Basic epidemiological principles in psychiatry and psychiatric rating scales

1. Basic epidemiological principles in psychiatry and psychiatric rating scales Sean Lynch Research Methodology and Epidemiology - 2

2. Research Methodology and Epidemiology -2 This is the second part of the afternoon module and today we will look at some aspects of rating scales and theory In psychiatry

3. Research Methodology and Epidemiology -2 Self-rated Scales Quick, save interviewer time Lack of bias Reliable Can be used for case detection Can be used as outcome measures Only as good as the questions they ask Problems with phrasing, ease of reading, language “Order effects” “Social desirability effects” “Central tendency”

4. Research Methodology and Epidemiology -2 Self-rated Scales Can be used for any diagnostic category, except arguably less well for psychosis, cognitive impairment Can be used to study core symptom dimensions in depth e.g. sleep, energy

5. Research Methodology and Epidemiology -2 Interview - Rated Scales Can be used to help assess whether a mental disorder is present or not Can be used to assess the severity of symptoms in a mental disorder Can be used with a taxonomical system to make diagnosis Can also be used to study certain dimensions of symptoms in great depth Can be highly structured with pre-determined questions Can be more flexible and allow more “open-ended” questions

6. Research Methodology and Epidemiology -2 Interview - Rated Scales Can be subject to observer bias Different raters might disagree on assessment Can be subject to changes in behaviour of the same rater over time Can be flexible and obtain supplementary information Probing questions can be used to ensure subject understand the questions Some say these scales can be sensitive to “clinical change”

7. Research Methodology and Epidemiology -2 Scales need to have an “anchor point” to distinguish between lack of pathology and an “extreme” to assess severe pathology Scales can be broad and have numerous intermediate points with phrases or words to help guide scoring of severity or degree Scales can be narrow and dichotomous

8. Research Methodology and Epidemiology -2 Scales can suffer from “ceiling” and “floor” effects i.e. if measuring dimensions within less severe or more severe examples of pathology e.g. depressed mood. It can be hard to show improvement in an item where there is not much opportunity to show change! e.g. trials in mild severity depression

9. Research Methodology and Epidemiology -2 Properties of Scales 1. Case finding Ability to detect “cases” (true positives) Ability to distinguish “non-cases” (true negatives) Performance on these with minimum of misclassification i.e. low false positive and low false negative The fine tuning of a scale cut-off point or score can be biased towards sensitivity (true positives/true positives and false negatives) in other words not “missing” too many cases, or specificity (true negatives/true negatives and false positives) in other words having a lower number of “non-cases” incorrectly identified as cases

10. Research Methodology and Epidemiology -2 Properties of Scales 2. Assessing severity Can less severe and more severe cases be separated by the scale? Would similar scales or measures show agreement on severity? 3. Assessing change Is a reduction or increase in score on the scale associated with changes in the clinical picture?

11. Research Methodology and Epidemiology -2 Reliability “It does what it says on the tin most times” Test-retest Inter-rater Internal Consistency

12. Research Methodology and Epidemiology -2 Validity “It really tells you what is in the tin most times” Convergent Face Construct A scale can be highly reliable but measure such a narrow concept it is clinically meaningless i.e. not valid

13. Research Methodology and Epidemiology -2 DEPRESSION RATING SCALES Interview-rated HAMILTON 17 and 21 item MONTGOMERY ASBERG 10 item Self-rated HAD (Hospital Anxiety and Depression) 7 item Beck (BDI) 21 and 13 item

14. Research Methodology and Epidemiology -2 ANXIETY RATING SCALES Interview-rated HAMILTON 14 item Self-rated HAD (Hospital Anxiety and Depression) 7 item

15. Research Methodology and Epidemiology -2 OBESSIONAL RATING SCALES Interview-rated Y-BOCS (Yale Brown) 10 item Self-rated OCI (Obsessive Compulsive Inventory) 42 item

16. Research Methodology and Epidemiology -2 SCHIZOPHRENIA RATING SCALES Interview-rated PANSS SANS SAPS BPRS

17. Research Methodology and Epidemiology -2 MANIA RATING SCALES Interview-rated YOUNG MANIA RATING SCALE

18. Research Methodology and Epidemiology -2 DIAGNOSTIC INTERVIEWS SCAN (Wing et al ) - ICD SCID - DSM

19. Research Methodology and Epidemiology -2 Disease concepts for diagnosis Competing paradigms were reductionist or more pragmatic and multidimensional Hierachical approach (Foulds) Multiaxial approach (DSM) Now concepts of subsyndromal disorder

20. Levels of psychological disturbance - severity Normal distress Monosymptomatic - but recognisable Subsyndromal - collection of several symptoms which fails to meet diagnostic criteria Syndrome

21. Other qualifying criteria Frequency and persistence of symptom Functional impairment or disability Symptom duration

22. Factors affecting agreement on diagnosis Can have the same information but different disease concepts Can evaluate the same information in a different way Can elicit different information from the same patient Can have changes in the clinical condition of the patient at different times

23. Factors affecting agreement on diagnosis Different raters have different levels of knowledge and expertise e.g. differences between primary and secondary care Our diagnoses have a degree of inbuilt uncertainty How confident are we that our diagnosis is right? How often will our colleagues agree with us?

