Beyond Functional Asymmetry: Sexual Dimorphism in the Concordance Between Cerebral Dominance and Handedness Among University Students

1. Introduction

The initial discovery of the relationship between cerebral hemispheric dominance and manual preference traces back to the early clinical observations of Marc Dax (1836/1865) [1], which were presented in 1836 and subsequently published through the efforts of his son in 1865. Later, Paul Broca (1865) systematically and comprehensively formalized this relationship, establishing that left-hemispheric dominance for speech is closely linked to motor preference for right-hand use [2,3,4]. the functional specialization of the cerebral hemispheres - or Brain lateralization- represent prominent neuropsychological phenomena that have garnered extensive attention within neuroscience and cognitive research. Hemisphericity- or Brain dominance- refers to an individual's propensity to rely more heavily on one hemisphere for information processing. The left hemisphere is typically associated with analytical, sequential, and linguistic processing styles, whereas the right hemisphere is characterized by spatial, holistic, and creative processing [5].

Conversely, handedness or manual dominance reflects motor superiority and the preferential use of one hand over the other in fine motor skills. Despite traditional neuroanatomical accounts assuming a strict crossed dominance that automatically renders the left hemisphere dominant in right-handed individuals, contemporary literature demonstrates that both cerebral and manual dominance exhibit neurobiological complexity and flexibility. Rather than adhering to a rigid dichotomy, both constructs lie on a continuous continuum [6,7]. In this regard, researchers distinguish between two primary dimensions of manual preference: the direction of handedness and the degree/strength of handedness. Neuropsychological evidence indicates that the strength of manual preference serves as a more robust predictor of functional brain lateralization than direction alone [8].

Regarding the nature of the relationship and congruence between these two forms of dominance, neurobiological models suggest a complex, non-linear interaction mediated by interhemispheric inhibition through the corpus callosum. While strongly right-handed individuals exhibit high congruence—with an almost absolute left-hemispheric dominance for language and cognitive functions reaching approximately 95%—this congruence significantly declines among left-handed and mixed-handed individuals. In the latter groups, hemispheric dominance is more variably distributed, showing left-sided specialization, right-sided specialization, or balanced bilateral representation across both cerebral hemispheres [9,10].

Despite the theoretical foundation of functional specialization, recent meta-analyses and systematic reviews reveal substantial empirical variability in estimating the degree of congruence between cerebral and manual dominance. This inconsistency is moderated by the strength of hand preference, quantitative measurement methodologies, and complex interactions with biological sex. The literature offers two main accounts regarding sex differences: the first posits that males exhibit greater hemispheric lateralization due to neurodevelopmental hormonal influences, whereas females demonstrate more flexible bilateral representation paired with larger callosal cross-sectional areas. The second account suggests that sex differences in lateralization are subtle and heavily dependent on the specific cognitive task invoked [11,12,13].

A critical research gap exists—particularly within the Arab context—regarding studies that evaluate the degree of congruence between cerebral and manual dominance using quantitative, continuous variables rather than traditional dichotomous frameworks, while simultaneously examining the moderating effect of sex. Investigating these dynamics in a sample of university students is highly pertinent, as early adulthood represents a neurodevelopmentally mature period characterized by fully integrated interhemispheric connectivity and stabilized functional brain organization.

Accordingly, the present study aims to determine the degree of congruence between cerebral dominance and handedness in light of biological sex among university students, while empirically testing the underlying neurofunctional interactions that account for this phenomenon.

2. Materials and methods

2.1. Participants

The total sample consisted of N = 350 undergraduate student volunteers (154 males versus 196 females), selected from an initial pool of N = 400 participants. Data collection was group-administered across four separate testing sessions (n = 100 participants per session) to address aspects related to statistical control. Prior to statistical analysis, n = 50 participants were excluded due to incomplete survey protocols or evidence of response invalidity. The participants' ages ranged from 18 to 24 years (mean = 19.015, standard deviation = 0.866). Prior to data collection, written informed consent was obtained from all participants, as participation was entirely voluntary. Based on their psychometric profiles, participants were categorized into sub-groups for empirical analysis. Regarding hand preference, participants were classified using a purposive sampling strategy matched for age and academic grade level into left-handedness (n = 106), right-handedness (n = 172), and mixed-handedness (n = 72). For brain hemispheric dominance, participants were classified into left-hemisphere dominance (n = 144), right-hemisphere dominance (n = 62), and integrated/balanced dominance (n = 144). Detailed demographic and Neuropsychological characteristics of the sample are summarized in Table 1.

