Attention–Performance Relationships

The desire to perform as well as possible in situations with a high degree of (personally felt) importance  is  thought  to  create  performance  pressure. Paradoxically,  despite  the  fact  that  performance pressure often results from aspirations to function at one’s best, pressure-packed situations are where major  performance  failures  may  be  most  visible. The term choking under pressure has been used to describe  this  phenomenon.  Choking  is  defined  as performing more poorly than expected given one’s skill  level  and  is  thought  to  occur  across  many diverse task domains where incentives for optimal performance are at a maximum. Two of the most common examples of situations in which choking under  pressure  can  occur  are  sport  competitions and exams or tests.

Many  different  theories  have  been  put  forth to  explain  how  and  why  choking  under  pressure occurs  with  the  ultimate  goal  of  developing  interventions and training methods to prevent it. These theories  can  be  roughly  divided  into  three  categories: drive theories, biomechanical theories, and attentional  theories.  Drive  theories,  which  are  primarily descriptive in nature, propose that there is an optimal level of physiological arousal for each skill that  we  perform.  Biomechanical  theories  provide hypotheses  about  how  the  kinematics  and  motor control  strategies  involved  in  skill  execution  (e.g., control of the velocity of the racquet head in a tennis  serve)  change  in  response  to  pressure.  Finally, attentional  theories  seek  to  describe  the  cognitive processes governing pressure-induced failure—how pressure  changes  the  attentional  mechanisms  and memory structures supporting performance.

The  remainder  of  this  entry  focuses  on  the major attentional theories.

Distraction Theory

Distraction  theory  is  one  of  the  primary  attentional  theories  of  choking  under  pressure.  This theory  assumes  that  every  performer  has  a  limited  amount  of  information  processing  capacity  that  can  be  devoted  to  the  execution  of  one’s skill.  Information  processing  involves  multiple resources, including perception, working memory, and  attention.  Successful  skill  execution  requires accurate perception of objects in environment such as judging the speed at which a ball is approaching or  discriminating  between  opponents  and  teammates  on  a  basketball  court.  Working  memory  is a short-term memory system that maintains, in an active state, a limited amount of information with immediate  relevance  to  the  task  at  hand  (e.g.,  a phone  number  you  are  about  to  dial)  while  preventing  distractions  from  the  environment  and irrelevant  thoughts.  Attention  is  a  resource  that allows  us  to  enhance  the  processing  of  relevant objects or locations in our environment (analogous to the way in which a spotlight allows one to see more  clearly  in  small  areas).  Resource  allocation models  of  human  performance  typically  assume that each of these resources is capacity limited.

As an example of these information processing capacity  limits  in  sport,  consider  an  attacker  in soccer  processing  the  locations  of  opponents  and teammates  on  a  pitch.  In  this  situation,  there  are only a limited number of players that the attacker can focus attention on in a given instant and there are  only  limited  number  of  player  locations  that can  be  held  in  working  memory.  Therefore,  anything else in the performer’s environment that uses processing  resources,  such  as  a  fan  drawing  the player’s attention by yelling an insult, may require that resources are taken away from skill execution, which  can  lead  to  degraded  performance  (e.g., the  attacker  passes  the  ball  to  an  opponent).  In this  example,  player  locations  are  an  example  of task-relevant  information,  an  information  source needed  for  successful  skill  execution,  while  the words spoken by the fan are an example of task irrelevant information, a source that does not aid skill execution.

According  to  distraction  theory,  the  introduction  of  performance  pressure  creates  additional sources  of  task-irrelevant  information  that  could potentially  draw  processing  resources  away  from skill  execution.  These  information  sources  primarily  come  in  the  form  of  negative  thoughts  or worries about the outcome of the action being performed  and  its  potential  consequences.  Examples of such worries could include losing a large monetary  prize,  being  booed  by  fans,  letting  down one’s teammates, or failing a class in school. These negative  thoughts  are  hypothesized  to  sap  both working  memory  (as  the  performer  plays  out  the disastrous outcomes in their mind) and attentional resources  (as  the  performer’s  attention  is  shifted from  the  external  environments  to  these  internal thoughts).  Another  way  to  conceptualize  this effect is that pressure serves to change a single task situation where the performer is only required to execute one particular skill into a multitasking situation in which the performer must do two things at once. In sum, in distraction theory, performance pressure serves to distract the performer and draw processing resources away from the task at hand. As described below, this account is the polar opposite to explicit monitoring theory, which proposes that  pressure  serves  to  increase  the  amount  of attention and working memory resources devoted to skill execution.

Processing Efficiency Theory

Does   the   distraction   created   by   the   negative thoughts and worries always lead to performance failure?  A  related  theory,  called  processing  efficiency theory, suggests this might not always be the case. Similar to distraction theory, processing efficiency theory proposes that pressure serves to draw processing resources away from task-relevant information; however, it further proposes that decreases in resources available to support skill execution can be partially or fully compensated for by an increase in  the  effort  devoted  to  the  task.  Therefore,  the main  outcome  predicted  by  processing  efficiency theory  is  that  skill  efficiency  (defined  as  the  ratio of  performance  to  the  amount  of  effort  exerted) will decrease under pressure. The extent to which associated declines in performance also occur will depend  on  how  much  additional  effort  is  exerted by  the  performer.  In  any  case,  both  theories  propose the same mechanism for the effects of pressure with the difference between them being the degree to which performance is affected in the end.

