The nature and focus of risk identification

The identification of predictors of outcome may enable us to select subgroups, whether in terms of possible benefit from treatment (‘screening in’) or failure to benefit from treatment (‘screening out’) (Foster et al. 2011). Furthermore, identification of predictors may lead to the identification of new and different approaches to treatment for patients with differing presenting characteristics, as in the screening/targeting approach developed by Hay and colleagues (Hay et al. 2008), or at different stages of pain chronicity.

Table 11.1 Individual clinical and psychosocial predictors of chronic pain and disability

Strength of evidence

Strength of predictor

Type of variable

Flag assignment

Age

***

***

Demog.

Gender

*

Variable

Demog.

Ethnicity

**

Not signif.

Marital status

*

Variable

Demog.

Education

*

*

Demog.

Clin. history

*** (LBP)

***

Clinical

?Red ?Yellow

Clin. exam

*

*

Clinical

?Red

Comorbidity

***

*

Clinical

?Red

Alc./sub. abuse

*

*

Clinical

Orange

Personality

*

*

Orange

Psychol. hist.

*

*

?Orange

Anxiety

*

*

?Orange

Stressful life events

*

*

?Orange

Pain intensity, functional disability

***

**

Clinical

?

Poor perceptions of general health

***

**

Clinical

Yellow

Psychological distress

***

***

Clinical

Yellow/orange

Depression

***

**

Clinical

Orange/yellow

Fear avoidance

**

**

Clinical

Yellow

Maladaptive coping (catastrophizing)

***

**

Clinical

Yellow

Pain behaviour

***

**

Clinical

Yellow

Duration sickness absence

***

***

Clin./Occ.

Yellow/blue ?Black

Employment status

***

***

Occ.

Blue/black

Job dissatisfaction

***

***

Occ.

Blue

Expectations re: RTW

***

***

Blue

Physical demands of work

***

*

Occ.

Black

Financial incentives

***

***

Occ.

Black

Unemployment rates

**

***

Occ.

Black

*** Strong; ** Moderate; * Weak.

 
Source
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