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International Journal of Mental Health Nursing (2014) 23, 490–497
doi: 10.1111/inm.12089
Feature Article
Does adherence therapy improve medication adherence among patients with schizophrenia? A systematic review Anna Hegedüs1,2 and Bernd Kozel1,2 1
Nursing & Social Education Research Unit, University of Bern Psychiatric Services, Bern, Switzerland and International Graduate Academy (InGrA), ‘Participation as Goal of Nursing and Therapy’, Institute of Health and Nursing Sciences, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
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ABSTRACT: Non-adherence to medication is highly prevalent in patients with schizophrenia. Adherence therapy aims to improve medication adherence of these patients by applying techniques of cognitive behavioural therapy, psycho-education, and motivational interviewing. Even though adherence therapy is frequently discussed and researched, its effectiveness is still uncertain. This paper aims to review the effectiveness of adherence therapy on the medication adherence of patients with schizophrenia. To this end, six electronic databases were systematically searched for randomized, controlled trials on adherence therapy from January 2002 to March 2013. Four trials met the inclusion criteria and were incorporated into the review. The findings suggest that adherence therapy does not improve patients’ medication adherence in comparison to treatment as usual or a control intervention. However, all the studies reviewed showed high-adherence ratings at baseline. Thus, further welldesigned studies that target adherence therapy to patients who are non-adherent to their medication are needed for a more profound understanding of its effectiveness. In addition, if adherence therapy is aimed not only at improving medication adherence, but also to reach an agreement whereby the patient’s decision not to take his medication is accepted, the shared decision-making process needs to be assessed as well. KEY WORDS: adherence, adherence therapy, antipsychotic agent, medication adherence, schizophrenia.
INTRODUCTION Non-adherence to medication presents a major concern in the management of long-term diseases, such as schizophrenia. Various studies have found that up to 72% of all schizophrenic patients discontinue their prescribed medication after discharge (Conti et al. 2012; Haro et al. 2009; Kilzieh et al. 2008). Non-adherence to prescribed
Correspondence: Anna Hegedüs, University of Bern Psychiatric Services, Bolligenstrasse 111, CH-3000 Bern 60, Switzerland. Email: [email protected] Anna Hegedüs, Mag. Bernd Kozel, MScN, RN. Accepted June 2014.
© 2014 Australian College of Mental Health Nurses Inc.
medication can result in an increased risk of relapse, hospitalization, and attempted suicide, as well as lower quality of life and higher levels of alcohol and cannabis use (Coldham et al. 2002; Novick et al. 2010). To improve adherence to antipsychotic medication, various interventions have been designed, tested, and reviewed. Zygmunt et al. (2002) reported that 26% of the randomized, controlled trials (RCT) they reviewed and 44% of non-randomized trials had a significant effect on medication adherence. While psycho-educational interventions alone showed little effect on medication adherence, interventions that additionally incorporated behavioural aspects of medication intake and motivational approaches seemed to be more effective (Zygmunt et al.
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2002). Nevertheless, the National Institute of Health and Clinical Excellence (NICE 2010) stated in a guideline that the evidence for improving patients’ attitudes towards medication is limited and inconsistent. Similarly, no effects were found on symptoms, quality of life, relapse, or rehospitalization (NICE 2010). What has been generally agreed upon, however, is that interventions with a greater number of sessions, longer duration, or family involvement tend to result in greater improvements in medication adherence (Barkhof et al. 2012; Nosé et al. 2003; Puschner et al. 2005). Compliance therapy (CT) (Kemp et al. 1996; 1998) and its advancement, adherence therapy (AT) (Gray et al. 2006), are frequently cited interventions in the context of medication adherence in patients with schizophrenia. CT was probably one of the first interventions to improve adherence in psychiatric patients that underlined the importance of treatment alliance and patient participation (Kemp et al. 1996; 1998). It uses techniques of motivational interviewing and cognitive behavioural therapy, and consists of four-to-six sessions lasting 20–60 min. In three phases, patients’ experiences and concerns with treatment are discussed, and strategies are developed to avoid relapse (Kemp et al. 1998). In an RCT addressing patients with psychosis and mood disorder, CT significantly improved adherence to medication, attitudes to treatment, and insight, but failed to improve symptoms and functioning, as compared to non-specific counselling (Kemp et al. 1998). In a similar RCT, including exclusively patients with schizophrenia, CT showed no significant advantage in any of the outcomes (O’Donnell et al. 2003). AT, an advancement of CT, primarily aims to achieve joint decisions about medication between nurse and patient (Gray et al. 2006). It is normally delivered over a series of eight sessions, each lasting up to 50 min (Gray et al. 2010).The key elements of the therapy are engagement, assessment, a medication timeline, exploring ambivalences, discussing beliefs and concerns about medication, and the use of medication in the future (Gray et al. 2006; 2010; Maneesakorn et al. 2007). Shared decision-making, as a central value of AT, helps to bridge the empirical evidence base with the personal concerns, values, and life context of the individual, and supports his recovery process (Deegan & Drake 2006). That is, if patients make decisions under the guidance of a health professional, they are more likely to adhere to these choices, as they become personal and meaningful (Gray et al. 2010). In the past decade, AT has been the focus of discussions (Winterberg 2013; Zuaboni & Schulz 2012) and © 2014 Australian College of Mental Health Nurses Inc.
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research (Anderson et al. 2010; Gray et al. 2006; 2010; Maneesakorn et al. 2007; Schulz et al. 2013). However, while the effectiveness of CT (McIntosh et al. 2006) and similar interventions aimed at improving adherence to antipsychotic medication (Barkhof et al. 2012; Zygmunt et al. 2002) have been summarized in systematic reviews, the effects of AT are still uncertain. To examine whether AT improves the medication adherence of patients with schizophrenia, we reviewed RCT that assessed the effectiveness of AT against treatment as usual (TAU) or a control intervention in adults with schizophrenia. We explicitly focused on AT, as discussed by Gray et al. (2006), in order to draw distinct conclusions on its effectiveness. Even though CT and AT seem to be broadly similar interventions, we explicitly excluded CT from our review, as differences in the durations of the interventions could influence their effectiveness (Barkhof et al. 2012). The results of this review will allow mental health practitioners and policy makers to make evidence-based decisions for or against the implementation of AT. Additionally, this review provides a starting point for further research on AT.
MATERIALS AND METHODS Inclusion criteria Studies were included if they met the following inclusion criteria: (i) RCT; (ii) AT by Gray; (iii) measurement of medication adherence; (iv) patients with an International Classification of Diseases-10 F2 diagnosis of schizophrenia, schizotypal and delusional disorder (World Health Organization 1994), or an equivalent Diagnostic and Statistical Manual of Mental Disorders-III or -IV diagnosis; and (v) published in English or German between 2002 and 2013. Papers were excluded if they reported on training programmes for nurses or included patients with somatic comorbidities, or if the full-text was not available after contacting the authors.
