Motor differences in autism have long been recognized but poorly measured. Autistic children and adults tend to score lower on classic dexterity assessments such as the Purdue Pegboard test, inserting fewer pegs into small holes within a time limit with either hand. Maximum finger tapping speed is reduced, and grip strength tends to be smaller. Studies of walking have documented larger step-to-step variability and abnormal gait patterns in autistic children, while autistic adults show less stable postural control. Yet these observations have been gathered with a patchwork of different tests, expensive motion capture systems, and separate assessments for arms and legs, making it nearly impossible to ask whether the same underlying factor drives motor differences throughout the body.

The new study, led by Atsushi Takagi and Chihiro Itoi of NTT Communication Science Laboratories together with colleagues, set out to close that gap with a single, common framework. The team built on a motor assessment previously validated on more than 1,600 people aged three to eighty-eight, which measures how consistently a limb repeats a circular movement. In the test, participants hold a smartphone and trace a ten-centimeter circle on a guide sheet, completing one revolution per metronome beat at 2.5 hertz for the hands. For the feet, the phone is strapped in an armband above the ankle, and the participant swings the straight leg from the hip to trace a fifteen-centimeter circle on the floor at a slower 1.5 hertz pace. Each limb is tested for just fifteen seconds.

The technical trick lies in how the raw accelerometer signal is turned into a measure of skill. The three-axis acceleration data are first centered and normalized, then rotated using principal component analysis so that the circular motion lies mainly in a two-dimensional plane. Each revolution is identified by successive crossings of the movement phase, and the similarity between neighboring revolutions is quantified with the Hausdorff distance, a metric that is fast to compute and robust to differences in sampling. Averaging the Hausdorff distances across all adjacent revolution pairs yields a single variability score for each limb. When every circle looks alike, variability is low and control is judged robust; when each revolution wanders along a slightly different path, variability is high and control is less consistent.

Crucially, the researchers first confirmed that both groups kept tempo equally well. Seventeen clinically diagnosed autistic adults, with a mean age of twenty-eight, and twenty age- and IQ-matched comparison participants traced circles at statistically indistinguishable speeds for every limb. This mattered because movement variability is known to rise with speed, a relationship described since Fitts’s classic 1954 work, so any group difference in variability could only be interpreted fairly if speed was matched. Prior studies have also found that autistic individuals can keep tempo with a single-frequency external rhythm without difficulty, and the present results are consistent with that picture.

When variability itself was compared, a clear asymmetry emerged. For the hands, statistical analysis revealed significant effects of dominance, group, and their interaction. Follow-up tests showed that the autistic group’s non-dominant hand was significantly more variable than that of the comparison group, while the dominant hand showed no reliable difference. For the feet, the pattern was broader: the autistic group showed greater variability across both the dominant and non-dominant lower limbs, with no specific dominance interaction. In other words, the upper limb difference was confined to the non-dominant side, whereas the lower limb difference appeared globally. The autistic group also displayed significantly greater hand laterality, meaning the gap between their dominant and non-dominant hands was larger than in comparison participants.

Perhaps the most intriguing result came from linking the limbs together. Using a linear mixed-effects model, the researchers asked whether a person’s foot variability predicted their hand variability after accounting for group, dominance, and their interaction. It did: the association was positive, with a slope of 0.28, meaning that individuals with wobblier feet also tended to have wobblier hands. Notably, this relationship held equally in both groups, since adding a group-by-foot-variability interaction did not improve the model. The authors are careful to stress that this does not prove a causal link or a single shared neural mechanism, because the group effects differed between the upper and lower limbs. Still, it suggests that common factors, such as motor timing variability, sensory variability, or habitual limb use, may influence movement consistency throughout the body, coexisting with limb-specific effects.

The increased hand laterality in the autistic group came as a surprise. Earlier questionnaire studies and meta-analyses have suggested that autistic individuals are more likely to be mixed-handed, which led the team to predict smaller, not larger, differences between the two sides. Yet on the Edinburgh Handedness Inventory both groups reported equally strong right-handedness, and a slight difference in footedness on the Coren quotient vanished after correction for multiple comparisons. The authors propose that what people say about their hand preferences may diverge from how skillfully they actually use each hand, and that questionnaire measures suffer from ceiling effects that blunt their sensitivity. Motor-based assessments, by contrast, may capture real differences in lateralized skill that self-report misses.

