capable of detecting field anomalies during beam operations without requiring human presence in the cavern. The measurement methodology, localisation pipeline, and uncertainty framework developed in this work constitute the foundation for such a fully autonomous airship-based survey system in underground physics environments.

Subject of Research: Robotic airship for measurement and validation of a CERN detector stray magnetic field

Article Title: Robotic airship for measurement and validation of a CERN detector stray magnetic field

Article References: Mazzei, F., Scaramuzzino, P. F., Bernardi, L., Curti, F., & Gargiulo, C. (2026). Robotic airship for measurement and validation of a CERN detector stray magnetic field. Frontiers in Robotics and AI, 13, Article 1926428. https://doi.org/10.3389/frobt.2026.1926428

Image Credits: AI Generated

DOI: 10.3389/frobt.2026.1926428

Keywords: Robotic, airship, measurement, validation, CERN, detector, stray, magnetic, field, scientific research

The study, published in Frontiers in Acoustics, builds on a previous experiment in which the researchers excited EDLs directly on the piezoelectric lithium niobate substrate of a surface acoustic wave (SAW) actuator. In that setup, the EDL was exposed to two influences at once. The Rayleigh-type SAW itself is a mechanical vibration traveling near the surface of the solid, and it drags with it a sub-micrometer-thick evanescent boundary layer flow in the neighboring water. But in a piezoelectric substrate, the same wave is accompanied by a voltage signal counterpart that spreads an electric field into the electrolyte, periodically migrating ions in its own right. Which of the two dominated the excitation of the EDL remained unclear. The periodic AC voltage applied to the actuator governs both the SAW intensity and the level of its electrical potential counterpart, so the two effects were convoluted in every measurement conducted directly on the actuator.

To disentangle them, the team transferred the SAW from the actuator into an ordinary glass slab. Glass is a dielectric with no mobile charges, so it supports pure mechanical vibration while attenuating the electrical field emanating from the piezoelectric substrate. The integrated device consisted of a 1-mm-thick glass microscope slide attached to a flat lithium niobate substrate of a 20 MHz SAW actuator, with a thin film of glycerol serving as an ultrasonic impedance-matching liquid between the two solids. The glycerol spread into the gap by capillary action, trapping itself there and coupling the mechanical power from the actuator into the glass. At the far end of the glass, a strip of wet paper absorbed much of the wave to suppress reflections.

The measurements revealed something unexpected about how the mechanical field travels through this sandwich. The normal vibration amplitude on the glass surface was similar to that on the lithium niobate substrate, and both supported a wavelength of roughly 200 micrometers. Near the interdigital transducer—the IDT that generates the wave—the vibration on both solids behaved as a nearly propagating wave. Farther away, at separations of 8 and 12 millimeters, it became a combination of propagating and standing waves, likely because the vibration source sits on one side of the device while reflections return from the opposite edge. Intriguingly, the SAW did not attenuate by simple diffraction into the glass, as it would if the glass were a half-space; instead, the vibrations in the two substrates appeared intimately connected, with power flowing back and forth between them. The behavior suggests the vibration in the glass is akin to a Lamb wave, spread throughout the slab, continuously absorbing and reflecting power to and from the actuator.

Meanwhile, the electrical field accompanying the wave in the piezoelectric substrate decayed exponentially through the glass. Solving the Poisson equation for the potential in a half-space of glass, subject to the spatiotemporal potential signal at the lithium niobate surface, showed that the field reaches a negligible magnitude at the upper surface of the glass slab. The measured electrical potential there was three to four orders of magnitude smaller than the input potential to the actuator. In other words, the mechanical wave alone is what reaches the upper glass surface to excite the EDL at the glass/electrolyte interface—precisely the isolation the experiment required.

