Many a time, populations are categorized with the assumption that handedness should be considered in a single dimension and there should be no borderlines within this continuum. Thus, studies report on categories of right-handedness, ambidextrous and left-handedness to the exclusion of others like right-biased ambidextrous and left-biased ambidextrous. It is expected that when one uses one hand for a specific activity or uses it more often than the other hand for all activities, that person develops the efficiency of the particular hand for the given activity. This suggests that hand performance is directly related to hand preference, and the extent of hand dominance can be established by the resultant efficiency that arises from the relationship between hand performance and hand preference.
In research terms, handedness is often used to imply hand preference. In which case the preferred hand is the hand which is most efficient in performing specific manual dexterity tasks such as writing or manipulating objects and tools. Hand dominance, on the other hand, reflects an inter-manual difference of motor performance which shows the best efficiency in performing a particular unimanual action. If hand function is to be adequately assessed between the dominant and nondominant hand among humans, there has to be a distinction between hand preference and hand performance.
In performing bimanual tasks, which are hand movements that involve both hands moving simultaneously, each hand adopts a particular function. The preferred hand executes the most complex action or takes up the manipulative role, whereas the nonpreferred hand acts mainly as a steadying effect or postural support. This is seen in tasks such as clapping, nailing, knitting, eating with a fork and knife, typing on a keyboard, drumming and even using sign language. However, when assessing hand dominance, it is important that the investigator makes consideration of the subject's need to learn the task at hand prior to carrying it out. The tests are first performed with each hand separately and then both hands together. The outcome of the assessment does not follow that the faster or better performing hand will be the same as the self-reported preferred hand. In fact, studies done over a span of a few decades have all showed that performance-based assessments are rather disassociated from self-reports.
As suggested by Adamo and Taufiq, hand preference may be determined by combining findings that associate handedness inventories with hand performance assessments. The argument being that investigations of hand functionality that do not fully assess hand preference restrict the interpretations and limit the application of the findings, thereby reducing the observed effects. On the other hand, well-determined hand preference is likely to enable better placement of individuals in the workplace so that they can perform work tasks that place them at less risk for injury.
In order to improve the skills training of preclinical medical students for performing certain clinical tasks that require a high level of precision and manual dexterity, it is important for the trainers, mentors, and preceptors to understand differences in hand dominance among them. This would help to identify students who might need more learning time for a particular task and also reduce relative risk for self-injury during performance of the said task. The purpose of the present study was to assess the differences in hand dominance by evaluating the relationship between hand preference and hand performance testing in a select group of preclinical medical students.
Material and Methods
Following approval by the KNH-UoN Ethics and Research Committee and with permission from the School of Medicine to conduct this study, a total of 162 willing participants were selected. We used a finite population of 900 preclinical medical students in applying the OpenEpi sample size calculation for cross-sectional studies using 15% as the hypothesized frequency of left-hand dominance in the population. In order to conclusively categorize hand dominance among the selected 162 preclinical medical students, both the subjective self-reported hand preference questionnaire of the modified Edinburgh Handedness Inventory (EHI) and the objective measure of hand performance testing by the Tapley and Bryden Dot-filling Tasks were applied.
Each subject was assessed using a modified Edinburgh Handedness Inventory, from which the Geschwind Score (GS) was calculated and applied. The EHI for each subject was translated into a laterality score based on a Likert scale of-5 (always left),-2.5 (usually left), 0 (no preference), +2.5 (usually right), and +5 (always right). This was used to calculate the laterality quotient, also called the Geschwind score, where a GS ≤ −100 indicated that the subject response was left-handed for all tasks; a GS ≥ +100 indicated right-handedness for all tasks; and a score that was between −100 and +100 indicated ambidextrous or mixed-handedness for various tasks.
Dominance in hand performance was determined by the observational measure of hand performance using the Tapley and Bryden dot-filling tasks. Subjects were presented with a single sheet of A4 paper, on which were open circles (dots) printed in 4 rows, linked at the top and bottom, to make a “W” shape. Each page had four such arrays. On the upper left-hand array, there was an arrow pointing down at the top left corner printed to indicate the starting point and the direction. The upper right array also had an arrow pointing down at the far-right corner with the starting point and direction of flow indicated. The bottom two arrays were identical to these two. Subjects were started with the writing hand (A), followed by the non-writing hand (B) and 4 trials were performed in the following sequence-ABBA. For example, a left-handed subject first performed the “Left-hand” start at the top, followed by the Right-hand start at the top, then the lower “Right-hand start,” and finished with the lower Left-hand start. Dots were counted only if they fell entirely within the circle and did not touch any edges (i.e., LRRL). All participants completed the dot-filling task with a fine-point black felt-tip marker.
