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The ‘Deliberate Practice Mindset’

Performance improvement is an interest of mine. I have previously blogged and podcasted about the strategies I employed to liftmy game (from rock-bottom) when working in an extreme environment – a South African township ED.

I first became aware of ‘deliberate practice’ after reading an excellent Sale Fashion Style Sonia Rykiel Woman Ruffletrimmed Striped Crepe Shirt Petrol Size 42 Sonia Rykiel Clearance 2018 Unisex Free Shipping 27UfW4
last year. I had never encountered the concept before, but it resonated with me becauseit resembles certain aspectsof how I’ve approached self-improvement in a professional setting, particularly when desperate to prove myself in South Africa.

The psychologist who originally described deliberate practice, Dr.Anders Ericsson , has recently published a book –. It exploresthe ‘science of expertise’, for which he is the world’s leading expert – the expert on experts.

I thought I’d discussa few of my take-home points from the book.

“I am not talented, I am obsessed” – Conor McGregor, UFC lightweight champion

Too often, wider society’s assumptionis thatelite performersare naturally ‘gifted’. They have been magically blessed with superhuman ability. According to Ericsson, this is false.

No-one is born with an innate ability to perform at expert level, in any domain. All exceptional performers, regardless of field, have had to push themselves through a very intense practice regime to get to where they are. They have learnt how to be brilliant.

Ericsson repeatedly makes the point that in his 30+ years of studying an extraordinarily wide range of expert performers, from grandmaster chess players to professional tennis playersto concert violinists, he is yet to encounter a genuine ‘prodigy’ – somebody born with prerequisite skills for expert performance.

Ericsson’s favourite example of the ‘God-given talent’ fallacy is legendary composer Wolfgang Amadeus Mozart . Froman astonishingly young age, Mozart wowed audiences in concert halls across Europe with his apparent mastery of multiple musical instruments, and was labelled a child prodigy.Not so much, it turns out. The history books reveal that Wolfgangcould barelywalk before commencing a comprehensivetraining regime designed by his father, a pioneer in musical training. Furthermore, Ericsson claims that if he were around today he would barely stand out from the crowd. In fact, it’s been demonstrated that Suzoki Method -trained child musicians are often able to perform to a higher level thanMozart was ever capable of achieving.

A key component of Mozart’s prodigious skillset was thought to be his possession of perfect pitch – the ability to accuratelyname a musical note upon hearing it in isolation. The assumption wasthat itspontaneously emerged from birth and was un-teachable. It has since been proven that anyone can be trained in perfect pitch, particularly if they’ve received appropriate training between theages of 3 and 5 years. Intriguingly, it is now acknowledged to be fairly commonfor children born in countries where tonal languages (e.g. Mandarin) are spoken to possess perfect pitch if musically trained. No magic involved.

Home video records (by means of smartphone technology) are very useful in all forms of TLOC to allow signs of an attack to be studied. Patients and their relatives should be urged to record attacks, if possible, in cases of diagnostic uncertainty. In epilepsy, advances are made towards prolonged video and EEG recording in patients' homes. ^{206 , 207} For syncope or PPS, experience suggests that the chances of obtaining a video record are higher for PPS than for syncope, which is probably the effect of a high frequency and long duration of attacks in PPS. It is rare for the beginning of events to be recorded. ²⁰⁶ Home video records allow complex events such as syncope-induced epileptic seizures to be diagnosed. ²⁰⁸

In an overview of eight studies, including 625 patients with syncope undergoing EPS, ²⁰⁹ positive results occurred predominantly in patients with structural heart disease. In recent years, the development of powerful non-invasive methods, i.e. prolonged ECG monitoring, showing a higher diagnostic value, has decreased the importance of EPS as a diagnostic test. In clinical practice, registry data show that approximately 3% of patients with unexplained syncope evaluated by cardiologists undergo EPS and even fewer if they are evaluated by other specialists. ⁷¹ Nevertheless, EPS remains useful for diagnosis in the following specific clinical situations: asymptomatic sinus bradycardia (suspected sinus arrest causing syncope), bifascicular BBB (impending high-degree AV block), and suspected tachycardia.

The pre-test probability of bradycardia-related syncope is relatively high when there is asymptomatic sinus bradycardia (<50 b.p.m.) or sinoatrial block, usually documented by 12-lead ECG or ECG monitoring. The prognostic value of a prolonged sinus node recovery time (SNRT) is not well defined. An abnormal response is defined as ≥1.6 or 2 s for SNRT, or ≥525 ms for corrected SNRT. ²¹⁰ One observational study showed a relationship between the presence of prolonged SNRT at EPS and the effect of pacing on symptoms. ²¹¹ Another small prospective study showed that a corrected SNRT ≥800 ms had an eight-fold higher risk of syncope than a SNRT below this value. ²¹²

Patients with bifascicular block and syncope are at higher risk of developing high-degree AV block. ²¹³ A prolonged HV interval ≥70 ms, or induction of second- or third-degree AV block by pacing or by pharmacological stress (ajmaline, procainamide, or disopyramide), identifies a group at higher risk of developing AV block. By combining the above-mentioned parts of the electrophysiological protocol, a positive EPS yielded a positive predictive value as high as ≥80% for the identification of patients who will develop AV block in old studies. ^214–216 This finding has been indirectly confirmed by recent studies that showed a significant reduction in syncopal recurrences in patients with prolonged HV implanted with a pacemaker compared with a control group of untreated patients with a negative EPS ¹⁸⁸ , or with a control group who received an empiric pacemaker. ²¹⁷ These results justify an upgrade of the recommendation for EPS-guided therapy (i.e. cardiac pacing) in patients with a positive EPS from class IIa to class I.