Search method To identify all articles eligible for inclusion, we systematically searched PUBMED, CINAHL, PsycINFO, PSYNDEX, EMBASE, and the Cochrane Central Register of Controlled Trials using combinations of the following medical subject headings (MeSH) or keywords: schizophrenia or psychotic disorder, compliance or adherence or concordance, medication or drug therapy, therapy or intervention, and random. Additionally, we searched Google Scholar, reference lists of relevant papers, and international trial registers for published,
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unpublished, or ongoing studies. In accordance with the date of Gray’s first publication on medication adherence in 2002 (Gray et al. 2002), the time period covered was from 1 January 2002 to 28 March 2013. After removing duplicates, we screened the identified records. Full-text articles were retrieved if the title and abstract of the studies indicated that the intervention focused on medication adherence in patients with schizophrenia. Subsequently, the selected full-text papers were assessed against the inclusion criteria by each reviewer independently.
Data extraction and assessment of risk of bias Of each study included, the following information was extracted: participants (age, sex, setting, country), control groups, duration of the study, outcomes (primary, secondary), and mean scores of medication adherence measures. One review author analysed the included studies for the respective data, which were then verified by the second author. After screening the results, it became evident that the few studies we identified applied a variety of assessment tools for medication adherence. Thus, we calculated standardized mean differences (SMD) (Hedges’s g) and 95% confidence intervals for all medication adherence measures using Review Manager (RevMan; version 5.2, The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen). The SMD converts the results to a uniform scale and allows for a better comparability of the effects. We interpreted the SMD using the following rule of thumb: 0.2 represents a small effect, 0.5 a moderate effect, and 0.8 a large effect (Schünemann et al. 2011). Medication adherence was treated as the principle outcome, as AT primarily aims to improve medication adherence and not symptom management or quality of life. For the sake of completeness, we reviewed other outcomes as well, albeit without calculating the SMD. To assess the risk of bias in the individual studies, we used the quality checklist for RCT, as proposed by Behrens and Langer (2010). The checklist consists of all common markers of validity mentioned in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (Liberati et al. 2009). Each author assessed the items independently before rating the overall risk of bias on a scale from one (very low risk of bias) to six (very high risk of bias). Disagreements with ratings were resolved through discussion. An assessment of a high risk of bias did not result in the exclusion of eligible studies, however, as this review aims to present a complete picture of study outcomes in this field.
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RESULTS Study selection The study selection process is presented in Figure 1. After screening 825 records for eligibility, 14 papers were selected for thorough assessment. A further two potentially-eligible papers were excluded, as the respective authors could not be contacted, namely a conference abstract (von Bormann 2009) and a second RCT that was published by Maneesakorn as part of her PhD thesis. Of the 14 full-texts selected, we ultimately included four RCTs in our review (Fig. 1). The search for ongoing RCT in trial registers resulted in one RCT that is currently being conducted in Hong Kong (clinicaltrials.gov identifier NCT01780116). Its completion is expected in April 2015.
Study characteristics The four RCT included in the review were published between 2006 and 2013. The study characteristics are shown in Table 1. On average, participants received seven sessions (Gray et al. 2006; Schulz et al. 2013), each lasting from 36 min (Gray et al. 2006) to 43 min (Maneesakorn et al. 2007; Schulz et al. 2013). Anderson et al. (2010) did not report attendance rates of AT. Participants in the control groups received either TAU or didactic health education. TAU consisted of day treatment, case management, employment placement, medication monitoring, and individual counselling (Anderson et al. 2010). It further included the administration of medication, occupational therapy, group counselling, and recreational therapy (Maneesakorn et al. 2007), or alternatively involved medication, psychotherapy, occupational therapy, and psycho-educational programmes (Schulz et al. 2013). In didactic health education, health education-related topics (e.g. diet) were presented in a didactic way in eight weekly sessions (Gray et al. 2006).
Risk of bias According to the results of our assessment of the risk of bias, Gray et al.’s (2006) RCT had a very low (1) risk of bias, and those of Schulz et al. (2013) and Maneesakorn et al. (2007) had a low (2) risk of bias. Anderson et al.’s (2010) study was rated as having a moderate risk of bias (3). Potential sources for the risk of bias were small sample sizes, increasing the possibility of a false-negative error (Anderson et al. 2010; Maneesakorn et al. 2007), raters not blind to the treatment condition (Anderson et al. 2010), and high drop-out rates (>20%) (Schulz et al. 2013). © 2014 Australian College of Mental Health Nurses Inc.
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Records identified through database search (n = 984)
Additional records identified through other sources (n = 2)
Records after duplicates removed (n = 825)
Records screened (title and abstract) (n = 825)
Full-text articles assessed for eligibility (n = 14)
Studies included in quality assessment (n = 4)
Records excluded according to eligibility criteria (n = 809) + no fulltext available (n = 2)
Full-text articles excluded (n = 10), reasons: review/meta-analysis (n = 5), commentary (n = 1), guideline (n = 1), intervention not adherence therapy (n = 2), missing comparative data (n = 1)
Studies included in data synthesis (n = 4)
FIG. 1:
Study selection process.
TABLE 1: Characteristics of the included studies Gray et al. 2006 Participants Mean age (years) Males (%) Setting Country Control group Follow up Primary outcome Secondary outcomes
41.5 60 Inpatient and community The Netherlands, Germany, Great Britain, Italy Didactic health education 1 year Quality of life Adherence Symptoms
Maneesakorn et al. 2007
Anderson et al. 2010
Schulz et al. 2013
40.8 72 Inpatient and community Thailand
29.0 79 Community USA
35.5 58 Inpatient Germany, Switzerland
TAU 9 weeks Symptoms Adherence Satisfaction with antipsychotic medication Functioning Side-effects
TAU Post-intervention Symptoms Adherence Satisfaction and experience with AT intervention
TAU 12 weeks Symptoms Adherence Attitude towards medication Functioning
AT, adherence therapy; TAU, treatment as usual.
Study outcomes Across all studies, medication adherence was assessed by seven different assessment tools, including self-ratings, keyworker ratings, and blood plasma level (Table 2). In © 2014 Australian College of Mental Health Nurses Inc.
