- Inga Usher, neurosurgical senior house officer123,
- Peter Hellyer, senior lecturer45,
- Keng Siang Lee, medical student36,
- Robert Leech, professor of neuroimaging analytics7,
- Adam Hampshire, professor of restorative neurosciences4,
- Alexander Alamri, neurosurgical registrar38,
- Aswin Chari, neurosurgical registrar3910
- on behalf of Brainbook
- 1Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- 2Cancer Institute, University College London, London, UK
- 3Brainbook, London, UK
- 4Department of Brain Sciences, Imperial College London, London, UK
- 5Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
- 6Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
- 7Department of Neuroimaging, Kings College London, London, UK
- 8Neurosciences Research Centre, Molecular and Clinical Sciences Institute, St George’s University of London, London, UK
- 9Great Ormond Street Institute of Child Health, University College London, London, WC1N 3JH, UK
- 10Department of Neurosurgery, Great Ormond Street Hospital, London, UK
- Correspondence to: A Chari aswin.chari.18{at}ucl.ac.uk (or @aswinchari on Twitter)
Abstract
Objective To compare cognitive testing scores in neurosurgeons and aerospace engineers to help settle the age old argument of which phrase—“It’s not brain surgery” or “It’s not rocket science”—is most deserved.
Design International prospective comparative study.
Setting United Kingdom, Europe, the United States, and Canada.
Participants 748 people (600 aerospace engineers and 148 neurosurgeons). After data cleaning, 401 complete datasets were included in the final analysis (329 aerospace engineers and 72 neurosurgeons).
Main outcome measures Validated online test (Cognitron’s Great British Intelligence Test) measuring distinct aspects of cognition, spanning planning and reasoning, working memory, attention, and emotion processing abilities.
Results The neurosurgeons showed significantly higher scores than the aerospace engineers in semantic problem solving (difference 0.33, 95% confidence interval 0.13 to 0.52). Aerospace engineers showed significantly higher scores in mental manipulation and attention (−0.29, −0.48 to −0.09). No difference was found between groups in domain scores for memory (−0.18, −0.40 to 0.03), spatial problem solving (−0.19, −0.39 to 0.01), problem solving speed (0.03, −0.20 to 0.25), and memory recall speed (0.12, −0.10 to 0.35). When each group’s scores for the six domains were compared with those in the general population, only two differences were significant: the neurosurgeons’ problem solving speed was quicker (mean z score 0.24, 95% confidence interval 0.07 to 0.41) and their memory recall speed was slower (−0.19, −0.34 to −0.04).
Conclusions In situations that do not require rapid problem solving, it might be more correct to use the phrase “It’s not brain surgery.” It is possible that both neurosurgeons and aerospace engineers are unnecessarily placed on a pedestal and that “It’s a walk in the park” or another phrase unrelated to careers might be more appropriate. Other specialties might deserve to be on that pedestal, and future work should aim to determine the most deserving profession.
Introduction
“It’s not rocket science” and “It’s not brain surgery” are common phrases that describe concepts or tasks that are easily understood or performed. Other phrases such as “It’s a piece of cake” or “It’s a walk in the park” have similar meanings, but the two related to the aerospace industry and neurosurgery are unique in their association with professions.123 The phrase “It’s not rocket science” is thought to have originated in America in the 1950s when German rocket scientists were brought over to support the developing space programme and design of military rockets—both endeavours that were considered intellectually challenging.2 By the 1970s “It’s not rocket science” had become embedded in American culture, when it started to appear in newspaper articles.2 The origin of “It’s not brain surgery” is less clear. It is tempting to speculate that the pioneering techniques of the polymath and neurosurgeon Harvey Cushing captured the attention of the public and promulgated the phrase.4
The interchangeable use of “It’s not rocket science” and “It’s not brain surgery” and their association with professions renders comparison inevitable. In a sketch by UK comedians David Mitchell and Robert Webb,5 a boastful neurosurgeon is put in his place by a rocket scientist who says “Brain surgery . . . it’s not exactly rocket science is it?” Although some public debate has occurred as to which pursuit is more difficult,67 it seems that the two phrases have not been subjected to rigorous scientific scrutiny.
