IQ is used synonymous and interchangeably with intelligence; however in this paper [pdf] Angela Duckworth et al argue that non-cognitive factors like test motivation also affect the IQ scores and have differential predictive validity.
Raven’s Progressive Matrices Example (Photo credit: Wikipedia)
Intelligence, which is the ability to flexibly adapt to complex situations, is usually measured using IQ scores on intelligence tests. IQ scores however do not measure juts the raw intelligence; they also measure how motivated someone is to take the test and achieve a high score.
Intelligence tests, that lead to IQ Scores, are supposed to measure the maximal intelligence ability that a person has and not the typical intelligence that he/she uses. In all intelligence testing it is assumed that the person will devote his entire attention and exert the maximum effort possible so as to achieve the highest score possible.
While the assumption that IQ measures maximal intelligence may be true in high-stake testing situations, where the IQ results would be used for academic admissions, job placement or promotions; in normal measurement of IQ, say in a typical school setting, the stakes are quite low (there are no real/tangible repercussions of doing bad or well on the test) and hence IQ does not typically measure the maximal intelligence, but is confounded by test motivation.
Test motivation refers to the fact that some people will be less motivated to take the test or continue with it and may display behaviors that indicate low motivation. While others may be highly motivated to take the IQ test. Thus, there would be individual differences at trait level on test motivation.
Test motivation is also a state variable that can be manipulated by incentivizing getting high scores on the tests. When such incentives are in place, the IQ score should increase from the baseline level or when the test was given under non-incentivized conditions.
Intelligence, as measured by IQ, has been associated with a number of good outcomes. Non cognitive factors as measured by test motivation are also theoretically linked to important life outcomes. For the purposes of this paper, two academic outcomes (years of education and academic achievement) and two non-academic outcomes (employment and criminal conviction) were measured and analyzed.
The study 1 performed a meta-analysis of various independent samples where a comparison was made between the IQ scores received in standardized conditions vis-a-vis under incentivized conditions. For analysis the sample was divided in high IQ (those with IQ greater than 100) and low IQ (those with IQ less than 100). The main results were that incentives did result in higher IQ scores, the effect was stringer for low IQ group and there was dose-response effect with larger incentives leading to greater IQ points gains.
Thus, for low IQ group, the lower IQ scores in standardized conditions could be due to lower intelligence or lower test motivation. If you increase the test motivation, you could bump up the IQ score of some of them. High IQ group, on the other hand had higher scores because they had both higher intelligence and higher test motivation.
In study 2, a thin-slice video of children giving the intelligence test was behaviorally rated for signs of low test motivation. This was a longitudinal study and the IQ scores, test motivation and four types of outcomes were analyzed to find the differential impact of IQ/intelligence and test-motivation/ non-cognitive factors on life outcomes.
The main finding was that test motivation had a significant impact, independent of IQ, on important life outcomes. This was specially pronounced for nonacademic outcomes like employment and criminal convictions. Intelligence as measured by IQ still had significant effect on all adult outcomes. They also found that test motivation predicted IQ scores, thus IQ score measures both intelligence and test motivation.
This is an important paper [pdf] that shows that IQ scores need to be interpreted with caution, and that both cognitive and non-cognitive factors are important for life outcomes.
Today’s research summary builds on the work of Gabrielle Oettingen on WOOP/mental contrasting with implementation intentions. The paper [pdf] is co-authored by Angela Duckworth et al and successfully demonstrates the utility and incremental benefit of mental contrasting over mere positive thinking in achieving desired outcomes.
The Power of Positive Thinking (EP) (Photo credit: Wikipedia)
When one wants to achieve goals, then the first step is to clearly articulate the desired goal. It has been shown that merely having a goal vs not having a clear goal is instrumental in goal achievement. Another process that is usually implicated in successful goal achievement is positive thinking, where you clearly visualize the positive outcomes from having achieved the goal.
The exercise ‘Best possible future selves’ is predicated on the same premise that visualizing a better future self leads to increase in hope and optimism and positive striving to achieve the goal.
In popular parlance though, positive thinking is equated with not thinking about any negatives at all, including the possible obstacles that may lie in the path. This obsession with just the positive aspects of future, to the ignoring of the current reality, may have detrimental effects as one’s commitment to the goal may not change with mere positive future visualizing.
Mental contrasting is a technique whereby a positive future outcome visualization is contrasted with current reality and the client encouraged to think about internal obstacles within them that may hamper the goal achievement.
