Perceptual speed refers to the ability to quickly and accurately identify visual information, patterns, and details.

Individuals with high perceptual speed can efficiently scan and interpret visual stimuli, which is particularly relevant in tasks that involve visual discrimination, such as proofreading, image analysis, and quality control. Verbal comprehension refers to the ability to understand and interpret written and spoken language.

It encompasses skills such as vocabulary, reading comprehension, and verbal reasoning. Individuals with strong verbal comprehension skills can effectively process and understand complex written information, communicate clearly, and extract key insights from conversations or presentations.

Numerical reasoning refers to the ability to understand and work with numbers, perform calculations, and reason using quantitative information. It involves skills such as mathematical operations, data analysis, and numerical problem-solving. Individuals with strong numerical reasoning skills can effectively analyze numerical data, make informed decisions based on quantitative information, and solve mathematical problems efficiently.

Spatial ability refers to the capacity to mentally visualize and manipulate objects and spatial relationships. It includes skills such as mental rotation, spatial reasoning, and visualization. Individuals with strong spatial ability can easily understand and interpret maps, blueprints, diagrams, and 3D models, making it valuable in fields such as architecture, engineering, and design.

Cognitive ability tests are standardized assessments designed to measure an individual's cognitive abilities. These tests are specifically developed to evaluate various aspects of cognitive functioning, such as reasoning, problem-solving, memory, and processing speed. They provide objective and reliable measures of cognitive ability and are commonly used in hiring and HR practices to assess an individual's potential for success in a specific role.

Norm-referenced testing compares an individual's performance on a cognitive ability test to a representative sample of the population. It provides a percentile rank that indicates how an individual's cognitive ability compares to others in the same group.

Norm-referenced scores allow for meaningful comparisons and help identify an individual's relative strengths and weaknesses in specific cognitive domains.

Criterion-referenced testing assesses an individual's performance against predetermined criteria or standards. Instead of comparing scores to a norm group, criterion-referenced tests determine whether an individual has met specific performance criteria or benchmarks.

These tests are particularly useful when assessing cognitive abilities required for specific job tasks or roles. Cognitive ability tests need to be free from bias to ensure fairness and equal opportunities for all individuals.

Test bias can occur when certain groups are systematically advantaged or disadvantaged due to factors such as cultural or linguistic differences.

It is essential to select and use tests that have been validated across diverse populations and to consider the impact of cultural and linguistic factors on test performance. Cognitive ability assessments should consider cultural differences to avoid potential biases and ensure fairness.

Factors such as language proficiency, cultural background, and educational experiences can influence an individual's performance on cognitive ability tests.

It is important to account for these differences by using culturally fair assessment measures or providing accommodations to create an equitable testing environment. Test accommodations are adjustments made to the testing process to ensure individuals with disabilities or specific needs can fully demonstrate their cognitive abilities.

Accommodations can include extended time, alternative formats, assistive technologies, or modifications to test administration. Providing reasonable accommodations allows individuals to showcase their true cognitive abilities, irrespective of any disabilities or impairments they may have.

Assessing cognitive ability in the hiring process brings several benefits and helps organizations make informed decisions about candidates.

Some key reasons why cognitive ability is crucial in hiring include:. Matching candidates' cognitive abilities with job requirements is essential to ensure job fit and maximize performance.

Consider the following aspects when assessing cognitive ability for job fit:. Ensuring fairness, equity, and diversity in cognitive ability assessments is crucial for promoting inclusive hiring practices. Consider the following factors to address diversity and inclusion in cognitive ability assessment:.

Adopting best practices in assessing cognitive ability can enhance the accuracy and effectiveness of hiring decisions. Integrating cognitive ability testing into the recruitment process requires careful planning and execution.

Effectively communicating cognitive ability results to candidates is essential for transparency and candidate experience.

Improving cognitive ability is a dynamic process that involves engaging in activities and practices that stimulate and enhance mental functioning.

While cognitive ability is influenced by both genetic factors and early development, individuals can still take proactive steps to enhance and sharpen their cognitive abilities throughout their lives. Some strategies include:. Remember, individual results may vary, and improving cognitive ability requires consistent effort and dedication.

It is essential to consult with healthcare professionals or cognitive experts for personalized advice and guidance on specific cognitive enhancement techniques or programs. Cognitive ability plays a crucial role in hiring decisions and overall job performance.

Understanding the different types of cognitive abilities, utilizing appropriate assessment methods, and considering job fit and diversity implications are essential for HR and hiring managers. By following best practices, organizations can effectively assess cognitive ability, make informed hiring decisions, and create inclusive and diverse work environments.

As advancements in technology and research continue, the field of cognitive ability assessment will evolve, providing more innovative and efficient approaches to evaluate cognitive abilities accurately.

Log in. Cognitive Ability Discover the importance of cognitive ability in hiring and HR practices. What is Cognitive Ability? Role of Cognitive Ability in Hiring and HR Practices Cognitive ability plays a significant role in hiring and HR practices, serving as a fundamental criterion for assessing a candidate's suitability for a role.

Relevance of Cognitive Ability for Job Performance Cognitive ability is highly relevant to job performance across various industries and roles.

Crystallized Intelligence Crystallized intelligence encompasses acquired knowledge, skills, and expertise through education, training, and life experiences. Working Memory Working memory refers to the ability to hold and manipulate information temporarily in one's mind.

Processing Speed Processing speed refers to the ability to quickly and accurately process information. Perceptual Speed Perceptual speed refers to the ability to quickly and accurately identify visual information, patterns, and details.

