 |
 |
|
|
|
Major depressive disorder (MDD), defined by the presence of one or more major depressive episodes (MDEs), is a common psychiatric condition with a point prevalence of approximately 4% among adults (1) and a lifetime risk for men and women of 12% and 20%, respectively (2,3). MDD is often a chronic disorder: up to 40% of patients continue to meet diagnostic criteria 1 year after symptom onset (4,5). MDD is also a serious condition associated with considerable comorbidity, disability, morbidity, and mortality (6,7). Despite increasing therapeutic choice among antidepressant agents available to treat MDD, medication compliance is often a major obstacle in both acute and long-term treatment of the disorder (8). The definition of compliance varies depending on the context in which it is being discussed. As well, compliance can have different meanings to clinicians and patients. In the medical context, for example, clinicians refer to compliance as the degree to which patients adhere behaviourally to their prescribed treatment regimen (most commonly, medications) (9,10). To suggest a more interactive, collaborative, and proactive approach, some researchers and clinicians have suggested using the terms adherence or alliance, rather than compliance (9–12). At present, the terms adherence and compliance are used interchangeably (for example, 13,14). Further, Besch states that, although compliance may be encouraged, it is still voluntary and within the individual’s control (13). It is apparent that the term compliance, despite its limitations, continues to be widely used in the medical and psychiatric literature (10,15,16). Therefore, we use the term compliance in this paper. Noncompliance with prescribed antidepressant medication regimens remains an important barrier to the effective pharmacologic treatment of MDD (14,17–20). Mounting evidence indicates that increased compliance is a factor in reducing future depressive episodes and preventing patterns of relapse and recurrence (21–23). Conversely, noncompliance has been found to be positively associated with poor treatment response (12) and risk of recurrence (21) and to be negatively associated with quality of life (5). All these factors contribute to the enormous economic costs associated with mood disorders, estimated to be in the order of $30.4 billion annually in the US (24). Clinically significant noncompliance to antidepressants has been observed during the acute, continuation, and maintenance phases of treatment (14,17). Up to 60% of patients do not comply with their prescribed antidepressant regimen (17,25,26). Lin and colleagues reported that approximately 28% of patients stopped taking their antidepressants during the first month of therapy and as many as 44% had stopped taking their antidepressants by the third month (14). Noncompliance with antidepressant regimens can affect both the efficacy of the drugs and their side effect profiles (27). An effective antidepressant may be deemed ineffective if taken irregularly, resulting in unnecessary dosage increases (28–30) or inappropriate switching to another medication (31). Indeed, treatment noncompliance is said to be one of the most prominent preventable causes of failure to respond to treatment (32). Treatment noncompliance, while widely documented, remains one of the least understood health-related behaviours. Its determinants are multifaceted and complex (9,14–16,18,33). Knowledge of patient characteristics that predict potential medication noncompliance can contribute to the formulation of a strategy for individualized treatment plans. Noncompliance may be minimized by identifying patients who are most at risk and developing appropriate interventions to address the risk factors. In searching for determinants of noncompliance with prescribed medication, investigators have primarily examined 2 broad categories: first, clinical factors (for example, patient-, illness-, drug-, and physician-related factors, as well as social influences and normative beliefs); and second, attitudes and beliefs regarding illness and treatment (19). Very little empirical research has been conducted on the relation between personality and compliance with antidepressant medication. Sirey and colleagues (34) used the Inventory of Interpersonal Problems (IIP) (35) to screen for personality pathology and reported that antidepressant compliance was associated with the absence of personality pathology. However, it is not clear whether the IIP measures personality pathology. Ekselius and others (36) used the Karolinska Scales of Personality (37) to investigate the relation between personality traits and compliance with