Why would the non-dominant hand and both feet be selectively affected? The researchers weigh several possibilities. One candidate is heightened sensory variability: autistic individuals show larger trial-to-trial variability in sensory percepts, and tasks like peg insertion that demand tactile processing are disproportionately affected. But it is unclear why such a difference would localize to the non-dominant side alone. Another candidate is motor timing. Autistic children show reduced cerebellar activity and connectivity during finger tapping, and the cerebellum is critical for precise timing; timing variability is itself known to be larger in the non-dominant hand. A third possibility involves practice and generalization. Autistic children have been reported to use their non-dominant hand less often, and previous work suggests that motor learning in autism may generalize poorly across limbs, with internal models formed in a highly limb-specific way and an increased reliance on proprioceptive feedback. Skills refined through years of dominant-hand use may simply fail to transfer, leaving the non-dominant hand and the comparatively unfamiliar feet less robustly controlled. The authors caution that habitual use was not measured, so this remains a hypothesis.

The practical implications may prove the most consequential part of the story. Because the test requires only a smartphone, fifteen seconds of movement, and no laboratory equipment, it could be deployed in clinics, schools, or homes as a rapid, quantitative probe of coordination. Related work by the same group has linked circular leg movement variability to postural stability, suggesting the measure carries functional meaning beyond the task itself. The study does have limits: nearly all participants were right-handed, so laterality findings need testing across a range of handedness, and only adults were studied, leaving open when in development these differences emerge. Even so, the image of autistic motor control that emerges is more nuanced than a simple deficit. Dominant-hand skill is intact, tempo-keeping is intact, and yet the less-practiced corners of the motor repertoire betray a measurable, quantifiable difference, one that a device in nearly every pocket can now detect.

Subject of Research: Motor variability during circular movements as a measure of limb control differences in autistic adults

Article Title: Motor Variability of Circular Movements Reveals Differences in Non-Dominant Hand and Foot Control in Autistic Adults

Article References: Takagi, A., Itoi, C., Honda, K., & Kashino, M. (2026). Motor Variability of Circular Movements Reveals Differences in Non-Dominant Hand and Foot Control in Autistic Adults. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-026-07546-3

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07546-3

Keywords: autism spectrum disorder, motor variability, sensorimotor control, smartphone accelerometer, non-dominant hand, lower limb control, laterality, Hausdorff distance, motor timing, cerebellum, clinical motor assessment, adults

The first of the two papers, published in the Journal of General Internal Medicine, examined the interplay between social-media-based emotional support, real-life emotional support and loneliness. Emotional support, in this context, refers to the sense of being cared for, understood and comforted by others, a resource long recognized in health psychology as a buffer against stress and illness. The researchers wanted to know whether the encouragement, sympathy and validation people receive through online platforms could compensate for deficits in the support they receive from people they know in person. The answer, according to the data, was decisively no. Participants with the lowest levels of real-life emotional support had more than eight times the odds of experiencing loneliness compared with those reporting the highest levels of in-person support, a difference the authors describe as striking in magnitude.

Lower levels of social-media-based emotional support were also associated with loneliness, but the relationship was much weaker. Critically, when the researchers entered both types of emotional support into the same statistical model, only real-life emotional support remained significantly associated with loneliness. In practical terms, this means that whatever comfort people derive from their online networks appeared to be dwarfed once the contribution of tangible, in-person relationships was accounted for. Geethika Koneru, a medical doctor and graduate student who led the study, noted that when the two forms of support were directly compared, the protective signal from real-life relationships overwhelmed the online signal. The implication is that an active digital social life is not a workaround for a thin offline one, at least when it comes to guarding against loneliness in adulthood.

Methodologically, the study rests on survey data collected in July and August 2023 from a nationally representative cohort of adults aged 30 to 70, allowing the researchers to generalize their findings to a broad swath of the American middle-aged and older population. This age focus is itself notable. Much of the existing scholarship on social media and well-being has concentrated on adolescents and young adults, partly because those groups were the earliest adopters and remain heavy users of platforms like Instagram and TikTok. Brian Primack, a physician and researcher at Oregon State University’s College of Health who directs the broader research program, emphasized that adults are substantial users of social media too, while loneliness and depression remain significant public health concerns across the entire adult lifespan. Filling that evidentiary gap, he argues, is essential for understanding how technology fits into the social lives of people who manage careers, families and aging parents.