Maneesakorn et al.’s (2007) study, AT was found to improve patients’ medication adherence significantly, as compared to TAU. In other studies, no significant difference between the intervention and control groups was
Anderson et al. 2010 Schulz et al. 2013
Maneesakorn et al. 2007
†Keyworker rating; ‡self-report; §blood plasma level; ¶not calculated due to missing data. CDR, concentration-to-dose ratio; CI, confidence interval; DAI-30, Hogan Drug Attitude Inventory; MAQ, Medication Adherence Questionnaire; MARS, Medication Adherence Rating Scale; NS, not significant (>0.05); PETiT, Personal Evaluation of Transitions in Treatment; SAI-C, keyworker rating of adherence on Schedule for the Assessment of Insight; SD, standard deviation; SMD, standardized mean differences; SWAM, Satisfaction with Antipsychotic Medication scale.
NS NS 0.001 0.019 NS NS NS NS 5.03 (1.55) 3.33 (1.02) 13.5 113.19 41.6 6.36 (10.56) 22.83 (5.89) 7.65 (1.87) 189 194 14 14 13 39 46 46 5.22 (1.57) 3.2 (1.07) 21.63 126.5 37.3 3.34 (5.36) 22.7 (6.59) 7.75 (2.01) 5.04 (1.39) 2.98 (1.24) 19.19 (95% CI: 15.48, 22.90) 116.81 (95% CI: 102.51, 131.11) 40.1 (9.24) 3.83 (6.8) 22.46 (6.83) 7.55 (2.07) 173 172 14 14 10 54 69 69 SAI-C† MAQ‡ DAI-30‡ SWAM‡ PETiT‡ CDR§ DAI-30‡ MARS‡ Gray et al. 2006
n
4.73 (1.63) 2.97 (1.20) 15.38 (95% CI: 10.14, 20.61) 115.13 (95% CI: 104.04, 126.21) 40.1 (10.29) 4.19 (5.79) 22.7 (6.69) 7.46 (1.73)
P-value Follow-up Mean (SD) n
Control group
Baseline Mean (SD) Follow up Mean (SD)
Intervention group
Baseline Mean (SD) Adherence measures
TABLE 2: Study outcomes: Comparison of baseline and follow-up scores of medication adherence (higher ratings indicate better adherence)
0.12 (−0.08, 0.33) −0.12 (−0.33, 0.08) ¶ ¶ ¶ −0.38 (−0.79, 0.04) −0.02 (−0.39, 0.35) 0.03 (−0.35, 0.40)
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SMD (95% CI)
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found in terms of medication adherence. Likewise, the SMD indicate a low and partially-negative effect of AT on medication adherence (Table 2). However, AT was found to significantly improve psychiatric symptoms in two RCT (Maneesakorn et al. 2007; Schulz et al. 2013), and satisfaction with antipsychotic medication in Maneesakorn et al.’s (2007) study. There were no differences between the intervention and control groups regarding global functioning (Maneesakorn et al. 2007; Schulz et al. 2013), side-effects (Maneesakorn et al. 2007), and quality of life (Gray et al. 2006).
DISCUSSION Our search resulted in four RCT, only one of which showed a significant improvement of medication adherence in the AT, as compared to the control group. Even though we could only calculate the SMD for two studies, the results indicate low effect sizes. These results suggest that AT is no more beneficial in improving medication adherence than TAU, or than a didactic health-education programme. However, while AT did not influence global functioning, side-effects, and the quality of life of the patients, it had the potential to improve their symptoms. In order to draw appropriate conclusions regarding the effectiveness of AT, several weaknesses of the trials need to be discussed first. First, the participants in all of the studies had high rates of medication adherence at baseline. Thus, the leeway for further enhancement was limited, and the possibility of detecting significant improvements was reduced. According to crisis theory, patients have the highest potential for change immediately after a crisis (Brandon 1970). Therefore, AT is most suitable for patients shortly after a crisis. Although Schulz et al. (2013) included such patients, they could not avoid recruiting relatively adherent participants. One explanation might be that individuals recruited in trials are required to undergo consenting procedures, and therefore, are likely to be more adherent (Kane et al. 2013). Additionally, patients with schizophrenia and substance abuse or dependency who are at high risk of nonadherence (Jonsdottir et al. 2013) were excluded from all RCT on AT. Researchers need to consider including these patient groups or applying a different research design to avoid a selection bias due to patient consent. For example, Brown et al. (2013) tested the effectiveness and practicability of AT in a mirror-image study that allowed them to analyse routinely-collected data, and thus include non-adherent patients. They trained all mental health workers of an early psychosis service in AT, and routinely assessed data in the year before and after training. The © 2014 Australian College of Mental Health Nurses Inc.
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application of AT resulted in a significantly lower number of relapse rates, while not affecting the number of inpatient admission, days as an inpatient, and referral to a crisis team in the year after training (Brown et al. 2013). However, these results could have been influenced by the fact that nurses tended to use elements of AT in their day-to-day consultations, rather than offering formal sessions (Brown et al. 2013). Nevertheless, through collecting routinely-assessed data and training an entire team, the authors avoided biasing selections and managed to access a representative sample. Future research on AT needs to consider similar study designs as alternatives to RCT. Second, a comparison of the studies’ effects is limited by the fact that the duration of follow-up varied between the RCT and that the assessment tools used in the trials showed some weaknesses. Several authors pointed out that there is little agreement between the different measurements of adherence, such as pill count, electronic monitoring, blood plasma level, and subjective measures (patient or physician ratings) when it comes to labelling patients as non-adherent and in predicting relapse, hospital admission, or psychotic symptoms (Kikkert et al. 2008; 2011; Velligan et al. 2007). The reasons for this might be because different methods of measurement explore different components of medication adherence (Lehmann et al. 2014) or that particularly subjective instruments do not measure the same concepts of adherence (Kikkert et al. 2008). This is hardly surprising, as the conceptual definition of the terms ‘compliance’, ‘adherence’, and ‘concordance’ vary and partly overlap, resulting in methodological weaknesses (Bissonnette 2008; Snowden et al. 2014; Vrijens et al. 2012). According to the original definitions, ‘compliance’ is the extent to which a person’s behaviour coincides with medical or health advice (Vrijens et al. 2012), while ‘adherence’ emphasizes the therapeutic alliance established between the patient and the professional and their agreed decision-making (Horne 2006). ‘Concordance’ highlights the agreement reached after negotiation between the patient and healthcare professional. Thus, a consultation is concordant if the views of the patient and the nurse are equally considered in the agreement, whereas the final decision as to whether to take the medication or not lies with the patient (Britten & Weiss 2004; Cushing & Metcalfe 2007). In fact, none of the RCT analysed in this paper stated which concept they adopted, that is, compliance, adherence, or concordance. Nevertheless, as their outcome measurements predominantly assessed the medication intake of patients, they seem to be based on the definition of medication ‘compliance’. However, as the shared © 2014 Australian College of Mental Health Nurses Inc.
