Using the Beck Depression Inventory to Predict Depression

in Patients with Chronic Pain

By Sean Dadswell

June 2007

Aims

To understand the prevalence and possible mechanisms for depression in patients that suffer from chronic pain

To understand how to use the Beck Depression Inventory (BDI) and its reliability and validity

To have knowledge of the literature surrounding the BDI

Contents Introduction to chronic pain and depression

Prevalence of chronic pain and depression

Why choose the BDI

BDI introduction and use

Literature regarding validity, reliability and comparison to other outcome measures

Chronic Pain and DepressionIs it important and why are they together? The more physical symptoms present the more likely depression will

develop (Gatchel 2004) Proposes 3 mechanisms

– Coinciding anatomy of nocioceptive and affective pathways

– Norepinephrine and serotonin implicated in chronic pain and depression mechanisms

– Social factors

Social Factors

(ADLs, Work,

Relationships)

Pain

Depression

Central

Sensitisation

Figure 1: Model representing interaction between Social factors, Pain Mechanisms and Depression Mechanisms

Chronic Pain and Depression Continued.

If both pain and depression are present then both need to be addressed or

treatment will be less effective

(Gatchel 2004)

Chronic Pain and Depression Continued.

Henningsen et al 2003: Large meta-analysis concluded depression more likely with chronic pain of unknown origin than known origin or normal population.

Emptage et al 2005: Huge study interviewing 9,825 individuals found people with pain and depression have significant more limitations with:

– ADL’s– Employment– Recurring Depression– Increasing limitations

Than those with pain or depression alone.

Pain of Unknown

origin

Pain of Known Origin

Normal Population

Figure 2: Likelihood of depression occurring related to pain origin

DEPRESSION

Prevalence Ohayon and Schatzber (2003):

Telephone interviews of 18,980 subjects across Europe

Investigated Depressive symptoms and Chronic pain

Results:– 4% General population had Major

depression– 40% of these had Chronic pain– 10.2% of all Chronic pain subjects had

Major Depression– Subjects with Major Depression 5x

more likely to suffer LBP– 16% General population had mild

depression– 25% of these had related chronic pain

problem

What makes a good outcome and why BDI? CSP Guidelines

(Hammond 2002) Outcome measures for people with depression:

– Assessment of pt change– Assessment of intervention

effect– Help pt’s monitor progress– Help assess service delivery

IMMPACT Guidelines (Dworkin et al 2005) Initiative on Methods Measurements and Pain Assessment in Clinical Trails

– Appropriate– Valid– Reliable– Responsive– Administrable

BDI recommended by both organisations

Beck Depression Inventory Designed 1961 by Beck et al Tool to assess for presence of depression Revisited 1971 and copyrighted 1978 Short form designed 1972 BDI II redesigned 1996 BDI I and II are 21 item Questionnaires Measures attitudes and symptoms depression Rated 0-3 on agreement with statement

i.e. Mood range:

0 = I do not feel sad

3 = I am so sad and unhappy I can’t stand it

(for a patient’s feeling in last week) Implemented in 10 minutes

BDI continued.

Original designed around DSM criteria (Diagnostic and Statistical Manual of Mental Disorders)

Both are scored out of 63 Outcome ranging for no to severe depression

BDI I

Score

Depression Severity

BDI II

Score

5-9 None 0-13

10-18 Mild 14-19

19-29 Moderate 20-28

30-63 Severe 29-63

Figure 3: BDI scores v’s Severity of depression

Not intended to be used as a sole diagnostic tool but to indicate further investigations.

BDI continued.

Original BDI By Beck et al (1961) Study of 226 and 183 subjects (replicated) Psychiatric in and out pt’s Psychiatric diagnosis v’s BDI score Valid (P=0.001) Reliable (coefficient 0.93) Low test re-test reliability (Memory and condition

fluctuation) Sensitive to change

BDI II Introduced 1996 to comply with changes to DSM IV Word and item changes Increased time scale (Pt’s symptoms 2 weeks)

Beck et al 1996 BDI I v’s BDI II Sample 140 in and out pt’s Randomisation not appropriate All subjects completed BDI I and II Results: High correlation between BDI I and II (p=0.001) Mean score BDI II>BDI I

BDI II continued.

Beck et al (1996) Limited as author involved in BDI invention

Dozois et al (1998) Statistical and factor analysis of 1022 students Good paper which has been heavily cited

Results:– High internal consistency between BDI I and II (P=0.001)– Recommended altered cut-offs– Validity confirmed by factor analysis– Reduced sensitivity secondary to time increase

Factor Analysis

Extensive research for BDI and factor analysis

Reduce number of variables Detects structure or relationships between

variable Each group called factor Types of factors relates to validity Implemented by exploratory and confirmatory

factor analysis

Literature Relating to Factor Analysis

Morley et al (2002) and Poole et al (2006) only papers related specifically to BDI and Chronic pain

Archival random samples 1942 and 1227 subjects respectively

Statistical methodology consistent with all factor analysis papers

2 Resultant factors:Cognitive-AffectiveSomatic

Conclusion: High validity for use of BDI II to screen patients with chronic pain for the presence of

depression

Literature Relating to Factor Analysis Continued.