Goal commitment is hypothesized to be made of two components: Goal desirability( which apparently does not change with either mental contrasting or positive future visualizing) and Goal feasibility (goal commitment increases in mental contrasting if the goal is considered of high feasibility as the current reality/obstacles become surmountable in one’s mind’s eyes; on the other hand if goal feasibility is low then goal commitment becomes less as the obstacles seem insurmountable and the goal is disengaged from while doing mental contrasting)
While the exact mechanism of how mental contrasting works in not known, it is believed to work by increasing efforts (towards overcoming surmountable obstacles) , by using better strategies ( for example to remain focused and not get distracted) or by seeking help from others.
The current studies consisted of making the class 2, 3 or 5 grade students learn foreign language words, and this learning was incentivized by promises of candy bag or small monetary reward (5 $). The gap between learning and recall varied from 2 weeks to 4 days. There were two conditions: in the positive future condition, the students filled out a section in which they listed the best possible outcomes from having mastered the foreign vocabulary words. In the mental contrasting condition, the students besides writing the best possible outcome, also reflected and wrote, what within them may prevent their achieving the goal of mastering the foreign language vocabulary.
The foreign language vocabulary task was something that was within the capability of the students and was thus considered a task with high goal feasibility and thus should have led to greater goal commitment in the mental contrasting condition.
Across two studies they found that indeed there was significant difference in recall of foreign language words between the two conditions, with mental contrasting leading to better learning/ recall.
One big limitation of the study , which is acknowledged by authors in the limitations section, is that they did not include a neutral control condition in which neither positive future visualization nor mental contrasting was used. It would have been interesting to know how big an impact positive visualization has and how big an impact mental contrasting has over and above that.
This paper is of immense practical utility as it showed that mental contrasting can also be used in group settings and is effective with minimum instructions and for a common goal. This enables tools like WOOP which build on this research to be extended to group settings. I myself use WOOP in my work with school children and have found it very useful.
Overall it is a pretty decent paper [pdf] that shows the benefits of mental contrasting over mere positive future visualization.
Today’s research summary is based on a shortish paper [pdf] by Angela Duckworth et al (Walter Mischel of Marshmallow effect fame is a co-author!) which focuses on how viewing oneself from a distance, or from a third person perspective, a previous emotional experience, can lead to better and more adaptive outcomes.
Out of body experience (Photo credit: Wikipedia)
Bad stuff happens. And we make it worse by brooding about it. There is some research that shows that thinking or ruminating about negative experiences can lead to bad outcomes in the present like compromised health or impeded cardiovascular recovery following exercise etc. Ruminative thinking style is known as a precursor and risk factor for depression.
On the other hand there is a rich tradition of expressive writing (for e.g. Pennebaker’s work) in which people write about their negative experiences and traumas and seem to benefit (boosts in long term mood and well-being) from such an expressive act.
Different sort of mechanisms are hypothesized in both the above cases. In the first case, one may be reliving the negative experience or recounting it and thus get overwhelmed once more in the present by such a recollection. In the second case, one may be reinterpreting the situation and making fresh sense of the events or reconstruing the events. So reflecting in a negative experience per se may not be bad or good but may lead to a good outcome only when reconstruing happens more than recounting.
Putting a distance between oneself or seeing events from a detached third person perspective have been shown to increase one’s self control and control one’s impulses and also helpful in alleviating depression by enabling better cognitions. It has been hypothesized that self-distancing or viewing things form a detached third person perspective will lead to better and more adaptive outcomes while self-reflecting, as one will not recount or relive the experiences but will be better able to reconstrue or make new sense of the experiences.
The current study looked at ~ 100 fifth grade students and asked them to recollect a negative angry outburst/ interaction which was interpersonal in nature. They were then instructed either to feel the event as of it was happening in the present and they were at the center of the action, or that they were watching the event unfold from a distance and observing the distant self. After they had recalled the experience in both conditions, they filled a brief survey measuring their emotional reactivity (how much power the vent still holds over them) and avoidance behavior (do they avoid talking/ thinking about that issue) . They were also asked to write an essay about their reflection and the essay was content analyzed for recounting thoughts, reconstruing thoughts and blame attributions.
The results showed that when you put a distance between self while recollecting a negative experience, then the emotional reactivity is lesser than when you feel as if you are reliving the experience. Thus, if you want to make a negative experiences hold smaller on you recollect it while putting a distance from self. Thus it was clear that self-distancing was a more adaptive outcome.