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decision-making process guided the conversation between nurse and patient, and all of the key elements of AT seem to support a concordant consultation, nurses could have achieved a concordant agreement by means of AT (Jones & Grey 2008; Zuaboni & Schulz 2012). If so, AT would be successful if the patient weighed up the advantages and disadvantages, and elaborately developed an attitude towards his medication, regardless of his/her decision to take medication or not. In this case, a measurement of ‘compliance’ to medication would distort the effect of the intervention, as the patients’ ‘noncompliance’ is considered as abortive despite the overall positive outcome. To avoid confusions and misunderstandings due to the inconsistent use of these terms, researchers need to state which definition (compliance, adherence, or concordance) their investigation of AT is based on and adjust their study design accordingly. Where AT aims to achieve a concordant agreement, the shared decision-making process needs to be assessed as a complement to medication ‘compliance’ and other clinically-meaningful outcomes. This could, for example, be done with a mixed-methods study that assesses the extent of a concordant agreement with qualitative methods and combines those with quantitative outcome measures. Additionally, to enable direct comparisons of the study effects between the studies, future research needs to use standard follow-up durations.
Strengths and limitations Our search for literature was conducted in six different databases. Consequently, it could be considered to include most of the relevant studies in the field. Furthermore, we minimized bias in the selection process through independent full-text reviews. For the assessment of the risk of bias, we used a standardized assessment tool that was also rated independently. Because we included only studies on AT, our results provide a complete picture of the effectiveness and problems specific to this type of therapy. The calculation of all SMD would have allowed us to compare the effects irrespective of the assessment instruments. Unfortunately, two RCT did not provide standard deviations, so we could not calculate their SMD. Thus, the comparability between the studies is still incomplete, which in turn limits the significance of our results. Another limitation is that we only included studies written in English and German. There might be relevant studies in other languages that we did not review due to language barriers. Finally, we did not consider two studies that were probably eligible for inclusion, as the respective full-text articles could not be made available.
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Implications According to the reviewed RCT, AT had no positive effect on the medication adherence of patients with schizophrenia who were moderately adherent or had positive attitudes towards their medication at baseline. However, the intervention showed slight improvements in the patients’ symptoms. In conclusion, the evidence presented in this review is not yet sufficient to draw any other conclusions on the effectiveness of AT. Thus, we suggest the following recommendations for future research on AT. First, future trials must recruit non-adherent participants or those at high risk of non-adherence, such as patients with substance dependencies. Non-adherence has to be either made an explicit inclusion criterion in RCT, or other study designs must be applied, such as mirror-image studies. Second, authors need to state whether they apply the definition of compliance, adherence, or concordance, and thus specify the aims envisaged when applying AT. If AT is aimed at improving medication ‘compliance’, we recommend recruiting ‘non-compliant’ participants and assessing ‘compliance’ through different measures (e.g. electronic monitoring, self-report, and blood plasma level) in order to obtain reliable results. In contrast, if AT is aimed at achieving adherence or concordance, the process leading to the patient’s decision as to whether to take the medication or not needs to be assessed as a secondary outcome.
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A. HEGEDÜS AND B. KOZEL Brown, E., Gray, R., Jones, M. & Whitfield, S. (2013). Effectiveness of adherence therapy in patients with early psychosis: A mirror image study. International Journal of Mental Health Nursing, 22, 24–34. Coldham, E. L., Addington, J. & Addington, D. (2002). Medication adherence of individuals with a first episode of psychosis. Acta Psychiatrica Scandinavica, 106, 286–290. Conti, V., Lora, A., Cipriani, A., Fortino, I., Merlino, L. & Barbui, C. (2012). Persistence with pharmacological treatment in the specialist mental healthcare of patients with severe mental disorders. European Journal of Clinical Pharmacology, 68, 1647–1655. Cushing, A. & Metcalfe, R. (2007). Optimizing medicines management: From compliance to concordance. Journal of Therapeutics and Clinical Risk Management, 3, 1047–1058. Deegan, P. E. & Drake, R. E. (2006). Shared decision making and medication management in the recovery process. Psychiatric Services, 57, 1636–1639. Gray, R., Wykes, T. & Gournay, K. (2002). From compliance to concordance: A review of the literature on interventions to enhance compliance with antipsychotic medication. Journal of Psychiatric and Mental Health Nursing, 9, 277–284. Gray, R., Leese, M., Bindman, J. et al. (2006). Adherence therapy for people with schizophrenia. European multicentre randomised controlled trial. British Journal of Psychiatry, 189, 508–514. Gray, R., White, J., Schulz, M. & Abderhalden, C. (2010). Enhancing medication adherence in people with schizophrenia: An international programme of research. International Journal of Mental Health Nursing, 19, 36–44. Haro, J. M., Novick, D., Suarez, D. & Roca, M. (2009). Antipsychotic treatment discontinuation in previously untreated patients with schizophrenia: 36-month results from the SOHO study. Journal of Psychiatric Research, 43, 265–273. Horne, R. (2006). Compliance, adherence, and concordance: Implications for asthma treatment. Chest, 130, 65S–72S. Jones, M. & Grey, R. (2008). Time to wake up and smell the coffee: Antipsychotic medication and schizophrenia. Journal of Psychiatric and Mental Health Nursing, 15, 344–348. Jonsdottir, H., Opjordsmoen, S., Birkenaes, A. B. et al. (2013). Predictors of medication adherence in patients with schizophrenia and bipolar disorder. Acta Psychiatrica Scandinavica, 127, 23–33. Kane, J. M., Kishimoto, T. & Correll, C. U. (2013). Nonadherence to medication in patients with psychotic disorders: Epidemiology, contributing factors and management strategies. World Psychiatry, 12, 216–226. Kemp, R., Hayward, P., Applewhaite, G., Everitt, B. & David, A. (1996). Compliance therapy in psychotic patients: Randomised controlled trial. BMJ (Clinical Research Ed.), 312, 345–349. Kemp, R., Kirov, G., Everitt, B., Hayward, P. & David, A. (1998). Randomised controlled trial of compliance therapy. 18-month follow-up. British Journal of Psychiatry, 172, 413– 419. © 2014 Australian College of Mental Health Nurses Inc.