Dozois et al (1998) Agrees with these findings Student population

Ward (2006) Feels 1 general factor more appropriate Does admit that it my only be AS effective as 2 factor

solution Extremely complex paper difficult to appraise for non-

statistician

How Does BDI Compare to Other Outcome Measures?Limited comparison for Chronic Pain Subjects

Geisser et al (1997) compared BDI to Epidemialogical studies depression scale

Positives Negatives

Relevant sample reasonable size (132)

Old

Excellent Lit review 3:1 women:men ratio

Blinded

Good methodology

Conclusion: Both equally valid in the prediction of depression in pt’s with

chronic pain

How Does BDI Compare to Other Outcome Measures? Continued.

Svanberg and Asberg (2001)

Compared BDI to Montgomgery Asberg Depression Rating Scale

Positives Negatives

Good methodology Small Sample (49)

Sample only Psychiatric pt’s with sever problems

Author involved in outcome design

Conclusion: Minimal difference in both measures although results of little use

How Does BDI Compare to Other Outcome Measures? Continued.

Aben et al (2002)

Compared BDI to Hospital Anxiety and Depression scale, SCL-90 and Hamilton Depression Scale

Positive Negative

Good sample size 202 Poor sample relevance

Control/comparison group to DSM IV diagnosis

Statistics for normal values and adjusted for optimal values

Conclusion: All outcomes are equally valid for screening for depression

Conclusion It is important to consider the effects of Depression

when treating patients with Chronic Pain

The BDI I and II are valid and reliable instruments in detecting the presence of Depression in patients with Chronic Pain

BDI is as effective as other outcome measures in the detection of Depression in Chronic Pain patients (limited evidence)

BDI should not be used as a sole diagnostic tool

Ideas for Future Development

More recent research aimed at BDI in Chronic Pain Samples

Specifically comparisons to other outcomes

References Aben I, Verhey F, Lousberg R, Lodder J, Honig A (2002) Validity of the Beck Depression Inventory,

Hospital Anxiety and Depression Scale, SCL-90 and Hamilton Depression Rating Scale as Screening Instruments for Depression in Stroke Patients. Psychosomatics. 43 pp 386-393

  Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J (1961) An Inventory for Measuring Depression.

Archive of General Psychiatry. 4 pp 561-571  Beck AT, Steer RA, Ball R, Ranieri WF (1996) Comparison of Beck Depression Inventories IA and II in

Psychiatric Outpatients. Journal of Personality Assessment. 67(3) pp 588-597  Dozois D, Dobson KS, Ahnberg JL (1998) A Psychmetric Evaluation of the Beck Depression Inventory II.

Psychological Assessment. 10(2) PP 83-89  Dworkin RH, Turk DC, Farrar JT, Haythornthwaite JA, Jensen MP, Katz NP, Kerns RD, Stucki G, Allen RR,

Bellamy N, Carr DB, Chandler J, Cowan P, Dionne R, Galer BS, Hertz S, Jadad AR, Kramer LD, Manning DC, Martin S, McCormick CG, McDermott MP, McGrath P, Quessy S, Rappaport BA, Robbins W, Robinson JP, Rothman M, Roya MA, Simon L, Stauffer JW, Stein W, Tollett J, Wernicke J, Witter J (2005) Core Outcome Measures for Chronic Pain Clinical Trails: IMMPACT Recommendations. Pain. 113 pp9-19

Emptage NP, Sturm R, Robinson RL (2005) Depression and Comorbid Pain as Predictors of Disability, Employment, Insurance Status and Health Care Costs. Psychiatric Services. 56(4) pp 468-474

Gatchel R (2004) Comorbidity of Chronic Pain and Mental Health Disorders: The Biopsychosocial Perspective. American Psychologist. 59(8) pp 795-805

Geisser ME, Roth RS, Robinson ME (1997) Assessing Depression Among Persons with Chronic Pain Using Epidemiological Studies-Depression Scale and the Beck Depression Inventory: A Comparative Analysis. Clinical Journal of Pain. 13(2) pp 163-170

References

Hammond R (2002) Outcome Measures for People with Depression (a working document) [online] CSP. Available from: www.csp.org.uk accessed 20th March 2007

Henningsen P, Zimmermann T, Sattel H (2003) Medically Unexplained Physical Symptoms, Anxiety and Depression: a Meta-Analytical Review. Psychosomatic Medicine. 65(4) pp 528-533

Morley S, Williams AC, Black S (2002) A Confirmatory Factor Analysis of the Beck Depressuion Inventory in Chronic Pain. Pain. 99(1-2) pp 289-298

Ohayon MM, Schatzberg AF (2003) Using Chronic Pain to Predict Depressive Morbidity in the General Population. Archive Gen Psychiatry. 60 pp 39-47

Poole H, Bramwell R, Murphy P (2006) Factor Structure of the Beck Depression Inventory II in Patients with Chronic Pain. Clinical Journal of Pain. 22(9) pp 790-798

Svanborg P, Asberg M (2001) A Comparison Between the Beck Depression Inventory (BDI) and the Self-rating Version of the Montgomery Asberg Depression Scale (MADRS). Journal of Affective Disorders. 64(2-3) pp 203-216

Ward LC (2006) Comparison of Factor Structure Models for the Beck Depression Inventory II. Psychological Assessment. 18(1) pp 81-88