Evidence based assessment/Instruments/Dimensional Obsessive Compulsive Scale

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Lead section[edit]

2.3. Acronyms/Purpose[edit]

DOCS-SF[edit]

The Dimensional Obsessive-Compulsive Scale (DOCS) was developed to take into account patients with uncommon Obsessive-Compulsive Disorder (OCD) symptoms, measure obsessions and compulsions together, and bring more dimensions into addressing OCD. It is a 20 item self-reported assessment regarding the severity of four dimensions of obsessive and compulsive symptoms: contamination, responsibility for harm and mistakes, unacceptable thoughts, and symmetry/completeness[1][2]

DOCS-SF is used by both clinicians and researchers. In regards to clinicians, it is used to give general practitioner’s a brief, initial screening for OCD symptoms before they refer them to a specialist for treatment. In regards to researchers, it is a new, valid and time - efficient measure of OCD symptom severity.[1]

DOCS[edit]

The Dimensional Obsessive-Compulsive Scale (DOCS) was developed to take into account patients with uncommon Obsessive-Compulsive Disorder (OCD) symptoms, measure obsessions and compulsions together, and bring more dimensions into addressing OCD. The DOCS was created to address the limitations of previous OCD symptom measures and further assess the severity of each symptom dimension on many different levels.[3][4]

The DOCS is intended for physicians to conduct on OCD patients in order to measure the severity of their symptoms. It is used on adults 18 and older who already have a current OCD diagnosis.[5] Clinicians also use the DOCS to track patients' progress throughout treatment.[6] The DOCS evaluates 20 items, with five for each of the OC symptom dimensions. Within these individual dimensions, the DOCS analyzes the severity of the symptoms over the past month, in terms of time occupied, avoidance behavior, associated distress, functional interference, and difficulty disregarding the obsessions and associated compulsions.[7]

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The lead section gives a quick summary of what the assessment is. Here are some pointers (please do not use bullet points when writing article):

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  2. What are its acronyms?
  3. What is its purpose?
  4. What population is it intended for? What do the items measure?
  5. How long does it take to administer?
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  7. What has been its impact on the clinical world in general?
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Psychometrics[edit]

Steps for evaluating reliability and validity[edit]

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    2. Validity rubric
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    2. Instrument rubric table: Validity
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Instrument rubric table: Reliability[edit]

Note: Not all of the different types of reliability apply to the way that questionnaires are typically used. Internal consistency (whether all of the items measure the same construct) is not usually reported in studies of questionnaires; nor is inter-rater reliability (which would measure how similar peoples' responses were if the interviews were repeated again, or different raters listened to the same interview). Therefore, make adjustments as needed.


Reliability[edit]

Not all of the different types of reliability apply to the way that questionnaires are typically used. Internal consistency (whether all of the items measure the same construct) is not usually reported in studies of questionnaires; nor is inter-rater reliability (which would measure how similar peoples' responses were if the interviews were repeated again, or different raters listened to the same interview). Therefore, make adjustments as needed.

Reliability refers to whether the scores are reproducible. Unless otherwise specified, the reliability scores and values come from studies done with a United States population sample. Here is the rubric for evaluating the reliability of scores on a measure for the purpose of evidence based assessment.

Evaluation for norms and reliability for the XXX (table from Youngstrom et al., extending Hunsley & Mash, 2008; *indicates new construct or category)
Criterion Rating (adequate, good, excellent, too good*) Explanation with references
Norms Good Multiple samples that were not random nor representative of census data[8]
Internal consistency (Cronbach’s alpha) Excellent Alpha usually between .87 and .95[3]
Interrater reliability Not applicable Designed as a self-report scale[1]
Test-retest reliability (stability r = .73 over 15 weeks. Evaluated in initial studies,[9] with data also show high stability in clinical trials[citation needed]
Repeatability Not publish No published studies formally checking repeatability

Instrument rubric table: Validity[edit]

Click here for instrument validity table

Validity[edit]

Validity describes the evidence that an assessment tool measures what it was supposed to measure. There are many different ways of checking validity. For screening measures, diagnostic accuracy and w:discriminative validity are probably the most useful ways of looking at validity. Unless otherwise specified, the validity scores and values come from studies done with a United States population sample. Here is a rubric for describing validity of test scores in the context of evidence-based assessment.

