Attention lesson 11 min read

What attention predicts

Employers and exam boards test attention because it is linked to how people learn and work. But the links are more modest, and more interesting, than the hype around "focus" suggests. This lesson walks through the strongest evidence, gives you the actual numbers, and is honest about what a short attention test can and cannot tell anyone about you.

At school: attention helps, knowledge helps more

The best single study on early skills and later achievement is Greg Duncan and colleagues' 2007 analysis of six large longitudinal datasets from the United States, Canada and the United Kingdom. They asked which skills at school entry predicted achievement years later, with everything else held constant.

What school-entry skills predicted later achievement
  • Maths skills0.34
  • Reading skills0.17
  • Attention skills0.1
  • Socioemotional behaviour0

Maths knowledge came first, reading second and attention third. Attention mattered, independently of the others, but its coefficient was less than a third of maths. The raw correlation between attention and later achievement was about .25, which shrank once early knowledge was accounted for.

Inhibitory control, the braking side of attention, shows a similar picture. A 2014 meta-analysis by Allan and colleagues pooled 75 studies of 14,424 young children and found an average correlation of .27 between inhibitory control and early literacy and maths skills. Clancy Blair and Rachel Razza, following 141 children from low-income homes, found that "the inhibitory control aspect of executive function was a prominent correlate of both early math and reading ability".

The practical lesson for a candidate is the same one the data teach: attention amplifies what you know. It does not replace it.

Across a life: self-control

The most striking long-run evidence comes from the Dunedin study in New Zealand. Terrie Moffitt and colleagues followed a complete birth cohort of 1,037 children to age 32, with 96 per cent retention. They measured childhood self-control, a broader trait than attention that includes impulse control and persistence, and compared adult outcomes for the fifth of children with the most self-control and the fifth with the least.

Adult outcomes by childhood self-control (Dunedin cohort, age 32)
  • Criminal conviction: lowest self-control fifth43%
  • Criminal conviction: highest fifth13%
  • Income under NZ$20,000: lowest fifth32%
  • Income under NZ$20,000: highest fifth10%
  • Multiple health problems: lowest fifth27%
  • Multiple health problems: highest fifth11%

The authors reported that these effects could be "disentangled from their intelligence and social class". Self-control is not the same thing as the millisecond-level inhibition in a go/no-go task, but it belongs to the same family, and the study is a large part of why researchers take impulse control seriously.

At work: ability matters, less than you were told

For decades the standard figure for how well general mental ability predicts job performance was Frank Schmidt and John Hunter's .51, from their 1998 review. In 2022, Paul Sackett and colleagues re-examined how those older studies had been corrected for statistical artefacts and concluded the corrections had been too generous. Their revised estimate for the same older data is .31, and newer 21st-century samples give about .23. Structured interviews now rank at least as well.

.51Classic estimate: general mental ability and job performance
.31The same older data, re-corrected
.23Estimate from 21st-century studies

Attention and processing speed are components of general ability, not substitutes for it. So an honest reading is: cognitive tests, including the attention tasks inside them, carry real but moderate information about later performance. That is exactly why employers combine them with interviews, simulations and technical tests rather than hiring on one score.

Evidence from people with attention difficulties points the same way. In a US workforce survey led by Ronald Kessler, adults with ADHD had the equivalent of 35 days of lost work performance a year compared with similar colleagues. A World Health Organization survey across ten countries found 22.1 excess days of lost role performance. And in two studies of workplace safety, Craig Wallace and Stephen Vodanovich found that everyday cognitive failures (lapses of attention and memory) predicted unsafe behaviour and accidents over and above conscientiousness.

Distraction and pressure

Much of what goes wrong with attention in real life is not a lack of ability but a competing demand.

Interruptions. In Gloria Mark and colleagues' experiment, people interrupted by calls and messages finished their tasks in less time with no loss of quality, but "this comes at a price: experiencing more stress, higher frustration, time pressure and effort". Interruptions are paid for in effort, even when the output looks fine.

Phones. Adrian Ward and colleagues reported in 2017 that the mere presence of your own smartphone reduced available cognitive capacity. Be cautious with this one: a pre-registered direct replication published in 2022 found no difference between phone-location conditions. Moving your phone out of sight costs nothing, but it is not a proven performance booster.

Anxiety. Michael Eysenck's attentional control theory proposes that anxiety impairs the goal-directed attention system, particularly inhibition and shifting, and lets stimulus-driven attention take over. Crucially, anxiety may damage efficiency more than effectiveness: you can often still get the right answer, but only by spending more effort.

scoreeffortCalmscoreeffortAnxiousConcept sketch, not datasame answer,more effort to get it
Attentional control theory in one picture: under anxiety, accuracy can hold up while the effort needed to reach it rises. On a timed test, that extra effort shows up as lost time.

Choking. Sian Beilock and Thomas Carr found that performance pressure harmed people high in working memory capacity, and only on maths problems that made the heaviest demands on working memory. Pressure competes for the very resources strong candidates rely on.

Mind wandering. Michael Mrazek and colleagues randomised 48 students to two weeks of mindfulness classes or a nutrition class. The mindfulness group wandered less and improved on a GRE reading-comprehension section by an amount the authors describe as analogous to 16 percentile points. It is one small study, but it shows that attention during a test is partly a state you can influence.

The limits: what one short test can say

Here is the part most test-prep material leaves out. The best-known attention tasks produce effects that almost everyone shows, but they rank individuals unreliably. Craig Hedge, Gavin Powell and Petroc Sumner called this the reliability paradox.

