Using the Beck DepressionInventory 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 Depression Is 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 Pain Social Factors Central (ADLs, Work, Sensitisation Relationships) DepressionFigure 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. DEPRESSION Pain of Pain of Normal Unknown Known Population origin Origin Figure 2: Likelihood of depression occurring related to pain origin 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.
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 IMMPACT Guidelines (Hammond 2002) (Dworkin et al 2005) Initiative on Methods Outcome measures for people Measurements and Pain with depression: Assessment in Clinical Trails – Assessment of pt change – Appropriate – Assessment of intervention – Valid effect – Reliable – Help pt’s monitor progress – Responsive – Help assess service delivery – 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 Depression BDI II Score Severity 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-Affective Somatic 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 OtherOutcome Measures?Limited comparison for Chronic Pain SubjectsGeisser et al (1997) compared BDI toEpidemialogical studies depression scale Positives Negatives Relevant sample Old reasonable size (132) 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 AsbergDepression 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 Depressionscale, 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
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