To determine hand performance dominance, both a differential score (right-hand average minus left-hand average), and a laterality score ([R-L/R + L] ×100) were calculated (where R and L refer to right and left hand, irrespective of the writing hand). Absolute values ranged from −1 (indicating left-hand dominance) to +1 (indicating right-hand dominance), with absolute value of manual skill asymmetry ranging from 0 (both hands equivalent) to 1 (one hand completely dominant).
Determination of dominance in hand performance using the Tapley and Bryden dot-filling tasks
The Tapley and Bryden Dot-filling Tasks were analyzed using the conventional laterality index (LI = [R-L/R + L] ×100). It gave a hand performance mean value = 22.31, with standard deviation = 12.753 (n = 162), and a resultant distribution curve of the hand performance tending towards normal [Figure 1]. Of note in this histogram was the clear demarcation between the right-oriented (LI score 10–100) and the left-oriented hands (−10 to −100). There was a small group which was classified as having no orientation (−10−10).
There were a total of six subjects (3.7% of the total population) with left-hand dominance in performance, who were equally distributed between males and females. There were 6 subjects (3.7% of the total) with equal-hand dominance in performance, who were also equally distributed by gender. There were 150 subjects (92.6% of the total) with right-hand dominance in performance. The Pearson Chi-Square goodness of fit test revealed that the distribution by gender groups was not statistically significant (χ2 = 0.343, P = 0.843 @95% confidence interval [CI]), thereby suggesting that hand dominance in performance testing is not a function of gender.
Assessment of hand preference in relation to hand performance
The results of hand performance were also subjected to a distribution box-plot test in relation to the GS hand preference where the majority of the study population was found to be right-hand dominant. Both the Kolmogorov–Smirnov test (P = 0.007) and Shapiro–Wilk test (P < 0.001) for normality confirmed skewness of data and gave a statistically significant P value for right-hand dominance, with skewness = 0.818 and kurtosis = 1.178.
The Pearson correlation test showed a very high statistically significant positive correlation between the Geschwind Score for Hand Preference and the Tapley and Bryden Laterality Index for Hand Performance Dominance (r = 0.655, P < 0.001 @ 0.01 significance level). This correlation suggests that hand preference testing and hand performance testing should be used together because they complement and reinforce the assessment of hand dominance.
The degree of association between the Geschwind Score Handedness Categories and Tapley and Bryden Dot Filling Hand Dominance Classification [Table 1] was analyzed using the Pearson Chi-Square goodness of fit test. A statistically significant difference was recorded between the hand dominance classification and the hand preference categories, with χ2 = 142.293 and P < 0.001 (@95% CI).
Cross-tabulation between hand preference categories and hand dominance in performance found 14 (100% of ambidextrous) ambidextrous persons by GS preference to be right-hand dominant by the Tapley and Bryden Dot filling Tasks (TBD) tasks. These were practically right-ambidextrous subjects, making up 8.6% of the total population and 9.3% of right-hand dominant persons. Of the 7 left-handed persons by GS preference, there were 6 (85.7% of left-handed) who were left-hand dominant. These were seemingly pure left-handed subjects, making up 3.7% of the total population. There was 1 left-handed person (14.3% of left-handed) found to show no-hand dominance (16.7% of no hand dominance), who was practically left-ambidextrous. Of the 141 (87% of total population) right-handed persons, there were 136 (84% of total population and 96.5% of right-handed persons) who were right-hand dominant. These were seemingly pure right-handed subjects. The other 5 (3.5% of right-handed persons) right-handed persons were found to have no-hand dominance. These were correctly right-ambidextrous, making up 83.3% of the no-hand dominance group and 3.1% of the total population. In summary, the resultant categorization of hand function following assessment of dominance using both hand performance and hand preference testing is shown in Table 2.
The characteristics and relevance of the Tapley and Bryden Dot Filling Tasks in relation to the GS EHI right hand revealed a sensitivity of 90.7% with a specificity of 58.3%. The positive predictive value (and precision value) was 96.5% with an accuracy of 88.3%. This suggests that in the absence of the EHI-GS, the Tapley and Bryden Dot Filling Task has a 90.7% chance of correctly classifying a person to be right-hand dominant in 96.5% cases; and this classification would be 88.3% accurate.
