Hostname: page-component-7c8c6479df-r7xzm Total loading time: 0 Render date: 2024-03-26T20:21:14.483Z Has data issue: false hasContentIssue false

Mapping modifiable determinants of medication adherence in bipolar disorder (BD) to the theoretical domains framework (TDF): a systematic review

Published online by Cambridge University Press:  19 May 2021

Asta Ratna Prajapati*
Affiliation:
Norfolk and Suffolk NHS Foundation NHS Trust, Norwich NR6 5BE, UK University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
Alexandra Dima
Affiliation:
University of Lyon, Lyon, France
George Mosa
Affiliation:
Devon Partnership NHS Trust, UK
Sion Scott
Affiliation:
University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
Fujian Song
Affiliation:
University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
Jonathan Wilson
Affiliation:
Norfolk and Suffolk NHS Foundation NHS Trust, Norwich NR6 5BE, UK University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
Debi Bhattacharya
Affiliation:
University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
*
Author for correspondence: Asta Ratna Prajapati, E-mail: asta.prajapati@nsft.nhs.uk
Rights & Permissions [Opens in a new window]

Abstract

Background

Around 40% of people with bipolar disorder (BD) are non-adherent to medication leading to relapse, hospitalisation and increased suicide risk. Limited progress in addressing non-adherence may be partly attributable to insufficient understanding of the modifiable determinants of adherence that require targeting in interventions. We synthesised the modifiable determinants of adherence in BD and map them to the theoretical domains framework (TDF).

Method

We searched CINAHL, Cochrane Library, Embase, LILACS, Medline, PsychINFO and PubMed until February 2020. We included studies reporting modifiable determinants of adherence in BD. Two reviewers independently screened studies, assessed quality, extracted modifiable determinants and mapped them to TDF.

Results

We included 57 studies involving 32 894 participants. Determinants reported by patients spanned 11 of the 14 TDF domains compared to six domains represented by clinician/researcher. The TDF domains most commonly represented (% and example) in studies were: ‘Environmental context and resources’ (63%, e.g. experiencing side effects), ‘Beliefs about consequences’ (63%, e.g. beliefs about medication effects), ‘Knowledge’ (40%, e.g. knowledge about disorder), ‘Social influences’ (33%, e.g. support from family/clinicians), ‘Memory, attention and decision processes’ (33%, e.g. forgetfulness), ‘Emotion’ (21%, e.g. fear of addiction) and ‘Intentions’ (21%, e.g. wanting alternative treatment). ‘Intentions’, ‘Memory, attention and decision processes’ and ‘Emotion’ domains were only reported by patients but not clinicians.

Conclusions

Clinicians may be underappreciating the full range of modifiable determinants of adherence and thus not providing adherence support reflective of patients' needs. Reporting of modifiable determinants in behavioural terms facilitates developing theory-based interventions to address non-adherence in BD.

Type
Review Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re- use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Background

Bipolar disorder (BD) is generally a recurrent, lifelong mental health condition with a high risk of disability and excess mortality (Grande, Berk, Birmaher, & Vieta, Reference Grande, Berk, Birmaher and Vieta2016; Vazquez, Holtzman, Lolich, Ketter, & Baldessarini, Reference Vazquez, Holtzman, Lolich, Ketter and Baldessarini2015). The worldwide lifetime prevalence of the BD is estimated at 1% (Rowland & Marwaha, Reference Rowland and Marwaha2018). BD usually requires long-term medication but an estimated 40% of people are non-adherent to medication leading to relapse, functional impairment and suicidality (Gonzalez-Pinto et al., Reference Gonzalez-Pinto, Mosquera, Alonso, Lopez, Ramirez, Vieta and Baldessarini2006; Lingam & Scott, Reference Lingam and Scott2002; Strakowski et al., Reference Strakowski, Keck, McElroy, West, Sax, Hawkins and Bourne1998; Velligan et al., Reference Velligan, Weiden, Sajatovic, Scott, Carpenter and Ross2009). Medication non-adherence increases the probability of hospitalisation by at least five times (Scott & Pope, Reference Scott and Pope2002).

