PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Compr Psychiatry. Author manuscript; available in PMC 2010 March 1.
Published in final edited form as:
PMCID: PMC2746444
NIHMSID: NIHMS98100

Predictors of non-adherence among individuals with bipolar disorder receiving treatment in a community mental health clinic

Abstract

Background

Subjective experience of illness is a critical component of treatment adherence in populations with bipolar disorder (BPD). This cross-sectional analysis examined clinical and subjective variables in relation to adherence in 140 individuals with BPD receiving treatment with mood stabilizing medication.

Methods

Non-adherence was defined as missing 30% or more of medication on the Tablets Routine Questionnaire (TRQ), a self-reported measure of medication treatment adherence. Adherent and non-adherent groups were compared on measures of attitudes towards illness and treatment including the Attitudes towards Mood Stabilizers Questionnaire (AMSQ), the Insight and Treatment Attitudes Questionnaire (ITAQ), The Rating of Medication Influences (ROMI), and the Multidimensional Health Locus of Control Scale (MHLC).

Results

Except for substance abuse comorbidity, adherent individuals (N=113, 80.7%) did not differ from non-adherent individuals (N=27, 19.3%) on clinical variables. However, non-adherent individuals had reduced insight into illness, more negative attitudes towards medications, fewer reasons for adherence, and more perceived reasons for non-adherence compared to adherent individuals. The strongest attitudinal predictors for non-adherence were difficulties with medication routines (OR 2.2) and negative attitudes towards drugs in general (OR 2.3).

Limitations

Results interpretation is limited by cross-sectional design, self-report methodology and sample size.

Conclusions

Comorbid substance abuse, negative attitudes towards mood stabilizing medication, and difficulty managing to take medication in the context of one's daily schedule are primary determinants of medication treatment adherence. A patient-centered, collaborative model of care that addresses negative attitudes towards medication and difficulty coping with medication routines use may be ideally suited to address individual adherence challenges.

Keywords: Bipolar disorder, treatment adherence, compliance, subjective experience, attitudes towards treatment, mood stabilizers

Introduction

Medication treatment non-adherence among populations with bipolar disorder (BPD) is widespread and pervasive. A recent large-scale (N=3,681) study found that 40% of individuals with bipolar mania were partially or totally non-adherent with prescribed medication treatments [1]. The effects of medication non-adherence include symptoms worsening, reduced quality of life and in some cases, suicide. A recent study of suicidal behavior in relation to mood stabilizer treatment found a sixteen-fold greater suicidal behavior rate after medication discontinuation compared with mood stabilizer monotherapy continuation (55.9 vs. 3.5 events/100 patient years) among 405 individuals with bipolar disorder followed for a 3-year period, suggesting that commonly utilized mood stabilizing drugs (lithium, divalproex, carbamazepine) are protective against suicidal behavior [2]. Reduced adherence with mood-stabilizer therapy is also associated with greater use of mental-health related emergency room visits and inpatient hospitalizations [3].

Factors reported to be associated with treatment non-adherence among individuals with BPD include demographic variables specific to an individual such as gender, ethnicity, age, and illness-specific features such as illness severity or comorbidity. However, more mutable factors, such as attitudes towards illness and treatments, also contribute to non-adherence, [4,5,6,7,8,9,10,11,12,13]. These factors can potentially be addressed in targeted psychosocial interventions, such as psychoeducation or social cognitive theory-based interventions that are used to supplement pharmacotherapy in bipolar disorder.

Individual perception of risks and benefits of medication treatment are known to affect treatment adherence in bipolar populations [14,15], and the experience of burdensome or intolerable side effects, complicated medication regimens, lack of knowledge of underlying illness and felt /experienced stigma in relation to mental illness are all known to have a negative effect on medication adherence [14,16,17,18,19,20,4] Additionally, an individual's beliefs regarding controllability of one's health, or health locus of control is likely to affect illness experience [15]. Self-reported adherence with health treatment has been associated with personal health locus of control beliefs [21,22, 23] with those individuals who perceive an internal locus of control being more likely to have good adherence with treatment compared to those individuals with an external locus of control. Finally, insight is another aspect of subjective experience of illness worth special mention. Although “lack of insight” has more traditionally been associated with primary psychotic illness, such as schizophrenia, increasing attention is being paid to the often – severe deficits in insight seen in individuals with BPD [24].

Patients are described as “the final health care decision-makers”, and satisfaction with and perceived value of medication treatments among individuals with BPD are strong drivers of medication adherence/non-adherence [25]. Identification of predictors of adherence in populations with BPD, particularly those that are mutable, provides a starting place for focused adherence enhancement interventions. Previously published studies on adherence in bipolar populations have not generally included reasons for adherence as well as non-adherence or an assessment of locus of control, and many studies have not adjusted for clinical characteristics and illness severity [26]. The aim of this analysis was to examine the relationships between demographic and clinical variables, selected illness severity markers, and markers of subjective illness and treatment attitudes in relation to treatment adherence in a sample of 140 individuals with BPD being treated with mood stabilizing medications in a community mental health clinic (CMHC). The study focuses on individuals with bipolar depression, a population known to be particularly disabled.