EFFECTIVENESS OF ADHERENCE THERAPY Kikkert, M. J., Barbui, C., Koeter, M. W. et al. (2008). Assessment of medication adherence in patients with schizophrenia: The Achilles heel of adherence research. Journal of Nervous and Mental Disease, 196, 274–281. Kikkert, M. J., Koeter, M. W., Dekker, J. J. et al. (2011). The predictive validity of subjective adherence measures in patients with schizophrenia. International Journal of Methods in Psychiatric Research, 20, 73–81. Kilzieh, N., Todd-Stenberg, J. A., Kennedy, A., Wood, A. E. & Tapp, A. M. (2008). Time to discontinuation and selfdiscontinuation of olanzapine and risperidone in patients with schizophrenia in a naturalistic outpatient setting. Journal of Clinical Psychopharmacology, 28, 74–77. Lehmann, A., Aslani, P., Ahmed, R. et al. (2014). Assessing medication adherence: Options to consider. International Journal of Clinical Pharmacy, 36, 55–69. Liberati, A., Altman, D. G., Tetzlaff, J. et al. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Plos Medicine, 6, e1000100. McIntosh, A. M., Conlon, L., Lawrie, S. M. & Stanfield, A. C. (2006). Compliance therapy for schizophrenia. Cochrane Database of Systematic Reviews, (3), art no.: CD003442. Maneesakorn, S., Robson, D., Gournay, K. & Gray, R. (2007). An RCT of adherence therapy for people with schizophrenia in Chiang Mai, Thailand. Journal of Clinical Nursing, 16, 1302–1312. NICE (2010). Core Interventions in the Treatment and Management of Schizophrenia in Adults in Primary and Secondary Care (Updated Edition). CG82. London: National Institute for Health and Clinical Excellence. Nosé, M., Barbui, C., Gray, R. & Tansella, M. (2003). Clinical interventions for treatment non-adherence in psychosis: Meta-analysis. British Journal of Psychiatry, 183, 197– 206. Novick, D., Haro, J. M., Suarez, D., Perez, V., Dittmann, R. W. & Haddad, P. M. (2010). Predictors and clinical consequences of non-adherence with antipsychotic medication in the outpatient treatment of schizophrenia. Psychiatry Research, 176, 109–113.
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497 O’Donnell, C., Donohoe, G., Sharkey, L. et al. (2003). Compliance therapy: A randomised controlled trial in schizophrenia. BMJ (Clinical Research Ed.), 327, 834. Puschner, B., Born, A., Giessler, A., Helm, H., Becker, T. & Angermeyer, M. C. (2005). [Effects of interventions to improve compliance with antipsychotic medication in people suffering from schizophrenia-results of recent reviews]. Psychiatrische Praxis, 32, 62–67. Schulz, M., Gray, R., Spiekermann, A., Abderhalden, C., Behrens, J. & Driessen, M. (2013). Adherence therapy following an acute episode of schizophrenia: A multi-centre randomised controlled trial. Schizophrenia Research, 146, 59–63. Schünemann, H., Oxman, A., Vist, G. et al. (2011). Chapter 12: Interpreting results and drawing conclusions. In: J. Higgins & S. Green (Eds). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. [Cited 18 August 2014]. Available from URL: www.cochrane-handbook.org Snowden, A., Martin, C., Mathers, B. & Donnell, A. (2014). Concordance: A concept analysis. Journal of Advanced Nursing, 70, 46–59. Velligan, D. I., Wang, M., Diamond, P. et al. (2007). Relationships among subjective and objective measures of adherence to oral antipsychotic medications. Psychiatric Services, 58, 1187–1192. Vrijens, B., De Geest, S., Hughes, D. A. et al. (2012). A new taxonomy for describing and defining adherence to medications. British Journal of Clinical Pharmacology, 73, 691–705. Winterberg, W. (2013). Wirksame Intervention oder nur besonders geschicktes Überreden? Medikamenten-AdherenceTherapie im Kontext der forensischen Psychiatrie. Psych Pflege, 19, 269–274. World Health Organization (1994). Pocket Book to ICD-10 Classification of Mental and Behavioral Disorders. Geneva: Churchill Livingstone. Zuaboni, G. & Schulz, M. (2012). [Adherence therapy. Making room for concerns and worries]. Krankenpflege. Soins Infirmiers, 105, 18–20. Zygmunt, A., Olfson, M., Boyer, C. A. & Mechanic, D. (2002). Interventions to improve medication adherence in schizophrenia. American Journal of Psychiatry, 159, 1653–1664.
International Journal of Mental Health Nursing (2014) 23, 490–497
doi: 10.1111/inm.12089
Feature Article
Does adherence therapy improve medication adherence among patients with schizophrenia? A systematic review Anna Hegedüs1,2 and Bernd Kozel1,2 1
Nursing & Social Education Research Unit, University of Bern Psychiatric Services, Bern, Switzerland and International Graduate Academy (InGrA), ‘Participation as Goal of Nursing and Therapy’, Institute of Health and Nursing Sciences, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
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ABSTRACT: Non-adherence to medication is highly prevalent in patients with schizophrenia. Adherence therapy aims to improve medication adherence of these patients by applying techniques of cognitive behavioural therapy, psycho-education, and motivational interviewing. Even though adherence therapy is frequently discussed and researched, its effectiveness is still uncertain. This paper aims to review the effectiveness of adherence therapy on the medication adherence of patients with schizophrenia. To this end, six electronic databases were systematically searched for randomized, controlled trials on adherence therapy from January 2002 to March 2013. Four trials met the inclusion criteria and were incorporated into the review. The findings suggest that adherence therapy does not improve patients’ medication adherence in comparison to treatment as usual or a control intervention. However, all the studies reviewed showed high-adherence ratings at baseline. Thus, further welldesigned studies that target adherence therapy to patients who are non-adherent to their medication are needed for a more profound understanding of its effectiveness. In addition, if adherence therapy is aimed not only at improving medication adherence, but also to reach an agreement whereby the patient’s decision not to take his medication is accepted, the shared decision-making process needs to be assessed as well. KEY WORDS: adherence, adherence therapy, antipsychotic agent, medication adherence, schizophrenia.
INTRODUCTION Non-adherence to medication presents a major concern in the management of long-term diseases, such as schizophrenia. Various studies have found that up to 72% of all schizophrenic patients discontinue their prescribed medication after discharge (Conti et al. 2012; Haro et al. 2009; Kilzieh et al. 2008). Non-adherence to prescribed
Correspondence: Anna Hegedüs, University of Bern Psychiatric Services, Bolligenstrasse 111, CH-3000 Bern 60, Switzerland. Email: [email protected] Anna Hegedüs, Mag. Bernd Kozel, MScN, RN. Accepted June 2014.
© 2014 Australian College of Mental Health Nurses Inc.
medication can result in an increased risk of relapse, hospitalization, and attempted suicide, as well as lower quality of life and higher levels of alcohol and cannabis use (Coldham et al. 2002; Novick et al. 2010). To improve adherence to antipsychotic medication, various interventions have been designed, tested, and reviewed. Zygmunt et al. (2002) reported that 26% of the randomized, controlled trials (RCT) they reviewed and 44% of non-randomized trials had a significant effect on medication adherence. While psycho-educational interventions alone showed little effect on medication adherence, interventions that additionally incorporated behavioural aspects of medication intake and motivational approaches seemed to be more effective (Zygmunt et al.