The scenario subset selection transformation ( T ₂ ) involves determining which values of f ^′ ( x _i ,  S ) to use in the robustness metric calculation ( T ₃ ) (i.e., f ^′ ( x _i ,  S ^′ ) ⊆  f ^′ ( x _i ,  S )), which is akin to selecting a subset of the available scenarios over which system performance is to be assessed. This reflects a particular degree of risk aversion, where consideration of more extreme scenarios in the calculation of a robustness metric corresponds to a higher degree of risk aversion and vice versa. As can be seen from Table 1 , which scenarios are considered in the robustness calculation is highly variable between different metrics.

The third transformation ( T ₃ ) involves the calculation of the actual robustness metric based on transformed system performance values ( T ₁ ) for the selected scenarios ( T ₂ ), which corresponds to the transformation of f ^′ ( x _i ,  S ^′ ) to a single robustness value, R ( x _i ,  S ). This equates to an identity transform in cases where only a single scenario is selected in T ₂ , as there is only a single transformed performance value, which automatically becomes the robustness value. However, in cases where there are transformed performance values for multiple scenarios, these have to be transformed into a single value by means of calculating statistical moments of these values, such as the mean, standard deviation, skewness or kurtosis.

In this section, a taxonomy of different robustness metrics is given in accordance with the three transformations introduced in Section 2 . A summary of the three transformations, as well as the relative level of risk aversion, is provided in Section 3.4 .

A categorization of different robustness metrics in accordance with the performance value transformation ( T ₁ ) is given in Table 2 . As can be seen, the categorization is based on (1) whether calculation of a robustness metric is based on the absolute performance of a particular decision alternative or the performance of a decision alternative relative to that of another decision alternative or a benchmark; and (2) whether a robustness metric provides an indication of actual system performance or whether system performance is satisfactory compared with a pre‐specified performance threshold.

Many of the classic decision analytic robustness metrics belong to the bottom‐right hand quadrant of Table 2 , including the maximax and maximin criteria, Hurwicz's optimism‐pessimism rule and Laplace's principle of insufficient reason, as well as well more recently developed metrics such as the mean‐variance criterion, percentile based skewness and percentile‐based peakedness. These metrics utilize information about the absolute performance (e.g., cost, reliability) of a particular decision alternative in a particular scenario. Consequently, values of f ( x _i ,  S ^′ ) consist of these performance values, and robust decision alternatives are those that maximize system performance across the scenarios. The difference between these metrics is which values of the distribution of performance values over the different scenarios f ( x _i ,  S ) they use in the robustness calculation (i.e., scenario subset selection ( T ₂ )) and how these values are combined into a single value of R (i.e., robustness metric calculation ( T ₃ )), as discussed in Sections Free Shipping Official For Sale Sale Online Ann Demeulemeester Woman Doublebreasted Striped Satintwill Jacket Red Size 40 Ann Demeulemeester Outlet Shopping Online Buy Cheap 100% Guaranteed QW1q9u
and 3.3 .

February 27, 2018 by 2 Comments

“Who gets to decide what is an age appropriate interest for a disabled or autistic child?” This is an issue that has been on my mind a lot lately. My son will be 9 this summer, and as I’ve posted many times, he just loves all things Sesame Street. At a very early age (between 6-12 months) he showed a strong preference to all things Elmo, which of course is normal for babies and toddlers. What we didn’t know, since he was not diagnosed with until age 2, is that he also has a strong preference for rich, saturated colors.

I am updating this post and republishing it, 2 years after original date.

Actually, all babies prefer those kinds of colors, which is why things like Sesame Street and Barney are more popular than pastel colored things. He has moved from Elmo to The Count to Ernie and back again, but he loves his Sesame Street toys and books, and it’s why I continue to be an ambassador for Sesame Place. We love it that much. It’s fun for him and nostalgic for me.

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has rides and attractions for tweens and up, Sesame Street is thought by most people to be for the preschool set. Maybe up to Kindergarten or 1st grade, but not much past that. Am I right?

For the most part, I have fostered and encouraged his interest in this while at the same time trying to introduce him to new things. Birthdays and holidays around here almost always have a bunch of Sesame Street items to be unwrapped and I am always on the hunt for more when I am out consignment shopping (he is very hard on toys and they wear out quickly). Almost daily, he reads one of his many Sesame Street books on his 35-minute commute to school.