Methods

This is a cross-sectional analysis of factors associated with treatment non-adherence among individuals receiving treatment for bipolar disorder in a CMHC. The analysis is part of a larger, prospective study on treatment adherence conducted by this group of investigators (K23 MH 065599-01, PI Sajatovic). This analysis was confined to baseline study data.

This analysis compared characteristics of individuals with BPD who were adherent and those who are non-adherent with treatment at a CMHC as defined by missing 30% or more of their medication on the self-reported Tablets Routine Questionnaire [TRQ,27,19]. In addition to standardized psychiatric diagnostic evaluation and assessment of baseline demographic variables, study participants also completed a variety of measures that evaluated illness severity (symptoms, substance abuse comorbidity and psychosocial supports), as well as their personal attitudes towards illness and treatment, insight into their disorder, reasons for adherence/non-adherence and perceived control over health.

All study participants met the following inclusion criteria: 1) Subjects had a clinical diagnosis of BPD Type I determined by a standardized diagnostic interview, the Mini-International Neuropsychiatric Interview (MINI) [28]; 2) Subjects had illness of at least two years duration; 3.) Subjects had an index depressive episode; 4) Subjects received treatment with medication to stabilize mood for at least six months (Mood stabilizing medications were: Lithium, lamotrigine, valproate, carbamazepine, oxcarbazepine, topiramate, gabapentin, aripiprazole, olanzapine, quetiapine, risperidone, clozapine, clonazepam. Medications, including atypical antipsychotics, could be utilized as either monotherapy or as part of a polytherapy regimen); and 5) Subjects were able to participate in psychiatric interviews and able to give written, informed consent to study participation. The study was approved by the local Institutional Review Board (IRB).

Specific Measures

Medication Treatment Adherence

Adherence was evaluated with the Tablet Routines Questionnaire [TRQ,26,19] a brief, self-report instrument which has been validated in populations with bipolar disorders [14, 26]. The revised version by Adams and Scott [19] has specificity for non adherence of 90%. The TRQ identifies “non-adherent” individuals, defined as those who miss 30% or more of their medication in the last month. A number of investigators have defined “good” adherence in seriously mentally ill populations, including those with BPD, as missing no more than 20% of medication [29,30,31], while Scott and Pope [14] have derived a clinically relevant definition of poor adherence in BPD as missing 30% or more of medications as identified by the TRQ. The conservative estimate of non-adherence as defined by Scott and Pope [14] was utilized in this study in order to maximize clinical relevance and focus on a population where non-adherence could be anticipated to be extensive enough to pose substantial risk for relapse.

Individuals were considered to be non-adherent if they self-reported missing 30% or more of prescribed medication in the past week. Weekly adherence (number of days medications were taken out of the past seven days) was calculated for each mood stabilizing medication, and then in cases of multiple medications, an average weekly adherence was calculated. Individuals who were unable to determine a percentage of adherence, but who self-reported missing 3 days or more of medication in the last week were also considered to be non-adherent. The TRQ does not separate medications by individual compound. In this analysis, in instances where an individual was prescribed multiple medications, an average of missed medications was calculated based upon their self-report.

Symptom severity variables and social supports

Overall psychopathology was evaluated with the Brief Psychiatric Rating Scale [BPRS, 32] and the Clinical Global Impression [CGI,33]. Depressive symptoms were evaluated with the 17-item version of the Hamilton Depression Scale [HAM-D,34]. Substance abuse comorbidity was assessed as a continuous measure using a portion of a standardized instrument, the Addiction Severity Index [ASI,35,36] items 1 through 14 of the Alcohol/Drug Index (ADI). The ASI evaluates both lifetime and past 30-day use of a wide variety of commonly abused substances. Psychosocial support was measured with the Interpersonal Support Evaluation List [ISEL,37], a 40-item self-report questionnaire that was developed to assess social support. The ISEL captures perceptions of resources provided by others. A total index is comprised of 4 subscales: tangible assistance (material aid), appraisal (availability of someone to talk to about life's problems), self-esteem (positive appraisal of self from others and positive comparison when comparing one's self with others), and belonging (people with whom one can do things.) Response for each item is coded on a four-point Likert scale ranging from definitely false to definitely true.

Subjective attitudes to illness and treatment

Attitudes toward medication treatment were evaluated with the Attitude toward Mood Stabilizers Questionnaire (AMSQ), a modification of the Lithium Attitudes Questionnaire [38] which evaluates an individual's attitudes towards mood stabilizing medication [14,19]. The AMSQ has seven subscales that represent key attitudinal domains with respect to adherence including 1.) opposition to prophylaxis, 2.) denial of therapeutic effectiveness, 3.) fear of side effects, 4.) difficulty with medication routines, 5.) denial of illness severity, 6.) negative attitude towards drugs in general, and 7.) lack of information about mood stabilizers [38,14]. Higher scores on each subscale represent more negative attitudes toward mood stabilizers. The AMSQ has been used by other investigators to predict adherence in BPD [14] and have been noted to improve with psychoeducational programs for BPD [27].