Evaluation of validity and utility for the XXX (table from Youngstrom et al., unpublished, extended from Hunsley & Mash, 2008; *indicates new construct or category)
Criterion Rating (adequate, good, excellent, too good*) Explanation with references
Content validity Excellent Covers both DSM diagnostic symptoms and a range of associated features[9]
Contruct validity (e.g., predictive, concurrent, convergent, and discriminant validity) Excellent Shows Convergent validity with other symptom scales, longitudinal prediction of development of mood disorders,[10][11][12] criterion validity via metabolic markers[9][13] and associations with family history of mood disorder.[14] Factor structure complicated;[9][3] the inclusion of “biphasic” or “mixed” mood items creates a lot of cross-loading
Discriminative validity Excellent Multiple studies show that GBI scores discriminate cases with unipolar and bipolar mood disorders from other clinical disorders[9][1][15] effect sizes are among the largest of existing scales[16]
Validity generalization Good Used both as self-report and caregiver report; used in college student[3][17] as well as outpatient[1][18][19] and inpatient clinical samples; translated into multiple languages with good reliability
Treatment sensitivity Good Multiple studies show sensitivity to treatment effects comparable to using interviews by trained raters, including placebo-controlled, masked assignment trials[20][21] Short forms appear to retain sensitivity to treatment effects while substantially reducing burden[21][22]
Clinical utility Good Free (public domain), strong psychometrics, extensive research base. Biggest concerns are length and reading level. Short forms have less research, but are appealing based on reduced burden and promising data

Development and history[edit]

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  • Why was this instrument developed? Why was there a need to do so? What need did it meet?
  • What was the theoretical background behind this assessment? (e.g. addresses importance of 'negative cognitions', such as intrusions, inaccurate, sustained thoughts)
  • How was the scale developed? What was the theoretical background behind it?
  • If there were previous versions, when were they published?
  • Discuss the theoretical ideas behind the changes.

Impact[edit]

  • What was the impact of this assessment? How did it affect assessment in psychiatry, psychology and health care professionals?
  • What can the assessment be used for in clinical settings? Can it be used to measure symptoms longitudinally? Developmentally?

Use in other populations[edit]

  • How widely has it been used? Has it been translated into different languages? Which languages?

Scoring instructions and syntax[edit]

We have syntax in three major languages: R, SPSS, and SAS. All variable names are the same across all three, and all match the CSV shell that we provide as well as the Qualtrics export.

Hand scoring and general instructions[edit]

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<Information about hand scoring and general instructions go here>

If there are any hand scoring and general administration instructions, it should go here.

CSV shell for sharing[edit]

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Here is a shell data file that you could use in your own research. The variable names in the shell corresponds with the scoring code in the code for all three statistical programs.

Note that our CSV includes several demographic variables, which follow current conventions in most developmental and clinical psychology journals. You may want to modify them, depending on where you are working. Also pay attention to the possibility of "deductive identification" -- if we ask personal information in enough detail, then it may be possible to figure out the identity of a participant based on a combination of variables.

When different research projects and groups use the same variable names and syntax, it makes it easier to share the data and work together on integrative data analyses or "mega" analyses (which are different and better than meta-analysis in that they are combining the raw data, versus working with summary descriptive statistics).

R/SPSS/SAS syntax[edit]

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R code goes here

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SPSS code goes here

Click here for SAS code

SAS code goes here

See also[edit]

Additional assessments on obsessive-compulsive disorder can be found at the page below:

External links[edit]

Example page[edit]

References[edit]