The glass surface itself becomes spontaneously charged at levels of tens of millivolts when in contact with an electrolyte, supporting an EDL much like the one on the piezoelectric substrate. The researchers dispensed sessile drops of two strong electrolytes—sodium nitrate and potassium chloride—chosen because their small ion pairs keep the double layers near ideal, well described by the Boltzmann–Poisson equation at low ionic concentrations. Sodium nitrate offers ions with dissimilar diffusion coefficients, while potassium chloride has ions with nearly identical ones at the precision of the measurement. A working microelectrode was positioned just 30 to 40 micrometers above the glass surface—closer than the 200-micrometer SAW wavelength, to avoid dispersion of the leakage field—with a reference electrode about a millimeter away in the bulk of the drop. An RF lock-in amplifier measured the 20 MHz component of the electrical leakage, the linear same-frequency response of the EDL to the exciting vibration.

What the electrodes recorded was a spectrum of electrical field leakage from an out-of-equilibrium EDL. At equilibrium, the nanometer-thick ion cloud fully screens the field of the surface charge. But the megahertz vibration renders the EDL out of equilibrium, and it leaks an electrical field into the electrolyte bulk—a field proportional to the zeta potential of the surface and modulated in time by the motion of the ions. The leakage takes on the frequency of the exciting wave and its harmonics. Crucially, the spectra were non-monotonic: they took local maxima where the period of the mechanical vibration synchronized with the relaxation times of specific ions in the EDL. At those frequencies, the synchronization maximizes the periodic displacement of the ions, amplifying the field leakage. The peaks are specific to ion mobilities, effectively reading out an array of ion relaxation times—and hence mobilities—within the double layer.

Three points of comparison with the previous study, in which the EDL was excited directly on the piezoelectric substrate, confirmed that the mechanical component alone reproduces the full phenomenon. First, the measured voltage peaks appeared where the vibration period matched the ion relaxation time in both studies, with the peaks for sodium nitrate and potassium chloride arising at acoustic-to-ion relaxation time ratios roughly 15 percent smaller than theoretical values, while their harmonics came closer to theory; for potassium chloride, the measured peaks agreed well with the theoretical values. Second, the magnitude of the leakage was of the same order in both studies, though the ratio of measured to applied voltage was greater in the previous study by a factor of about two to three—attributable to a lower vibration displacement on the glass surface per applied voltage level. Third, scaling the measured voltage by the applied voltage collapsed the data onto unifying curves in both cases: one curve for sodium nitrate, and two curves for potassium chloride, the second associated with a response about 15 to 20 percent greater. The similar collapse suggests similar governing physical mechanisms, with the double curve in the potassium chloride case flagged as a caveat for further study.

The work is reminiscent of classic electroacoustic measurements, in which bulk ultrasonic waves interacting with ions in electrolytes or charged colloids generate a potential difference across an entire volume of dispersion—techniques long used to analyze ionic species and, most notably, the zeta potential of particle suspensions. The difference here is that the ultrasonic vibration is generated in the solid itself, exciting ions in an isolated EDL emanating from a single flat surface. That opens the door to measuring the static and dynamic electrokinetic properties of flat solid surfaces of many kinds, provided they support a corresponding mechanical vibration. Silica-based glass, the platform used in this experiment, is a workhorse of surface chemistry manipulation, making it a versatile stage for studying how different surface chemistries shape ion dynamics in EDLs—relevant to membranes, batteries, and supercapacitors.

There is also a cautionary message embedded in the findings for the growing field of SAW-actuated micro- and nanofluidics. If a mechanical vibration traveling along a solid in an electrolyte vibrates the ions of the EDL at its own frequency, then double layers on such platforms are not at equilibrium—and their electrical properties may differ substantially from equilibrium ones. Out-of-equilibrium EDLs govern ion transport through ion-selective membranes and the stability of liquid films of electrolyte solutions, and they may alter membrane ion-screening properties and film stability in ways that equilibrium theory cannot predict. For anyone designing acoustic microfluidic devices, the hidden nanometer-thin layer at every solid/liquid interface may be far more dynamic than it appears.