Reasons for adherence/non-adherence were evaluated using the Rating of Medication Influences (ROMI), a standardized assessment of selected reasons for compliance and non-compliance with medications [39]. Insight was evaluated with the Insight and Treatment Attitudes Questionnaire (ITAQ), an 11-item rating scale to evaluate patient recognition of illness and need for treatment in psychiatric illness. The ITAQ has been widely utilized in both populations with schizophrenia and bipolar disorder [40,41,42,43]. Each ITAQ item is scored on a 0 to 2 scale (0 = no insight, 2 = good insight), and the scale has high inter-rater reliability (r=0.82, p<.001) [44]. Locus of control was assessed with the Multidimensional Locus of Control (MHLC), an 18-item instrument that measures three dimensions of locus of control of reinforcement as it pertains to health (internal, IHLC: external-chance, CHLC: and external powerful others, PHLC) [45]. The MHLC has been utilized to study locus of control in populations with severe affective illness where treatment adherence has been a focus of evaluation [19]. Scoring is from 6-36 with higher scores indicating stronger beliefs.

Statistical analysis

Individuals who self-identified as non-adherent with medications (missing 30% or more of prescribed treatments) were compared to individuals who self-identified as adherent with treatment. Descriptive statistics were used to characterize demographic and clinical characteristics of patients with BPD who were adherent and those who were non-adherent with treatment. Chi-square analysis and t-tests were used to test statistical significance for categorical and continuous variables, respectively. Multiple logistic regression models were used to compare clinical characteristics, severity markers and attitudinal variables of adherent and non-adherent groups. As there have been reports of clinical and illness-related variables being associated with non-adherence in bipolar populations [26], sex, age, ethnicity, education, duration of illness, symptom rating scores, and substance abuse were included as covariates in the models. To evaluate the strongest factors in attitudes towards treatment, a logistic model for non-adherence vs. adherence was estimated with AMSQ subscales 1 through 7 in the model, while controlling for sex, age, ethnicity, education, duration of illness, BPRS, HAM-D, CGI scores, and substance abuse.

Results

Table 1 demonstrates characteristics of individuals with BPD who were adherent (N= 113, 80.7%) and those who are non-adherent (N=27, 19.3%) with treatment. There were no significant differences in age, gender, ethnicity, education, or duration of illness. Individuals who were non-adherent had more substance use comorbidity (p=.0039), while depressive and psychotic psychopathology was not significantly different between adherent and non-adherent individuals. Global psychopathology (CGI score) was statistically greater (p=.0183) for non-adherent individuals, but appeared to be of marginal clinical difference (CGI mean for adherent individuals was 4.9 compared to 5.3 for non-adherent individuals).

Table 1
Characteristics of 140 individuals with BPD who are adherent vs. non-adherent with treatment as measured by the Tablets Routine Questionnaire (missing 30% or more of medications)

In contrast to the relative similarities on clinical characteristics and illness severity among adherent and non-adherent individuals, there were substantial and significant differences in illness and treatment attitudes between the two groups. Individuals who were non-adherent with prescribed medication had significantly more negative attitudes towards mood stabilizers (p<.0001), reduced insight into illness (p=.0039), fewer reasons for adherence (p=.0248) and more reasons for non-adherence compared with adherent individuals (p=.0001). Additionally, non-adherent individuals more often perceived an external locus of control compared to adherent individuals (p=.0422).

In addition to overall more negative attitudes towards mood stabilizing medications, there were differences in specific negative attitudes among adherent vs. non-adherent individuals with BPD. Except for the AMSQ subscale for denial of therapeutic effectiveness, non-adherent individuals had significantly higher mean scores in the AMSQ subscales (p<.01) indicating more negative attitudes toward mood stabilizers, with differences in mean scores ranging from 0.3 to 1.8. Controlling for the effects of clinical characteristics and illness severity in a multiple logistic model for non-adherence vs. adherence, subscales of the AMSQ that appeared most predictive for non-adherence were negative attitudes towards drugs in general (Odds ratio, OR= 2.3, 95% CI=(1.08, 4.8), p=.0305) and difficulty with medication routines (OR=2.2, 95% CI=(1.36, 3.6), p=.0014). Domains with the construct of negative attitudes towards medications included feeling that relief from personal stress was more important than taking medications, believing that “most people” would not be in favor of taking a mood stabilizer and feeling that taking a mood stabilizer was an “artificial” way to keep stable. Domains with the construct of medication routines included difficulty fitting medication-taking into daily schedule, needing to be reminded to take medication/forgetting medication and difficulty remembering to take medication if daily routine changes for any reason.

Looking at the strongest predictor of non-adherence in each of the 3 main domains (demographic, severity/social support variable, and attitudes/subjective experience) and overall, logistic regression models for non-adherence vs. adherence were calculated separately for each domain and an overall model with all factors in the model. None of the demographic factors appeared to have significant relationship with treatment adherence. Substance abuse, measured by ASI score, was the only significant clinical predictor (p=.0479), while AMSQ (p=.0246) was a significant attitudinal predictor. There was a trend for statistical significance for the ROMI compliance score (p=.0568), and ROMI non-compliance score (p=.0869) among the attitudinal factors.