Verbal Comprehension Verbal comprehension refers to the ability to understand and interpret written and spoken language. Numerical Reasoning Numerical reasoning refers to the ability to understand and work with numbers, perform calculations, and reason using quantitative information.

Spatial Ability Spatial ability refers to the capacity to mentally visualize and manipulate objects and spatial relationships. We would also like to thank Sylvia Bunge, Murali Doraiswamy, Jerri Edwards, Amit Etkin, Anett Gyurak, Christine Hooker, Joseph Ventura, and Mike Walker for their thoughtful comments on the manuscript.

Conceived and designed the experiments: JLH FF RAN MET DAS MS. Performed the experiments: JLH FF DAS MS. Analyzed the data: DAS KK. Wrote the paper: JLH RAN MET DAS KK FF MS. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Article Authors Metrics Comments Media Coverage Reader Comments Figures.

Abstract Background A variety of studies have demonstrated gains in cognitive ability following cognitive training interventions. Methods The present study evaluated an online cognitive training program comprised of 49 exercises targeting a variety of cognitive capacities.

Conclusion Taken together, these results indicate that a varied training program composed of a number of tasks targeted to different cognitive functions can show transfer to a wide range of untrained measures of cognitive performance. Trial Registration ClinicalTrials.

gov NCT Greenlee, University of Regensburg, GERMANY Received: March 4, ; Accepted: July 8, ; Published: September 2, Copyright: © Hardy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: The study data for the statistical comparisons of outcomes for cognitive training relative to crosswords are in a CSV file in Supporting Information.

Introduction Recent evidence suggests that engaging in cognitively challenging activities can positively impact brain function, with studies demonstrating behavioral [ 1 , 2 ], physiological [ 3 , 4 ], and real-world functional [ 5 , 6 ] gains.

Methods Ethics statement Participants provided informed consent by clicking a dialogue box on a digital consent form prior to participation in the study.

Trial registration The study was registered on ClinicalTrials. Participants Participants were recruited from the Lumosity website www. Download: PPT. Table 1. Demographic information for fully evaluable participants.

Treatment and control groups All participants were instructed to log into the website and do one session per day of their activity cognitive training for the treatment group or crossword puzzles for the control group , 5 days a week for 10 weeks. Cognitive training treatment.

Crossword puzzles control. Outcome measures Outcomes were assessed using a battery of seven neuropsychological tests, as well as a participant-reported outcomes survey. Neuropsychological assessment battery. Assessment scaling procedure.

Participant-reported outcomes. Results Primary outcome measure Our primary hypothesis was that the treatment program would lead to greater improvements in aggregate cognitive performance compared to the active control, as measured by the neuropsychological assessment battery.

Fig 2. Change in composite score Grand Index for the cognitive training treatment and crossword puzzle control conditions. Table 2. Neuropsychological assessment baseline means, change scores, and effect sizes. Individual assessments Based on the significant main effect on our primary outcome measure, we performed secondary analyses consisting of additional ANCOVA models for each assessment.

Effects of amount of engagement If the cognitive training treatment was more effective than playing crossword puzzles for improving cognitive abilities, we may observe a larger effect of active days of study engagement for the treatment condition compared to the control condition.

Fig 4. Change in composite score Grand Index by number of active days in treatment and control conditions. Participant-reported outcomes Of the 4, participants included in the analyses above, 4, Discussion The findings of this study are consistent with the extant literature on cognitive training that shows that progressively challenging, targeted cognitive training can be an effective tool for improving core cognitive abilities including speed of processing [ 13 ], working memory [ 46 ], and fluid reasoning [ 10 ].

Supporting Information. S1 CONSORT Checklist. Completed CONSORT checklist of information to include when reporting a randomized trial. s PDF. S1 Appendix. Descriptions of each of the cognitive training tasks used in this study.

s DOCX. S2 Appendix. A more thorough description of the seven neuropsychological assessments used to measure cognitive performance at pre-test and post-test.

S1 Dataset. The study data for the statistical comparisons of outcomes for cognitive training relative to crosswords.

s CSV. S2 Dataset. A description of the data columns in S1 Dataset. S1 File. Additional Analyses. S1 Protocol. The IRB-approved study protocol. Acknowledgments We would like to acknowledge the efforts of all the dedicated people who have worked to create Lumosity.

Author Contributions Conceived and designed the experiments: JLH FF RAN MET DAS MS. References 1. Green CS, Bavelier D.

Action video game modifies visual selective attention. Smith GE, Housen P, Yaffe K, Ruff R, Kennison RF, Mahncke HW, et al. A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training IMPACT study.

J Am Geriatr Soc. Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI.

Neurobiol Aging. Anguera JA, Boccanfuso J, Rintoul JL, Al-Hashimi O, Faraji F, Janowich J, et al. Video game training enhances cognitive control in older adults. Ball K, Edwards JD, Ross LA, McGwin G Jr.

Cognitive training decreases motor vehicle collision involvement of older drivers. Wolinsky FD, Unverzagt FW, Smith DM, Jones R, Stoddard A, Tennstedt SL. The ACTIVE cognitive training trial and health-related quality of life: protection that lasts for 5 years.

J Gerontol A Biol Sci Med Sci. Woollett K, Maguire EA. Acquiring "the Knowledge" of London's layout drives structural brain changes. Curr Biol. Munte TF, Altenmuller E, Jancke L. The musician's brain as a model of neuroplasticity.