antidepressant medication. These researchers found that medication noncompliance—determined based on out-of-range plasma levels of medication—was associated with elevated scores on the Sensation-Seeking subscale. Similarly, Wingerson and others (38) found that, in patients with panic disorder and generalized anxiety disorder, early discontinuation from clinical trials was positively associated with the “novelty seeking” dimension on the Tridimensional Personality Questionnaire (39). Some other anecdotal literature does suggest an association between personality factors and medication noncompliance in psychiatric populations (9,12,40). Based on evidence from the combined use of the Minnesota Multiphasic Personality Inventory (MMPI-2) Basic and Content Scales for depression and the NEO Personality Inventory (NEO PI), Stein and Hackerman hypothesized that the following indicate potentially poor treatment compliance: low MMPI-2 Content scores on the subscales Work Interference and Negative Indicators and low NEO PI scores on the dimension Conscientiousness coupled with high scores on the dimension Neuroticism (40). However, these conclusions were drawn from a single case study, and a prospective controlled approach is required to confirm or refute them. Our study was designed as a prospective investigation of the relation between personality, as measured by the NEO PI-Revised Version (NEO PI-R) (41), and compliance with antidepressant medication in a population of patients receiving treatment for an episode of major depression in the context of MDD. MethodSubjects Measures We used the Toronto Side Effects Scale (TSES) (44) to measure the frequency and severity of the side effects most commonly associated with antidepressant medication. Frequency ratings ranged from “never” = 1 to “every day” = 5, and severity ratings ranged from “no trouble” = 1 to “extreme trouble” = 5. Higher scores indicate greater frequency and (or) severity of side effects. We used the Medication Event Monitoring System (MEMS; APREX Corporation, Fremont, CA) to evaluate compliance. This electronic system provides data on time and frequency of opening and closing of the medication container. Openings and closings recurring within 15 minutes of one another were ignored, as they were assumed to indicate difficulties in either opening or reclosing the lid. This methodology assumes that opening the MEMS container correlates with medication compliance. We defined compliance as the percentage of days on which we assumed that patients took the correct amount of their prescribed antidepressant medication. More specifically, we defined compliance as the percentage of days on which the number of container-opening events coincided with prescribing instructions. We calculated compliance rates for 3 time periods: for 0 to 2 weeks after enrollment, for 0 to 4 weeks after enrollment, and for the 14-week period of the study. Individual medication compliance rates were manually computed as percentages according to the following formulae: 1. For individuals on a once-daily dosing regimen,  2. For individuals on a twice-daily dosing regimen,  These formulae for calculating compliance do not distinguish between normal dosing and overdosing. Conversely, they do not incorrectly penalize opening the MEMS to add medication to the container or to count pills. Procedure ResultsSample Characteristics Of the 71 patients who were asked to participate in this study, 6 declined. The remaining 65 outpatients included 38 women (58.5%) and 27 men (41.5%) with a mean age of age of 41.4 years (SD 11.4 years). Eight patients were excluded from further analyses, 2 for misuse of the MEMS (that is, for providing inaccurate data), 2 for treatment reasons, and 4 for failing to attend a minimum of 2 clinic visits. We therefore further analyzed 57 patients, and all subsequent reports are based on this sample. Owing to missing data, subsequent analyses show some variation in the number of subjects. Of the 57 subjects, 34 were women (59.6%) and 23 were men (40.4%), aged 21.7 to 74.1 years (mean 41.2 years, SD 10.8). The ages of the men (mean 42.9 years, SD 9.6) and women (mean 40.1 years, SD 11.6) did not differ significantly (t55 = 0.963, P = 0.340). The sample was predominantly white. Eighteen patients (31.6%) were married or living with someone as if married; 22 (38.6%) had never been married; 3 (5.3%) were widowed; and 8 (14%) and 4 (7.0%) participants had been divorced or separated, respectively. Less than one-half (47.4%) were working, almost one-third (31.6%) were receiving disability payments, and 6 (10.5%) were students. Axis I Diagnoses. At the time of enrolment, 46/57 subjects (80.7%) met criteria for current MDD (DSM-IV), and 11/57 subjects (19.3%) met criteria for MDD in partial remission. Those in partial remission had been diagnosed with MDD in the past 12 months. Of the 46 individuals who met criteria for current MDD, 17 (29.8%) had melancholic features, and 10 (17.5%) had atypical features. As well, 13 (22.8%) individuals met criteria for “double depression,” or concurrent dysthymia and MDD. Of the total 57 subjects, 28 (49.1%) had at least 1 secondary Axis I disorder, predominantly across anxiety disorder diagnoses (see Table 1). Medications. Of the 57 subjects, 18 (31.6%) were treated with a selective serotonin reuptake inhibitor. Of these 18 subjects, 4 (7%) were taking fluoxetine, 9 (15.8%) were taking paroxetine, 4 (7%) were taking sertraline, and 1 (1.8%) was taking citalopram. Twenty-six (45.6%) individuals were being treated with bupropion, 3 (5.3%) were taking moclobemide, 8 (14%) were prescribed venlafaxine, and 2 (3.5%) were taking nefazodone. Most subjects were in the midst of ongoing treatment when they entered this study, and these figures represent the medications that they were taking at the time of enrolment. In some cases, medications were switched owing to poor response or adverse events. Approximately one-third of our subjects were receiving combined therapy: 14 (24.6%) were taking 2 antidepressants, and 3 (5.3%) were taking 3 antidepressants. In these cases, we monitored compliance with the primary antidepressant medication, as identified by the subject’s treating psychiatrist. As well, approximately 50% of subjects were taking anxiolytic or hypnotic medication. Dosing regimens were limited to either once daily or twice daily. >Medication Compliance in the Short and Long Term Mean compliance for the 14-week study period was 83.4% (SD 16.3). The distribution was negatively skewed (–1.658), and the Kolmogorov–Smirnov Test revealed that it differed significantly from a normal distribution (P = 0.021). As a result, we performed a logit transformation on the compliance data. This logit transformation successfully normalized the data, and the Kolmogorov–Smirnov Test revealed that the distribution did not differ significantly from normal (P = 0.805). While the change in mean compliance was negligible at 84.1%, the variability increased (SD 50.2). All subsequent analyses that incorporate compliance data are based on the 14-week log-transformed compliance scores.
We conducted a 1-way repeated measures analysis of variance (ANOVA) to investigate compliance rates over time. When we used an epsilon-adjusted F-test, the ANOVA revealed a significant time effect (F2,90 = 2596.972, P = 0.000). Post hoc analyses using Tukey’s HSD procedure to test the pairwise difference between means at the familywise 0.05 level showed that compliance declined significantly from the 2-week to the 14-week period (HSD90,3 = 6.010, P < 0.05). Relation Between Sociodemographic, Clinical, and
Treatment Variables and Compliance Severity of Depression and Compliance. Using HRSD scores from the 7 study visits over time, we conducted a 1-way repeated measures ANOVA to investigate changes in depression severity. When we used an epsilon-adjusted F-test, the ANOVA revealed a nonsignificant time effect (F5,65 = 0.389, P = 0.817). Owing to the small sample size resulting from missing data, we conducted a 1-way repeated measures ANOVA using HRSD data corresponding to the compliance data reported (that is, at baseline, week 2, week 4, and week 14). The ANOVA revealed a nonsignificant time effect (F3,90 = 0.872, P = 0.459). Because HRSD scores did not vary significantly over time, we calculated a mean HRSD score (mean 14.5, SD 6.2). There was no significant relation between depression severity and compliance (r55 = –0.146, P = 0.280). We analyzed the relation between compliance and depression severity in a 2-step multiple regression analysis, with HRSD scores at baseline (mean 16.0, SD 7.1) entered as the first step and HRSD scores at week 14 (mean 13.3, SD 7.5) entered as the second step. Neither the HRSD baseline scores nor the HRSD week 14 scores accounted for a significant amount of the compliance variability (F1,50 = 0.426, P = 0.517, 02 = 0.01; F2,49 = 0.555, P = 0.578, 02 = 0.01, respectively). Side Effects and Compliance. We conducted a 1-way repeated measures ANOVA to investigate the frequency and severity of side effects over time. Each mean score considers both the frequency and the severity of the side effects. The ANOVA results revealed a nonsignificant time effect (F7,329 = 0.600, P = 0.756). Because TSES scores did not vary significantly over time, we calculated a mean score (mean 4.26, SD 