Discussion

These data demonstrate a relatively high prevalence of treatment non-adherence among individuals with BPD receiving treatment at a CMHC, and suggest that comorbid substance abuse, negative attitudes towards mood stabilizing medication, and difficulty managing to take medication in the context of one's daily schedule are primary determinants of medication treatment adherence. In this CMHC-treated sample, approximately 1 in 5 individuals identified themselves as being non-adherent with mood stabilizing medications to a clinically significant degree (missing 30% or more medications in the recent past).

Treatment non-adherence sharply increases personal, social and financial costs among individuals with BPD [46,47]. Begley and colleagues [46] noted that health care costs for severe/relapsing BPD (often characterized by non-adherence with prescribed treatments and comorbid substance misuse) is approximately $264,785 per person compared with $11,720 for individuals who experiences only a single manic episode [46]. Similarly, Durrenberger and colleagues [48] reported that over a 6- year period, the cost of care for one non-adherent patient with frequent manic relapses was equal to that for 13 adherent individuals. Identification of potentially changeable variables that are associated with treatment non-adherence in bipolar populations offers the potential to design interventions that address these areas of concern, and potentially to minimize the negative consequence for individuals with bipolar disorder who are at risk for stopping their medication treatments.

In common with some other investigators [20], our study found few demographic or clinical variables that are clearly associated with non-adherence among patients with BPD. Identifying individuals at risk for future non-adherence thus goes beyond the need to focus on any specific age, gender or ethnic sub-groups. An exception to the similar demographic and clinical findings between adherent vs. non-adherent patients with BPD is more substance use among those who are non-adherent. Alcohol and other substance use disorders complicate the course of and prognosis of BPD [49,50], and in most instances, treatment adherence is reduced among individuals with BPD who abuse substances [51, 49]. Large, epidemiological surveys of the general U.S. population have found BPD to have the highest association with alcohol or other psychoactive substance use disorders compared to other Axis I psychiatric disorders [52, 53]. Unfortunately, substance use comorbidity among patients with bipolar disorder may be under-recognized, and is often not addressed within the context of treatment for bipolar disorder. It has been demonstrated that individuals with more serious mental illness (including bipolar disorder) and co-existing substance use disorders are extensive users of costly crisis/emergency room care and inpatient services [54]. However, the literature on evidence-based treatments for individuals with bipolar disorder and substance abuse is quite limited [55].

Our study findings suggest that individuals who are non-adherent have negative attitudes towards medications, have difficulty managing medication routines and have more perceived reasons for non-adherence compared to adherent individuals. These are likely shaped by how the individual interprets and personally experiences bipolar illness. Models of health behaviors, such as the Health Belief Model [56] focus on determinants of adherence as a product of an individual's health beliefs. The fact that there was little symptom difference between adherent and non-adherent individuals in the study presented here supports the notion that adherence attitudes may be relatively independent of symptoms (particularly in the case of bipolar depression) and are more a product of the individual's established health beliefs. Perceptions of susceptibility to illness, perceived severity of illness, the benefits of treatment, the costs and burdens of treatment as well as cues to action all factor into treatment adherence outcomes [57,16].

In the population presented here, the strongest attitudinal predictors for non-adherence were difficulties with medication routines (OR 2.2) and negative attitudes towards drugs in general (OR 2.3). Individuals had difficulty always remembering to take medications, easily forgot their medication if they had a change in daily routine, and at times needed reminding by others to take their medications. Negative attitudes included the notion that taking medication for someone with BPD was not indicated or normal, and that the disorder might be best managed in other, perhaps non-pharmacological ways. These represent areas in which specific therapeutic interventions may be of benefit. The complexity of a treatment regimen can often affect treatment adherence [58]. For example, adherence may improve when an individual is prescribed a pill that can be taken once daily rather than in divided daily dosing [59]. When frequency of drug regimen is not modifiable, timing of medication can be matched to an individual's activities of daily living to improve adherence. Misinterpretation of common medication instructions can be addressed to improve treatment adherence. For example, Eraker [60] noted that only 36% of patients correctly interpreted the meaning of “every six hours”. In addition to careful review of medication instructions, adherence aids such as pill boxes/pill reminders and pre-set dose alarms [60] can be helpful. Compensatory strategies to enhance functioning in patients with schizophrenia have been successfully utilized by Velligan and colleagues [61], and many of these methods appear likely to benefit bipolar patients with functional deficits as well [62].

Inadequate or incorrect understanding of illness and treatment needs are not uncommon in populations with serious mental illness, including individuals with BPD [63,64], and lithium knowledge has been demonstrated to be correlated with serum lithium levels [65]. One study of psychiatric inpatients found that more than half of psychiatric inpatients did not know the condition for which they were being treated, the names of the medications prescribed, or the role the medications had in addressing the illness [66]. Lack of communication or poor treatment alliance with providers may result in perpetuation of false beliefs regarding prescribed medications, which if addressed, could result in improved adherence [67]. For example, fear of becoming “addicted” or dependent upon mood stabilizing medications may become an issue that affects adherence for some individuals with BPD [13]. Psychosocial interventions that enhance knowledge and understanding of BPD, such as the Psychoeducational approach refined by Colom and colleagues [68] may simultaneously improve both treatment adherence and more global illness outcomes.