The main purpose of our study was to settle this debate once and for all and to provide rocket scientists and brain surgeons with evidence to support their self-assuredness in the company of the other party. We tested participants across several cognitive domains, including emotional discrimination and motor control. Instead of seeking an outright winner, we assessed the cognitive characteristics of each specialty using a validated online test, the Great British Intelligence Test (GBIT) from the Cognitron platform. This test had been used to measure distinct aspects of human cognition, spanning planning and reasoning, working memory, attention, and emotion processing abilities in more than 250 000 members of the British public as part of the GBIT project in association with BBC Two’s Horizon programme.8 The battery of tests should not be considered an IQ test in the classic sense, but instead is intended to differentiate the aspects of cognitive ability more finely. The large existing dataset also enabled us to benchmark both professions against the general population.9
The secondary aim of our study was to question whether public perceptions of rocket science and brain surgery are borne out in reality. Falling under the umbrella of science, technology, engineering, and mathematics (STEM) industries, neurosurgery and aerospace engineering face difficulties in maintaining their workforce and are predicted to be understaffed in coming decades.1011 Considerable evidence suggests that school aged children’s desire to pursue a career is influenced by their perceptions of particular professions, in turn impacting on the diversity of the workforce and the trajectory of specialties.1213 School aged children perceive STEM to be “masculine” and “clever.” This perception is heavily influenced by gender, class, and race, and deters females, people from lower socioeconomic groups, and people of non-white ethnicity from pursuing STEM careers.14 Perceptions and the stereotypes underlying them are derived from various sources, but school experiences and mass media are important.13 Questioning these stereotypes could have implications for public outreach and future recruitment.
Methods
We performed an international prospective comparative study, with participants recruited through the internet. Anyone who self-identified as an aerospace engineer or a neurosurgeon in the United Kingdom, Europe, the United States, and Canada was eligible to participate.
The roles were defined as any individual who had completed a degree relating to the relevant specialty. As specialisation occurs at the postgraduate stage, we excluded individuals who were studying for their primary degree (undergraduate science or primary medical degree).
This study was publicised via email and LinkedIn through our collaborators. The Society of British Neurological Surgeons and the Canadian Neurological Sciences Federation cascaded the invitation email to respective members. The UK Space Agency advertised the study on LinkedIn and through their partner organisations. The Royal Astronomical Society advertised the study in their June members’ bulletin. The European Space Agency advertised the study via its mailing list. To ensure responses were genuine, access to the study website was restricted to listed members of these groups and the study was not publicised on social media platforms.
Data collection
Data collection took place from 2 June to 23 July 2021. The study comprised a sequence of 12 tasks from a library available on the Cognitron server (www.cognitron.co.uk). The test took about 30 minutes to complete.
The tasks were selected on the basis of previous data, which showed they can be used to measure distinct aspects of human cognition, spanning planning and reasoning, working memory, attention, and emotion processing abilities. Previous work has shown that the battery of tasks is robust to the type of device that a person uses to complete the test; sensitive to population variables of interest such as age, gender, and education level; and not so strongly correlated as to measure just one overarching ability. As a result, the raw scores on each task are not of interest; instead, the meaningful findings are obtained by comparing standardised scores between individuals or groups to showcase differences in the measures.
Before doing the test, participants completed a questionnaire comprising six questions related to specialist area, gender, age, geographical location, handedness, and level of experience (years in specialty).
Task designs and data preprocessing
The 12 tasks were prospective word memory, digit span, spatial span, block rearrange test (two dimensional spatial problem solving), four towers test (three dimensional spatial problem solving), the Tower of London test (spatial planning), two dimensional manipulation, target detection, verbal analogies, rare word definitions, emotional discrimination, and delayed recall of words (see supplementary figure 1). Each task was scored, and, except for the rare word definitions task, was based on reaction time (ie, speed of response).
Data were preprocessed in a similar fashion to previous studies using the Cognitron platform.9 Briefly, only those datasets in which all tasks had been completed were included for analysis. In addition, we excluded participants who we considered had lost task focus—that is, the window had been inactive (in the background) for more than two seconds. We also performed a manual check for inconsistencies in questionnaire responses and excluded these datasets. Scores for each task >8 standard deviations from the mean were winsorised to reduce the effect of spurious outliers.