Nat Rev Neurosci. Mackey AP, Whitaker KJ, Bunge SA. Experience-dependent plasticity in white matter microstructure: reasoning training alters structural connectivity.

Front Neuroanat. Jaeggi SM, Buschkuehl M, Jonides J, Perrig WJ. Improving fluid intelligence with training on working memory. Proc Natl Acad Sci U S A.

Ball K, Berch DB, Helmers KF, Jobe JB, Leveck MD, Marsiske M, et al. Effects of cognitive training interventions with older adults: a randomized controlled trial. Schmiedek F, Lovden M, Lindenberger U. Hundred days of cognitive training enhance broad cognitive abilities in adulthood: findings from the COGITO study.

Front Aging Neurosci. View Article Google Scholar Wolinsky FD, Vander Weg MW, Howren MB, Jones MP, Dotson MM. A randomized controlled trial of cognitive training using a visual speed of processing intervention in middle aged and older adults. PLoS One. Klingberg T, Fernell E, Olesen PJ, Johnson M, Gustafsson P, Dahlstrom K, et al.

Computerized training of working memory in children with ADHD—a randomized, controlled trial. J Am Acad Child Adolesc Psychiatry. Dahlin E, Neely AS, Larsson A, Backman L, Nyberg L. Transfer of learning after updating training mediated by the striatum. Berry AS, Zanto TP, Clapp WC, Hardy JL, Delahunt PB, Mahncke HW, et al.

The influence of perceptual training on working memory in older adults. Owen AM, Hampshire A, Grahn JA, Stenton R, Dajani S, Burns AS, et al.

Putting brain training to the test. Redick TS, Shipstead Z, Harrison TL, Hicks KL, Fried DE, Hambrick DZ, et al. No evidence of intelligence improvement after working memory training: a randomized, placebo-controlled study. J Exp Psychol Gen. Hunter JE. Cognitive ability, cognitive aptitudes, job knowledge, and job performance.

J Vocat Behav. McClelland MM, Acock AC, Piccinin A, Rhea SA, Stallings MC. Relations between preschool attention span-persistence and age 25 educational outcomes. Early Child Res Q. Evans JJ, Floyd RG, McGrew KS, Leforgee MH. The relations between measures of Cattel-Horn-Carroll CHC cognitive abilities and reading achievement during childhood and adolescence.

School Psych Rev. Floyd RG, Evans JJ, McGrew KS. Relations between measures of Cattell-Horn-Carroll CHC cognitive abilities and mathematics achievement across the school-age years. Psychol Sch. Owsley C, Sloane M, McGwin G Jr. Timed instrumental activities of daily living tasks: relationship to cognitive function and everyday performance assessments in older adults.

Bavelier D, Green CS, Pouget A, Schrater P. Brain plasticity through the life span: learning to learn and action video games. Annu Rev Neurosci. Kesler SR, Sheau K, Koovakkattu D, Reiss AL. Changes in frontal-parietal activation and math skills performance following adaptive number sense training: preliminary results from a pilot study.

Neuropsychol Rehabil. Kesler SR, Lacayo NJ, Jo B. A pilot study of an online cognitive rehabilitation program for executive function skills in children with cancer-related brain injury. Brain Inj. Hardy JL, Drescher D, Sarkar K, Kellett G, Scanlon M.

Enhancing visual memory and attention with a web-based cognitive training program. MENSA Research Journal. Mayas J, Parmentier FB, Andres P, Ballesteros S.

Plasticity of attentional functions in older adults after non-action video game training: a randomized controlled trial. Finn M, McDonald S. Computerised cognitive training for older persons with mild cognitive impairment: a pilot study using a randomised controlled trial design.

Brain Impair. Take home point: Be an "Einstein". Always look to new activities to engage your mind—expand your cognitive horizons. Learn an instrument. Take an art class. Go to a museum. Read about a new area of science.

Be a knowledge junkie. There are absolutely oodles of terrible things written and promoted on how to "train your brain" to "get smarter". I'm going to shatter some of that stuff you've previously heard about brain training games. Here goes: They don't work. Individual brain training games don't make you smarter —they make you more proficient at the brain training games.

Now, they do serve a purpose, but it is short-lived. The key to getting something out of those types of cognitive activities sort of relates to the first principle of seeking novelty. Once you master one of those cognitive activities in the brain-training game, you need to move on to the next challenging activity.

Figure out how to play Sudoku? Now move along to the next type of challenging game. There is research that supports this logic. A few years ago, scientist Richard Haier wanted to see if you could increase your cognitive ability by intensely training on novel mental activities for a period of several weeks.

They used the video game Tetris as the novel activity, and used people who had never played the game before as subjects I know—can you believe they exist?! What they found, was that after training for several weeks on the game Tetris, the subjects experienced an increase in cortical thickness, as well as an increase in cortical activity, as evidenced by the increase in how much glucose was used in that area of the brain.

Basically, the brain used more energy during those training times, and bulked up in thickness—which means more neural connections, or new learned expertise—after this intense training. And they became experts at Tetris. Cool, right? However, they remained just as good at Tetris; their skill did not decrease.

The brain scans showed less brain activity during the game-playing, instead of more, as in the previous days. Why the drop? Their brains got more efficient. Once their brain figured out how to play Tetris, and got really good at it, it got lazy. Efficiency is not your friend when it comes to cognitive growth.

In order to keep your brain making new connections and keeping them active, you need to keep moving on to another challenging activity as soon as you reach the point of mastery in the one you are engaging in.