The literature suggests that concerns over medication adverse effects is a major reason for non-adherence [4,25], and that fear of side effects may play a larger role in treatment non-adherence among patients with BPD compared to the actual side effects themselves [19]. Recent studies in large populations of individuals with bipolar disorder noted that non-adherence rates are remarkably similar across a wide variety of medications including traditional mood stabilizers and atypical antipsychotics [69,70]. The medication concerns perceived by an individual may play a more important role in determining adherence rather than the specific type of medication prescribed. A recent survey of 233 members of the Manic Depression Fellowship [71] noted that over 60% of individuals were dissatisfied with information about the risks of side effects with their medication treatments. Clear and readily understandable information on medication treatments with ample opportunity to provide feedback and address ongoing medication concerns may improve treatment adherence.

There is evidence to suggest that exploration of an individual's beliefs about bipolar illness and then implementing a therapy that directly addresses these beliefs may lead to changes in treatment planning and improve attitudes and adherence to mood stabilizers [72,73]. This study found that non-adherent individuals more often had a strong powerful external locus of control compared to adherent individuals, contrasting with some previous reports in bipolar populations which found that adherence was more often associated with dependence on others or being more readily controlled/affected by others [18, 19]. However, this study also did not evaluate specific qualities of the types of social environment individuals in this sample experienced. It is possible that external or social influences may have not been supportive of medication taking in this group of individuals with BPD—a recent qualitative analysis by this group of investigators found that up to 40% of patients with BPD reported that family members or others specifically advised them against taking medications [6]. An approach like Bauer and colleagues' [74,75] Collaborative Care Model (CCM), in which individuals with BPD are actively involved in care planning/self-management is associated with better outcomes than more traditional medical-model care. A CCM approach may also promote positive and constructive alliances with care providers that enhance adherence in individuals with external locus of control. Likewise, family-focused therapy that includes education, communication training and problem-solving skills training for individuals with bipolar disorder is associated with better medication compared to less intensive crisis management [76].

Our study has a number of important limitations including cross-sectional design and relatively small sample size. It is very likely that our analysis identified only a “lower boundary” of non-adherence given the possible under-detection of non-adherence when relying upon self-report. Additionally, expressed attitudes towards medication and adherence as evaluated on rating scales may not identify actual attitudes that individuals may be reluctant to share. Interpretation of study results can not be extrapolated to all bipolar populations who are non-adherent. Our study did not specifically focus on recruiting individuals who are non-adherent, and the most non-adherent patients are unlikely to volunteer to participate in a research study. Additionally, while adherent vs. non-adherent populations in this sample did not appear to differ substantially on symptoms, the study enrolled only individuals with bipolar depression, and it is possible that if individuals with mania were included the findings would have been different.

Conclusions

There are significant differences between adherent vs. non-adherent individuals with BPD, including such potentially changeable factors as substance abuse, level of comfort in coping with medication concerns/side effects, attitudes towards medication, and individual reasons for adherence/non-adherence. A patient-centered, collaborative model of care may be ideally suited to address specific and individual vulnerability to treatment non-adherence.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Martha Sajatovic, Professor of Psychiatry and of Biostatistics and Epidemiology, Case Western Reserve University School of Medicine, Cleveland, Ohio.

Rosalinda V. Ignacio, Senior Research Associate, Serious Mental Illness Treatment Research and Evaluation Center (SMITREC), Health Services Research and Development, Ann Arbor VA Healthcare System and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan.

Jane A. West, Research Associate, Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio.

Kristin A. Cassidy, Research Associate, Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio.

Roknedin Safavi, Assistant Clinical Professor of Psychiatry, Case Western Reserve University School of Medicine, Cleveland, Ohio; Medical Director, Connections, Cleveland, Ohio.

Amy M. Kilbourne, VA Ann Arbor National Serious Mental Illness Treatment Research and Education Center, Associate Professor of Psychiatry, University of Michigan, Ann Arbor, MI.

Frederic C. Blow, Director, Serious Mental Illness Treatment Research and Evaluation Center (SMITREC), Health Services Research and Development, Ann Arbor VA Healthcare System, and Professor, Department of Psychiatry, University of Michigan, Ann Arbor, Michigan.