Because it is based on the assumption that information  processing  capacity  is  limited,  a  strong prediction made by distraction theory is that pressure-induced performance failures will be greatest for  skills  that  normally  in  nonpressure  situations require  a  large  amount  of  working  memory  and attentional  resources.  When  a  task  has  very  low processing  demands,  it  follows  that  a  performer will have more available capacity, that is, will have more  working  memory  and  attention  resources available  for  handling  task-irrelevant  information,  as  compared  to  a  skill  with  high  processing demands.  Therefore,  when  a  low  demand  skill  is performed under pressure, it is less likely that the additional  resources  required  to  process  distracting thoughts and worries will cause an overloading of  processing  capacity.  Instead,  it  is  possible  that the performer will be able to successfully process both  task-relevant  and  task-irrelevant  information.  This  prediction  has  received  strong  support from research involving academic test anxiety. For example, it has been demonstrated that individuals who become highly anxious during test situations, and  consequently  perform  at  a  suboptimal  level, often  divide  their  attention  between  task-relevant and  task-irrelevant  thoughts  more  so  than  those who  do  not  become  overly  anxious  in  high  pressure situations. However, suboptimal performance only appears to occur for test problems with high working  memory  demands  like  a  difficult  math problem,   while   performance   for   low-demand problems is relatively unaffected.

Thus,  there  is  evidence  that  pressure  can  compromise  working  memory  resources,  causing  failure in tasks that rely heavily on this system. But, not all tasks do rely heavily on working memory. Specifically,  the  types  of  high-level  motor  skills that have been the subject of the majority of choking  research  in  sport  (well-learned  golf  putting, baseball  batting,  soccer  dribbling)  are  thought  to become  proceduralized  (unconscious,  automatic) with practice. Proceduralized skills do not require constant online attentional control and are in fact thought to run largely outside of working memory. Such skills, then, should be relatively robust to conditions  that  consume  working  memory  resources as  distraction  theory  proposes.  However,  these types of skills may be sensitive to other attention induced disruptions under pressure. A second class of  theories,  generally  known  as  explicit  monitoring theories, has been used to explain such failures.

Explicit Monitoring Theories

Explicit  monitoring  theories  suggest  that  pressure  situations  raise  self-consciousness  and  anxiety  about  performing  correctly.  This  focus  on the  self  is  thought  to  prompt  individuals  to  turn their attention inward on the specific processes of performance in an attempt to exert more explicit monitoring and control than would be applied in a nonpressure situation. Explicit attention to step-by-step  skill  processes  and  procedures  is  thought to  disrupt  well-learned  or  proceduralized  performance processes that normally run largely outside of conscious awareness. This proposal is based on the  assumption  that  the  processing  demands  for complex motor skills change systematically during skill acquisition.

For  example,  consider  a  golfer  attempting  to make  a  putt.  A  performer  relatively  new  to  the sport is likely to have been given a lot of explicit instructions  about  how  to  putt  effectively  (e.g., keep  head  down,  use  a  smooth  backstroke,  keep your eye on the ball, etc.). Executing a skill based on these types of instructions is assumed to require a  large  amount  of  working  memory  (the  golfer must  actively  hold  in  working  memory  all  these instructions  and  the  order  they  should  be  executed)  and  attentional  resources  (the  golfer  must focus attention on the position of the head, hands, etc.  to  determine  consistency  with  the  instructions).  Through  extensive  practice,  it  is  assumed these  instructions  become  internalized  (or  proceduralized)  so  that  expert  performance  is  guided by a set of motor programs, and procedures, once initiated,  can  run  without  the  need  for  working memory or attention. How to perform the skill is no  longer  held  actively  in  working  memory  but rather it is stored in muscle memory. And the performer no longer needs to consciously monitor the position of the body by focusing attention because the  execution  of  movement  is  now  controlled  by unconscious,  automatic  processes.  Instead,  more attentional  and  working  memory  capacity  can be  devoted  to  processing  external  or  strategic information.

In explicit monitoring theory, it is assumed that not  only  is  attention  to  the  execution  of  a  complex motor skill not required, but also that it can be  harmful  for  performance  if  it  does  occur.  It  is argued  that  directing  one’s  attention  to  a  well-learned skill effectively serves to disrupt the highly efficient  and  automatic  motor  procedures  developed  through  practice.  Instead,  if  skill  execution is controlled consciously in a step-by-step manner using  a  large  amount  of  attentional  and  working memory  resources,  performance  becomes  slow, nonfluent  and  error  prone,  outcomes  typical  of novice performance. Evidence for explicit monitoring  theory  is  provided  by  dual-task  experiments, which  require  a  performer  to  execute  a  skill— such  as  putting  or  batting—while  simultaneously performing  a  secondary  task  designed  to  reorient attention toward skill execution (judging the angle of the putter head or direction of bat movement) or  away  from  skill  execution  (judging  the  pitch of  an  irrelevant  sound).  Consistent  with  explicit monitoring theory, it is typically found that expert performance  suffers  for  tasks  that  direct  attention to skill execution and is relatively unaffected by  tasks  that  direct  attention  away  from  it.  Also consistent with the theory, novice performers typically show the reverse pattern where performance is  harmed  by  irrelevant  dual  tasks  and  relatively unaffected (or in some cases actually improved) by skill-focused dual tasks.