2.2. Materials

2.2.1. Brain Hemispheric Dominance

Hemispheric dominance was assessed using the Human Information Processing Survey [14; Arabic adaptation by 15]. The psychometric stability of the instrument was confirmed via test–retest reliability over a 22-day interval, yielding reliability coefficients of .79 for the right-hemisphere style, .71 for the left-hemisphere style, and .73 for the integrated (mixed) style. Criterion-related validity was established through a significant concurrent correlation with the Preferred Hand Inventory (Musa, 2009; r = .83).

2.2.2. Hand Preference

Handedness was evaluated using the Preferred Hand Inventory [16]. The inventory demonstrated robust test–retest reliability over a 22-day interval, with stability coefficients of .74 for right-hand preference, .79 for left-hand preference, and .76 for mixed-hand preference. Concurrent criterion validity was corroborated by a strong correlation with the Human Information Processing Survey (Torrance et al., 1984; r = .83).

2.2.3. Procedures

Ethical approval and written informed consent were obtained prior to data collection, which proceeded in two stages. In the first stage, hand preference was evaluated individually via the Preferred Hand Inventory [16]. To mitigate self-report bias and enhance empirical validity, participants performed simulated motor tasks (e.g., writing, utensil use) under real-time observation, with untimed administration to eliminate performance speed pressure. Left- and mixed-handed participants were selected via purposive sampling and matched with right-handed peers based on age and academic grade level.

In the second stage, the Human Information Processing Survey [15] was group-administered across four open-ended, untimed sessions (n ≈ 100 per session) to assess hemispheric dominance. From the initial pool of 400 participants, 50 were excluded due to incomplete responses or response invalidity. Consequently, a final sample of N = 350 fully completed and valid protocols was retained for statistical analysis.

2.3. Data Analysis

Data were processed and analyzed using the Statistical Package for Social Sciences (version 24.0 Inc.). Descriptive statistics were calculated, namely: percentages, frequencies, means (M), and standard deviations (SD) - were computed to summarize demographic characteristics, describe participant distributions across hemispheric dominance patterns and handedness levels, and assess cross-tabulated concordance rates. To evaluate the relationship and agreement between handedness and hemispheric dominance, Cohen’s kappa (κ) was calculated to quantify agreement beyond chance. Additionally, a chi-square (χ²) test of independence was performed to evaluate the association between the two variables, with Phi coefficient (ϕ ) utilized as a measure of effect size. All statistical tests were evaluated at a significance level of α = .05.

3. Results

3.1. Results of descriptive analysis

The demographic and neuropsychological characteristics of the study sample (N = 350) revealed diversity across the primary variables (see Table 1). Females constituted the majority of participants at 56%, with a mean age of (19.07) years (SD = 0.87). Regarding hemispheric lateralization and manual dominance, the proportion of left-hemisphere dominance was equivalent to that of integrated/bilateral hemisphere dominance at 41.1% each, whereas right-hand preference was the most prevalent among sample members at 49.1%.

Table 1. Demographic and Neuropsychological Characteristics of the Study Sample (N = 350).

Characteristic	Category	n	%	M(SD)
Sex	Male	154	44.0	—
	Female	196	56.0	—
Age (Years)	Total Sample	—	—	19.065 (.866)
Brain Hemisphericity	Left Hemisphere Dominant	144	41.1	—
	Right Hemisphere Dominant	62	17.7	—
	Integrated / Bilateral	144	41.1	—
Manual Dominance (Handedness)	Right Handed	172	49.1	—
	Left Handed	106	30.3	—
	Mix Handed	72	20.6	—

Note. N = total sample size; n = subsample size; M = Mean; SD = Standard Deviation.

Table 1. Demographic and Neuropsychological Characteristics of the Study Sample (N = 350).

Characteristic	Category	n	%	M(SD)
Sex	Male	154	44.0	—
	Female	196	56.0	—
Age (Years)	Total Sample	—	—	19.065 (.866)
Brain Hemisphericity	Left Hemisphere Dominant	144	41.1	—
	Right Hemisphere Dominant	62	17.7	—
	Integrated / Bilateral	144	41.1	—
Manual Dominance (Handedness)	Right Handed	172	49.1	—
	Left Handed	106	30.3	—
	Mix Handed	72	20.6	—

Note. N = total sample size; n = subsample size; M = Mean; SD = Standard Deviation.