References

1. Montoya A, Perez J, Gilaberte I, Gonzalez-Pinto A, Haro J, Vieta E, Tohen M, 2007 Patterns of drug treatment for manic episode in the clinical practice. Outcomes of the Spanish sample in the EMBLEM Study. Actas Esp Psiquiatr. 2007;35(5):315–322. [PubMed]
2. Yerevanian BI, Koek RJ, Mitz J. Bipolar pharmacotherapy and suicidal behavior. Part1: Lithium, divalproex and carbamazepine. J Affect Disorder. 2007;103(13):5–11. Epub 2007 July 12. [PubMed]
3. Lew KH, Change EY, Rajagopalan K, Knoth RL. The effect of medication adherence on health care utilization in bipolar disorder. Managed Care Interface. 2006;19:4106. [PubMed]
4. Perlick DA, Rosenheck RA, Kacynski R, Kozma L. Medication non-adherence in bipolar disorder: a patient-centered review of research findings. Clinical Approaches in Bipolar Disorders. 2004;3:56–54.
5. Mark TL, Palmer LA, Russo PA, Vasey J. Examination of treatment pattern differences by race. Men Health Serv Res. 2003;5:241–50. [PubMed]
6. Sajatovic M. Treatment adherence in late-life bipolar disorder. AAGP Annual Meeting; New Orleans, Louisiana. 2007.
7. Opolka JL, Rascati KL, Brown CM, Gibson PJ. Ethnicity and prescription patterns for haloperidol, Risperidone, and olanzapine. Psychaitric Ser. 2004;55:151–56. [PubMed]
8. Cooper LA, Gonzales JJ, Gallo JJ, Rost KM, Meridith LS, Rubenstein LV, et al. The acceptability of treatment for depression among African-American, Hispanic and White primary care patients. Med Care. 2003;41:479–89. [PubMed]
9. Dwight-Johnson M, Sherbourne CD, Liao D, Wills KB. Treatment preferences among depressed primary care patients. J Gen Intern Med. 2000;15(8):527–34. [PMC free article] [PubMed]
10. Wagner AW, Bystritsky A, Russo JE, Craske MG, Sherbourne CD, Stein MB, et al. Beliefs about psychotropic medication and psychotherapy among primary care patients with anxiety disorders. Depress Anxiety. 2005;21:99–105. [PubMed]
11. McCabe R, Priebe S. Explanatory models of illness in schizophrenia: comparison of four ethnic groups. Br J Psychiatry. 2004;185:25–30. [PubMed]
12. Marsh M. Feminist Psychopharmacology: An Aspect of Feminist Psychiatry. Women and Therapy. 1995;16:73–84.
13. Fleck DE, Keck PE, Corey KB, Strakowski SM. Factors associated with medication adherence in African American and White patients with bipolar disorder. J Clin Psychiatry. 2005;66:646–52. [PubMed]
14. Scott J, Pope M. Nonadherence with mood stabilizers: prevalence and predictors. J Clin Psych. 2002;63:384–90. [PubMed]
15. Scott J. Using Health Belief Models to understand the efficacy-effectiveness gap for mood stabilizer treatments. Neuropsychobiology. 2002a;46:13–15. [PubMed]
16. Scott J, Pope M. Self-reported adherence to treatment with mood stabilizers, plasma levels, and psychiatric hospitalization. Am J Psychiatry. 2002b;159:1927–29. [PubMed]
17. Schumann C, Lenz G, Berghofer A, Muller-Oerlinghausen B. Non-adherence with long-term prophylaxis: A six year naturalistic follow-up study of affectively ill patients. Psychiatry Research. 1999;27:247–57. [PubMed]
18. Cochran SD, Gitlin MJ. Attitudinal correlates of lithium compliance in bipolar affective disorders. J Nerv Mental Disease. 1988;176:457–64. [PubMed]
19. Adams J, Scott J. Predicting medication adherence in severe mental disorder. Acta Psychiatrica Scand. 2000;101:119–24. [PubMed]
20. Berk M, Berk L, Castle D. A collaborative approach to the treatment alliance in bipolar disorder. Bipolar Disord. 2004;6:504–18. [PubMed]
21. McDonald-Miszczak L, Maki SA, Gould ON. Self-reported medication adherence and health status in late adulthood: the role of beliefs. Exp Aging Res. 2000;26:189–207. [PubMed]
22. Barlow JH, Macey SJ, Struther GR. Health locus of control, self-help and treatment adherence in relation to ankylosing spondylitis patients. Patient Educ Couns. 1993;20:153–66. [PubMed]
23. Reynaert C, Janne P, Donckier J, Buysschaert M, Zdanowicz N, Lejeune D, Cassiers L. Locus of control and metabolic control. Diabetes Metab. 1995;21:180–87. [PubMed]
24. Pini S, Cassano GB, Dell'Osso L, Amador XF. Insight into illness in schizophrenia, schizoaffective disorder, and mood disorders with psychotic features. American Journal of Psychiatry. 2001;158:122–25. [PubMed]
25. Johnson FR, Ozdemir S, Manjunath R, Hauber AB, Burch SP, Thompson TR. Factors that affect adherence to bipolar disorder treatments: a stated-preference approach. Med Care. 2007;45:545–52. [PubMed]
26. Vieta E. Improving treatment adherence in bipolar disorder through psychoeducation. J Clinical Psychiatry. 2005;66(Suppl 1):24–29. [PubMed]
27. Peet M, Harvey NS. Lithium maintenance 1. A standard education programme for patients. Br J Psychiatry. 1991;158:197–200. [PubMed]