Efforts to improve medication adherence have had marginal effects (Easthall, Taylor, & Bhattacharya, Reference Easthall, Taylor and Bhattacharya2019; Nieuwlaat et al., Reference Nieuwlaat, Wilczynski, Navarro, Hobson, Jeffery, Keepanasseril and Haynes2014). This may be due to limited understanding of the modifiable determinants of medication adherence and existing support focussing on a narrow range of adherence determinants. We define modifiable determinants as ‘any determinants (barriers or facilitators) of medication adherence that can be modified by the patient, carer, or the prescriber within a short timeframe (days or weeks) to improve adherence’. We define a barrier as ‘a circumstance that prevents the patient from taking their medication as prescribed’, whereas a facilitator is ‘a circumstance that makes the process easy or easier’ (Oxford English dictionary online: Oxford university press, 2017). Some evidence syntheses report determinants of adherence to mental health treatment but they do not clearly distinguish between those that are modifiable, such as knowledge regarding how to take medication and non-modifiable such as age and gender. Such distinction is vital to allow adherence interventions to target modifiable determinants.

Furthermore, any differences between the perspective of clinicians and patients on determinants of medication adherence require exploration. Clinicians are the treatment experts but patients are the experts of their lived experience. Their goals, priorities and knowledge of the situation may differ. Thus, clinicians and patients may see the determinants of medication adherence differently (Devine, Edwards, & Feldman, Reference Devine, Edwards and Feldman2018; Velligan et al., Reference Velligan, Weiden, Sajatovic, Scott, Carpenter and Ross2009). Exploring such differences will help design adherence support based on the patient's needs.

A recent systematic review by Garcia et al. provides an overview of barriers to medication adherence in BD and schizophrenia (Garcia et al., Reference Garcia, Martinez-Cengotitabengoa, Lopez-Zurbano, Zorrilla, Lopez, Vieta and Gonzalez-Pinto2016). However, the study limited on determinants of adherence to antipsychotics (one group of medication to manage BD). Other common medications for BD are known as mood stabilisers which includes lithium. The omission of adherence determinants to lithium and other mood stabilisers is significant since lithium is recognised as the first-line gold standard long-term therapy in BD [Grunze et al., Reference Grunze, Vieta, Goodwin, Bowden, Licht and Moller2013; National Institute of Health and Care Excellence (NICE), 2014]. It is also noteworthy that the challenges to adhere to lithium may be different as lithium is a narrow therapeutic index drug and thus require a regular blood test, some dietary restrictions and has significant interactions with other medications [National Institute of Health and Care Excellence (NICE), 2014]. Furthermore, the review does not delineate modifiable from non-modifiable determinants which lack specific behaviour change techniques (BCTs) (Michie, Johnston, Francis, & Hardeman, Reference Michie, Johnston, Francis and Hardeman2008).

Additionally, the lack of behavioural theory underpinning the evidence synthesis in medication adherence in BD is evident. Thus, a systematic review of modifiable determinants of all treatment option in BD underpinned by theoretical framework is needed. Further details regarding the rationale for this systematic review are provided in the published protocol (Prajapati et al., Reference Prajapati, Dima, Clark, Gant, Gibbons, Gorrod and Bhattacharya2019).

This systematic review aimed to identify modifiable determinants of medication adherence in BD reported in the literature and map them to the theoretical domains framework (TDF).

This study is a part of the Collaborative Medication Adherence in Bipolar disorder (C-MAB) project funded by Health Education England/National Institute for Health Research UK. The C-MAB project aims to develop a medication adherence tool for people with BD. The project advisory board includes stakeholders, patients, carers, clinicians, health psychologist and experts in behavioural medicine.

Method

The study was registered with PROSPERO, registration number: CRD42018096306.

The protocol with detailed methods for this systematic review is published elsewhere (Prajapati et al., Reference Prajapati, Dima, Clark, Gant, Gibbons, Gorrod and Bhattacharya2019), and a summary of the methods is provided below.