3.2. Results of basic analysis

As presented in Table 2, a higher rate of concordance between handedness and brain dominance was observed among male participants compared to females; The number of males showing compatibility reached 94 out of 154 (61.0%), compared to 80 out of 196 (40.8%) of females. Across the total sample, the overall concordance rate between the two types of dominance was 49.7% (n = 174). Although the overall concordance rate did not exceed 50%, Cohen's κ coefficient indicated a statistically significant agreement (κ = .238, p < .001), confirming that the observed concordance between handedness and brain dominance reflects a genuine statistical association rather than random chance.

as presented in Table 3, A chi-square test of independence and Phi coefficient revealed a statistically significant association between handedness and cerebral hemisphere dominance across sex groups, Overall, agreement between brain dominance and handedness was observed in 174 participants (49.7% of the total sample), comprising 94 males (26.9%) and 80 females (22.9%). A chi-square test demonstrated a statistically significant difference between males and females in brain–handedness agreement rates, χ² (1, N = 350) = 14.11, p < .001. Additionally, the Phi coefficient (ϕ = .201) indicated a small-to-moderate statistically significant effect size of sex on the degree of congruence between handedness and cerebral dominance.

4. Discussion

The primary objective of the present study was to provide a deep, theoretically grounded neuropsychological account of the concordance between manual dominance and cerebral hemisphere dominance among university students (N = 350), evaluating study hypotheses regarding sex differences in agreement rates and examining the structural mechanics of the cross-tabulation matrix. From a structural contingency perspective, strict contralateral neuro-behavioral alignment occurs within the primary diagonal cells of the cross-tabulation matrix, specifically where right-handedness couples with left-hemisphere dominance, left-handedness couples with right-hemisphere dominance, and mixed-handedness maps onto integrated or bilateral hemisphere dominance.

Regarding the first research hypothesis, which posited a high and statistically significant concordance between cerebral dominance and manual preference, empirical results provided only partial support. Specifically, 49.7% of the total sample populated the primary diagonal cells of direct alignment. Although Cohen’s kappa coefficient confirmed that this agreement was statistically significant above chance (κ = .238, p < .001), the overall concordance rate did not reach a majority, indicating a pronounced degree of divergence in the off-diagonal cells. This concordance rate presents an empirical divergence from classical neuro-behavioral models and early deterministic frameworks, such as Geschwind and Galaburda’s hypothesis and classical lateralization studies, which posited an almost absolute alignment between right-handedness and left-hemisphere language dominance exceeding 90% in normative samples [9,17]. Furthermore, these findings diverge from regional studies such as Al-Sulaymani, which reported an absolute predominance of left-hemisphere dominance aligning with dextral preference [18], and Meziane and Zaqai [19].

However, our empirical findings align closely with modern neuro-epidemiological paradigms, genetic lateralization models, and contemporary empirical studies, such as Annett’s Right-Shift Theory and McManus’s Dextral/Chance Allele Model [20,21], alongside recent neuro-imaging evidence by Ahrens et al. and Belcher et al. demonstrating that manual preference and cognitive lateralization operate through functionally uncoupled mechanisms [22,23]. These results directly corroborate recent neuropsychological investigations revealing widespread parallel and bilateral processing profiles independent of overt manual preference [24,25]. The underlying mechanism for this observed non-concordance stems from the fact that motor preference and cerebral cognitive specialization follow functionally and evolutionarily distinct genetic and epigenetic pathways. While motor hand preference is established early via spinal corticospinal tracts and spinal gene expression, cognitive hemisphere dominance develops through distributed cortical association networks influenced by developmental plasticity and environmental exposure, thereby explaining non-concordant profiles as reflections of neural plasticity, developmental instability, or prenatal hormonal modulation [26,27,28].

Regarding the second research hypothesis, which predicted statistically significant sex differences in diagonal concordance rates, the empirical results fully confirmed the hypothesis, χ² (1, N = 350) = 14.11, p < .001, with a Phi coefficient (ϕ = .201) indicating a small-to-moderate effect size. Specifically, male participants demonstrated a markedly higher and more consistent concentration within primary diagonal alignment cells at 61.1%, whereas female representation within these diagonal alignment cells was significantly lower at 40.8%, exhibiting greater dispersal toward off-diagonal cells and integrated processing patterns. This confirmation of the second hypothesis is strongly supported by contemporary connectomic frameworks of sexual dimorphism, sex-differentiated neural connectomics, and modern neuro-hormonal modulation models, anchored in foundational hemispheric theories [29,30,31].