Primack is careful to frame the results as a caution rather than a condemnation. The findings, he said, do not mean that social media is inherently harmful, but they do suggest that individuals and society should think carefully about how it is used. This nuance matters because the popular discourse often swings between portraying platforms as engines of connection and dismissing them as purely corrosive forces. The Oregon State data points toward a more textured reality: online interactions can generate some emotional support, and that support correlates weakly with lower loneliness, but it operates on a fundamentally different and smaller scale than the support transmitted through embodied, in-person relationships. For public health purposes, the takeaway is that investments in digital connectivity cannot be expected to substitute for community infrastructure, family ties and friendships that exist beyond the screen.

The second paper, published in the Journal of Prevention, shifted the analytical lens from the content of social media use to its timing. Rather than asking how much support people extracted from platforms, the researchers asked when people first reached for them each day. The specific question was whether using social media soon after waking was associated with depression, independent of how much time people spent on platforms overall. The team found that social media use within the first 30 minutes after waking was strongly associated with depression, and the association held even after the researchers statistically accounted for total social media use and demographic characteristics such as age, sex, income and education. That persistence after adjustment is what makes the finding noteworthy, since it suggests the morning behavior is not merely a proxy for being a heavier user in general.

Hyosin Kim, a research assistant professor at Oregon State University who led the timing study, stressed that the direction of the relationship remains unresolved. It is possible that reaching for a phone immediately upon waking contributes to depressed mood, perhaps by flooding the mind with comparisons, notifications and stressors before the day has begun. It is equally possible that depression leads people toward the phone, since disrupted sleep, low morning motivation and rumination are hallmarks of depressive episodes, and the low-effort stimulus of a social feed can be an appealing retreat for someone struggling to face the day. A third possibility is bidirectional, with each factor reinforcing the other in a cycle. Kim’s team is explicit that their cross-sectional survey design cannot disentangle cause from consequence, and they frame the result as a signal that warrants longitudinal and experimental follow-up rather than a verdict on causation.

Taken together, the two studies sketch a research agenda in which the patterns of social media use matter as much as the raw quantity. Primack and colleagues, including Memuna Aslam, Jessica Gorman, Kari-Lyn Sakuma and Cesar Arredondo alongside Koneru and Kim, are pursuing a broader program examining how different dimensions of platform engagement relate to social connection and mental health across adulthood. The timing study suggests that circadian context, the intersection of technology habits with sleep and morning routines, may be an underappreciated variable in mental health research. The support study suggests that the functional quality of online interaction, specifically whether it delivers genuine emotional support, matters more than the sheer presence of an online network. Both framings move the field past blunt screen-time tallies toward more precise questions about who uses platforms, when, how, and to what psychological effect.

The timing of these publications carries its own historical resonance. July 15 marked the 20th anniversary of Twitter’s public launch, and September 26 marks 20 years since Facebook became available to anyone aged 13 or older with an email address, transforming the platforms from campus experiments into universal utilities. Two decades of data have now accumulated, and the Oregon State findings contribute an adult perspective to what has often been a youth-centered debate. For the millions of adults who have integrated scrolling into their morning routines and their social lives, the message is not that the technology must be abandoned. It is that the emotional weight lifted by an online network is modest compared with the weight carried by the people who show up in person, and that the first half hour after waking may be a more consequential moment for mental health than anyone imagined when the feeds were born.

Subject of Research: The relationship between social media use, emotional support, loneliness and depression among U.S. adults

Article Title: Social media offers little substitute for real-life emotional support, research suggests

Article References: Social media offers little substitute for real-life emotional support, research suggests. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: social media, loneliness, emotional support, depression, mental health, Oregon State University, public health, real-life relationships, morning social media use, adults, social isolation, Journal of General Internal Medicine

The research, published in the Journal of Activity, Sedentary and Sleep Behaviors, paired two kinds of objective measurement that are rarely captured simultaneously: passive smartphone sensing and wrist-worn accelerometer data. Instead of asking people to recall their habits, the team recorded, second by second, when a phone’s screen was actually in use and whether the person wearing the accelerometer was sitting still or moving. The result is one of the most granular portraits yet of how digital device use and physical behavior intertwine in everyday life.