They also found that those students who had put a distance between their earlier self while reflecting on their angry interaction, had fewer recounting statements in their essays and more reconstruing statements. They also made fewer blame attributions.
They also did a path analysis and found that self-distancing had its impact on more adaptive outcomes (less negative affect and emotional reactivity) via the mediating variables of more reconstruing statements than recounting statements, which in turn led to lesser blame attributions and thus a closure that led to lesser emotional reactivity.
The take home message, children can benefit form self reflective exercises that make them reflect on negative experiences as long as they are supported in putting a distance between themselves and their past self, so that they don’t merely recount the experience but are able to reconstrue the experience.
Overall, a pretty decent paper [pdf] that stresses the importance of self-distancing while reflecting about past negative experiences.
Today’s research summary looks at another paper [pdf] by Angela Duckworth et al this time focusing on whether it makes sense to include personality variables in long national longitudinal surveys/studies like the MIDUS/ Dunedin/ HRS.
Nonconcordant traits (Photo credit: Wikipedia)
Personality differences can be conceptualized to be either differences in ability (like cognitive ability), traits (stable patterns of thinking, feeling, acting) , motives or narratives and this paper focuses on traits to the exclusion of other measures of personality. Even in traits, the traits of concern are the Big Five traits of Neuroticism, Extraversion, Agreeableness, Conscientiousness and Openness.
Personality, in general, and these traits, in particular, are known to predict a range of outcomes like health, achievement, and relationships. The authors believe that large panel surveys should measure these traits to find the correlations with other outcomes being measured. They review research on how traits predict wealth and health and are predicted by underlying genetic polymorphisms or variations.
For elaborating the association between traits and genes they look at candidate gene studies as well as GWAS. Extraversion is associated with polymorphisms in Dopamine subsystem related genes. Nueroticism is primarily associated with serotenergic genes. Agreeableness and Conscientiousness are both affected by polymorphsism in genes related to dopamine as well as serotonin. Openness to COMT variation. Read the paper to get additional nuances.
When it comes to economic outcomes, more introverted and more emotionally stable (less in neuroticism) individuals were more likely to save over the lifetime and borrow less; reverse was found for those high in agreeableness. Emotional stability was the best predictor of earnings; extraversion had a complex relation but overall positively predicted earnings; while agreeableness had a very slight negative impact on earning.
In terms of health, traits like Conscientiousness had a direct effect on health as well as indirect effects mediated by healthy behaviors and educational attainments. In general it is safe to conclude that personality traits do not affect health outcomes directly but by their impact on problematic or protective behaviors. Personality traits have also been linked to mortality.
The authors recommend that personality traits should be measured in large panel studies, and measured as far as consistently, using say BFI, so that they can be used to predict important life outcomes. Moreover they recommend that as personality traits can change , they should be treated as dependent variables too and measured in each subsequent measurement time.
One recommendation they have is to keep such trait measures short and relevant; also they recommend multiple measures using informant reports or cognitive tests like go-no go task. However I ‘m not sure if that may be practical in large surveys.
They also highlight the concerns about ‘flush-right’ responding where some unmotivated participants who are juts going through the motions of filling the survey may keep choosing the extreme right option making the survey results suspect. The instruments should have something inbuilt to detect such responding just like one detects social desirability.
Overall its a pretty decent paper to understand some of the antecedents (genetics) as well as consequents (health and wealth) of Big Five traits and makes a strong case for incorporating big five measures in such large scale studies and surveys. Check the paper here [pdf] .
Today’s research summary is slightly technical. It is based on this paper [pdf] by Angela Duckworth et al that shows a causal relation between self-control and academic achievement.
The Illustrated Sutra of Cause and Effect. 8th century, Japan (Photo credit: Wikipedia)
Some personality variables like self-control predict important life outcomes. It is well know that self-control as measured at age 4 (using the marshmallow test) can predict important life outcomes years later. However, prediction may not imply causality as a third factor may be responsible for causing both the phenomena under consideration.
The test for causality is a) causal variable must precede the effect in time; b) the causal variable and outcome variable should be correlated; and c) any third party confound or variable should be ruled out. This is easy to achieve in double blind randomized placebo controlled experiments, but personality traits like self-control are hard to manipulate as trait variables in experimental settings.