Subject of Research: Acoustofluidics

Article Title: Measurement of dynamic electrokinetic effects at the glass/electrolyte interface using a mega-Hertz-level mechanical wave

Article References: Aremanda, S., Li, Y., Onuh, G., & Manor, O. (2025). Measurement of dynamic electrokinetic effects at the glass/electrolyte interface using a mega-Hertz-level mechanical wave. Frontiers in Acoustics, 3, Article 1568083. https://doi.org/10.3389/facou.2025.1568083

Image Credits: AI Generated

DOI: 10.3389/facou.2025.1568083

Keywords: surface acoustic wave, electrical double layer, electrokinetics, electroacoustics, acoustofluidics, ions, microfluidics, Measurement, dynamic, electrokinetic, effects, glass

The tool in question is the trailing limb angle, or TLA, an angle that describes how far behind the body the pushing leg has swung at a given moment. It is defined as the angle between the vertical axis of the laboratory and a vector connecting the greater trochanter, the bony prominence at the top of the thigh, to a distal landmark on the leg, most commonly the head of the fifth metatarsal or the lateral malleolus. The larger the angle, the more the limb has extended behind the body, and the better positioned it is to push the ground backward rather than downward. Because TLA can be estimated with a small set of inertial measurement units rather than a laboratory full of force plates, it has been heralded as an accessible point-of-care estimate of the propulsive forces that are usually quantified with the anterior component of the ground reaction force, or AGRF.

But there is a hidden assumption baked into much of the literature: that the peak value of TLA, the maximum angle the limb reaches, is equivalent to the angle at the moment of peak propulsion. Sally Kenworthy and Stacey Gorniak set out to test that assumption directly, and their findings, published in Frontiers in Rehabilitation Sciences, challenge it in a way that could ripple through both research protocols and clinical practice. In a state-of-the-art review of 39 studies that used TLA as a measure of propulsion, the authors had already noted substantial variation in when researchers calculated the angle: some measured it at toe-off, some during double support, some at terminal stance, some in pre-swing, and some at peak AGRF. Crucially, none of the twelve studies measuring TLA at its peak reported measuring it at the time of peak AGRF, and studies measuring TLA at peak AGRF avoided calling it peak TLA. The new study validates that critical distinction with hard numbers.

Nineteen middle-aged adults without impairment, with a mean age of 56.42 years, walked on an instrumented split-belt treadmill while a sixteen-camera motion capture system recorded three-dimensional positions of reflective markers on their lower extremities. Marker data were captured at 100 hertz and ground reaction force data at 2,000 hertz, with all data time-normalized to 100 percent of the gait cycle. The researchers defined propulsion as the peak amplitude of the AGRF, expressed as a percentage of body weight, and calculated TLA using the two most common definitions in the literature: one connecting the greater trochanter to the fifth metatarsal head, and one connecting it to the lateral malleolus. They then compared the peak value of each TLA measure to the value measured at the exact moment of peak AGRF, and described the timing of peak propulsion relative to key gait events such as contralateral heel strike and ipsilateral toe-off.

The results were striking. Peak propulsion occurred at 47.50 percent of the gait cycle, just before contralateral heel strike, which occurred at 49.99 percent. This timing aligns with the dynamic model of walking, which holds that generating push-off just before the opposite foot lands minimizes the energy cost of the step-to-step transition. But the peak value of TLA, measured with the fifth metatarsal head landmark, occurred at 57.83 percent of the gait cycle, a full 10.38 percent later than peak AGRF. When measured with the lateral malleolus, peak TLA occurred 8.61 percent later. Both timing differences were statistically significant, with enormous effect sizes. In amplitude terms, the gap was equally dramatic: peak TLA with the fifth metatarsal landmark averaged 22.77 degrees, while TLA at the moment of peak propulsion averaged just 16.08 degrees, a difference of 6.69 degrees. With the lateral malleolus, the difference was smaller but still significant at 4.20 degrees, with peak values of 27.94 degrees versus 23.50 degrees at peak propulsion.