You want to be in a constant state of slight discomfort, struggling to barely achieve whatever it is you are trying to do, as Einstein alluded to in his quote. This keeps your brain on its toes, so to speak. When I say thinking creatively will help you achieve neural growth, I am not talking about painting a picture, or doing something artsy, like we discussed in the first principle, Seeking Novelty.

When I speak of creative thinking, I am talking about creative cognition itself, and what that means as far as the process going on in your brain. Contrary to popular belief, creative thinking does not equal "thinking with the right side of your brain".

It involves recruitment from both halves of your brain, not just the right. In order to do this well, you need both right and left hemispheres working in conjunction with each other.

Several years ago, Dr Robert Sternberg , former Dean at Tufts University, opened the PACE Psychology of Abilities, Competencies, and Expertise Center, in Boston.

Sternberg has been on a quest to not only understand the fundamental concept of intelligence, but also to find ways in which any one person can maximize his or her intelligence through training, and especially, through teaching in schools. As part of a research study, The Rainbow Project [pdf], he created not only innovative methods of creative teaching in the classroom, but generated assessment procedures that tested the students in ways that got them to think about the problems in creative and practical ways, as well as analytical, instead of just memorizing facts.

He wanted to find out if by teaching students to think creatively and practically about a problem, as well as for memory, he could get them to i Learn more about the topic, ii Have more fun learning, and iii Transfer that knowledge gained to other areas of academic performance.

He wanted to see if by varying the teaching and assessment methods, he could prevent "teaching to the test" and get the students to actually learn more in general.

He collected data on this, and boy, did he get great results. In a nutshell? On average, the students in the test group the ones taught using creative methods received higher final grades in the college course than the control group taught with traditional methods and assessments.

But—just to make things fair— he also gave the test group the very same analytical-type exam that the regular students got a multiple choice test , and they scored higher on that test as well.

That means they were able to transfer the knowledge they gained using creative, multimodal teaching methods, and score higher on a completely different cognitive test of achievement on that same material.

Sound familiar? I mentioned earlier that efficiency is not your friend if you are trying to increase your intelligence. Unfortunately, many things in life are centered on trying to make everything more efficient.

This is so we can do more things, in a shorter amount of time, expending the least amount of physical and mental energy possible. Take one object of modern convenience, GPS. GPS is an amazing invention.

I am one of those people GPS was invented for. My sense of direction is terrible. I get lost all the time. So when GPS came along, I was thanking my lucky stars. But you know what? After using GPS for a short time, I found that my sense of direction was worse.

If I failed to have it with me, I was even more lost than before. So when I moved to Boston—the city that horror movies and nightmares about getting lost are modeled after—I stopped using GPS. I had a new job which involved traveling all over the burbs of Boston, and I got lost every single day for at least 4 weeks.

I got lost so much, I thought I was going to lose my job due to chronic lateness I even got written up for it. But—in time, I started learning my way around, due to the sheer amount of practice I was getting at navigation using only my brain and a map.

I began to actually get a sense of where things in Boston were, using logic and memory, not GPS. I can still remember how proud I was the day a friend was in town visiting, and I was able to effectively find his hotel downtown with only a name and a location description to go on—not even an address.

It was like I had graduated from navigational awareness school. Technology does a lot to make things in life easier, faster, more efficient, but sometimes our cognitive skills can suffer as a result of these shortcuts, and hurt us in the long run.

Not a big deal. Your overall health will probably decline as a result. Your brain needs exercise as well. If you stop using your problem-solving skills, your spatial skills, your logical skills, your cognitive skills—how do you expect your brain to stay in top shape—never mind improve?

Think about modern conveniences that are helpful, but when relied on too much, can hurt your skill in that domain. Translation software: amazing, but my multilingual skills have declined since I started using it more. Same goes for spell-check and autocorrect.

In fact, I think autocorrect was one of the worst things ever invented for the advancement of cognition. You know the computer will catch your mistakes, so you plug along, not even thinking about how to spell any more. As a result of years of relying on autocorrect and spell-check, as a nation, are we worse spellers?

I would love someone to do a study on this. There are times when using technology is warranted and necessary.

An area of interest in recent research [pdf] is neural plasticity as a factor in individual differences in intelligence. Plasticity is referring to the number of connections made between neurons, how that affects subsequent connections, and how long-lasting those connections are. Basically, it means how much new information you are able to take in, and if you are able to retain it, making lasting changes to your brain.

Constantly exposing yourself to new things helps puts your brain in a primed state for learning. Novelty also triggers dopamine I have mentioned this before in other posts , which not only kicks motivation into high gear, but it stimulates neurogenesis—the creation of new neurons—and prepares your brain for learning.

All you need to do is feed the hunger. This particular dopamine receptor, the D1 type, is associated with neural growth and development, among other things. This increase in plasticity , allowing greater binding of this receptor, is a very good thing for maximizing cognitive functioning. Take home point: Be an "Einstein".

Always look to new activities to engage your mind—expand your cognitive horizons. Learn an instrument. Take an art class. Go to a museum.

Read about a new area of science. Be a knowledge junkie. There are absolutely oodles of terrible things written and promoted on how to "train your brain" to "get smarter".

I'm going to shatter some of that stuff you've previously heard about brain training games. Here goes: They don't work. Individual brain training games don't make you smarter —they make you more proficient at the brain training games.