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2002). Nevertheless, the National Institute of Health and Clinical Excellence (NICE 2010) stated in a guideline that the evidence for improving patients’ attitudes towards medication is limited and inconsistent. Similarly, no effects were found on symptoms, quality of life, relapse, or rehospitalization (NICE 2010). What has been generally agreed upon, however, is that interventions with a greater number of sessions, longer duration, or family involvement tend to result in greater improvements in medication adherence (Barkhof et al. 2012; Nosé et al. 2003; Puschner et al. 2005). Compliance therapy (CT) (Kemp et al. 1996; 1998) and its advancement, adherence therapy (AT) (Gray et al. 2006), are frequently cited interventions in the context of medication adherence in patients with schizophrenia. CT was probably one of the first interventions to improve adherence in psychiatric patients that underlined the importance of treatment alliance and patient participation (Kemp et al. 1996; 1998). It uses techniques of motivational interviewing and cognitive behavioural therapy, and consists of four-to-six sessions lasting 20–60 min. In three phases, patients’ experiences and concerns with treatment are discussed, and strategies are developed to avoid relapse (Kemp et al. 1998). In an RCT addressing patients with psychosis and mood disorder, CT significantly improved adherence to medication, attitudes to treatment, and insight, but failed to improve symptoms and functioning, as compared to non-specific counselling (Kemp et al. 1998). In a similar RCT, including exclusively patients with schizophrenia, CT showed no significant advantage in any of the outcomes (O’Donnell et al. 2003). AT, an advancement of CT, primarily aims to achieve joint decisions about medication between nurse and patient (Gray et al. 2006). It is normally delivered over a series of eight sessions, each lasting up to 50 min (Gray et al. 2010).The key elements of the therapy are engagement, assessment, a medication timeline, exploring ambivalences, discussing beliefs and concerns about medication, and the use of medication in the future (Gray et al. 2006; 2010; Maneesakorn et al. 2007). Shared decision-making, as a central value of AT, helps to bridge the empirical evidence base with the personal concerns, values, and life context of the individual, and supports his recovery process (Deegan & Drake 2006). That is, if patients make decisions under the guidance of a health professional, they are more likely to adhere to these choices, as they become personal and meaningful (Gray et al. 2010). In the past decade, AT has been the focus of discussions (Winterberg 2013; Zuaboni & Schulz 2012) and © 2014 Australian College of Mental Health Nurses Inc.
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research (Anderson et al. 2010; Gray et al. 2006; 2010; Maneesakorn et al. 2007; Schulz et al. 2013). However, while the effectiveness of CT (McIntosh et al. 2006) and similar interventions aimed at improving adherence to antipsychotic medication (Barkhof et al. 2012; Zygmunt et al. 2002) have been summarized in systematic reviews, the effects of AT are still uncertain. To examine whether AT improves the medication adherence of patients with schizophrenia, we reviewed RCT that assessed the effectiveness of AT against treatment as usual (TAU) or a control intervention in adults with schizophrenia. We explicitly focused on AT, as discussed by Gray et al. (2006), in order to draw distinct conclusions on its effectiveness. Even though CT and AT seem to be broadly similar interventions, we explicitly excluded CT from our review, as differences in the durations of the interventions could influence their effectiveness (Barkhof et al. 2012). The results of this review will allow mental health practitioners and policy makers to make evidence-based decisions for or against the implementation of AT. Additionally, this review provides a starting point for further research on AT.
MATERIALS AND METHODS Inclusion criteria Studies were included if they met the following inclusion criteria: (i) RCT; (ii) AT by Gray; (iii) measurement of medication adherence; (iv) patients with an International Classification of Diseases-10 F2 diagnosis of schizophrenia, schizotypal and delusional disorder (World Health Organization 1994), or an equivalent Diagnostic and Statistical Manual of Mental Disorders-III or -IV diagnosis; and (v) published in English or German between 2002 and 2013. Papers were excluded if they reported on training programmes for nurses or included patients with somatic comorbidities, or if the full-text was not available after contacting the authors.
Search method To identify all articles eligible for inclusion, we systematically searched PUBMED, CINAHL, PsycINFO, PSYNDEX, EMBASE, and the Cochrane Central Register of Controlled Trials using combinations of the following medical subject headings (MeSH) or keywords: schizophrenia or psychotic disorder, compliance or adherence or concordance, medication or drug therapy, therapy or intervention, and random. Additionally, we searched Google Scholar, reference lists of relevant papers, and international trial registers for published,
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unpublished, or ongoing studies. In accordance with the date of Gray’s first publication on medication adherence in 2002 (Gray et al. 2002), the time period covered was from 1 January 2002 to 28 March 2013. After removing duplicates, we screened the identified records. Full-text articles were retrieved if the title and abstract of the studies indicated that the intervention focused on medication adherence in patients with schizophrenia. Subsequently, the selected full-text papers were assessed against the inclusion criteria by each reviewer independently.
Data extraction and assessment of risk of bias Of each study included, the following information was extracted: participants (age, sex, setting, country), control groups, duration of the study, outcomes (primary, secondary), and mean scores of medication adherence measures. One review author analysed the included studies for the respective data, which were then verified by the second author. After screening the results, it became evident that the few studies we identified applied a variety of assessment tools for medication adherence. Thus, we calculated standardized mean differences (SMD) (Hedges’s g) and 95% confidence intervals for all medication adherence measures using Review Manager (RevMan; version 5.2, The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen). The SMD converts the results to a uniform scale and allows for a better comparability of the effects. We interpreted the SMD using the following rule of thumb: 0.2 represents a small effect, 0.5 a moderate effect, and 0.8 a large effect (Schünemann et al. 2011). Medication adherence was treated as the principle outcome, as AT primarily aims to improve medication adherence and not symptom management or quality of life. For the sake of completeness, we reviewed other outcomes as well, albeit without calculating the SMD. To assess the risk of bias in the individual studies, we used the quality checklist for RCT, as proposed by Behrens and Langer (2010). The checklist consists of all common markers of validity mentioned in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (Liberati et al. 2009). Each author assessed the items independently before rating the overall risk of bias on a scale from one (very low risk of bias) to six (very high risk of bias). Disagreements with ratings were resolved through discussion. An assessment of a high risk of bias did not result in the exclusion of eligible studies, however, as this review aims to present a complete picture of study outcomes in this field.
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RESULTS Study selection The study selection process is presented in Figure 1. After screening 825 records for eligibility, 14 papers were selected for thorough assessment. A further two potentially-eligible papers were excluded, as the respective authors could not be contacted, namely a conference abstract (von Bormann 2009) and a second RCT that was published by Maneesakorn as part of her PhD thesis. Of the 14 full-texts selected, we ultimately included four RCTs in our review (Fig. 1). The search for ongoing RCT in trial registers resulted in one RCT that is currently being conducted in Hong Kong (clinicaltrials.gov identifier NCT01780116). Its completion is expected in April 2015.