We searched CINAHL, Cochrane Library, Embase, LILACS, Medline, PsychINFO and PubMed from database inception to October 2018 using the search terms ‘Treatment Adherence and Compliance’, ‘Bipolar Disorder’ and ‘Psychotropic Drugs’. We updated the search in February 2020. The detailed search strategy is available in online Supplementary file.

We included primary, qualitative and quantitative studies published in the English language and studies explicitly reporting modifiable determinants of medication adherence in BD in adults. We excluded reviews, intervention studies to improve adherence, case reports, clinical guidelines or general disease management articles, studies involving short-term treatment of acute agitation or treatment other than medication such as psychotherapy.

Two reviewers (AP, DB, FS, GM, JW and SS) independently screened the study abstracts and full-texts and carried out the quality assessment. Disagreements were resolved through discussion and referral to a third reviewer for arbitration if necessary. A range of quality assessment tools (Center for Evidence Based Management, 2014; Critical Appraisal Skills Programme, 2018; National Institute of Health, 2014) was used according to the study designs (Frambach, van der Vleuten, & Durning, Reference Frambach, van der Vleuten and Durning2013).

We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Moher, Liberati, Tetzlaff, Altman, & The PRISMA Group, Reference Moher, Liberati, Tetzlaff and Altman2009) checklist for data extraction and reporting. The completed PRISMA checklist is available in online Supplementary file 2.

Underpinning theoretical framework

We used framework analysis with the TDF as an a priori framework, to map modifiable determinants of medication adherence to their relevant TDF domain. The use of a theoretical framework provides a broad lens through which to capture the literature identified modifiable determinants. The TDF is a comprehensive framework capturing 33 theories and 84 theoretical constructs related to behaviour change (Atkins et al., Reference Atkins, Francis, Islam, O'Connor, Patey, Ivers and Michie2017). Atkins et al. report the definition of each TDF domain and construct within each domain (Atkins et al., Reference Atkins, Francis, Islam, O'Connor, Patey, Ivers and Michie2017). TDF was developed as a consensus framework by experts in health service research and behaviour science (Michie et al., Reference Michie, Johnston, Abraham, Lawton, Parker and Walker2005). The TDF offers the additional advantage that each of its 14 domains is coupled with BCTs (Michie et al., Reference Michie, Johnston, Francis and Hardeman2008). Thus, mapping modifiable determinants of adherence to the TDF offers a significant utility for intervention development.

Two independent reviewers (AP, AD, DB and SS), with experience in using the TDF, extracted modifiable determinants and coded them to the TDF domains using Nvivo 12 (QSR International Pty Ltd, 2018). For example, the extracted text ‘lack of awareness that medication needed to be taken regularly led to non-adherence’ in the study was coded to the TDF domain ‘Knowledge’. In addition to the 14 TDF domains, we also created another domain called ‘Others’ for any modifiable determinant not suitable to map to those 14 domains. Agreement between two reviewers in mapping modifiable determinants to the same TDF domain was calculated in SPSS version 25 using Cohen's kappa.

We grouped the modifiable determinants into overarching themes (Gale, Heath, Cameron, Rashid, & Redwood, Reference Gale, Heath, Cameron, Rashid and Redwood2013). We also coded whether the modifiable determinants were barriers or facilitators and whether it was reported by patients, clinicians, carers or any other third parties.

Results

From the 2517 studies retrieved, we included 57, comprising 32 894 patients and clinicians. Figure 1 provides the screening process, number of retrieved studies, number of studies included and excluded during title screening, abstract screening and full text screening as well as the reasons for exclusion. The primary reasons for exclusion at full-text screening were failure to report modifiable determinants or reporting an intervention to address adherence.

Fig. 1. PRISMA flow diagram.

PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Study characteristics

Summary characteristics such as study design, participant details and, country in which the included study was conducted are presented in Table 1. Fifty studies explored determinants from the perspective of patients and two (Vieta et al., Reference Vieta, Azorin, Bauer, Frangou, Perugi, Martinez and Schreiner2012; Younas, Bradley, Holmes, Sud, & Maidment, Reference Younas, Bradley, Holmes, Sud and Maidment2016) from clinicians' perspective. Three studies included both patient and clinician perspectives (Baldessarini, Perry, & Pike, Reference Baldessarini, Perry and Pike2008; Maczka, Siwek, Skalski, Grabski, & Dudek, Reference Maczka, Siwek, Skalski, Grabski and Dudek2010; Pope & Scott, Reference Pope and Scott2003). Further two studies were from the researcher's perspective (Gianfrancesco, Sajatovic, Tafesse, & Wang, Reference Gianfrancesco, Sajatovic, Tafesse and Wang2009; Greene et al., Reference Greene, Yan, Chang, Broder, Hartry and Touya2018). However, none of the studies included carers. Most of the included studies collected data via surveys or interviews. The majority (79%) of the studies were conducted in the USA and Europe. A majority of the studies (64%) were focused purely on BD. Of the 57 included studies, 33% (Arvilommi et al., Reference Arvilommi, Suominen, Mantere, Valtonen, Isometsa and Leppamaki2014; Baldessarini et al., Reference Baldessarini, Perry and Pike2008; Bauer et al., Reference Bauer, Glenn, Alda, Sagduyu, Marsh, Grof, Whybrow and C2013; Fleck, Corey, Strakowski, & Keck, Reference Fleck, Corey, Strakowski and Keck2005; Grover, Ghosh, Sarkar, Chakrabarti, & Avasthi, Reference Grover, Ghosh, Sarkar, Chakrabarti and Avasthi2014; Hajda et al., Reference Hajda, Kamaradova, Latalova, Prasko, Ociskova, Mainerova and Tichackova2015; Johnson et al., Reference Johnson, Ozdemir, Manjunath, Hauber, Burch and Thompson2007; Jonsdottir et al., Reference Jonsdottir, Opjordsmoen, Birkenaes, Simonsen, Engh, Ringen and Andreassen2013; Jose, Bhaduri, & Mathew, Reference Jose, Bhaduri and Mathew2003; Manwani et al., Reference Manwani, Szilagyi, Griffin, Weiss, Hennen and Zablotsky2007; Nagesh, Kishore, & Raveesh, Reference Nagesh, Kishore and Raveesh2016; Pope & Scott, Reference Pope and Scott2003; Ralat, Depp, & Bernal, Reference Ralat, Depp and Bernal2018; Roe, Goldblatt, Baloush-Klienman, Swarbrick, & Davidson, Reference Roe, Goldblatt, Baloush-Klienman, Swarbrick and Davidson2009; Scott & Pope, Reference Scott and Pope2002; Stentzel et al., Reference Stentzel, van den, Schwaneberg, Radicke, Hoffmann, Schulze and Langosch2018; Vieta et al., Reference Vieta, Azorin, Bauer, Frangou, Perugi, Martinez and Schreiner2012) explicitly focused on exploring barriers to adherence. Table 2 describes the quality of the included studies. The majority (65%) of the studies was of moderate quality, 19% were of high quality and 16% were of low quality.

Table 1. Summary of included studies

Table 2. Quality of included studies

Reported modifiable determinants of medication adherence

We extracted 290 modifiable determinants, which were grouped into 33 themes and mapped to 11 TDF domains. Inter-rater reliability for mapping the modifiable determinants to the TDF domains was 76% (Cohen's kappa 0.71), indicating substantial agreement between the reviewers (Landis & Koch, Reference Landis and Koch1977). Cohen's kappa was calculated using SPSS 25.0 (IBM Corporation, 2017). Examples of the modifiable determinants, themes of determinants and TDF domains to which they were mapped are reported in Table 3.

Table 3. TDF domains, themes of determinants and examples of determinants (barriers and facilitators)

a Clinicians only reported these themes of determinants.

