Pain FINAL

when is pain said to be chronic pain

3 months

what is acute pain

protective, useful, expected to resolve as tissue heals

why is chronic pain a disease

nervous system has changed, pain persist even when original injury gone

what do we mean by pain is a perception

it is shaped by the brain, not just tissue damage

how many adults worldwide live with chronic pain

1/5

why is chronic pain the leading cause of disability

more years lived with disability than any other condition globally

what is the estimated economic burden of chronic pain

635$ billion annually in US alone

what is the primary driver of opioid prescribing which leads to opioid crisis

chronic pain

what is an explanation

find association between x and y

what has psychology been great at

explaining behavior, yet it cannot predict behavior

what is the replication crisis

failure studies to produce the same results when repeated

what was the reason for the replication crisis

due to prediction failure

what is the main goal in using predictions over explanation

both are different goals requiring different methods, one that exlpains may be usuless at predicting

what are out of sample models

models that evaluate on new data that was NOT used to build them

what is the true test of a model

out of sample accuracy

why is out of data the true tests of a model

more data beats better theory when goal is prediction

what is a solution to make better prediction theories

• use cross validation

• use large datasets

• change question to can i predict pain for this person

what is cross validation

test your model on data it has never seen, new individuals not tested

what is prediction

capacity of a model to predict disease states from high dimensional data

what is the problem of most pain studies

claimed to establish prediction while only providing correlation

what is the goal of predictive models for pain

generalize these predictions in new individuals that were never encountered

what could we do with a great prediction model of pain

• predict risk of developing pain or worsening of their pain

• improve personalized treatment

• improve allocation of health care resources

• refine diagnoses and phenotypes

• provide mechanistic insights

what are phenotypes

observable characteristics or traits of an organism

what is the dominant model of pain

biopsychosocial model

what are risks factors

who and why develops pain

what are high impact pain risks

same persistant injury and pain

depression, lost work, opioid use

what are some risk factors that increase likelihood of worse outcomes

• fear avoidance behaviours

• psychiatric comorbidities

• high baseline pain

• low general health status

what factors might predict recovery

• low fear avoidance

• good baseline function

• strong social support

• positive recovery expectations

what is fear avoidance

• pain

• fear and catastrophizing

• avoidance of movements

• lose physical fitness and functional decline over time

what are some biological factors to pain

• sex differences

• genetic variants

• brain imaging

what are some gene variants

they influence pain senstivity, opioid response, susceptibility to chronic pain

what are some brain imaging difference to pain

brain based biomarkers predict subjective experience of pain has become an obsession for the field, with limited results

what are the general principles determining chronic pain

reductionism problem

what is the reductionism problem

trying to explain complex phenomena by breaking them into simpler parts can miss important aspects of the whole

will find associations but no prediction

what is the high dimensionality data

complex model built to optimize predictions even if they fail to respect known psychological or neurobiological constraints

choosing a predictive framework could allow us to answer what questions

• are biomarkers for chronic pain real and what to expect from them

• how is context influencing the performance of biomarkers

• what is the best target

what are the 2 main problems with traditional pain research

• explains but doesnt predict

• results dont always replicate

what is the goal of explanation

what factors are associated with chronic pain

• identifies correlates

• builds theory

• small samples ok

• what psychology has done well

what is the goal of predictions

will this persons develop chronic pain in x years

• forecasts individual outcomes

• needs to generalize

• requires large samples

• what big data enable

what is the UK biobank

massive long term research project thats aims to predict pain

where does the data from uk biobank come from

• 500000 participants

• 40-69 age

• 22 assesments across uk

• 15+ years of ongoing follow up

what was collected in uk biobank

• biological samples

• questionnaires

• brain and body imaging

• health records linkage

what does uk biobank make possible for pain research

• detect small genetic effects

• build models that actually generalize

• ask longitudinal questions

• combine data types

what did they find using UKbiobank

a prognostic rosk score for dev and spread of chronic pain

99 feature in mental health, physical health ,sociodemographic

what were the strongest predictor of pain

1. mood

2. sleep

3. personality

4. life stressors

where did demogrsphic and occupational stand in predictor of pain

relatively weakly

what was UKBiobank interested in also see

how bio and psych factors predict chronic pain conditions

what does PRS stand for

polygenic risk course

what is a polygenic risk course

genetic risk for a trait or disease based on many genes.

what was the number that says psychosicial factors predict subjective report of pain

+0.7

why are psychosocial factors better at predicting subjective pain than biomarkers

1. they are self reports

2. better way to classify and break them down

what do we get if we classify pain-associated diagnoses using biological elements

we do hae super good classifications

what does the likelihood of receiving a diagnosis determined by

• expression of psychosocial risk and biomarkers

what is the direction of causality

does depression cause chronic pain, or does chronic pain cause depression?

why do treatments works for some and not others

Pain management programs, which have good evidence,

don't help everyone. Risk factors may explain who benefit

who is missing from big data

The UK Biobank over-represents healthy, educated, white

participants. Do our risk factor findings generalize to other

populations?

what are some ethical dimensions one but think about when working with risk factors

• make sure not to stigmatize patients

• consent and data use of nowdays

• who benefits from research

how can people be stigmatized with the ukbiobank research

If we can predict who will develop chronic pain, what do we do with that information? Could risk scores lead to discrimination in insurance or employment

what should we keep in mind with consent and data use

Biobank participants consented broadly. As analyses become more sophisticated, are we still within the spirit of that consent in the age of A

who benefits from this research

If the Biobank underrepresents marginalized groups, do the treatments and policies derived from it work equally well for everyone?