1.87). There was no significant relation between side effects and compliance (r55 = 0.036, P = 0.789). Personality Characteristics and Compliance. We compared mean scores on the 5 NEO dimensions with published means for a comparable depression patient population (46) and found them to be similar. We conducted a multiple regression analysis to predict medication compliance from the NEO dimensions. The predictor variables were the 5 dimensions of the NEO, and the criterion variable was medication compliance over the study period. The regression equation with the 5 NEO personality dimensions was not significantly related to medication compliance (F5,43 = 1.58, P = 0.187, 02 = 0.06). To investigate whether the independent dimensions of the NEO significantly predicted medication compliance, we conducted bivariate linear regression analyses using each dimension as the independent variable and medication compliance as the dependent variable. We found that Extraversion was a significant predictor of compliance to antidepressant medication (F1,47 = 5.48, P = 0.024, 02 = 0.09). Scores on Extraversion accounted for approximately 10% of the variance in compliance scores, and we found a significant negative relation between Extraversion and compliance (r47 = –0.323, P = 0.024). None of the other 4 dimensions were significantly related to compliance. To investigate the relation between the various facets of each of the 5 NEO dimensions and medication compliance, we analyzed correlations. We found significant relations between compliance and the following facets: Activity (Extraversion dimension), r47 = –0.365, P = 0.005; Feelings (Openness- to-Experience dimension), r47 = –0.248, P = 0.043; and Modesty (Agreeableness dimension), r47 = 0.372, P = 0.004. To investigate whether these facets significantly predicted medication compliance, we conducted bivariate linear regression analyses with the facets as the independent variable and medication compliance as the dependent variable. We found that Activity is a significant negative predictor of compliance to antidepressant medication (F1,47 = 7.231, P = 0.010, 02 = 0.115): approximately 12% of the variance in compliance scores was accounted for by scores on Activity. The dimension Feelings was not a significant predictor of compliance to antidepressant medication (F1,47 = 3.076, P = 0.086, 02 = 0.041). Conversely, we found Modesty to be a significant positive predictor of compliance to antidepressant medication (F1,47 = 7.556, P = 0.008, 02 = 0.12): approximately 12% of the variance in compliance scores was accounted for by scores on Modesty. DiscussionThis study’s primary goal was to investigate the relation between medication compliance and personality characteristics in individuals with MDD. The findings with respect to personality dimensions and medication compliance are intriguing and potentially important. It is known that personality pathology is a significant negative predictor of outcome (47,48); however, past research dealing with the relation between personality and compliance in depression patients is limited and speculative. This study found that Extraversion (and specifically, differences in the Activity facet within the Extraversion dimension) was negatively related to antidepressant compliance and significantly predicted medication noncompliance. Characteristics of Extraversion include liking people, excitement, and stimulation, as well as being active. People with elevated Extraversion scores also tend to prefer large groups and gatherings and tend to be cheerful in their disposition toward others (41). Individuals with a high Activity score tend to be energetic, quick, determined, enthusiastic, aggressive, and active (41). Such people may be “too busy” or too engaged to remember or prioritize taking medication. Although Excitement Seeking as measured by the NEO PI-R was not significantly related to medication compliance, these findings are consistent with those of Ekselius and colleagues (36), who found that noncompliance with antidepressant medication was associated with a sensation-seeking personality. They are also in line with other reports that found a strong association between “novelty seeking personality traits” in patients with panic disorder and generalized anxiety disorder and early discontinuation from clinical trials, another form of noncompliance (38). Elevated scores on the Feelings facet of Openness- to-Experience were also significantly related to compliance: elevated scores were negatively associated with medication compliance. Characteristics of the Feelings facet include being excitable, spontaneous, insightful, imaginative, affectionate, talkative, and