Modern diffusion tensor imaging and functional connectivity studies, such as those by Azoor et al. and Fuerst et al., demonstrate that male brains exhibit significantly greater intra-hemispheric connectivity and modular structural organization [32,33]. This modular architecture promotes rigid, compartmentalized lateralization, tightly binding manual motor execution directly to contralateral dominant processing along classic diagonal pathways. Conversely, consistent with recent findings on female neuro-plasticity and diffuse connectivity by Cary et al. and Williams et al., female brains demonstrate significantly enhanced inter-hemispheric network connectivity, mediated by higher structural density across the corpus callosum [34,35]. This heightened inter-hemispheric crosstalk in females reduces rigid single-hemisphere specialization, fostering diffuse and bilateral cognitive processing. Consequently, elevated inter-hemispheric communication in females decouples manual preference from strict single-hemisphere dominance, shifting females away from rigid diagonal alignment into off-diagonal, integrated processing categories, thereby accounting for the lower concordance rates observed among females and fully confirming the study hypothesis.

5. Conclusion

The present study evaluated the concordance between cerebral dominance patterns and manual preference among undergraduate university students (N = 350). Participants were classified into distinct cross-tabulation patterns based on manual dominance (right-handed, left-handed, mixed) and cerebral hemisphere dominance (left-hemisphere, right-hemisphere, integrated/bilateral), while systematically examining sex-differentiated diagonal concordance rates. Empirical findings revealed that less than half of the total sample (49.7%) exhibited strict diagonal concordance between manual preference and cerebral dominance, demonstrating a pronounced degree of divergence in off-diagonal processing categories. However, significant sex differences emerged in diagonal alignment rates, with male students demonstrating a markedly higher and more consistent diagonal concordance rate (61.0%) compared to female students (40.8%), who showed greater dispersal toward integrated processing patterns. These non-concordant profiles and sex-specific alignment patterns are likely mediated by Variation in the anatomical and functional structure of the brain, such as heightened inter-hemispheric callosal connectivity in females versus intra-hemispheric modularity in males. Consequently, while overall alignment between cerebral dominance and manual preference remains limited, biological sex functions as a robust moderator in shaping functional neurobehavioral asymmetry.

These empirical insights yield crucial educational, clinical, and theoretical implications. Educational institutions and curriculum designers must avoid assuming a deterministic alignment between manual preference and cognitive cerebral dominance when structuring pedagogical frameworks. Instructors should instead adopt "Whole Brain" instructional strategies that allow students to acquire academic skills through parallel, flexible educational methodologies leveraging integrated cerebral processing to maximize bilateral functional capacity [19,36]. Theoretically, scholars should reconsider the dynamic relationships between manual dominance, cerebral lateralization, and cognitive adaptability in light of underlying neurodevelopmental and hormonal moderators, designing interventions that enhance cognitive flexibility based on individualized neural processing profiles rather than gross motor preferences. Moving forward, longitudinal investigations across diverse age groups are warranted to track neural plasticity and lateralization stability over time, while interdisciplinary collaborations among cognitive psychologists, neurologists, and educational researchers should be expanded to assess lateralization across clinical and experimental conditions using integrated behavioral batteries and neuroimaging connectivity models.

6. Limitations

Several methodological limitations of the present study must be acknowledged when interpreting these results. First, sample data were gathered exclusively from undergraduate students (enrolled in bachelor’s degree programs: Bachelor of Arts and Bachelor of Science) within specific academic faculties at a single university, which constrains the demographic generalizability of the findings across broader populations. Second, the quantitative, cross-sectional architecture precludes causal inferences regarding the neurodevelopmental trajectory of functional lateralization; future investigations would benefit from qualitative or mixed-methods approaches to explore the underlying mechanisms of cerebral dominance, handedness, and sex differences in greater depth. Finally, because the findings were derived solely from behavioral assessment inventories without incorporating direct neurophysiological recordings, such as functional magnetic resonance imaging (fMRI) or diffusion tensor imaging (DTI), the connectomic and structural mechanics discussed remain theoretically inferred. Researchers should therefore exercise appropriate caution when generalizing these conclusions beyond the specific contextual, behavioral, and demographic boundaries of the current sample.