Now, they do serve a purpose, but it is short-lived. The key to getting something out of those types of cognitive activities sort of relates to the first principle of seeking novelty. Once you master one of those cognitive activities in the brain-training game, you need to move on to the next challenging activity.

Figure out how to play Sudoku? Now move along to the next type of challenging game. There is research that supports this logic. A few years ago, scientist Richard Haier wanted to see if you could increase your cognitive ability by intensely training on novel mental activities for a period of several weeks.

They used the video game Tetris as the novel activity, and used people who had never played the game before as subjects I know—can you believe they exist?! What they found, was that after training for several weeks on the game Tetris, the subjects experienced an increase in cortical thickness, as well as an increase in cortical activity, as evidenced by the increase in how much glucose was used in that area of the brain.

Basically, the brain used more energy during those training times, and bulked up in thickness—which means more neural connections, or new learned expertise—after this intense training.

And they became experts at Tetris. Cool, right? However, they remained just as good at Tetris; their skill did not decrease. The brain scans showed less brain activity during the game-playing, instead of more, as in the previous days.

Why the drop? Their brains got more efficient. Once their brain figured out how to play Tetris, and got really good at it, it got lazy. Efficiency is not your friend when it comes to cognitive growth.

In order to keep your brain making new connections and keeping them active, you need to keep moving on to another challenging activity as soon as you reach the point of mastery in the one you are engaging in.

You want to be in a constant state of slight discomfort, struggling to barely achieve whatever it is you are trying to do, as Einstein alluded to in his quote. This keeps your brain on its toes, so to speak.

When I say thinking creatively will help you achieve neural growth, I am not talking about painting a picture, or doing something artsy, like we discussed in the first principle, Seeking Novelty. When I speak of creative thinking, I am talking about creative cognition itself, and what that means as far as the process going on in your brain.

Contrary to popular belief, creative thinking does not equal "thinking with the right side of your brain". It involves recruitment from both halves of your brain, not just the right. In order to do this well, you need both right and left hemispheres working in conjunction with each other.

Several years ago, Dr Robert Sternberg , former Dean at Tufts University, opened the PACE Psychology of Abilities, Competencies, and Expertise Center, in Boston. Sternberg has been on a quest to not only understand the fundamental concept of intelligence, but also to find ways in which any one person can maximize his or her intelligence through training, and especially, through teaching in schools.

As part of a research study, The Rainbow Project [pdf], he created not only innovative methods of creative teaching in the classroom, but generated assessment procedures that tested the students in ways that got them to think about the problems in creative and practical ways, as well as analytical, instead of just memorizing facts.

He wanted to find out if by teaching students to think creatively and practically about a problem, as well as for memory, he could get them to i Learn more about the topic, ii Have more fun learning, and iii Transfer that knowledge gained to other areas of academic performance.

He wanted to see if by varying the teaching and assessment methods, he could prevent "teaching to the test" and get the students to actually learn more in general. He collected data on this, and boy, did he get great results.

In a nutshell? On average, the students in the test group the ones taught using creative methods received higher final grades in the college course than the control group taught with traditional methods and assessments.

But—just to make things fair— he also gave the test group the very same analytical-type exam that the regular students got a multiple choice test , and they scored higher on that test as well. That means they were able to transfer the knowledge they gained using creative, multimodal teaching methods, and score higher on a completely different cognitive test of achievement on that same material.

Sound familiar? I mentioned earlier that efficiency is not your friend if you are trying to increase your intelligence. Unfortunately, many things in life are centered on trying to make everything more efficient. This is so we can do more things, in a shorter amount of time, expending the least amount of physical and mental energy possible.

Take one object of modern convenience, GPS. GPS is an amazing invention. I am one of those people GPS was invented for. My sense of direction is terrible. I get lost all the time. So when GPS came along, I was thanking my lucky stars.

But you know what? After using GPS for a short time, I found that my sense of direction was worse. If I failed to have it with me, I was even more lost than before. So when I moved to Boston—the city that horror movies and nightmares about getting lost are modeled after—I stopped using GPS.

I had a new job which involved traveling all over the burbs of Boston, and I got lost every single day for at least 4 weeks. I got lost so much, I thought I was going to lose my job due to chronic lateness I even got written up for it.

But—in time, I started learning my way around, due to the sheer amount of practice I was getting at navigation using only my brain and a map. I began to actually get a sense of where things in Boston were, using logic and memory, not GPS. I can still remember how proud I was the day a friend was in town visiting, and I was able to effectively find his hotel downtown with only a name and a location description to go on—not even an address.

It was like I had graduated from navigational awareness school. Technology does a lot to make things in life easier, faster, more efficient, but sometimes our cognitive skills can suffer as a result of these shortcuts, and hurt us in the long run.

Not a big deal. Your overall health will probably decline as a result. Your brain needs exercise as well. If you stop using your problem-solving skills, your spatial skills, your logical skills, your cognitive skills—how do you expect your brain to stay in top shape—never mind improve?

Cognitive health is just one aspect of overall brain health. A growing body of scientific research suggests that the following steps are linked to cognitive health. Small changes may really add up: Making these part of your routine could help you function better.

Preventing or controlling high blood pressure , not only helps your heart, but may help your brain too. Decades of observational studies have shown that having high blood pressure in midlife — the 40s to early 60s — increases the risk of cognitive decline later in life.

In addition, the SPRINT-MIND study, a nationwide clinical trial, showed that intensive lowering of blood pressure even below the previous standard target of for systolic blood pressure lowers the risk for mild cognitive impairment, which is a risk factor for dementia.