Why does this matter clinically? Because when TLA is measured at its peak value rather than at the moment of peak propulsion, it is consistently overestimated by roughly four to seven degrees. A patient’s propulsive capacity may appear adequate when measured at peak TLA but is actually impaired when measured at the clinically relevant time point of peak propulsion. This misclassification can delay or prevent diagnosis of true propulsive deficits and can obscure whether a gait impairment reflects genuine motor control deficiency or merely compensatory limb positioning. While peak TLA may be adequate for tracking relative progress within a single patient over time, precision remains critical for establishing normative data, comparing outcomes across facilities, and determining whether propulsive deficits represent true motor control impairment or a measurement artifact due to inconsistent timing protocols. The authors also caution that the proportional relationship between peak TLA and TLA at peak propulsion may be fundamentally altered in individuals with movement disorders, potentially masking clinically meaningful changes in propulsive mechanics if peak TLA is used as a surrogate without verification in impaired populations.

The kinematic analysis adds further texture to the story. At the moment of peak propulsion, the trailing limb ankle was dorsiflexed at 12.07 degrees, the knee slightly flexed at 11.68 degrees, and the hip extended at 10.24 degrees behind neutral, near its position of maximum extension in the gait cycle. Meanwhile, the leading limb ankle was approaching a neutral position for heel strike, the knee slightly flexed, and the hip flexed at 22.18 degrees. These joint positions are reflective of the terminal stance phase of gait, occurring during single limb support just before the opposite foot lands, rather than during double limb support. This finding suggests that peak propulsion does not occur during the period of double support in middle-aged unimpaired adults, challenging diagrams in previous studies that depict TLA during double limb support. It also means that if TLA is measured at toe-off or in pre-swing, phases often used interchangeably, it is capturing the peak value of TLA rather than TLA at the time of peak propulsion, as originally intended.

The study also contributes to an ongoing debate about when propulsion actually peaks. While the dynamic model of walking and exoskeleton studies by Malcolm and colleagues support the idea that push-off before contralateral heel strike optimizes energy efficiency, Kuhman and Hurt found that in young unimpaired adults, all measures of propulsion occurred after contralateral heel strike, regardless of walking speed. The Houston team suggests that conflicting findings may stem from data processing decisions, such as the thresholds used to identify heel strike and toe-off events. In the current study, a vertical ground reaction force threshold of 30 newtons was used, in accordance with work by Revi and colleagues that validated a minimal set of wearable sensors for indirect AGRF measurement. But acceptable thresholds in the literature range from 10 to 30 newtons, and a lower threshold would detect heel strike earlier, potentially shifting the timing relationships reported here. Walking speed also modulates both TLA magnitude and propulsive force generation, so the specific timing percentages should be replicated across unimpaired and impaired populations walking at slower speeds.

The authors acknowledge limitations. Participants walked significantly slower on the treadmill than overground, and fourteen of the nineteen were recruited from a local running club, making the sample likely more active and healthier than the average middle-aged adult at risk of stroke. Significant left-right differences were also observed despite participants being unimpaired, likely reflecting natural biomechanical variation related to limb dominance or the unfamiliar task of split-belt treadmill walking. Still, the core message stands: the maximum value of TLA is not methodologically equivalent to TLA measured at the time of peak propulsion, which occurs just before contralateral heel strike in middle-aged unimpaired adults. The findings provide concrete evidence supporting standardized TLA reporting in future research and clinical practice, and underscore that whether in the laboratory or the clinic, timing is everything.