Statistical analysis
Confounding variables (age, handedness, and gender) were regressed out of the raw task scores and reaction times using generalised linear modelling, leaving adjusted scores. Through factor analysis, the eigenvalues of the correlations between adjusted task scores and reaction times were used to split the scores into several domains, with each task contributing weights to the domain. Two factor analyses were conducted, one for the task scores (12 tasks) and one for the reaction times (11 tasks). The number of domains for each factor analysis was based on the Kaiser criteria (eigenvalue >1). Using generalised linear modelling we then compared the domain scores between groups.
The comparator group comprised members of the UK general population who had completed the same set of tasks. This is a subset of the more than 250 000 participants who completed the GBIT but incorporates all eligible participants who had completed the battery of tests undertaken by the aerospace engineers and neurosurgeons. Only 18 257 were eligible because the initial battery of GBIT went through iterative amendments before settling on this final battery. The GBIT cohort was recruited through diverse sources, including the BBC Two’s Horizon programme, the BBC, and BBC News home pages and news meta-apps. Members of the cohort were predominantly white (226 257/269 264; 84.0%), had completed secondary school (84 860/269 264; 31.5%), and had a university degree (154 656/269 264; 51.4%). The task weightings derived from this study were applied to create domain scores for the general population. Z scores for each participant were then generated using the mean and standard deviation of domain scores from the general population. To assess if the z scores from each group were different from those of the general population, we used two tailed one sample t tests.
All data processing, analysis, and visualisation were conducted on Matlab v2020b (Mathworks). P values <0.05 were considered significant.
Patient and public involvement
Although patients and the public were not involved in the conception, design, or execution of the study, the study was conceived as part of the research arm of Brainbook, a UK charity dedicated to science communication and public engagement in neurosurgery and the neurosciences. Members of the researchers’ families reviewed the manuscript before submission.
Results
A total of 748 participants took part in the study: 600 aerospace engineers (80.2%) and 148 neurosurgeons (19.8%). As the mailing lists were under the control of their parent organisations and the size of these were not determined, it was not possible to calculate a response rate; only a small proportion (<20%) completed the survey.
The groups were matched for gender, handedness, and experience (years) in their specialty but not for age (table 1). Both groups comprised more males than females (72.8% of aerospace engineers and 71.6% of neurosurgeons). Most of the aerospace engineers were based in mainland Europe (n=459, 76.5%), whereas most of the neurosurgeons were based in the UK (n=108, 73.0%).
After data cleaning, 401 complete datasets were included in the final analysis, including 329 aerospace engineers (82.0%) and 72 neurosurgeons (18.0%). The factor analysis revealed six domains (four from the task scores and two from the reaction times), and the loading from each task suggested that these domains corresponded to memory, spatial problem solving, semantic problem solving, mental manipulation and attention, problem solving speed, and memory recall speed (see supplementary figure 2).
When the domain scores were compared between the groups, neurosurgeons showed significantly higher scores in semantic problem solving (difference 0.33, 95% confidence interval 0.13 to 0.52, P=0.001; fig 1). Aerospace engineers showed significantly higher scores in mental manipulation and attention (−0.29, −0.48 to −0.09, P=0.004). No difference was found between the groups in domain scores for memory (−0.18, −0.40 to 0.03, P=0.09), spatial problem solving (−0.19, −0.39 to 0.01, P=0.07), problem solving speed (0.03, −0.20 to 0.25, P=0.82), and memory recall speed (0.12, −0.10 to 0.35, P=0.29).
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In the final analysis, the domain scores were compared with 18 257 members of the general population who completed the same tasks as part of the GBIT (fig 2, table 2).89 Across all six domains, only two differences were significant: problem solving speed was quicker for neurosurgeons than for the general population (mean z score 0.24, 95% confidence interval 0.07 to 0.41, P=0.008) and memory recall speed was slower for neurosurgeons than for the general population (−0.19, −0.34 to −0.04, P=0.01).
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