Typically personality traits and their outcomes are studied using a longitudinal study design where changes in say self control at time T1 are correlated with outcomes like academic achievements at a later time T2, of course measure other confounding variables and factoring their effects; thus self-control, along with IQ, may be measured at the beginning of a school session and at the end of session the CGPA obtained will be used to find whether and how much self-control led to academic achievement. This however cannot establish causality in a strict sense as not all variables of interest can be identified and measured. Often the dependent variable (CGPA in our case) is itself controlled for to ensure that a higher CGPA at point T1 does not lead to higher CGPA at time T2 independent of self-control at T1.
To take care of third party confounding variables, Angela et al used growth curve analysis with Hierarchical Linear Modelling (HLM). This involves taking multiple measures of say self -control at different times and also multiple measures of the outcome say CGPA. The independent variable is considered a time varying co-variate and used to figure the within-person relationship between the two variables of interest. Consider a between subjects confound like socio economic status (SES) that could potentially lead to different outcomes (CGPA) – if not controlled for the self control- CGPA relation arrived at by analysis of between subjects data might lead to erroneous conclusions. However, a stable thing like SES (which doesn’t change with time and is constant for an individual) will have no impact on the correlation or causal relation between how changes in self-control affect CGPA over time in the same individual.
The direction of causality can also be ascertained by using HLM with reversed time lagged, time varying co-variates. What this means os that we can try to see of the causal arrow runs in other direction by taking measures of CGPA as predictor and self control as outcome variable.
In this study, self control was measured using self-report, parents and teachers ratings of students for four consecutive academic years (as they moved from fifth grade to eighth grade) using the Brief Self-Control Scale ; CGPA was measured each year as the outcome variable. Self-esteem and IQ was also measured and so was gender, ethnicity etc.
They found that self control measured 6 months earlier predicted CGPA six months later; average self-control predicted the baseline CGPA as well as the slope of CGPA changes (how fast the CGPA increased or decreased over time). Howsoever, the reverse analysis whereby short term CGPA was used to predict self-control gave negative results thus establishing the causal direction.
It was thus established that self-control does indeed cause or lead to higher academic outcomes like higher CGPA. A limitation of the study was that a time varying third variable that increased and decreased in tandem with self-control can still account for the relationship between self control and academic achievement.
I liked the paper, though its more methodological. You can find the full paper here [pdf].
Adolescents are known to indulge in risk taking activities like recreational drug use and various theories abound as to why adolescence is a particularly sensitive time.
As per one theory, there is a dopamine surge in reward centers of the brain during adolescence which leads to impulsive sensation seeking behavior. Traditionally, it is believed that the prefrontal cortex , which can override such impulsive behavior, does not mature in teenage and continues to mature till late thirties, and thus unable to self-regulate behavior in the teenage adequately.
The above view posits that there is not much one can do about impulsive and risk taking behavior as the brain will take its own sweet time to mature; another view suggests that there are two independent processes involved in risk taking behavior- an underlying propensity to indulge in impulsive sensation seeking behavior (which can be considered as the accelerator moving one towards risk taking behavior) and an ability to delay gratification in service of long term goals (which can be considered as the brakes which moves one away from risk taking behaviors).
Literature review suggests that sensation seeking is uncorrelated with delay of gratification and both may independently impact risk taking behavior. It was unclear from prior research if delay of gratification can be an effective brake even in adolescents who were very high on sensation seeking. Also future time perspective, or the tendency to think about future more than present, is related to reduced risk taking, but the effect may be mediated by ability to delay gratification (because that ability directly depends on an ability to visualize the future) .
900 US adolescents were administered a delay discounting task (choice between larger reward later and a smaller reward now) to ascertain their ability to delay gratification. Their sensation seeking and future time perspective was measured using self-report measures. Risk taking was again measured using self report about three risky behaviors viz cigarette smoking, marijuana use, and binge drinking.Structural equation modeling was used to determine the relation between all variables.
As expected, sensation seeking in teens and delay of gratification were uncorrelated; delay of gratification predicted less risk taking behavior, future time perspective also predicted less risk taking behavior , but not over and beyond its impact on delay of gratification. Sensation seeking peaked around age 18 and then started decreasing; future time perspective kept increasing with age; and temporal discounting showed an upward trend with age.
For teens that were high in sensation seeking, their temporal discounting increased with age more sharply. The authors explained this due to the fact that teens who were high in sensation seeking would indulge in more risky behavior and on getting negative feedback from environment on these behaviors will learn to self-regulate and increase delay of gratification.
From this research it seems there are at least two routes to increase your temporal discounting muscle and hence reduce your risk taking behavior. The first approach is to become explicitly future focused and have a stronger future time perspective; the second approach is to explore, experiment and learn from your mistakes as your risk taking backfires. If done in a conducive environment, like graded driving tests, then this can lead to good outcomes.