High blood pressure often does not cause signs of illness that you can see or feel. Routine visits to your doctor will help pick up changes in your blood pressure, even though you might feel fine.

To control or lower high blood pressure, your doctor may suggest exercise, changes in your diet, and if needed — medications. These steps can help protect your brain and your heart.

A healthy diet can help reduce the risk of many chronic diseases such as heart disease or diabetes. It may also help keep your brain healthy. In general, a healthy diet consists of fruits and vegetables; whole grains; lean meats, fish, and poultry; and low-fat or nonfat dairy products.

You should also limit solid fats, sugar, and salt. Be sure to control portion sizes and drink enough water and other fluids. Researchers are looking at whether a healthy diet can help preserve cognitive function or reduce the risk of Alzheimer's. For example, there is some evidence that people who eat a Mediterranean diet have a lower risk of developing dementia.

In contrast, the typical Western diet often increases cardiovascular disease risk, possibly contributing to faster brain aging.

Researchers have developed and are testing another diet, called MIND , a combination of the Mediterranean and DASH Dietary Approaches to Stop Hypertension diets.

Being physically active — through regular exercise, household chores, or other activities — has many benefits. It can help you:. In one study, exercise stimulated the human brain's ability to maintain old network connections and make new ones that are vital to cognitive health. Other studies have shown that exercise increases the size of a brain structure important to memory and learning, resulting in better spatial memory.

Aerobic exercise, such as brisk walking, is thought to be more beneficial to cognitive health than nonaerobic stretching and toning exercise. Federal guidelines recommend that all adults get at least minutes 2. Walking is a good start. You can also join programs that teach you to move safely and prevent falls, which can lead to brain and other injuries.

Check with your health care provider if you haven't been active and want to start a vigorous exercise program. Being intellectually engaged may benefit the brain. People who engage in personally meaningful activities , such as volunteering or hobbies, say they feel happier and healthier.

Learning new skills may improve your thinking ability, too. For example, one study found that older adults who learned quilting or digital photography had more memory improvement than those who only socialized or did less cognitively demanding activities.

Some of the research on engagement in activities such as music, theater, dance, and creative writing has shown promise for improving quality of life and well-being in older adults, from better memory and self-esteem to reduced stress and increased social interaction.

However, a recent, comprehensive report reviewing the design and findings of these and other studies did not find strong evidence that these types of activities have a lasting, beneficial effect on cognition. Additional research is needed, and in large numbers of diverse older adults, to be able to say definitively whether these activities may help reduce decline or maintain healthy cognition.

Lots of activities can keep your mind active. For example, read books and magazines. Play games. Take or teach a class. Learn a new skill or hobby. Participants randomized into the active control group received a daily session timed at a minimum of 15 minutes.

They were instructed to complete as many crossword puzzles as possible in the allotted time. If a participant completed a puzzle within the minute time period, the crossword application would provide a new puzzle. At the end of the minute period, participants were able to continue to work on the current puzzle for as long as they chose but were not given additional puzzles that day.

The crossword puzzles were produced by professional crossword constructors and presented in a web-based crosswords platform. Constructors were asked to create crosswords that were of medium difficulty, approximately equivalent to a Thursday New York Times crossword puzzle note: the New York Times puzzles increase in difficulty throughout the week, culminating with the most difficult puzzle on Saturday.

Participants filled out the puzzles by typing the answers in the appropriate boxes. Feedback about correct and incorrect responses was given immediately following submission of a completed crossword.

The puzzles were placed in a website frame that replicated the look and feel of the cognitive training website in order match as closely as possible the experience across the two conditions. See the Supporting Information S1 File for additional details on how engagement time was estimated.

Secondary analyses based on total time are included in S1 File. Outcomes were assessed using a battery of seven neuropsychological tests, as well as a participant-reported outcomes survey. The primary outcome measure used in this study was change in aggregate cognitive performance, as measured by the Grand Index described further below of the neuropsychological assessment battery, from before to after the week study period.

Secondary outcome measures included change in performance on each of the subtests in the neuropsychological battery and changes in responses to the survey. The assessments and survey were administered online in a pre-test one day prior to beginning the treatment or control condition.

Participants were directed to take the post-test 70 days later, one day following the end of the treatment or control. Seven neuropsychological assessments were used in this study. These assessments required participants to recall a sequence of randomized spatial locations in either forward or reverse order.

This task was designed to measure divided visual attention and required participants to recall the locations of briefly presented target letters while ignoring distractors.

See the Supporting Information S2 Appendix for more detailed information about the design of these assessments. Importantly, none of the tasks used in the outcome assessment battery were presented during training.

Rather, outcome assessments were implemented as measures of transfer to underlying cognitive abilities. Our assessment scaling procedure follows standard rank-based normalization approaches used in well-established IQ tests [ 42 , 43 ].

Normalization tables were created based on the pre-test data from participants who completed both the pre- and post-tests, including control participants who completed some amount of cognitive training during the study period.

Norms were generated in 5-year age bins and tables were created within each age bin for each assessment. These normalization tables were created by taking the empirically observed percentile rank for each raw score and finding the value corresponding to that percentile from a normal distribution with a mean of and standard deviation of 15 i.

This sum was then transformed using the same percentile rank normalization procedure described above. Participants also completed a survey including nine questions related to specific cognitive failures [ 44 ] and successes as well as emotional status.

Participants took the survey immediately after completing the neuropsychological test battery, once before beginning the study period pre-test and once upon completion of the study post-test.