Subject of Research: Timing is everything: the effect of measurement timing on trailing limb angle in gait analysis

Article Title: Timing is everything: the effect of measurement timing on trailing limb angle in gait analysis

Article References: Kenworthy, S., & Gorniak, S. (2026). Timing is everything: the effect of measurement timing on trailing limb angle in gait analysis. Frontiers in Rehabilitation Sciences, 7, Article 1897235. https://doi.org/10.3389/fresc.2026.1897235

Image Credits: AI Generated

DOI: 10.3389/fresc.2026.1897235

Keywords: Timing, everything, effect, measurement, trailing, limb, angle, gait, analysis, scientific research

The new approach, described in Frontiers in Analytical Science by Rong Fu, Diane J. Sutcliffe, Ashok R. Dinasarapu, Ellen J. Hess and H. A. Jinnah, relies on ultra performance liquid chromatography coupled with photodiode array ultraviolet detection, commonly abbreviated UPLC-PDA. Unlike mass spectrometry-based metabolomics, which can be expensive and technically demanding, PDA detection exploits the strong ultraviolet absorbance of purines at 254 nanometers, allowing straightforward identification by retention time and spectral profile. The system consists of a Waters ACQUITY H-Class plus core with a quaternary solvent manager and an eLambda PDA detector, operating on a 2.1 by 100 millimeter reverse-phase C18 column packed with 1.8 micrometer particles at 40 degrees Celsius.

Separation chemistry is the crux of the method. Purines carry ionizable groups whose charge states shift dramatically with pH, so the Emory team designed a stepped gradient between two carefully formulated buffers. Buffer A contains 10 millimolar ammonium acetate and 1.5 millimolar tetrabutylammonium phosphate at pH 5.0, while buffer B contains 10 millimolar ammonium phosphate with the same ion-pairing reagent and 25 percent acetonitrile at pH 7.0. The tetrabutylammonium phosphate acts as an ion-pairing agent, taming the highly polar nucleotides so they interact with the reverse-phase column and elute as discrete peaks rather than co-eluting in the void volume. The gradient holds 100 percent buffer A for 11 minutes, ramps to 75 percent buffer B, then climbs to 100 percent buffer B before the column re-equilibrates for 9.5 minutes ahead of the next injection.

With this configuration, the method resolves all 15 target metabolites: ATP, ADP, AMP, adenosine, adenine, GTP, GDP, GMP, IMP, ZMP, guanosine, hypoxanthine, inosine, xanthine and uric acid. Only 5 microliters of sample are injected per run. Calibration with purified standards confirmed linear detection across a remarkable four-order-of-magnitude range from 0.1 to 100 micromolar, with all metabolites detectable down to approximately 100 nanomolar. Reproducibility proved equally impressive. When the same sample was analyzed five times within a single batch and across three batches on different days, the within-run coefficient of variance averaged 0.8 percent and the between-run variance averaged 1 percent for most analytes, comfortably under the 2 percent threshold the authors cite as evidence of excellent reliability.

The improvements over the team’s earlier HPLC-PDA method are substantial. The original technique required 65 minutes per sample; the new UPLC version cuts that to 33 minutes. Sensitivity is higher with half the sample volume, a critical advantage when working with scarce clinical specimens or small cell cultures. Perhaps most importantly, the new method cleanly discriminates GMP from IMP, two metabolites that co-eluted and could not be separately quantified with the older protocol. Because GMP and IMP occupy distinct positions in purine interconversion pathways, their separate measurement opens new analytical possibilities for studies of guanine nucleotide synthesis and purine salvage.

To demonstrate performance in genuine biological material, the researchers applied the method to induced pluripotent stem cells derived from three publicly available lines: KOLF2.0, NCRM1 and PGP-1. Each line was studied in matched pairs, with and without a c.508C>T stop codon mutation in the HPRT1 gene. This mutation abolishes hypoxanthine-guanine phosphoribosyltransferase, the salvage enzyme whose complete loss causes Lesch-Nyhan disease, a rare X-linked disorder marked by self-injurious behavior, dystonia and severe motor impairment. Cells were grown in six-well plates to roughly one million cells per well, with culture medium freshly replaced 24 hours before collection.

