lecture 12 * diagnosis *

1. test popularity
2. confirmation bias
3. availability bias
4. reasercehrs's theoretical orientation
5. client factors

when we have a prediction of a study we tend to look at behaviour that confirms our expectations

**the human tendency to think that examples of things that come readily to mind are more representative than is actually the case**

make sure that information is recent

the resercher looks at the specific things he is interested in / his favourite fild and not the whole image

due to client individualities it might be different to show simptoms , less likey to be diagnosed

**tendency to interpret a word or action according to culturally derived meaning assigned to it**

for the saying : " the shaow side of life "

negative in most countries

in countries where is too hot it is a positive on

1. semantic equivalence
2. content equivalence
3. conceptual equivalence
4. criterium equivalence
5. techical equivalnce

adventure / adevntura : spanish word makes it a completly different word

same behaviour , different meaning

same construct measured : alcohol dependece

equal interpetation ( experssion of diesease )

forms , asking , topics

e.g. if someone asks a second question : did i say it wrong the first time ?

based on statistical information , no subjective judgement

less prone to bias

1. scientist vs therapist
2. construct validity vs client help fast
3. clinical benefit

the reliable and valid description of reality :

however we cannot know for sure wht the realitiy is in regards to the perception

the likelyhood that a child has the disorede whit it scores poitive ( 5%)

the likeyhood that a child scores positive when it has that disorder (100%)

NOT THE SAME CONSTUCT !

the alarm goes off or not but is it true ?

the likeyhood of a bulgler when alarm goes offf not the same as alarm go off when there is a bulglr

P= (D+ / C+)

likeyhood of alarm when bulgler

P ( D+/C+)

likeyhood of bulglr when alarm goes off

P ( C+ / D+)

likeyhood of no alarm and no bulglr

P( C_/D_)

due to low prevalance , regardless of quality instument , chances are small tha an individual with positive test result actually suffering

type one error worst when diagnosis will stigmatize / medication will cause harm

type two error worst wehn diagnosis is needed / medication is needed to survive

alpha ( p value ) smaller than .05