24. Agreement on diagnosis - case example Man of 40 who presents to GP Insomnia for ten days Panic attacks for three weeks Irritability at work for two weeks Reduced libido for ten days

25. Agreement on diagnosis - case example Man of 40 who presents to GP Insomnia for ten days Panic attacks for three weeks Irritability at work for two weeks Reduced libido for ten days Hopelessness about future (week) Appetite reduced (two weeks) Reduced energy (two weeks)

26. Agreement on diagnosis - case example BUT has auditory hallucinations in third person for three days!

27. Agreement on diagnosis What is a psychiatric case? “Gold standard” - Kendell, Shepherd Inter-rater reliability Intra-rater reliability Diagnostic interviews and index of definition “Cut-offs” based on symptom severity on rating instruments Computerised

28. Agreement on diagnosis Generally improved with more severe illness Difficulty in milder illness levels distinguishing from the normal range More difficult for certain diagnostic concepts e.g. personality disorder and new DSM V

29. Usefulness of diagnosis Categorical verus dimensional models of illness Hypertension is not “all-or-nothing” but spectrum form obvious disease to normal range Rose “not important if he has it, the question is how much of it he has” Bentall - distribution of psychotic symptoms

30. Prevalence The number of defined cases of disease in an area Includes older and more recently diagnosed cases Can be influenced by the chronicity of illness more than the incidence of illness Cases can develop and remit (or die) and influence prevalence

31. Prevalence Point prevalence Period prevalence “Life-time rates”

32. Prevalence - interpretingchanges Can be due to true changes in incidence Can be due to changes in effectiveness of interventions Can be due to changes in nature or course of illness Can be due to changes in detection rate

33. Incidence The number of new cases of illness in an area over a period of time Changes more likely to reflect influences on causation or associated risk Does not in itself give information on total number of cases in community Changes can be due to changes in detection rate Problem of including relapses inadvertently

34. Incidence Diseases with low incidence can become prevalent in community if chronic illnesses Prevalence can change without change in incidence necessarily e.g. change in severity of illness or effectiveness of treatment

35. Methods to assess incidence and prevalence A case register to document all contacts over a defined period “Observatory” method Case notification methods Population based studies

36. Methods to assess incidence and prevalence These methods can have limitations in diseases with low incidence rates and prevalence rates The first three methods are particularly prone to error if there are problems (or there is not full consensus) on the case definition The detection rate of cases should also be measured to assess accuracy (against best available standards)

37. Methods to assess incidence and prevalence Case ascertainment methods Prodromal phases Changes to case definition Need to have reliable and valid raw data to review estimates

38. Methods to assess incidence and prevalence Other problems in psychiatry:- “Diagnostic overlapping” Cultural influences on case ascertainment Co-morbidity Diagnostic stability over time Social changes (“pathoplastic”)

39. Methods to assess incidence and prevalence “Head count” methods in psychiatry:- Case notification depends on accuracy of diagnostic assessment and health seeking behaviour Case registers depend on capturing all cases and do not cope well with migration effects and changes to housing or centres of population

40. Methods to assess incidence and prevalence Survey methods in psychiatry:- Need to carefully define area studied Feasible methods of case detection Often expensive as need to cover large areas and numbers Need to have accurate estimate of population base

41. Methods to assess incidence and prevalence Survey methods in psychiatry:- Catchment area and “house to house” methods Telephone methods For less prevalent conditions and low incidence conditions will need to screen a large number of “normals” Need a socially acceptable screening tool

42. Methods to assess incidence and prevalence Survey methods in psychiatry:- Much more problematic for more severe illness Problems of selection bias e.g. “cold-spots” of participation, wrong time of day

43. Methods to assess incidence and prevalence Other methods Postal questionnaire Two-stage screening Representative sample e.g. random selection as per some marketing approaches Quota samples Convenience samples Consecutive attendances

44. Methods to assess incidence and prevalence Error rate in study has to be defined. Common methods:- Reference to “gold standard” With reference to known reliability and stability of case definition Random resampling Non-participation and non-completion rates Estimates of “double counting” or “missing” cases

45. Causation Confounding variables “Latent” variables Interactions Protective factors Causative factors

46. Causation Consider the following hypothesis:- The risk of lung cancer is 100 times higher in men aged 30-35 who smoke than in non-smokers. Smokers on average watch 50% more television than non-smokers. Smokers watching only the average amount of television of non-smokers could reduce their risk of lung cancer by one third. Television might also be a causal factor in lung cancer.

47. Causation Is there an argument to support this conclusion? Is the evidence convincing? Can you see any flaws in this argument? Are there alternative methods of studying the causal relationship between smoking, television viewing and lung cancer?

48. Exposure and risks Case control method is classical method It gives an indication of differences in the rate of disease on exposure to a potential risk factor Cross-sectional studies only give information on association Longitudinal studies give some more information on causation Exposure or “at risk” studies give the best quality information

49. Exposure and risks There are several assumptions:- An equal chance of exposure to a risk factor in all the population? Controls are “normal” We can measure the level of risk or exposure Exposure levels might vary in intensity Duration of exposure might be relevant

50. Exposure and risks Risk measures:- These attempt to quantify the increase in the number or proportion of cases in a population exposed to the risk factor, compared to those not exposed Odds ratio Relative risk ratio Attributable risk