Because this question did not apply equally to the treatment and control groups, and was not included in the original protocol, it was removed from the analysis. For completeness, responses to this question are included along with the rest of the study data in the attached S1 Dataset.

The survey items are presented in the Results section. Our primary hypothesis was that the treatment program would lead to greater improvements in aggregate cognitive performance compared to the active control, as measured by the neuropsychological assessment battery.

If this hypothesis were correct, we would expect to see larger improvements from pre-test to post-test on the Grand Index of the assessment battery for the treatment group relative to the control group.

Such differences in change scores were observed. The mean increase on the Grand Index score post-pre in the treatment group was 5. Error bars represent confidence intervals bootstrapped over , iterations. Mean change scores and error bars are based on unadjusted summary statistics.

P value is based on results from the ANCOVA analysis described in Table 2. The difference in composite Grand Index change scores between the two groups treatment vs. control was evaluated with an ANCOVA model measuring the effect of group, controlling for the pre-test score.

Pre-test score was included as a covariate to control for regression to the mean effects as well as any effects of baseline performance. These results indicate that the cognitive training treatment condition was more effective than the crosswords control for improving cognitive performance on the assessment battery on an aggregate basis.

To ensure that the exclusion of control participants who did some cognitive training with the treatment program see Participants section in Methods could not explain these results, we performed an additional set of ANCOVA analyses S1 File.

The pattern of results and conclusions remained consistent across all comparisons see S1 File , indicating that these exclusions could not explain the main result that cognitive training led to larger gains in cognitive performance compared to crosswords.

In the primary analysis conducted here, no outliers were removed. All completed assessments were included in the analysis.

In order to ensure that outliers did not play an important role in the findings, we completed a secondary outlier analysis see S1 File. In this analysis, any raw scores that were outside the range of three standard deviations above or below the mean were removed prior to further statistical analysis.

The conclusions remained the same across all subtests included in the battery. The Grand Index change score analysis was recalculated for participants with no outliers. Based on this analysis, outlier effects could not account for the results of this study. Based on the significant main effect on our primary outcome measure, we performed secondary analyses consisting of additional ANCOVA models for each assessment.

The models revealed that the cognitive training treatment group improved significantly more than the crossword puzzles control group on five of the seven assessments. There was no statistically significant difference between the groups for the Two-Target Search task.

Fig 3 provides an illustration of the unadjusted change scores for each assessment for both groups. ANCOVA model p values and effect sizes along with unadjusted pre-test means and change scores for each assessment are shown in Table 2.

P values are based on results from the ANCOVA analyses listed in Table 2. If the cognitive training treatment was more effective than playing crossword puzzles for improving cognitive abilities, we may observe a larger effect of active days of study engagement for the treatment condition compared to the control condition.

In order to test for a group difference in the effect of active days, we constructed a general linear model predicting Grand Index change score from pre-test score, treatment group, active days, and the group-by-active-days interaction.

Lines represent estimates from the general linear model including effects of group, active day, and the group-by-active-days interaction. The estimated total time participants engaged with their respective conditions provides an additional measure of compliance.

These results indicate that participants in both conditions on average complied with the instructions to engage for at least 15 minutes per day, 5 days per week for 10 weeks See S1 File for matched sample analyses demonstrating that the observed group differences in overall cognitive performance improvement are not explained by differences in the distributions of total engagement time.

Of the 4, participants included in the analyses above, 4, In order to calculate change scores on the survey, participant responses were first numerically coded on a scale from 0 to 4, with the scale always ranging from 0 as the most negative response to 4 as the most positive response.

Responses to questions 1, 2, 3, 7, 8, and 9 were reverse coded to maintain consistency of response coding across all questions i. An average of the scores was taken for both pre- and post-tests as an overall measure of self-reported real-world cognitive performance and emotional status.

The differences between pre- and post-test overall scores and scores on each question were analyzed. The hypothesis that participants in the treatment group would show greater self-reported improvements in cognition and emotional status relative to control participants was tested via an ANCOVA model measuring the effect of group treatment vs.

control on the change in average survey score, controlling for average pre-test score. These results indicate that, overall, the cognitive training treatment was more effective than the crosswords control for improving self-reported real-world cognition and emotional status.

For all nine questions, both groups tended to report improvements following study participation, compared to the pre-test. The changes were significant for both groups on all questions except for question 4 memory for a new name. Results for each question are presented in Table 3.

The three largest group differences were on questions 1, 3 and 6, all of which were related to concentration. The findings of this study are consistent with the extant literature on cognitive training that shows that progressively challenging, targeted cognitive training can be an effective tool for improving core cognitive abilities including speed of processing [ 13 ], working memory [ 46 ], and fluid reasoning [ 10 ].

The results presented here extend previous findings by demonstrating that a cognitive training program targeting a variety of cognitive capacities with different exercises can be more effective than crossword puzzles at improving a broad range of cognitive abilities.

In addition, improvement on the overall measure of cognitive function used as the primary outcome measure in this study—the Grand Index for the assessment battery—was more than twice as large in the cognitive training group as it was in the crossword puzzles control group.

Thus, for improving a variety of core cognitive abilities, the treatment used in this trial was more effective than crossword puzzles. Another approach to appreciating the magnitude of these results is to contextualize them in the distribution of scores on the outcome measures. We observe that participants in the training group improve by 2.

Given that the scores are scaled on a mean ± 15 sd scale, we can evaluate how far an average participant would move within the population distribution for their age based on moving a given number of points.