As various researches have revealed, in young healthy subjects self-rated hand dominance, hand preference and hand efficiency are all highly correlated based on the level of motor performance. Nevertheless, the differences in the performance of the dominant and nondominant hands are expected to diminish with increasing age and to become more balanced in early adulthood. If hand preference is considered over hand performance, there is a likelihood of misclassifying ambidextrous (or apparently neutral-handed) persons as pure-handed (be it right-or left-handed, ambidextrous or ambivalent), thereby omitting significant details about efficient hand use by the said mixed-or cross-handed individual.
As the results in the present study have showed, those who were initially classified by the EHI GS as ambidextrous, were all reclassified by the combined tests as right-ambidextrous. This is a significant change that can influence results in proficiency testing. It is also likely that the individual who had to be reclassified as left-ambidextrous might have a degree of mixed proficiency results given that there was no-hand dominance in the performance testing. The results of the present study are also in favour of reporting more mixed-and cross-handedness than pure ambidextrous as suggested by EHI-GS categories. The most consistent result was that of the left-handed individuals, which gave a 3.7% pure left-handed population. This proportion might appear small, but it could as well be clinically/practically significant when assessing the skills of these individuals in training using right-biased tools.
It is noteworthy that the results of the current study support the view by Corey et al. about performance-based measures such as the Tapley and Bryden Dot Filling Tasks not to be considered independently when predicting hand dominance. It is necessary to combine such performance tests with other hand preference tests, even if they are from self-reported questionnaires such as the EHI, to be able to more clearly distinguish hand dominance. This is signified by the 96.5% precision value and the 88.3% accuracy rate of determining hand dominance obtained by combining the GS hand preference with the dot-filling tasks.
The results in the present study are similar to the findings by Brown et al., which indicated that the combination of the results from a handedness questionnaire and a series of performance measures gives the best predictors of hand dominance. The current study further enforces the thought that habitual use of either the right or left hand can typically be observed during the performance of everyday tasks. However, it should be acknowledged that task-specific training effects may influence the extent to which one identifies and describes their dominant hand.
It is clear that measures of hand dominance are based on individual hand use preference or hand performance testing; but there really are no clear categories for each one, such as being exclusively left-or right-hand dominant. As demonstrated earlier, each individual shows a preference for the use of one hand for a given manual action, even though it is not always the same hand that is preferred for two different actions. Now, whether one is right-or left-hand dominant is therefore a function of the given task at hand, and not a generalization of the dominant hand. Furthermore, there are several studies which report of individuals who are specialized in highly skilled and complex tasks who demonstrate very strong correlations between different tasks.
In their study of handedness and musical ability in a group of professional musicians, Aggleton et al. demonstrated that the dominant hand performs tasks requiring force or a series of rapid movements while the other hand offers stabilization and support. There is no doubt that the habitual use of the same hand for a given task contributes and promotes skills development of the same hand for the particular tasks; yet, habitual use does not appear to transfer the acquired skill to other tasks. It is therefore possible for one to gain proficiency in the use of a certain tool, but this level of proficiency does not transfer to other tools with similar physical properties.
Since hand preference for some tasks could also be modified by social or religious influences, the tasks selected for use in hand assessments should apply typical tools amongst the said specific populations from different cultures so that hand dominance variations in a given population can be adequately studied. Although researchers like Bishop allege that hand dominance might be a by-product of brain lateralization in human beings, this notion does not explain the 5%–15% left-handed population that is reported in every culture.
The present study evaluates of hand dominance among preclinical medical students echoes the thought by others like Baldwin et al., that a combination of hand preference and hand performance testing should be used in assessing manual dexterity skills that are required during precise surgical procedures. The results also support the notion that self-reported questionnaires by experienced clinicians may identify a specific skill that is needed to perform a given task, but the students must still be subjected to an objective test that is used when measuring their skills performance. This viewpoint was likewise expressed by the research which experimented with virtual reality laparoscopy simulators, and another one which used a motion-tracking system to assess laparoscopic suturing skills.
Suffice to say that the use of multiple measures to determine hand performance is a stronger predictor for determining hand dominance than reliance on a single measure. However, it must be kept in mind that the number of previously performed procedures will strongly influence the level of proficiency reached in performing specific tasks. This therefore means that hand preference and hand performance must be considered together when assessing for potential differences in performance outcomes of the dominant and nondominant hands.
Conflicts of interest
There are no conflicts of interest.
Financial support and sponsorship
We acknowledge contributions made by Mr. Martin I. Inyimili and Ms. Esther W. Mburu in recruiting subjects and ensuring complete data collection. Appreciation to all preclinical students of the University of Nairobi who willingly gave consent and participated in the study.
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