outgoing (41). Taken together, the characteristics associated with Feelings, coupled with the characteristics associated with the facet Activity, particularly being energetic, hurried, quick, excitable, and spontaneous, are somewhat related to characteristics of Excitement- Seeking. It is speculated that high scorers on both Activity and Feelings are similar in certain ways to those with an Excitement-Seeking personality. Another facet that was significantly related to, and a positive predictor of, medication compliance was Modesty (within the Agreeableness dimension). Interpreting this finding is not straightforward. Interestingly, and as for Extraversion, a considerable part of the Agreeableness scale is interpersonal in nature (41). Individuals with a high score on this scale can be described as being humble and self-effacing. They may show more deference to authority and be more likely to follow medication instructions closely. Individuals with depression who are humble may also have more insight into their condition and therefore be more likely to follow their prescribed medication regimen. The “flip side” of modesty is narcissism. Patients who have narcissistic tendencies as well as elevated scores for Extraversion, particularly on the Activity facet, are more likely not to comply with a prescribed medication regimen. Interestingly, the Compliance facet of the Agreeableness dimension was not associated with medication compliance in this study. This study has several limitations that need to be considered. First, while the MEMS is said to be the current gold standard for measuring medication compliance, issues do exist regarding its reliability and validity. In particular, it is assumed that medication is ingested when the MEMS container is opened. Also, it could be argued that the compliance rate reported in this study is unusually high. Other studies have reported rates of noncompliance with antidepressants around 60% (14,17,18,25). Yet, studies that have used the MEMS as a compliance measure in populations with depression have shown compliance rates comparable to those found in the present study (49,50). However, frequent patient contact in this study may have produced artificially high compliance rates. Individuals were seen every 2 weeks and also received telephone calls to confirm appointments. This likely exceeded standard practice over a 3-month window of routine treatment. Demyttenaere and colleagues, for example, reported that clinic visits had a positive effect on compliance behaviour in the short-term (26). It is also possible that the “Hawthorne effect” (whereby individuals modify their behaviour when they know they are being measured) indirectly increased compliance rates: not only was contact frequent, compliance was also closely monitored. However, Cramer and colleagues found that the “Hawthorne effect” dissipated after the first few days and that individuals returned to their normal behaviour patterns (49). Nonetheless, we cannot exclude the possibility that many patients maintained an artificially high level of compliance throughout the study. It has also been acknowledged that the nature and continuity of the doctor–patient relationship (including, for example, regular follow-up and empathy) is key to improving both medication compliance and treatment outcome (12,16,19). This study provided excellent continuity of care, in the form of regular follow-up appointments, and involved the research team as well as the treating psychiatrist. We believe that a therapeutic alliance was developed with most, if not all, study participants. Thus, it is probable that the degree of compliance we observed was influenced by the nature of the patient–staff relationship. As in previous reports (9,10,14,18), we did not find a significant relation between demographic variables and compliance with antidepressant medication. Severity of the depressive illness, both at baseline and at the end of the study, also did not significantly predict medication compliance. However, this finding may have been influenced by the relative lack of change in scores over the course of the study in a population with chronic depression. Others have also found a weak relation between severity of depression and compliance with antidepressant therapy (10,14), although Demyttenaere and colleagues found that a higher initial score on the HRSD predicted greater compliance (18). Side effects were not associated with medication compliance. This is consistent with research by Blackwell (51) and Demyttenaere and colleagues (18) but contrasts with findings by Lin and colleagues, who found that severe levels of side