Sample preparation demanded meticulous attention to chemistry. For intracellular purines, cells were released by trypsinization, pelleted, and extracted in 0.2 molar perchloric acid, which instantly denatures the enzymes that would otherwise degrade labile nucleotides. Sonication at 4 degrees Celsius liberated the contents, and after centrifugation the acidic supernatant was neutralized with potassium carbonate, precipitating potassium perchlorate before final filtration through PVDF microcentrifuge tubes. For extracellular purines, 450 microliters of conditioned medium were acidified with perchloric acid to 0.1 molar and processed identically. Intracellular results were normalized to total cellular protein measured with a BCA assay, while extracellular results were corrected for culture volume and duration.

The biological findings were striking. In keeping with decades of prior work, the adenine derivatives dominated the intracellular purine pool, with ATP present in the greatest amounts, roughly 33 to 46 nanomoles per milligram protein across the lines, followed by GTP at 11 to 16 nanomoles per milligram. The adenylate energy charge, calculated as ([ATP] + 0.5 × [ADP]) / ([ATP] + [ADP] + [AMP]), ranged from 0.81 to 0.88, confirming that all cultures retained a healthy nucleotide energy state above the 0.80 benchmark typical of viable cells. Multivariate analysis of variance revealed significant main effects for both mutation status and cell type, along with a significant interaction between the two variables.

Most intracellular purines showed small or no changes in the HPRT1-mutant cells, but the extracellular compartment told a very different story. Conditioned medium contained no detectable purines except hypoxanthine, which was elevated by an average of 30-fold in the mutant lines, with individual increases ranging from 12-fold to as much as 225-fold depending on the genetic background. The explanation is elegant: without functional HPRT, the cells cannot recycle hypoxanthine back into nucleotides, so they simply dump it into the extracellular space. This finding underscores why measuring extracellular purines is essential, since changes outside the cell were far more obvious than those within it.

The authors acknowledge limitations. The method focuses on free purines and does not capture purines incorporated into DNA, RNA, NAD(H), NADP(H), FAD(H) or other complex molecules, though it can be adapted for some of these derivatives. Cyclic nucleotides and deoxynucleotides occur at levels too low for direct detection without prior sample concentration. The team also emphasizes the extraordinary speed of purine degradation: within seconds, ATP is dephosphorylated to ADP and then AMP, and within minutes AMP is further catabolized to adenosine, inosine, hypoxanthine and uric acid. Tissue measurements demand freeze-clamping in situ or focused microwave irradiation to halt degradation. Finally, the authors caution that isolated ATP measurements can be misleading, since they cannot distinguish energy impairment from wholesale purine depletion; only the simultaneous measurement of ATP, ADP and AMP, captured by the adenylate energy charge, provides a faithful picture of cellular energy state. With its speed, sensitivity and comprehensive coverage, the new UPLC-PDA method appears well suited to simultaneous analysis of the most abundant biologically relevant purines across blood, urine, cerebrospinal fluid and cultured cells, offering a powerful new lens on disorders of purine metabolism.

Subject of Research: Biomedical Analysis and Diagnostics

Article Title: Comprehensive measurement of purines in biological samples

Article References: Fu, R., Sutcliffe, D. J., Dinasarapu, A. R., Hess, E. J., & Jinnah, H. A. (2025). Comprehensive measurement of purines in biological samples. Frontiers in Analytical Science, 5, Article 1600781. https://doi.org/10.3389/frans.2025.1600781

Image Credits: AI Generated

DOI: 10.3389/frans.2025.1600781

Keywords: purine metabolism, UPLC-PDA, Lesch-Nyhan disease, hypoxanthine, adenylate energy charge, metabolomics, HPRT1, analytical chemistry, Comprehensive, measurement, purines, biological