The study drew on an ongoing cohort of adult caregivers of preschool-aged children, a population whose days are punctuated by childcare demands, errands and fragmented activity. Smartphone screen time was captured objectively with Chronicle, an Android-based passive sensing application that logs device usage without relying on user self-report. Movement behavior, meanwhile, was assessed with wrist-worn accelerometers, the small motion sensors that have become the gold standard for measuring physical activity and sedentary time in free-living conditions.

The technical processing was correspondingly detailed. Accelerometer signals were analyzed using GGIR, a widely used open-source pipeline, together with the SedUp algorithm, which classifies brief time epochs as sedentary or non-sedentary based on the posture and motion information embedded in the wrist signal. The researchers then aligned the two data streams at an unusually fine resolution: five-second epochs, restricted to waking wear time. Across the analytic sample of 63 participants, this alignment produced 785 person-days of data, or roughly 3.3 million individual five-second windows in which both smartphone state and body movement were known at once.

The headline finding is striking in its simplicity: a substantial share of smartphone screen time happens while people are not sedentary. At the participant level, the median proportion of smartphone use occurring during non-sedentary behavior was 25.9 percent. That means roughly one in every four seconds of phone use, for the typical person in this study, took place while the body was up and about. The range of individual differences was enormous, stretching from 5.6 percent to 73.7 percent, suggesting that for some people the phone is almost entirely a couch companion, while for others it functions nearly as a mobile device in the literal sense.

The researchers dug further into what was happening during those non-sedentary moments of screen use. Among the epochs in which people used their phones while not sedentary, 52.1 percent occurred during inactive behavior and 47.9 percent during active behavior. The distinction matters because non-sedentary is not automatically synonymous with physically active; someone standing still at a kitchen counter is not sedentary, but neither are they accumulating meaningful movement. Even so, the finding that nearly half of non-sedentary screen time occurred during genuine activity challenges the deepest layer of the screen-time-as-sitting assumption.

Perhaps the most intuitive results emerged at the level of individual apps. Social media applications were predominantly used during sedentary behavior, fitting the popular image of endless scrolling from a seated position. But utility and media apps told a different story. The Phone, Maps, Camera, and YouTube applications all showed higher proportions of non-sedentary use, a pattern that maps neatly onto how people actually live: checking directions while walking, photographing a moment on the go, or watching a video while standing in a queue. Screen time, in other words, is not a single behavior but a bundle of behaviors with distinct postural signatures.

The implications reach well beyond measurement pedantry. Sedentary behavior is an established risk factor for cardiometabolic disease, and interventions designed to reduce sitting time often use screen time as both a target and a proxy outcome. If a quarter or more of phone use occurs during movement, then studies that equate screen time with sedentary time may systematically misclassify behavior, potentially underestimating sedentary levels in some people and overestimating them in others. Momentary misclassification of this kind can distort the estimated effectiveness of interventions, obscure real relationships between screen habits and health, and misdirect resources toward reducing screen use when the actual problem, for a given individual, is prolonged sitting.

The study’s authors argue that smartphone screen time fails as a momentary proxy for sedentary behavior because the proportion occurring during non-sedentary activity is substantial, highly variable between individuals, and dependent on which apps a person uses. That variability itself is a finding: any fixed correction factor applied to self-reported or passively sensed screen time would misfit a large share of the population. The work also hints at more sophisticated future interventions, in which app-level context could inform whether a nudge to move more, or a nudge to put the phone down, is actually warranted in a given moment.

There are, of course, limits to what a single study can settle. The sample consisted of 63 adult caregivers of young children, a group whose smartphone and movement patterns may differ from those of retirees, office workers or adolescents, and the analysis focused on Android users whose devices could run the sensing application. The researchers describe their work as an opportunistic analysis within an ongoing cohort, and the findings will need replication across more diverse populations and device ecosystems. But the methodological template, aligning passive phone sensing with accelerometry at five-second resolution, offers a way forward that does not depend on fallible human recall. As screens migrate from fixed locations into every pocket, the study suggests that the science of sedentary behavior must follow, measuring where the body is, not just where the eyes are.