Click here for references
  1. 1.0 1.1 1.2 1.3 Eilertsen, Thomas; Hansen, Bjarne; Kvale, Gerd; Abramowitz, Jonathan S.; Holm, Silje E. H.; Solem, Stian (2017-09-05). "The Dimensional Obsessive-Compulsive Scale: Development and Validation of a Short Form (DOCS-SF)". Frontiers in Psychology 8. doi:10.3389/fpsyg.2017.01503. ISSN 1664-1078. PMID 28928693. PMC PMC5591872. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591872/.  Cite error: Invalid <ref> tag; name ":2" defined multiple times with different content
  2. Raines, Amanda M.; Allan, Nicholas P.; Oglesby, Mary E.; Short, Nicole A.; Schmidt, Norman B.. "Examination of the relations between obsessive–compulsive symptom dimensions and fear and distress disorder symptoms". Journal of Affective Disorders 183: 253–257. doi:10.1016/j.jad.2015.05.013. https://doi.org/10.1016/j.jad.2015.05.013. 
  3. 3.0 3.1 3.2 3.3 Abramowitz, Jonathan S.; Deacon, Brett J.; Olatunji, Bunmi O.; Wheaton, Michael G.; Berman, Noah C.; Losardo, Diane; Timpano, Kiara R.; McGrath, Patrick B. et al.. "Assessment of obsessive-compulsive symptom dimensions: Development and evaluation of the Dimensional Obsessive-Compulsive Scale.". Psychological Assessment 22 (1): 180–198. doi:10.1037/a0018260. http://dx.doi.org/10.1037/a0018260.  Cite error: Invalid <ref> tag; name ":1" defined multiple times with different content
  4. "Dimensional Obsessive Compulsive Scale - DOCS". www.unc.edu. Retrieved 2018-04-05.
  5. Eilertsen, Thomas; Hansen, Bjarne; Kvale, Gerd; Abramowitz, Jonathan S.; Holm, Silje E. H.; Solem, Stian (2017). "The Dimensional Obsessive-Compulsive Scale: Development and Validation of a Short Form (DOCS-SF)" (in English). Frontiers in Psychology 8. doi:10.3389/fpsyg.2017.01503. ISSN 1664-1078. http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01503/full. 
  6. Rapp, Amy M.; Bergman, R. Lindsay; Piacentini, John; McGuire, Joseph F. (2016-08-21). "Evidence-Based Assessment of Obsessive–Compulsive Disorder". Journal of Central Nervous System Disease 8: 13–29. doi:10.4137/JCNSD.S38359. ISSN 1179-5735. PMID 27594793. PMC PMC4994744. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994744/. 
  7. Melli, Gabriele; Chiorri, Carlo; Bulli, Francesco; Carraresi, Claudia; Stopani, Eleonora; Abramowitz, Jonathan (2015-06-01). "Factor Congruence and Psychometric Properties of the Italian Version of the Dimensional Obsessive-Compulsive Scale (DOCS) Across Non-Clinical and Clinical Samples" (in en). Journal of Psychopathology and Behavioral Assessment 37 (2): 329–339. doi:10.1007/s10862-014-9450-1. ISSN 0882-2689. https://link.springer.com/article/10.1007/s10862-014-9450-1. 
  8. Eilertsen, Thomas; Hansen, Bjarne; Kvale, Gerd; Abramowitz, Jonathan S.; Holm, Silje E. H.; Solem, Stian (2017). "The Dimensional Obsessive-Compulsive Scale: Development and Validation of a Short Form (DOCS-SF)" (in English). Frontiers in Psychology 8. doi:10.3389/fpsyg.2017.01503. ISSN 1664-1078. https://www.frontiersin.org/articles/10.3389/fpsyg.2017.01503/full. 
  9. 9.0 9.1 9.2 9.3 9.4 Depue, Richard A.; Slater, Judith F.; Wolfstetter-Kausch, Heidi; Klein, Daniel; Goplerud, Eric; Farr, David (1981). "A behavioral paradigm for identifying persons at risk for bipolar depressive disorder: A conceptual framework and five validation studies.". Journal of Abnormal Psychology 90 (5): 381–437. doi:10.1037/0021-843X.90.5.381. 
  10. Klein, DN; Dickstein, S; Taylor, EB; Harding, K (February 1989). "Identifying chronic affective disorders in outpatients: validation of the General Behavior Inventory.". Journal of consulting and clinical psychology 57 (1): 106–11. PMID 2925959. 