effects were predictive of medication compliance levels (14). Subjects in the present study were not considered non- compliant if they experienced severe side effects and were advised by their pharmacist or physician to discontinue or decrease the dosage of medication. The inherent complications in compliance research— including how compliance is measured—contribute to its complexity. Nevertheless, the intricate relation between personality and medication compliance in patients with MDD requires further attention. Identifying predictors of compliance can help in the development of personalized treatment regimens and improve the clinical management of depression. Funding and SupportThis study was supported in part by an educational grant from GlaxoSmithKline. AcknowledgementMs Kari Fulton provided data management assistance. References1. Parikh SV, Lesage AD, Kennedy SH, Goering PN. Depression in Ontario: under-treatment and factors related to antidepressant use. J Affect Disord 1999;52:67–76. 2. Parikh SV, Wasylenki D, Goering P, Wong J. Mood disorders: Rural/urban differences in prevalence, health care utilization, and disability in Ontario. J Affect Disord 1996;38:57–65. 3. Weissman MM, Leaf PJ, Tischler GL, Blazer DG, Karno M, Bruce ML, and others. Affective disorders in five United States communities. Psychol Med 1988;18:141–53. . Berti Ceroni GB, Neri C, Pezzoli A. Chronicity in major depression—a naturalistic prospective study. J Affect Disord 1984;7:123–32. 5. Keller MB. Depression: a long-term illness. Br J Psychiatry 1994;165(Suppl 26):9–15 6. Hays RD, Wells KB, Sherbourne CD, Rogers W, Spritzer K. Functioning and well-being outcomes of patients with depression compared with chronic general medical illnesses. Arch Gen Psychiatry 1995;52:11–9. 7. Angst J, Kupfer DJ, Rosenbaum JF. Recovery from depression: risk or reality? Acta Psychiatr Scand 1996;93:413–9. 8. Kennedy SH, Lam RW, Cohen NL, Ravindran AV. Clinical guidelines for the treatment of depressive disorders. IV. Medications and other biological treatments. Can J Psychiatry 2001;46(Suppl 1):38S–58S. 9. Fawcett J. Compliance: definitions and key issues. J Clin Psychiatry 1995;56(Suppl 1):4–8. 10. Frank E, Perel JM, Mallinger AG, Thase ME, Kupfer DJ. Relationship of pharmacologic compliance to long-term prophylaxis in recurrent depression. Pharmacol Bull 1992;28:231–5. 11. Frank E, Kupfer DJ, Siegel LR. Alliance not compliance: a philosophy of out- patient care. J Clin Psychiatry 1995;56(Suppl 1):11–6. 12. Kusumakar V, Kennedy S. Promoting therapeutic alliance and adherence to medication treatment in depression. The Canadian Journal of Diagnosis 1996;(Suppl):2–9. 13. Besch CL. Compliance in clinical trials. AIDS 1995;9:1–10. 14. Lin EHB, Von Korff M, Katon W, Bush T, Simon GE, Walker E, and others. The role of the primary care physician in patients’ adherence to antidepressant therapy. Med Care 1995;33:67–74. 15. Bebbington PE. The content and context of compliance. Int Clin Psychopharmacol 1995;9(Suppl 5):41–50. 16. Demyttenaere K. Compliance during treatment with antidepressants. J Affect Disord 1997;43:27–39. 17. Caligiuri MP, Lohr JB, Jeste DV. Parkinsonism in neuroleptic-naive schizophrenic patients. Am J Psychiatry 1993;150:1343–8. 18. Demyttenaere K, Van Ganse E, Gregoire J, Gaens E, Mesters P. Compliance in depressed patients treated with fluoxetine or amitriptyline. Int Clin Psychopharmacol 1998;13:11–7. 19. Cohen NL, Parikh SV, Kennedy SH. Medication compliance in mood disorders: relevance of the Health Belief Model and other determinants. Primary Care Psychiatry 2000;6:101–10. 20. Pampallona S, Bollini P, Tibaldi G, Kupelnick B, Munizza C. Patient adherence in the treatment of depression. Br J Psychiatry 2002;180:104–9. 21. Kupfer DJ. Long-term treatment of depression. J Clin Psychiatry 1991;52(Suppl):28–34. 22. Greden JF. Antidepressant maintenance medications: when to discontinue and how to stop. J Clin Psychiatry 1993;54(Suppl 8):39–45. 23. Keller MB, Hirschfeld RM, Demyttenaere K, Baldwin DS. Optimizing outcomes in depression: focus on antidepressant compliance. Int Clin Psychopharmacol 2002;17:265–71. 24. Rice DP, Miller LS. Health economics and cost implications of anxiety and other mental disorders in the United States. Br J Psychiatry 1998;34:4–9. 25. Johnson DAW. Depression: treatment compliance in general practice. Acta Psychiatr Scand 1981;290(Suppl):447–53. 26. Demyttenaere K, Mesters P, Boulanger B, Dewe W, Delsemme M-H, Gregoire J, and others. Adherence to treatment regimen in depressed patients treated with amitriptyline or fluoxetine. J Affect Disord 2001;65:243–52. 27. Porter AMW. Drug defaulting in general practice. BMJ 1969;1:218. 