Subject of Research: The alignment of smartphone screen-time sensing with accelerometer data to test whether screen time is a valid momentary proxy for sedentary behavior in adults

Article Title: Not all screen time is sedentary: evidence from aligned smartphone sensing and accelerometry data in adults

Article References: Culverhouse, J., Finnegan, O. L., Bowen, K., Nelakuditi, S., Ghosal, R., Radesky, J. S., Adair, T., Restino, M., White, J. W., III, Zhong, Z., Hadj-Amar, B., Holmes, A., Kiely, K., Burkart, S., Adams, E. L., Weaver, R. G., Beets, M., & Armstrong, B. (2026). Not all screen time is sedentary: evidence from aligned smartphone sensing and accelerometry data in adults. Journal of Activity, Sedentary and Sleep Behaviors. https://doi.org/10.1186/s44167-026-00109-y

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00109-y

Keywords: screen time, sedentary behaviour, smartphone use, physical activity, accelerometry, passive sensing, GGIR, SedUp algorithm, public health, mobile apps, measurement, adults

The theoretical starting point is the auditory deprivation hypothesis, which holds that early suboptimal auditory stimulation impairs the development of language, and that language, in turn, scaffolds the emergence of executive functioning. Classic work in this tradition, including Conway, Pisoni, and Kronenberger’s account of how sound supports cognitive sequencing, and Botting and colleagues’ demonstration that nonverbal executive function is mediated by language in deaf and hearing children, has framed deafness as a neurocognitive risk factor. Kesarwani and Debbarma accept this framework but add a crucial twist: the instruments used to measure executive functioning are themselves saturated with language, meaning that any assessment in the deaf population risks confounding true cognitive differences with linguistic load.

The search strategy combined terms for executive functioning and hearing impairment, including cognitive functioning, linguistic influence on executive functioning, and the influence of cochlear implants, with the keyword ‘young adults’ added to isolate the relevant age group. Databases such as Scopus, PsycINFO, and PubMed were queried, and twelve studies survived the inclusion criteria. The multidimensional nature of executive functioning was mapped using measures spanning working memory, inhibitory control, cognitive flexibility, planning, and theory of mind, ranging from self-report inventories such as the Behavior Rating Inventory of Executive Function–Adult version to behavioral paradigms like the Eriksen flanker task, which requires participants to respond to a target letter while ignoring distracting flanking letters—a design that can be delivered almost entirely visually.

The pattern that emerges is striking. On language-dependent measures—verbal fluency tasks, self-report questionnaires, and complex verbal reasoning batteries—deaf young adults consistently score lower than hearing peers. But when the review examined visually presented, low-language behavioral paradigms, the group differences shrank substantially, and in some domains disappeared altogether. This dissociation suggests that what has been interpreted as an executive functioning deficit in deaf young adults may, in considerable measure, reflect the linguistic demands of the assessment tools rather than a core cognitive impairment. In other words, the measuring stick itself may be bent.

The findings are consistent with the broader literature on visual attention in deaf populations. Studies such as those by Sladen and colleagues and Rothpletz and colleagues found that deaf adults can show intact, and in some cases enhanced, attentional deployment to the visual periphery, a plausible adaptation to a world perceived primarily through vision. Similarly, research on visual-spatial skills by Marschark, Spencer, and colleagues indicates that hearing status interacts with language experience in ways that do not map neatly onto simple deficit narratives. The new review synthesizes this evidence to argue that executive functioning in deaf young adults is mediated jointly by language exposure and task modality—two factors that most standard clinical batteries fail to disentangle.

Cochlear implants add another layer of complexity. The review reports that implantation is associated with improved cognitive skills, aligning with longitudinal work by Sarant and colleagues showing cognitive gains in older adults receiving implants, and with Kronenberger and colleagues’ neurocognitive risk model for implanted children. Yet even among implanted individuals, linguistic skills remain the primary predictor of executive functioning outcomes. This is a crucial nuance: restoring auditory input appears to help, but it does not erase the foundational role of early language access. The implication is that language-rich environments—whether signed or spoken—during the critical early years remain the strongest protective factor for later executive functioning.

The review also engages with theory of mind, the capacity to attribute mental states to others, which is often classified under the broader executive functioning umbrella. Studies of deaf college students by Marschark, Edwards, and colleagues, and work by Lecciso and colleagues on deaf adults, show that theory-of-mind performance is heavily dependent on linguistic proficiency and conversational access. Native signers with deaf signing parents frequently perform comparably to hearing peers, while deaf individuals with delayed or impoverished early language access show the largest gaps. This mirrors Woolfe’s findings with deaf native signing children and reinforces the review’s central thesis: language experience, not deafness per se, drives many of the cognitive differences documented in the literature.