28. Sheehan DV, Lecubier Y, Sheehan KH, Amorim P, Janaus J, Weiller E, et al. Development and Validation of a Structured Diagnosis Psychiatric Interview for DSM-IV and ICD-10. J Clinical Psychiatry. 1998;20:22–3. [PubMed]
29. Valenstein M, Blow FC, Copeland LA, McCarthy JF, Zeber JE, Gillon L, Bingham CR, Stavenger T. Poor antipsychotic adherence among patients with schizophrenia: medication and patient factors. Schizophr Bull. 2004;30(2):255–264. [PubMed]
30. Gilmer TP, Dolder CR, Lacro JP, Folsom DP, Lindamer L, Garcia P, Jeste DV. Adherence to treatment with antipsychotic medication and health care costs among Medicaid beneficiaries with schizophrenia. Am J Psychiatry. 2004;161(4):692–699. [PubMed]
31. Lew KH, Chang EY, Rajagopalan K, Knoth RL. The effect of medication adherence on health care utilization in bipolar disorder. Manag Care Interface. 2006 Sep;19(9):41–6. [PubMed]
32. Overall JA, Gorham DR. The Brief Psychiatric Rating Scale. Psychological Reports. 1962;10:799–812.
33. Guy W. ECDEU Assessment Manual for Psychopharmacology. US Department of Health Education and Welfare Publication (ADM). National Institute of Mental Health; Rockville MD: 1976.
34. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatr. 1960;23:56–62. [PMC free article] [PubMed]
35. McLellan AT, Luborsky L, Woody GE. An improved diagnostic instrument for substance abuse patients: The Addiction Severity Index. J Nerv Ment Dis. 1980;168:26–33. [PubMed]
36. McLellan AT, Luborsky L, Cacciola J, et al. New data from the Addiction Severity Index, Reliability and validity in three center. J Nerv Ment Dis. 1985;173:412–23. [PubMed]
37. Cohen S, Marmelstein R, Kamarch T, Hoberman HM. Measuring the functional components of support. In: Sarason R, editor. Social Support: Theory, research and applications. M Nihjoff; Hingham, MA: 1985.
38. Harvey NS. The development and descriptive us of the Lithium Attitudes Questionnaire. J Affective Disorders. 1991;22:211–19. [PubMed]
39. Weiden P, Havens L. Psychotherapeutic management techniques in the treatment of outpatients with schizophrenia. Hospital and Community Psychiatry. 1994;45:549–55. [PubMed]
40. Ghaemi SN, Stoll AL, Pope HG. Lack of insight in bipolar disorder. The acute manic episode. J Nerv Ment Dis. 1995;183:464–67. [PubMed]
41. Cassidy F, McEvoy JP, Yang YK, Wilson WH. Insight is greater in mixed than in pure manic episodes of bipolar I disorder. J Nerv Ment Dis. 2001;189:398–99. [PubMed]
42. Swanson CL, Jr, Freudenreich O, McEvoy JP, Nelson L, Kamaraju L, Wilson WH. Insight in schizophrenia and mania. J Nerv Ment Dis. 1995;183:752–55. [PubMed]
43. Michalakeas A, Skoutas C, Charalambous A, Peristeris A, Marinos V, Keramari E, et al. Insight in schizophrenia and mood disorders and its relation to psychopathology. Acta Psychiatr Scand. 1994;90:46–9. [PubMed]
44. McEvoy JP, Aland J, Wilson WH, Guy W, Hawkins L. Measuring chronic schizophrenic attitudes toward their illness and treatment. Hospital and Community Psychiatry. 1981;12:856–58. [PubMed]
45. Wallston KA, Wallston BS, Devellis R. Development of the multidimensional health locus of control (MHLC) scales. Health Education Monographs. 1978;6:160–70. [PubMed]
46. Begley CE, Annegers JF, Swann AC, Lewis C, Coan S, Schnapp WB, et al. The lifetime cost of bipolar disorder in the US: an estimate for new cases in 1998. Pharmacoeconomics. 2001;19:483–95. [PubMed]
47. Colom F, Vieta E, Tacchi MJ, Sánchez-Moreno J, Scott J. Identifying and improving non-adherence in bipolar disorder. Bipolar Disorders. 2005;7(5 Suppl):24–31. [PubMed]
48. Durrenberger S, Rogers T, Walker R, de Leon J. Economic grand rounds: the high costs of care for four patients with mania who were not compliant with treatment. Psychiatric Services. 1999;50:1539–42. [PubMed]
49. Salloum IM, Thase ME. Impact of substance abuse on the course and treatment of bipolar disorder. Bipolar Disord. 2000;2:269–80. [PubMed]
50. Salloum IM, Cornelius JR, Daley DC, Kirisci L, Spotts CR. Differential pattern of alcohol use profile among bipolar alcoholics. Paper presented at the 10th Annual meeting of the American Academy of Addiction Psychiatry; Nassau, Bahamas. 1999.
51. Weiss RD, Greenfield SF, Najavits LM, Soto JA, Wyner D, Tohen M, et al. Medication compliance among patients with bipolar disorder and substance use disorder. J Clin Psychiatry. 1998;59:172–74. [PubMed]
52. Regier DA, Farmer ME, Rae DS, Locke BZ, Keith SJ, Judd LL, et al. Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study. JAMA. 1990;264:2511–18. [PubMed]
53. Kessler RC, Crum RM, Warner LA, Nelson CB, Schulenberg J, Anthony JC. Lifetime co-occurrence of DSM-III-R alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Arch Gen Psychiatr. 1997;54:313–21. [PubMed]