In this case, 2. This is a potentially meaningful move within the distribution. A significant group-by-active-days interaction was observed in this study, such that an additional active day engaging with the cognitive training intervention was related to larger gains on the cognitive battery composite score compared to an additional active day engaging with crossword puzzles Fig 4.

This suggests that additional training could lead to larger gains. While it is unlikely that the linear relation holds indefinitely i.

In addition to the enhanced performance observed in the cognitive training group on the neuropsychological measures of cognitive function, participants in this group also self-reported experiencing benefits that were significantly greater than those reported by participants in the active control.

These participant-reported improvements were particularly strong on questions related to the ability to concentrate. These results suggest that participants in the treatment group experienced benefits from the training in their everyday lives.

Crossword puzzles were chosen as the active control because they are commonly believed to be a cognitively stimulating activity that is good for brain health [ 31 , 32 ].

This is important because it has been suggested that belief in the efficacy of a training intervention could affect effort and performance on testing outcomes [ 47 ]. While not as large as the gains seen in the treatment group, participants in the crosswords control group also showed improvements in cognitive performance.

Without a no-contact control group in this study, it is not possible to conclusively determine whether these improvements in the active control condition were due to practice effects, placebo effects, real treatment effects, or some combination of these.

Further study will be needed to better understand the benefits of crossword puzzles for maintenance and enhancement of cognition. It is worth noting that participants in the crosswords group improved slightly more than the cognitive training group on a measure of grammatical reasoning.

There are several reasons why the treatment program might have outperformed crossword puzzles in enhancing cognitive function. First, the cognitive training program is specifically targeted to core cognitive functions.

This distinguishes the treatment from crossword puzzles, which are not designed with the goal of cognitive enhancement.

Another central feature of the cognitive training program studied here is that it is progressively challenging —that is, many of the tasks explicitly increase in difficulty as the individual improves, while others encourage the individual to perform at threshold by rewarding increasingly faster and more accurate performance see S1 Appendix.

This follows a long-established tenet in the psychological literature, that learning conditions are optimized when the task is challenging, but not prohibitively difficult [ 48 , 49 ]. Task variety and novelty are also potentially important. In the case of crossword puzzles, participants are primarily involved in vocabulary retrieval, challenging a more limited set of neural pathways.

In the cognitive training program studied here, participants are challenged to engage with a variety of cognitive tasks that challenge different neural processing systems and do so in different ways.

This variety limits the opportunity to solve the tasks with a single task-specific strategy, thus encouraging the learning of new strategies and the development of new neural connections. We noted that there have been several studies that have reported not finding benefits from cognitive training.

The only other similarly powered study that did not find positive results is a study that recruited 11, participants through a BBC television show and collected data online [ 17 ]. The authors concluded that brain training had no measureable benefits.

Several key aspects of that study differ from the one presented here. First, neither of the two treatment conditions they used had been studied empirically prior to that experiment. As we demonstrate in this study, not all cognitively stimulating activities are equally effective for enhancing cognition, and it is possible that other programs not examined in their study are more effective.

Also, the average amount of training exposure in the BBC study was less than half of that in this study. This is an important distinction as results of this study indicate that amount of training is related to the magnitude of gains in cognitive performance Fig 4.

Our results represent statistically significant improvements in cognitive processes through training. This study included a sufficiently large number of participants and enough training to reliably detect these effects. As has been noted previously [ 50 ], most cognitive training studies that have shown null results have not been powered in such a way that either a positive or a null outcome would be informative, and often include quite short training periods.

In the broader context of factors influencing cognitive processes i. Further research will be needed to understand how the current effects extrapolate over much longer training periods.

In this study, There was little difference in dropout rates between the two groups, and supplemental analyses S1 File that equated the engagement characteristics of completers from both groups demonstrated that these differences in dropout between the two groups could not explain the results.

This study utilized an entirely online design. The online methodology is ecologically valid, since most users in the real world experience the program at home or in some other personal environment outside a laboratory or clinic. In traditional laboratory-based training studies, participants experience considerable contact with study personnel.

Contact with study personnel may lead to lower rates of loss to follow up. However, this personal interaction introduces a variable that could affect the results and is not reflective of how most normal, healthy adults use these programs.

A possible limitation of the current study is that it does not isolate specific mechanisms. For example, adaptive difficulty may play an important role in driving the transfer of training [ 51 ]. Many of the tasks in the cognitive training program were explicitly adaptive i. The two conditions differed on other dimensions as well.

The cognitive training program incorporated a variety of tasks that targeted specific cognitive functions, while the crosswords condition did not. Future research is needed to more fully elucidate the relative contributions of particular components of activities that lead to improvements in cognitive performance.

Future studies could also extend the cognitive domains tested. Our neuropsychological assessment battery was relatively comprehensive across a variety of domains, but not every possible dimension of cognition was addressed. For example, this battery did not include any assessment explicitly targeting learning e.

Research on training to improve cognitive skills is not complete, and there remain many open questions. The ability to efficiently collect large data sets in controlled experiments over the Internet may prove crucial to answering the open questions related to cognitive training in the future.

The first supplementary analysis is an ANCOVA analysis that includes participants assigned to the control group who engaged in some cognitive training during the study period. The second supplementary analysis describes how engagement time is estimated in the two conditions and provides a paired-matching analysis that controls for the total time spent engaging with the two conditions.

The third supplementary analysis includes an outlier removal procedure.