Methodologically, the authors validated their instruments where possible. Hauser, Lukomski, and Samar demonstrated that the BRIEF-A can be reliable and valid for deaf college students, but only after careful adaptation, and their work appears alongside studies using the Adult Executive Functioning Inventory and general ability measures such as the General Ability Measure for Adults. The review highlights that self-report inventories pose a particular problem in the deaf population because their items are embedded in idiomatic written English, and comprehension of such language is itself a variable under study. When the test’s language load correlates with the construct’s linguistic dependence, measurement error and true variance become indistinguishable—a psychometric trap the authors urge the field to escape.

The real-world stakes are considerable. Executive functioning predicts academic achievement, employment, social maturity, and psychological adjustment, and Xiong and colleagues recently showed that executive dysfunction contributes to anxiety in hearing-impaired college students through pathways involving smartphone addiction and academic procrastination. If assessments systematically overestimate executive difficulties in deaf young adults, misdiagnosis, inappropriate support decisions, and lowered expectations may follow. Conversely, if genuinely deficient skills in verbal working memory or sequencing are masked by poorly designed visual tasks, individuals may miss interventions that could help. Accurate, linguistically sensitive measurement is thus not an academic nicety but a prerequisite for equitable education, clinical care, and workplace policy.

The authors close with a forward-looking recommendation: future assessment of executive functioning in deaf young adults should be linguistically sensitive by design, favoring visually delivered, low-language behavioral paradigms, reporting participants’ language histories explicitly, and treating modality of presentation as an experimental variable rather than a fixed convenience. They acknowledge the review’s limitations—twelve studies is a modest evidence base, and heterogeneity in samples, signing status, implantation history, and measures complicates synthesis—and note that no datasets were generated or analysed beyond the published literature. Still, the message lands with force. A generation of findings portraying deaf young adults as cognitively at risk may need recalibration, because a substantial share of the measured gap may belong to the tests, not the test-takers. For a population already navigating environments built for the hearing, that distinction matters: cognitive capacity should be measured on its own terms, not filtered through the language of those doing the measuring.

Executive functioning is not a single capacity but a family of interrelated processes that continue developing well into the mid-twenties, with the prefrontal cortex maturing gradually across adolescence and early adulthood. This protracted developmental trajectory means that the young adult years represent a window in which individual differences in cognitive control become consequential for real-world outcomes such as higher education, employment, and independent living. It also means that measurement choices made during this period can shape trajectories of support, since a young adult identified as having weak planning or working memory skills may be steered toward particular academic accommodations or clinical services on that basis.

The auditory scaffolding account underlying the review draws on a wider body of work in cognitive neuroscience suggesting that early sensory experience shapes the neural architecture available for later cognition. Temporal sequencing, in particular, is thought to depend on experience with the rapid, sequential structure of spoken language, so that children deprived of clear auditory input during sensitive periods may develop alternative but differently organized strategies for encoding order and sequence. Research with deaf native signers is informative here: when sign language is acquired from birth, many aspects of cognitive development proceed on a typical timetable, indicating that a fully accessible visual language can serve the same scaffolding function that spoken language serves for hearing children.

This perspective reframes deafness-related cognitive research as a natural experiment in modality and language experience rather than a search for deficits. Comparisons among deaf native signers, deaf late signers, oral deaf individuals with cochlear implants, and hearing controls allow researchers to separate the contributions of auditory access, language timing, and communication modality. Studies that include such detailed language histories tend to find that the timing and richness of early language exposure predict cognitive outcomes more consistently than audiological factors such as degree of hearing loss.

For practitioners, the practical takeaway is that assessment batteries for deaf young adults should be selected and interpreted with the linguistic demands of each instrument made explicit. Visual, nonverbal tasks can serve as a baseline against which performance on verbal measures is compared, and discrepancies between the two may signal linguistic load rather than cognitive weakness. Bilingual assessment frameworks that account for both signed and spoken language proficiency, and that involve examiners fluent in the client’s preferred language, offer a promising route toward measurement that reflects genuine ability rather than the accident of test design.