I found the paper pretty interesting as it clearly dissociates the tow mechanisms that lead to risky behavior. If you found the above interesting, check out the paper here.
Today’s paper co-authored by Angela Duckworth again straddles the two worlds of psychology and economics.
English: A comparison of the discount factor of hyperbolic discounting with that of exponential discounting. (Photo credit: Wikipedia)
Temporal discounting or time preference is the preference people show towards immediate short-term rewards over higher but later long-term gains. People are willing to accept much lower sums (of say money) now, than they would, for sure, receive at some time in the future. This preference is for sure sums and is distinct and different form uncertainty/risk avoidance.
Different people have different temporal discounting rates; some discount future gains much more steeply than others – these people will prefer immediate rewards much more strongly than those who have a less steep discount function.
Typical rewards considered in temporal discounting studies are monetary rewards; however a case can be made that other non-equivalent types of rewards exist like edible items, vacation experiences, health outcomes etc. Previous research has shown that contrary to classical economics models, people have different discount rates for different types of rewards; this is called domain-specificity of temporal discounting.
Different people desire and like different types of rewards to different degrees; for e.g., someone may desire to be healthy and prioritize over monetary rewards. Although, as per research done by Berridge et al, liking and desire are different functions, they are treated together in this paper and operationalized as temptation for the reward.
There is evidence that there are two systems involved in decision-making – the system I or ‘hot’ and system II or ‘cold’ popularized by Kahneman et al. The beta-delta preference model formalizes this by positing that there are two factors influencing choice- a beta factor making a sharp distinction in present and future and a constant delta discount factor.
If you like and desire a reward very much, your emotional/ ‘hot’ system will get activated and will override the ‘cold’ system to the extent that you will discount this reward very steeply (prefer strongly the immediate reward) . If however, you are not too excited by the reward and are indifferent to it, the ‘cold’ system will be much more dominant and discounting will not be as steep.
The experiment conducted of three reward conditions- eating candy, eating chips, drinking beer and temptation was measured using self-report for these rewards.
Temporal discounting was measured using a choice task in which choices were presented for different quantities of all three rewards (plus dollars) and the delay contrasted with now, versus a delayed reward at time ranges form one week to 3 years.
What they found were that were indeed subgroups of people like chip lovers (those who were tempted more strongly by chips than say beer) who also discounted chips more strongly; similarly their discount rates was steeper for chips only and not so for beer.
Thus, they conclude that discount rate depends on how tempting you find that reward and there is no one domain independent discount rate. In other words, temporal discounting is domain specific. What is discounted steeply by a chip lover (guess, guess, its chips!) is not discounted that steeply by beer lover and vice versa.
This is important imho as it shows that if you want to counter a particular temptation or distraction, you have to be cognizant of that domain and work within that domain.
If you find papers like these, that are at intersection of economics and psychology interesting do check out the full version that is present online.
This research summary is similar to the earlier one where self-control predicted overweight status; Angela and team have co-authored a similar paper, though based on a different data set and controlling for more confounds.
Picture of an Obese Teenager (146kg/322lb) with Central Obesity, side view.Self Made Picture of an Obese Teenager (Myself) (146kg/322lb) with Central Obesity, Front View. Feel Free to use. (Photo credit: Wikipedia)
Self-control is a variable of concern as ” In this obesogenic context, self control, the capacity to regulate behavior, attention, and emotion in the service of personal standards and goals, is required to forego immediate gratification and choose instead options that protect against weight gain.”
Weight control may be important for teens, not only for its long term health associations, but also because of its impact on physical attractiveness.
This study was a prospective longitudinal study that looked at over 100 children in a school setting, and measured their self control and BMI while in grade 5 (mean age 10.5) and correlated it with their BMI when in grade 8.
Self-control was measured using a variety of methods. Students filled 2 self-report measures of self-control: The Impulsivity subscale of the Eysenck I6 Junior Questionnaire and The Brief Self-Control Scale. Parents as well as teachers also filled the informant version of Brief self-control scale. Apart from this Kirby Delay-Discounting Rate Monetary Choice Questionnaire was used to present hypothetical choices between small reward now and large reward later, meant to judge the delay of gratification. Also an actual behavioral delay of gratification task was used to ascertain self-control. A composite measure was created from these measures.