54. Clark RE, Samnaliev M, McGovern MP. Treatment for co-occurring mental and substance use disorders in five state Medicaid programs. Pyschiatr Serv. 2007;58(7):942–48. [PubMed]
55. Ostacher MJ, Sachs GS. Update on bipolar disorder and substance abuse: recent findings and treatment strategies. J Clin Psychiatry. 2006;67:e10. [PubMed]
56. Becker MH, Maimon LA. Sociobehavioral determinants of compliance with health and medical care recommendations. Med Care. 1975;13:10–24. [PubMed]
57. Valenstein M, Sajatovic M. Late-life bipolar disorder. Hopkins Press; Treatment adherence in older adults with bipolar disorder. In Press.
58. Atreja A, Bellam N, Levy SR. Strategies to enhance patient adherence: Making it simple. Medscape General Medicine. 2005. [3/22/05]. www.medscape.com. [PubMed]
59. Morningstar BA, Sketris IS, Kephart GC, Sclar DA. M Clin Pharm Ther. Vol. 27. Nova Scotia, Canada: 2002. Variation in pharmacy prescription refill adherence by type of oral antihyperglycaemic drug therapy in seniors; pp. 213–20. [PubMed]
60. Eraker SA, Kirscht JP, Becker MH. Understanding and improving patient compliance. Ann Intern Med. 1984;100:258–68. [PubMed]
61. Velligan DI, Bow-Thomas CC, Hunzinger D, Ritch J, Ledbetter N, Prihoda TJ, et al. Randomized controlled trial of the use of compensatory strategies to enhance adaptive functioning in outpatients with schizophrenia. American Journal of Psychiatry. 2000;157:1317–23. [PubMed]
62. Basco MR, Merlock M, McDonald N. Treatment Compliance. In: Johnson SL, Leahy RL, editors. Psychological Treatments of Bipolar Disorder. Guilford Press; NY: 2004. pp. 245–64.
63. Dharmendra MS, Eagles JM. Factors associated with patient's knowledge of attitudes towards treatment with lithium. Journal of Affective Disorders. 2003;75:29–33. [PubMed]
64. Kessing LV, Hansen HV, Bech P. Attitudes and beliefs among patients treated with mood stabilizers. Clin Pract Eidemol Ment Health. 2006;19:8. [PMC free article] [PubMed]
65. Rosa AR, Marco M, Fachel JM, Kapczinski F, Stein AT, Barros HM. Correlation between treatment adherence and lithium treatment attitudes and knowledge by bipolar patients. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31:217–24. [PubMed]
66. Clary C, Dever A, Schweizer E. Psychiatric inpatients' knowledge of medication at hospital discharge. Hosp Community Psychiatry. 1992;43:140–44. [PubMed]
67. Strauss JL, Johnson SL. Role of treatment alliance in the clinical management of bipolar disorder: stronger alliances prospectively predict fewer manic symptoms. Psychiatry Research. 2006;145:215–23. [PMC free article] [PubMed]
68. Colom F, Vieta E, Martinez-Aran A, Reinares M, Goikolea JM, Benabarre A, et al. A randomized trial on the efficacy of group psychoeducation in the prophylaxis of recurrences in bipolar patients whose disease is in remission. Arch General Psychiatry. 2003;60:402–7. [PubMed]
69. Sajatovic M, Valenstein M, Blow FC, Ganoczy D, Ignacio RV. Treatment adherence with antipsychotic medications in bipolar disorder. Bipolar Disorders. 2006;8(3):232–41. 2006. [PubMed]
70. Sajatovic M, Valenstein M, Blow F, Ganozcy D, Ignacio R. Treatment adherence with lithium and anticonvulsant medications among patients with bipolar disorder. Psychiatric Services. 2007;58(6):855–863. [PubMed]
71. Bowskill R, Clatworthy J, Parham R, Rank T, Horne R. Paitent's perceptions of information received about medication prescribed for bipolar disorder: Implications for informed choice. J Affect Disorde. 2007;100:253–7. [PubMed]
72. Makela EH, Griffith RK. Enhancing treatment of bipolar disorder using the patient's belief system. Annals of Pharmacotherapy. 2003;37:543–45. [PubMed]
73. Sajatovic M. Poster Presentation: Psychosocial intervention to enhance treatment attitudes. American Psychiatric Association Annual Meeting; Atlanta, Georgia. 2005.
74. Bauer MS, McBride L, Williford WO, Glick H, Kinosian B, Altshuler L, et al. Cooperative Studies Program 430 Study Team. Collaborative care for bipolar disorder, part I: Intervention and implementation in a randomized effectiveness trial. Psychiatric Services. 2006;57:927–36. [PubMed]
75. Bauer MS, McBride L, Williford WO, Glick H, Kinosian B, Altshuler L, et al. Cooperative Studies Program 430 Study Team. Collaborative care for bipolar disorder, part II: Impact on clinical outcome, function and costs. Psychiatric Services. 2006a;57:937–45. [PubMed]
76. Miklowitz DJ, George EL, Richards JA, Simoneau TL, Suddath RL. A randomized study of family-focused psychoeducation and pharmacotherapy in the outpatient management of bipolar disorder. Arch Gen Psychiatry. 2003;60:904–12. [PubMed]