Subject of Research: Executive functioning in deaf young adults: a systematic review of measures and linguistic influence

Article Title: Executive functioning in deaf young adults: a systematic review of measures and linguistic influence

Article References: Kesarwani, S., & Debbarma, R. (2026). Executive functioning in deaf young adults: a systematic review of measures and linguistic influence. SN Social Sciences, 6(9), Article 402. https://doi.org/10.1007/s43545-026-01694-0

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01694-0

Keywords: Executive, functioning, deaf, young, adults, systematic, review, measures, linguistic, influence, scientific research

The answer, according to the findings, is a clear no. Among the fifth-grade children who participated, stronger comprehension went hand in hand with markers of reading fluency. Children who understood the texts better tended to make fewer fixations overall, produced fewer regressions back to previously read material, and executed longer saccades, meaning their eyes jumped farther forward with each movement. These are classic signatures of an efficient, automatic decoding process. In contrast, the adults in the sample, who included twenty undergraduates and nine faculty members, showed a different pattern. For them, better comprehension was associated with slower reading, more fixations, and generally more attentive, effortful engagement with the text. Rather than fluency signaling understanding, in adults it was deeper cognitive investment that predicted how well the material was grasped.

This developmental reversal makes sense when situated within established theories of reading acquisition. The influential framework proposed by LaBerge and Samuels in the 1970s holds that reading depends on automaticity: when lower-level processes such as letter recognition and word decoding become automatic, attentional resources are freed for higher-level comprehension. For children still consolidating these lower-level skills, the efficiency of basic word recognition remains a bottleneck. A child who must laboriously assemble words letter by letter has little capacity left to build a coherent mental model of the passage. Consequently, in young readers, fluency measures function as a reasonable proxy for comprehension potential, a view consistent with the large body of evidence showing that text reading fluency mediates the relationship between decoding skill and comprehension throughout the elementary school years.

By adulthood, however, decoding is typically fully automatized for skilled readers, and variation in fluency among competent adult readers no longer constrains understanding in the same way. Instead, comprehension differences among adults reflect what happens after individual words are recognized: integrating sentences into a discourse model, drawing inferences, monitoring understanding, and relating new information to prior knowledge. Walter Kintsch’s construction-integration framework describes comprehension as the construction of a textbase and a situation model, processes that demand deliberate cognitive engagement. The finding that adults who read more slowly and fixated more often comprehended better suggests that these adults were allocating extra time to exactly these integrative operations. Slower reading in a skilled adult is not a sign of weakness but often a sign of deeper processing, particularly when texts are expository and informationally dense.

The distinction maps onto the difference between lexical and post-lexical processing. Fixation durations and word-based measures during a first pass through a sentence largely reflect lexical access and syntactic parsing, whereas regressions, second-pass reading, and selective reinspection often reflect repair, integration, and inference generation. In children, the study’s correlational pattern suggests that the first-pass efficiency measures dominate the comprehension picture. In adults, the engagement measures, including the willingness to slow down and dwell on the text, take over as the meaningful correlates of understanding. This shift from reliance on low-level skill to reliance on high-level processing represents a developmental progression in the very architecture of comprehension.

Several features of the study’s design merit attention when interpreting these results. Participants read age-appropriate expository texts, which means children and adults were not reading identical material. This choice, while necessary to avoid floor and ceiling effects, means the developmental comparison concerns comprehension of suitably calibrated texts rather than comprehension of a single fixed passage. Expository texts were a sensible choice because they place heavy demands on background knowledge and inference, and they resemble the kinds of reading required in educational settings from middle childhood onward. Eye-tracking data were collected during the participants’ first read of each text, which is important because rereading changes eye-movement patterns substantially; prior work by Hyönä and Kaakinen has shown that fixation durations drop and patterns reorganize when a text is encountered a second time. Capturing the first encounter ensures that the recorded eye movements reflect genuine online comprehension processes rather than memory-supported review.

The sample itself was modest but appropriate for a correlational study of this kind: twenty-one fifth-graders and twenty-nine adults. All participants were native Spanish speakers, which matters for several reasons. Spanish has a relatively shallow orthography, meaning that grapheme-to-phoneme correspondences are largely regular and decoding is typically mastered earlier and more completely than in deep orthographies such as English. Meta-analytic work, including the recent analysis by Leachman, Wolters, and Kim, has demonstrated that the relationship between text reading fluency and comprehension varies systematically with orthographic depth and developmental phase. In a transparent orthography, the fluency-comprehension link in children may reflect a somewhat different balance of skills than it would in English, where decoding struggles persist longer. The fact that fluency still emerged as the key correlate of comprehension in Spanish-speaking children underscores how central automatized word processing remains for comprehension even when the writing system is relatively friendly to the learner.