Potential confounds like demographics (SES), Happiness (measured by SSLS and PANAS-C) and Intelligence (Otis- Lennon School Ability Test—Seventh Edition Level F) were measured and controlled for in the analysis.
The authors replicated their earlier result that low self-control in childhood, indeed leads to weight gain in transition to adolescence. High self-control, on the other hand, protects children form weight gain.
Overall, this is a nice addition and replication of the earlier paper that we have already summarized. If you want to check out the paper its available online here.
Grit and self-control are the two character strengths on which Angela Duckworth focuses a lot, and this research summary is about a paper co-authored by Angela that shows how a lack of self-control can lead to obesity and weight gain in adolescence; while being more self-controlled helps one stay leaner.
Body mass index. Graphics is made language independent. (Photo credit: Wikipedia)
The authors define self-control as ” the ability to override impulses in order to achieve goals and maintain standards”. It is also the ability to resist short term temptations and distractions in service of long term benefits.
Self-Control has many positive associations like increased life expectancy, higher report card grades and achievement test scores and career success. However not many have looked at whether and how self-control may be related to the right amount of body weight.
Weight gain from childhood to adolescence is natural, but excessive weight gain that leads to high BMI (body mass Index) is problematic and associated with negative outcomes like coronary diseases, diabetes etc. some risk/ protective factors like Socio economic status (SES) and pubertal development are well established; however not much work has been done linking personality variables like self-control with excessive weight gain.
As children enter adolescence they start exercising more and more autonomy regarding their lifestyle choices like when to eat , sleep etc. Self-control, or the ability to delay short term gratification in view of long term well-being, thus becomes a salient feature for them with regards to how they manage their weight.
This study was a prospective longitudinal study that looked at nearly 850 children in a birth cohort, and measured their self control at age 9 and correlated it with their BMI at age 15.
Self-control at age 9 was operationalised using informant ratings by mother, father and teacher on the items related to self-control on the Social Skills Rating System (SSRS)questionnaire. Overweight status was established by classifying those with BMI z-scores falling above 85th percentile as overweight.
Other potential confounds like intelligence, pubertal status etc were also measured and used in the analysis.
The results showed that the overweight children (at age 15) were half a standard deviation lower on self-control (at age 9) that the normal weight children. Similarly, those children who showed higher self control than average at age 9, were less likely to become overweight at age 15.
The study is important because it points to one mutable, and under one’s control, factor that leads to excessive weight gain – Self control. Thus, this factor , self-control, can and should be taught during the childhood to adolescence transition. It will not only help the obesity epidemic but will lead to other gains too!
If you want to dig deeper, here is the original article.
This research summary will be especially attractive to those who have interest in psychometric and would like to see how the concept and measure of grit has evolved. In this paper, Angela Duckworth refines her measurement of grit and establishes the test-retest stability of the concept apart form predictive and consensual validity.
Animation of a vernier caliper measuring a bolt (Photo credit: Wikipedia)
The authors wanted to come up with a briefer version of the grit scale, which would have better internal consistency and still retain the predictive power and the two factor structure of Consistency of Interests and Perseverance of effort.
As such they dropped 2 items each from both the factor items and retained just 4 items each for each of the factors. The decision to drop the items was taken on the basis of analyzing data across four studies as delineated in their earlier paper, whose research summary is present here. The newer 8 item Grit scale called Grrit -S retained predictive power and showed the same two factor structure.
Similar to their earlier paper, they did an online study measuring grit-S/grit -O, big five traits as predictors and career changes and educational levels as outcome variables. Grit -S correlated with conscientiousness, but was still able to predict the outcomes over and beyond conscientiousness.
Using the same online procedure, they asked subjects as well as informants (their friends family members) to complete the Grit-S/Grit -O measures and established the consensual validity of the scale.
In another study with students, they measured Grit-S/Grit -O for two consecutive springs and established the test-retest stability of the scale as well as its predictive validity where GPA obtained was an outcome variable and so was the number of hours watching television.
The next study was similar to the West point study they had done for earlier paper, but with grit-S predicting who makes it through the beast barracks.
The last study was again a followup study of the national spelling bee competitors, this time with a new cohort, and using a new scale and led to similar results, whereby girt predicted who reached which round etc. based partly on who practiced how much and had prior experience participating.
So, if you were looking for some more areas/ examples of the predictive power of grit, this doesn’t add much to what Anagela et al had presented in the earlier paper, but it does reconfirm finding with a shorter measure that also appears to be a better measure of grit.
so, if you are the one who is fascinated by how scales evolve, do check out this paper here.