28. Bronson JG. Is noncompliance with outpatient Rx therapy common? Drug Topics 1991. 29. Rudd P. Partial compliance: implication for clinical practice. J Cardiovasc Pharmacol 1993;22(Suppl A):S1–S5. 30. Waterhouse DM, Calzone KA, Mele C, Brenner DE. Adherence to oral tamoxifen: a comparison of patient self-report, pill counts, and microelectronic monitoring. J Clin Oncol 1993;11:1189–97. 31. Feinstein AR. On white-coat effects and the electronic monitoring of compliance. Arch Intern Med 1990;150:1377–8. 32. Kemp R, Hayward P, Applewhaite G, Everitt B, David A. Compliance therapy in psychotic patients: randomized controlled trial. BMJ 1996;312:345–9. 33. Becker MH, Maiman LA. Sociobehavioral determinants of compliance with health and medical care recommendations. Med Care 1975;13:10–24. 34. Sirey J, Bruce ML, Alexopoulos GS, Perlick DA, Friedman SJ, Meyers BS. Perceived stigma and patient-rated severity of illness as predictors of antidepressant drug adherence. Psychiatr Serv 2001;52:1615–20. 35. Horowitz LM, Rosenberg SE, Baer BA, Ureño G, Villaseñor VS. The Inventory of Interpersonal Problems: psychometric properties and clinical applications. J Consult Clin Psychol 1988;56:885–95. 36. Ekselius L, Bengtsson F, Knorring L. Non-compliance with pharmacotherapy of depression is associated with a sensation seeking personality. Int Clin Psychopharmacol 2000;15:273–8. 37. Schalling D, Asberg M, Edman G, Oreland L. Markers for vulnerability to psychopathology: temperament traits associated with platelet MAO activity. Acta Psychiatr Scand 1987;76:172–82 38. Wingerson D, Sullivan M, Dager S, Flick S, Dunner D, Roy-Byrne, P. Personality traits and early discontinuation from clinical trials in anxious patients. J Clin Psychopharmacol 1993;13:194–7. 39. Cloninger CR, Przybeck TR, Svrakic DM. The Tridimensional Personality Questionnaire: US normative data. Psychol Rep 1991;69:1047–57. 40. Stein MB, Hackerman FR. The use of the MMPI-2 in conjunction with the Neo-Personality Inventory. Psychol Rep 1991;69:955–8. 41. Costa PT, McCrae RR. NEO-PI-R professional manual. Revised NEO PI Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO-FFI). Odessa (FL): Psychological Assessment Resources; 1992 42. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56–62. 43. Williams JB. A structured interview guide for the Hamilton Depression Rating Scale. Arch Gen Psychiatry 1988;45:742–7. 44. Vanderkooy JD, Kennedy SH, Bagby RM. Antidepressant side effects in depression patients treated in a naturalistic setting: a study of bupropion, moclobemide, paroxetine, sertraline, and venlafaxine. Can J Psychiatry 2002;47:174–80. 45. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders, Patient Edition (SCID-P). Version 2. New York: New York State Psychiatric Institute, Biometrics Research; 1995. 46. Bagby RM, Schuller DR, Levitt AJ, Joffe RT, Harkness KL. Seasonal and non-seasonal depression and the five-factor model of personality. J Affect Disord 1996;38:89–95 47. Reich JH, Green AI. Effect of personality on outcome of treatment. J Nerv Ment Dis 1991;179:74–82. 48. Santor DA, Bagby RM, Joffe RT. Evaluating stability and change in personality and depression. J Pers Soc Psychol 1997;73:1354–62. 49. Cramer JA, Mattson RH, Prevey ML, Scheyer RD, Ouellette VL. How often is medication taken as prescribed? A novel assessment technique. JAMA 1989;261:3273–7. 50. Engstrom FW. Clinical correlates of antidepressant compliance. In: Cramer JA, Spilker B, editors. Patient compliance in medical practice and clinical trials. New York: Raven Press; 1991 p187–94. 51. Blackwell B. Compliance. Psychother Psychosom 1992;58:161–9. Author(s)Manuscript received May 2003 and accepted June 2003. 1. Research Coordinator, Department of Psychiatry, University Health Network; PhD Candidate, Department of Psychology, York University, Toronto, Ontario 2. Associate Professor, Department of Psychology, Atkinson Faculty of Liberal and Professional Studies, York University, Toronto, Ontario 3. Head, Clinical Research Department, Centre for Addiction and Mental Health; Professor of Psychiatry, Department of Psychiatry, University of Toronto, Toronto, Ontario 4. Research Scientist, Personality and Psychopathology Section, Clinical Research Department, Centre for Addiction and Mental Health; Assistant Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario 5. Psychiatrist-in-Chief, University Health Network; Professor of Psychiatry, University of Toronto, Toronto, Ontario Address for correspondence: Dr SH Kennedy, University Health Network, 200 Elizabeth Street, 8 Eaton North - Suite 222, Toronto, ON M5G 2C4 e-mail: sidney.kennedy@uhn.on.ca
1 | 2
|
||||||||||||||