The study also connects to a broader movement in reading science away from overly simple models. The classic Simple View of Reading proposed by Gough and Tunmer in 1986 framed comprehension as the product of decoding and linguistic comprehension, a formulation that has been enormously productive but increasingly recognized as incomplete. More recent integrative models, such as Kim’s Direct and Indirect Effects Model of Reading and the framework advanced by Duke and Cartwright, emphasize that reading comprehension rests on a constellation of skills, including executive functions, vocabulary, background knowledge, and inference-making, whose relative contributions shift across development. The eye-tracking evidence from this study provides a behavioral, moment-to-moment signature of exactly such a shift: the same observable behavior, such as a high fixation count, carries different implications about comprehension depending on the reader’s developmental stage.

Executive functions deserve particular mention in this context. Butterfuss and Kendeou have argued that working memory, inhibition, and cognitive flexibility support the construction and maintenance of a coherent situation model, especially during the integration of information across sentences and paragraphs. The adult pattern observed here, in which more fixations and slower reading accompanied better comprehension, is consistent with readers strategically deploying these executive resources. Similarly, research on prior knowledge by Kaakinen and colleagues has shown that readers allocate longer fixations to text segments that are relevant to their reading goals, particularly when background knowledge must be actively coordinated with incoming information. Adults who engage in this kind of selective, effortful reading are, in effect, trading speed for depth, and the comprehension measures reward that trade.

Practically, the findings carry implications for assessment and instruction. For children in the intermediate grades, the results reinforce the value of building reading fluency, not as an end in itself but as the gateway to comprehension. Repeated reading, wide independent reading of connected text, and instruction that promotes automatic word recognition all serve to free cognitive resources for meaning-making. For adolescents and adults, especially those in teacher education programs where concerns about reading comprehension demands have recently been raised in the literature, the results suggest that interventions should target higher-level skills: inference generation, discourse integration, metacognitive monitoring, and the strategic slowing down that deep texts require. A one-size-fits-all approach that treats slow, effortful reading as a problem to be corrected would, for adult readers, mistake engagement for inefficiency.

The study’s methodological choices also illustrate good practice in eye-tracking research. The authors addressed outlier detection and treatment following established statistical guidance, an important step given that fixation distributions are typically skewed and sensitive to occasional anomalous measurements. The decision to include both undergraduate students and faculty professors within the adult group introduced a range of reading expertise among the adults, which may have sharpened the contrast between fluency-driven and engagement-driven comprehension profiles. The openness of the data on the Open Science Framework allows other researchers to verify the analyses, test alternative models, and pool evidence across studies, practices that strengthen the cumulative reliability of the field.

Some caveats remain. The correlational design cannot establish causal direction: it is possible that children who comprehend better become more fluent, rather than fluency driving comprehension, although longitudinal and intervention evidence elsewhere supports the latter pathway as well. The modest sample sizes, while adequate for regression-based analyses according to minimum sample size guidance, limit the precision of estimates and the ability to detect interactions. The inclusion of professors alongside undergraduates raises questions about whether the adult pattern is homogeneous or driven by the most expert readers. And because comprehension was measured after a single reading, the study cannot speak to how readers strategically reread or study text over time.

Nevertheless, the central contribution stands out clearly: the eye movements that betray comprehension are not universal but developmental. What looks like skill in a child, namely swift, forward-moving, uninterrupted reading, looks different in an adult, for whom comprehension is signaled by deliberate, resource-intensive engagement with the text. Understanding this progression helps researchers build more accurate models of reading development, helps educators match instruction to the reader’s current stage, and reminds us that the path from fluent decoding to deep understanding is not a single leap but a gradual reorganization of the entire reading system.

Subject of Research: Comprehension is in the Eye of the Reader: An Eye Tracking Study of Children and Adults

Article Title: Comprehension is in the Eye of the Reader: An Eye Tracking Study of Children and Adults

Article References: Tabullo, Á., Jofre, E. M. G., Del-Punta, J. A., Rodríguez, K. V., & Gasaneo, G. (2026). Comprehension is in the Eye of the Reader: An Eye Tracking Study of Children and Adults. Trends in Psychology. https://doi.org/10.1007/s43076-026-00537-4

Image Credits: AI Generated

DOI: 10.1007/s43076-026-00537-4

Keywords: Comprehension, Reader, Tracking, Children, Adults, scientific research