Across a groupcongruentincongruentalmost everyone is slowerFor one person, day to daythe ranking reshufflesday 1day 2you
The reliability paradox. The flanker slowdown is near-universal across a group, but one person's cost varies enough from session to session that rankings reshuffle.

When they tested the same people on two occasions:

Test-retest reliability of attention measures (Study 1)
  • Go/no-go false presses0.76
  • Plain reaction time, congruent flanker rows0.74
  • Stroop interference cost0.6
  • Stop-signal reaction time0.47
  • Flanker interference cost0.4

The reason is not sloppy measurement. Difference scores like "incongruent minus congruent" cancel out the part of reaction time that varies a lot between people and keep a smaller part that varies less. The Attention Network Test shows the same pattern: its conflict score had a test-retest reliability of .77, but its alerting score only .52.

This has three consequences for you.

  1. One session means little. A good or bad day moves an attention score more than it moves a vocabulary score. Judge your progress over weeks.
  2. Vendors know this. Serious test publishers build attention measures from many trials and combine several tasks, rather than trusting a single difference score. Our own scoring works on accuracy across many trials and shrinks small samples towards the middle of the scale until you have enough evidence.
  3. Accuracy is the stable part. Error counts, like false presses on a go/no-go task, were among the more reliable measures. Being consistently right is more visible than being a few milliseconds faster.

What the evidence supports

  • Attention skills predict school achievement, but less strongly than early maths and reading knowledge (.10 vs .34).
  • Inhibitory control correlates about .27 with early academic skills across 75 studies.
  • Childhood self-control predicts adult health, wealth and crime in a large birth cohort, beyond IQ and social class.
  • Ability tests predict job performance moderately: about .31 on re-corrected classic data and about .23 in recent samples.
  • Anxiety, interruptions and mind wandering cost effort and time even when accuracy survives.
  • Single attention scores are noisy. Many trials, many sessions and accuracy give the truest picture.

Next, Where attention is tested shows how placement tests, entrance exams and game-based assessments actually measure these skills.

Sources
  1. Duncan, G. J., et al. (2007). School readiness and later achievement. Developmental Psychology, 43(6), 1428–1446. doi.org/10.1037/0012-1649.43.6.1428
  2. Allan, N. P., Hume, L. E., Allan, D. M., Farrington, A. L., & Lonigan, C. J. (2014). Relations between inhibitory control and the development of academic skills in preschool and kindergarten: A meta-analysis. Developmental Psychology, 50(10), 2368–2379. doi.org/10.1037/a0037493
  3. Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Development, 78(2), 647–663. doi.org/10.1111/j.1467-8624.2007.01019.x
  4. Moffitt, T. E., et al. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. PNAS, 108(7), 2693–2698. doi.org/10.1073/pnas.1010076108
  5. Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology. Psychological Bulletin, 124(2), 262–274. doi.org/10.1037/0033-2909.124.2.262
  6. Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity in personnel selection. Journal of Applied Psychology, 107(11), 2040–2068. doi.org/10.1037/apl0000994
  7. Sackett, P. R., et al. (2023). Revisiting the design of selection systems in light of new findings regarding the validity of widely used predictors. Industrial and Organizational Psychology, 16(3), 283–300. doi.org/10.1017/iop.2023.24
  8. Kessler, R. C., et al. (2005). The prevalence and effects of adult attention deficit/hyperactivity disorder on work performance in a nationally representative sample of workers. Journal of Occupational and Environmental Medicine, 47(6), 565–572. doi.org/10.1097/01.jom.0000166863.33541.39
  9. de Graaf, R., et al. (2008). The prevalence and effects of adult attention-deficit/hyperactivity disorder on the performance of workers: Results from the WHO World Mental Health Survey Initiative. Occupational and Environmental Medicine, 65(12), 835–842. doi.org/10.1136/oem.2007.038448
  10. Wallace, J. C., & Vodanovich, S. J. (2003). Workplace safety performance: Conscientiousness, cognitive failure, and their interaction. Journal of Occupational Health Psychology, 8(4), 316–327. doi.org/10.1037/1076-8998.8.4.316
  11. Mark, G., Gudith, D., & Klocke, U. (2008). The cost of interrupted work: More speed and stress. Proceedings of CHI 2008, 107–110. doi.org/10.1145/1357054.1357072
  12. Ward, A. F., Duke, K., Gneezy, A., & Bos, M. W. (2017). Brain drain: The mere presence of one's own smartphone reduces available cognitive capacity. Journal of the Association for Consumer Research, 2(2), 140–154. doi.org/10.1086/691462
  13. Ruiz Pardo, A. C., & Minda, J. P. (2022). Reexamining the "brain drain" effect: A replication of Ward et al. (2017). Acta Psychologica, 230, 103717. doi.org/10.1016/j.actpsy.2022.103717
  14. Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7(2), 336–353. doi.org/10.1037/1528-3542.7.2.336
  15. Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and "choking under pressure" in math. Psychological Science, 16(2), 101–105. doi.org/10.1111/j.0956-7976.2005.00789.x
  16. Mrazek, M. D., Franklin, M. S., Phillips, D. T., Baird, B., & Schooler, J. W. (2013). Mindfulness training improves working memory capacity and GRE performance while reducing mind wandering. Psychological Science, 24(5), 776–781. doi.org/10.1177/0956797612459659
  17. Hedge, C., Powell, G., & Sumner, P. (2018). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods, 50(3), 1166–1186. doi.org/10.3758/s13428-017-0935-1
  18. Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347. doi.org/10.1162/089892902317361886