Reinvestment Theory

One type of explicit monitoring theory, called reinvestment theory, suggests that the specific mechanism governing explicit monitoring is dechunking. Pressure-induced attention to execution causes an integrated or proceduralized control structure that normally runs off without interruptions to be broken  back  down  into  a  sequence  of  smaller,  independent  units—similar  to  how  the  performance was organized early in learning. Once dechunked, each  unit  must  be  activated  and  run  separately. Not  only  does  this  process  slow  performance,  it creates an opportunity for error at each transition between  units  that  was  not  present  in  the  integrated control structure.

Explicit Monitoring and Distraction Theories Compared

Explicit monitoring and distraction theories essentially  make  opposite  predictions  regarding  how pressure exerts its impact. While distraction theories  suggest  that  pressure  shifts  needed  attention away from execution, explicit monitoring theories suggest that pressure shifts too much attention to skill execution processes. Can both theories be correct? One possibility is that performance pressure creates two effects that alter how attention is allocated  to  execution:  (1)  Pressure  induces  worries about  the  situation  and  its  consequences,  thereby reducing  working  memory  capacity  available  for performance—as  distraction  theories  would  propose;  and  (2)  at  the  same  time,  pressure  prompts individuals  to  attempt  to  control  execution  in order  to  ensure  optimal  performance—in  line with  explicit  monitoring  theories.  This  suggests that how a skill fails is dependent on performance representation and implementation. That is, skills that demand working memory will fail when pressure  consumes  the  resources  necessary  for  performance,  while  proceduralized  skills  that  run largely outside of working memory will fail when pressure-induced  attention  brings  such  processes back  into  conscious  awareness.  Therefore,  it  is perhaps  better  to  think  of  these  two  theories  of pressure-induced  failures  of  performance  as  complementary rather than competing.

It is important to note that it does not seem to be merely a cognitive versus motor distinction that predicts how a skill will fail under pressure. That is, just because one is performing an academically based, cognitive task does not mean this task will show signs of failure via pressure-induced distraction.  And,  likewise,  sports  skills  do  not  necessarily  fail  via  pressure-induced  explicit  monitoring. Rather, it appears to be the manner in which skills utilize  on-line  attentional  resources  that  dictates how they will fail (though often, this is related to skill domain). Thus, sports skills that make heavy demands on working memory, such as strategizing, problem solving, and decision making (skills that involve  considering  multiple  options  simultaneously and updating information in real time), will likely fail as a result of pressure-induced working memory  consumption—similar  to  a  working-memory-dependent  academic  task.  In  contrast, motor  skills  that  run  largely  outside  of  working memory—for instance, a highly practiced golf putt or baseball swing—will fail when pressure-induced attention disrupts automated control processes.

Explicit  monitoring  and  distraction  theories have  very  different  implications  for  how  to  prevent choking under pressure. According to explicit monitoring  theory,  choking  is  best  prevented  by not allowing a performer to turn attention inward and explicitly control movements. Two promising interventions for achieving this end have been identified. First, it has been shown that allowing a performer to become accustomed to the desire to turn attention inward during practice (through the use of videotaping or some other means of evaluation that  tends  to  induce  self-consciousness)  can  help prevent  choking  from  occurring  during  a  subsequent competition. A more radical solution, based on  the  reinvestment  theory  described  above,  is  to change the way a performer acquires a skill: If the performer  acquires  less  knowledge  about  how  to explicitly control a skill (e.g., a golfer is not given instructions about where to place the feet, hands, etc.),  it  is  less  likely  he  or  she  will  switch  to  this control mode under pressure. Indeed, research evidence suggests that skills acquired implicitly, as in learning by doing as opposed to following instructions, are less prone to choking under pressure.

The  primary  means  for  remedying  pressure-induced  failure,  according  to  distraction  theory, is  to  increase  the  amount  of  processing  resources devoted  to  task-relevant  information  when  a performer  is  placed  in  a  high  pressure  situation. This  could  be  achieved  in  different  ways.  First, as  discussed  above  with  reference  to  processing efficiency  theory,  it  is  theoretically  possible  to reduce  (or  eliminate)  the  effects  of  pressure  on performance  by  increasing  effort.  Studies  that incorporated  effort  measurement  under  pressure have shown that this does indeed occur for many performers,  suggesting  that  learning  to  put  more effort  into  one’s  skill  can  be  an  effective  means of  handling  pressure.  An  alternative  remedy  is  to reduce  the  level  of  processing  demands  required for   the   task-irrelevant   worries   and   negative thoughts that can occur under pressure. Research has shown that this can be achieved by having the performer explicitly verbalize (or write down) the negative thoughts immediately prior to performing the high-pressure skill.


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