Study characteristics The four RCT included in the review were published between 2006 and 2013. The study characteristics are shown in Table 1. On average, participants received seven sessions (Gray et al. 2006; Schulz et al. 2013), each lasting from 36 min (Gray et al. 2006) to 43 min (Maneesakorn et al. 2007; Schulz et al. 2013). Anderson et al. (2010) did not report attendance rates of AT. Participants in the control groups received either TAU or didactic health education. TAU consisted of day treatment, case management, employment placement, medication monitoring, and individual counselling (Anderson et al. 2010). It further included the administration of medication, occupational therapy, group counselling, and recreational therapy (Maneesakorn et al. 2007), or alternatively involved medication, psychotherapy, occupational therapy, and psycho-educational programmes (Schulz et al. 2013). In didactic health education, health education-related topics (e.g. diet) were presented in a didactic way in eight weekly sessions (Gray et al. 2006).
Risk of bias According to the results of our assessment of the risk of bias, Gray et al.’s (2006) RCT had a very low (1) risk of bias, and those of Schulz et al. (2013) and Maneesakorn et al. (2007) had a low (2) risk of bias. Anderson et al.’s (2010) study was rated as having a moderate risk of bias (3). Potential sources for the risk of bias were small sample sizes, increasing the possibility of a false-negative error (Anderson et al. 2010; Maneesakorn et al. 2007), raters not blind to the treatment condition (Anderson et al. 2010), and high drop-out rates (>20%) (Schulz et al. 2013). © 2014 Australian College of Mental Health Nurses Inc.
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Records identified through database search (n = 984)
Additional records identified through other sources (n = 2)
Records after duplicates removed (n = 825)
Records screened (title and abstract) (n = 825)
Full-text articles assessed for eligibility (n = 14)
Studies included in quality assessment (n = 4)
Records excluded according to eligibility criteria (n = 809) + no fulltext available (n = 2)
Full-text articles excluded (n = 10), reasons: review/meta-analysis (n = 5), commentary (n = 1), guideline (n = 1), intervention not adherence therapy (n = 2), missing comparative data (n = 1)
Studies included in data synthesis (n = 4)
FIG. 1:
Study selection process.
TABLE 1: Characteristics of the included studies Gray et al. 2006 Participants Mean age (years) Males (%) Setting Country Control group Follow up Primary outcome Secondary outcomes
41.5 60 Inpatient and community The Netherlands, Germany, Great Britain, Italy Didactic health education 1 year Quality of life Adherence Symptoms
Maneesakorn et al. 2007
Anderson et al. 2010
Schulz et al. 2013
40.8 72 Inpatient and community Thailand
29.0 79 Community USA
35.5 58 Inpatient Germany, Switzerland
TAU 9 weeks Symptoms Adherence Satisfaction with antipsychotic medication Functioning Side-effects
TAU Post-intervention Symptoms Adherence Satisfaction and experience with AT intervention
TAU 12 weeks Symptoms Adherence Attitude towards medication Functioning
AT, adherence therapy; TAU, treatment as usual.
Study outcomes Across all studies, medication adherence was assessed by seven different assessment tools, including self-ratings, keyworker ratings, and blood plasma level (Table 2). In © 2014 Australian College of Mental Health Nurses Inc.
Maneesakorn et al.’s (2007) study, AT was found to improve patients’ medication adherence significantly, as compared to TAU. In other studies, no significant difference between the intervention and control groups was
Anderson et al. 2010 Schulz et al. 2013
Maneesakorn et al. 2007
†Keyworker rating; ‡self-report; §blood plasma level; ¶not calculated due to missing data. CDR, concentration-to-dose ratio; CI, confidence interval; DAI-30, Hogan Drug Attitude Inventory; MAQ, Medication Adherence Questionnaire; MARS, Medication Adherence Rating Scale; NS, not significant (>0.05); PETiT, Personal Evaluation of Transitions in Treatment; SAI-C, keyworker rating of adherence on Schedule for the Assessment of Insight; SD, standard deviation; SMD, standardized mean differences; SWAM, Satisfaction with Antipsychotic Medication scale.
NS NS 0.001 0.019 NS NS NS NS 5.03 (1.55) 3.33 (1.02) 13.5 113.19 41.6 6.36 (10.56) 22.83 (5.89) 7.65 (1.87) 189 194 14 14 13 39 46 46 5.22 (1.57) 3.2 (1.07) 21.63 126.5 37.3 3.34 (5.36) 22.7 (6.59) 7.75 (2.01) 5.04 (1.39) 2.98 (1.24) 19.19 (95% CI: 15.48, 22.90) 116.81 (95% CI: 102.51, 131.11) 40.1 (9.24) 3.83 (6.8) 22.46 (6.83) 7.55 (2.07) 173 172 14 14 10 54 69 69 SAI-C† MAQ‡ DAI-30‡ SWAM‡ PETiT‡ CDR§ DAI-30‡ MARS‡ Gray et al. 2006
n
4.73 (1.63) 2.97 (1.20) 15.38 (95% CI: 10.14, 20.61) 115.13 (95% CI: 104.04, 126.21) 40.1 (10.29) 4.19 (5.79) 22.7 (6.69) 7.46 (1.73)
P-value Follow-up Mean (SD) n
Control group
Baseline Mean (SD) Follow up Mean (SD)
Intervention group
Baseline Mean (SD) Adherence measures
TABLE 2: Study outcomes: Comparison of baseline and follow-up scores of medication adherence (higher ratings indicate better adherence)
0.12 (−0.08, 0.33) −0.12 (−0.33, 0.08) ¶ ¶ ¶ −0.38 (−0.79, 0.04) −0.02 (−0.39, 0.35) 0.03 (−0.35, 0.40)
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SMD (95% CI)
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found in terms of medication adherence. Likewise, the SMD indicate a low and partially-negative effect of AT on medication adherence (Table 2). However, AT was found to significantly improve psychiatric symptoms in two RCT (Maneesakorn et al. 2007; Schulz et al. 2013), and satisfaction with antipsychotic medication in Maneesakorn et al.’s (2007) study. There were no differences between the intervention and control groups regarding global functioning (Maneesakorn et al. 2007; Schulz et al. 2013), side-effects (Maneesakorn et al. 2007), and quality of life (Gray et al. 2006).