  11. Mesman, Esther; Nolen, Willem A.; Reichart, Catrien G.; Wals, Marjolein; Hillegers, Manon H.J. (May 2013). "The Dutch Bipolar Offspring Study: 12-Year Follow-Up". American Journal of Psychiatry 170 (5): 542–549. doi:10.1176/appi.ajp.2012.12030401. 
  12. Reichart, CG; van der Ende, J; Wals, M; Hillegers, MH; Nolen, WA; Ormel, J; Verhulst, FC (December 2005). "The use of the GBI as predictor of bipolar disorder in a population of adolescent offspring of parents with a bipolar disorder.". Journal of affective disorders 89 (1-3): 147–55. PMID 16260043. 
  13. Depue, RA; Kleiman, RM; Davis, P; Hutchinson, M; Krauss, SP (February 1985). "The behavioral high-risk paradigm and bipolar affective disorder, VIII: Serum free cortisol in nonpatient cyclothymic subjects selected by the General Behavior Inventory.". The American journal of psychiatry 142 (2): 175–81. PMID 3970242. 
  14. Klein, DN; Depue, RA (August 1984). "Continued impairment in persons at risk for bipolar affective disorder: results of a 19-month follow-up study.". Journal of abnormal psychology 93 (3): 345–7. PMID 6470321. 
  15. Findling, RL; Youngstrom, EA; Danielson, CK; DelPorto-Bedoya, D; Papish-David, R; Townsend, L; Calabrese, JR (February 2002). "Clinical decision-making using the General Behavior Inventory in juvenile bipolarity.". Bipolar disorders 4 (1): 34–42. PMID 12047493. 
  16. Youngstrom, Eric A.; Genzlinger, Jacquelynne E.; Egerton, Gregory A.; Van Meter, Anna R. (2015). "Multivariate meta-analysis of the discriminative validity of caregiver, youth, and teacher rating scales for pediatric bipolar disorder: Mother knows best about mania.". Archives of Scientific Psychology 3 (1): 112–137. doi:10.1037/arc0000024. 
  17. Alloy, LB; Abramson, LY; Hogan, ME; Whitehouse, WG; Rose, DT; Robinson, MS; Kim, RS; Lapkin, JB (August 2000). "The Temple-Wisconsin Cognitive Vulnerability to Depression Project: lifetime history of axis I psychopathology in individuals at high and low cognitive risk for depression.". Journal of abnormal psychology 109 (3): 403–18. PMID 11016110. 
  18. Klein, Daniel N.; Dickstein, Susan; Taylor, Ellen B.; Harding, Kathryn (1989). "Identifying chronic affective disorders in outpatients: Validation of the General Behavior Inventory.". Journal of Consulting and Clinical Psychology 57 (1): 106–111. doi:10.1037/0022-006X.57.1.106. 
  19. Youngstrom, EA; Findling, RL; Danielson, CK; Calabrese, JR (June 2001). "Discriminative validity of parent report of hypomanic and depressive symptoms on the General Behavior Inventory.". Psychological assessment 13 (2): 267–76. PMID 11433802. 
  20. Findling, RL; Youngstrom, EA; McNamara, NK; Stansbrey, RJ; Wynbrandt, JL; Adegbite, C; Rowles, BM; Demeter, CA et al. (January 2012). "Double-blind, randomized, placebo-controlled long-term maintenance study of aripiprazole in children with bipolar disorder.". The Journal of clinical psychiatry 73 (1): 57–63. PMID 22152402. 
  21. 21.0 21.1 Youngstrom, E; Zhao, J; Mankoski, R; Forbes, RA; Marcus, RM; Carson, W; McQuade, R; Findling, RL (March 2013). "Clinical significance of treatment effects with aripiprazole versus placebo in a study of manic or mixed episodes associated with pediatric bipolar I disorder.". Journal of child and adolescent psychopharmacology 23 (2): 72–9. PMID 23480324. 
  22. Ong, ML; Youngstrom, EA; Chua, JJ; Halverson, TF; Horwitz, SM; Storfer-Isser, A; Frazier, TW; Fristad, MA et al. (1 July 2016). "Comparing the CASI-4R and the PGBI-10 M for Differentiating Bipolar Spectrum Disorders from Other Outpatient Diagnoses in Youth.". Journal of abnormal child psychology. PMID 27364346.