DISCUSSION Our search resulted in four RCT, only one of which showed a significant improvement of medication adherence in the AT, as compared to the control group. Even though we could only calculate the SMD for two studies, the results indicate low effect sizes. These results suggest that AT is no more beneficial in improving medication adherence than TAU, or than a didactic health-education programme. However, while AT did not influence global functioning, side-effects, and the quality of life of the patients, it had the potential to improve their symptoms. In order to draw appropriate conclusions regarding the effectiveness of AT, several weaknesses of the trials need to be discussed first. First, the participants in all of the studies had high rates of medication adherence at baseline. Thus, the leeway for further enhancement was limited, and the possibility of detecting significant improvements was reduced. According to crisis theory, patients have the highest potential for change immediately after a crisis (Brandon 1970). Therefore, AT is most suitable for patients shortly after a crisis. Although Schulz et al. (2013) included such patients, they could not avoid recruiting relatively adherent participants. One explanation might be that individuals recruited in trials are required to undergo consenting procedures, and therefore, are likely to be more adherent (Kane et al. 2013). Additionally, patients with schizophrenia and substance abuse or dependency who are at high risk of nonadherence (Jonsdottir et al. 2013) were excluded from all RCT on AT. Researchers need to consider including these patient groups or applying a different research design to avoid a selection bias due to patient consent. For example, Brown et al. (2013) tested the effectiveness and practicability of AT in a mirror-image study that allowed them to analyse routinely-collected data, and thus include non-adherent patients. They trained all mental health workers of an early psychosis service in AT, and routinely assessed data in the year before and after training. The © 2014 Australian College of Mental Health Nurses Inc.
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application of AT resulted in a significantly lower number of relapse rates, while not affecting the number of inpatient admission, days as an inpatient, and referral to a crisis team in the year after training (Brown et al. 2013). However, these results could have been influenced by the fact that nurses tended to use elements of AT in their day-to-day consultations, rather than offering formal sessions (Brown et al. 2013). Nevertheless, through collecting routinely-assessed data and training an entire team, the authors avoided biasing selections and managed to access a representative sample. Future research on AT needs to consider similar study designs as alternatives to RCT. Second, a comparison of the studies’ effects is limited by the fact that the duration of follow-up varied between the RCT and that the assessment tools used in the trials showed some weaknesses. Several authors pointed out that there is little agreement between the different measurements of adherence, such as pill count, electronic monitoring, blood plasma level, and subjective measures (patient or physician ratings) when it comes to labelling patients as non-adherent and in predicting relapse, hospital admission, or psychotic symptoms (Kikkert et al. 2008; 2011; Velligan et al. 2007). The reasons for this might be because different methods of measurement explore different components of medication adherence (Lehmann et al. 2014) or that particularly subjective instruments do not measure the same concepts of adherence (Kikkert et al. 2008). This is hardly surprising, as the conceptual definition of the terms ‘compliance’, ‘adherence’, and ‘concordance’ vary and partly overlap, resulting in methodological weaknesses (Bissonnette 2008; Snowden et al. 2014; Vrijens et al. 2012). According to the original definitions, ‘compliance’ is the extent to which a person’s behaviour coincides with medical or health advice (Vrijens et al. 2012), while ‘adherence’ emphasizes the therapeutic alliance established between the patient and the professional and their agreed decision-making (Horne 2006). ‘Concordance’ highlights the agreement reached after negotiation between the patient and healthcare professional. Thus, a consultation is concordant if the views of the patient and the nurse are equally considered in the agreement, whereas the final decision as to whether to take the medication or not lies with the patient (Britten & Weiss 2004; Cushing & Metcalfe 2007). In fact, none of the RCT analysed in this paper stated which concept they adopted, that is, compliance, adherence, or concordance. Nevertheless, as their outcome measurements predominantly assessed the medication intake of patients, they seem to be based on the definition of medication ‘compliance’. However, as the shared © 2014 Australian College of Mental Health Nurses Inc.
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decision-making process guided the conversation between nurse and patient, and all of the key elements of AT seem to support a concordant consultation, nurses could have achieved a concordant agreement by means of AT (Jones & Grey 2008; Zuaboni & Schulz 2012). If so, AT would be successful if the patient weighed up the advantages and disadvantages, and elaborately developed an attitude towards his medication, regardless of his/her decision to take medication or not. In this case, a measurement of ‘compliance’ to medication would distort the effect of the intervention, as the patients’ ‘noncompliance’ is considered as abortive despite the overall positive outcome. To avoid confusions and misunderstandings due to the inconsistent use of these terms, researchers need to state which definition (compliance, adherence, or concordance) their investigation of AT is based on and adjust their study design accordingly. Where AT aims to achieve a concordant agreement, the shared decision-making process needs to be assessed as a complement to medication ‘compliance’ and other clinically-meaningful outcomes. This could, for example, be done with a mixed-methods study that assesses the extent of a concordant agreement with qualitative methods and combines those with quantitative outcome measures. Additionally, to enable direct comparisons of the study effects between the studies, future research needs to use standard follow-up durations.
Strengths and limitations Our search for literature was conducted in six different databases. Consequently, it could be considered to include most of the relevant studies in the field. Furthermore, we minimized bias in the selection process through independent full-text reviews. For the assessment of the risk of bias, we used a standardized assessment tool that was also rated independently. Because we included only studies on AT, our results provide a complete picture of the effectiveness and problems specific to this type of therapy. The calculation of all SMD would have allowed us to compare the effects irrespective of the assessment instruments. Unfortunately, two RCT did not provide standard deviations, so we could not calculate their SMD. Thus, the comparability between the studies is still incomplete, which in turn limits the significance of our results. Another limitation is that we only included studies written in English and German. There might be relevant studies in other languages that we did not review due to language barriers. Finally, we did not consider two studies that were probably eligible for inclusion, as the respective full-text articles could not be made available.
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Implications According to the reviewed RCT, AT had no positive effect on the medication adherence of patients with schizophrenia who were moderately adherent or had positive attitudes towards their medication at baseline. However, the intervention showed slight improvements in the patients’ symptoms. In conclusion, the evidence presented in this review is not yet sufficient to draw any other conclusions on the effectiveness of AT. Thus, we suggest the following recommendations for future research on AT. First, future trials must recruit non-adherent participants or those at high risk of non-adherence, such as patients with substance dependencies. Non-adherence has to be either made an explicit inclusion criterion in RCT, or other study designs must be applied, such as mirror-image studies. Second, authors need to state whether they apply the definition of compliance, adherence, or concordance, and thus specify the aims envisaged when applying AT. If AT is aimed at improving medication ‘compliance’, we recommend recruiting ‘non-compliant’ participants and assessing ‘compliance’ through different measures (e.g. electronic monitoring, self-report, and blood plasma level) in order to obtain reliable results. In contrast, if AT is aimed at achieving adherence or concordance, the process leading to the patient’s decision as to whether to take the medication or not needs to be assessed as a secondary outcome.
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