Some facilitators were reported as the opposite of barriers. For example, ‘cost of medication’ was identified as a barrier in the ‘Environmental context and resources’ domain, for which ‘medication being free of charge’ represented the corresponding facilitator. In other cases, facilitators were occasionally worded as BCTs. For example, forgetfulness represented a barrier in the ‘memory, attention, and decision processes’ domain, for which the corresponding facilitators were reminders and formulating routines; these were classified in the BCT category of ‘prompts and cues’ which may successfully modify behaviour by addressing determinants in this TDF domain (Johnston et al., Reference Johnston, Carey, Connell Bohlen, Johnston, Rothman, de Bruin and Michie2020).

The TDF domains represented in the greatest number of studies were ‘Environmental context and resources’ (63% of studies) and ‘Beliefs about consequences’ (63% of studies). Experience of side effects (49% of studies) and the nature of the medication, e.g. tablet, injection and dose frequency (22% of studies) were the main determinants mapped to the former; acting as barriers when unacceptable and facilitators when acceptable to patients. Beliefs about the likely positive/negative outcomes arising from adhering (36% of studies) and a belief that the medication is not needed (25% of studies) were the main determinants mapped to the latter.

Other TDF domains (and corresponding themes of determinants) reported in 20% or more studies, among all studies, were ‘Knowledge’ (whether the patient had sufficient knowledge about BD or its treatment); ‘Social influences’ (support or opposition from family, friends, relatives, clinicians regarding adherence); ‘Emotion’ (fear of addiction to or side effect from medication); ‘Memory, attention, and decision process’ (forgetfulness/carelessness with medication taking) and ‘Intentions’ (denial of illness or need for treatment).

Modifiable determinants were most frequently reported in the context of barriers rather than facilitators. However, unlike most other TDF domains, for ‘social influences’, facilitators and barriers were reported with similar frequency. This trend was also observed for ‘Social/Professional Role and identity’. Modifiable determinants related to ‘Goals’ and ‘Skills’ were infrequently reported. No determinants were mapped to the TDF domains of ‘Optimism’, ‘Reinforcement’ and ‘Behavioural regulation’.

Determinants from the perspectives of patients and clinicians

Figure 2 illustrates the TDF domains reported in patient studies compared to clinician studies. ‘Beliefs about consequences’ and ‘Environmental context and resources’ were the two most frequently reported TDF domains in both patient studies as well as clinicians studies. There were, however, noticeable differences in the range and nature of determinants reported by patients relative to clinicians. Determinants reported by clinicians were mapped to only six TDF domains compared to 11 TDF domains covered by patient studies. Only patient studies reported determinants which were mapped to the TDF domains ‘Intention’, ‘Memory, attention and decision process’ and ‘Emotion’. These domains included determinants such as denial of the illness or need for treatment, forgetfulness/carelessness and fear of addiction to or side effect of medication respectively (see Table 3 for more details).

Fig. 2. Comparison of TDF domains reported by patients and clinicians. No. of patients only studies = 50; no. of clinicians only studies = 2; no. of studies including patients and clinicians = 3. Two studies exploring researchers' perspectives were not included in this graph.

Furthermore, ‘Goals’ and ‘Skills’ domains were reported in patient studies, albeit infrequently. An example of determinants in these two domains includes different priorities over medication taking and provision of training to manage BD, as shown in Table 3.

Clinicians reported modifiable determinants of adherence themed around lack of knowledge about medication, shared decision making, belief in self and perceived control, belief that medication is not needed, belief about positive or negative effects of medication, side effects, ineffective medication and irregular routine.

Two studies reported determinants from the researcher perspective (Gianfrancesco et al., Reference Gianfrancesco, Sajatovic, Tafesse and Wang2009; Greene et al., Reference Greene, Yan, Chang, Broder, Hartry and Touya2018) namely medication formulations (such as tablets and injections) and the number of medications, both of which were mapped to ‘Environmental context and resources’ domain.

Discussion

Synthesis of the literature through the theoretical lens of the TDF has enabled us to identify that negative emotions evoked by medication taking and intentional non-adherence make a notable contribution to non-adherent behaviour. In contrast to the focus of existing interventions on practical barriers to adherence (MacDonald, Reference MacDonald2017; Torres-Robles et al., Reference Torres-Robles, Wiecek, Tonin, Benrimoj, Fernandez-Llimos and Garcia-Cardenas2018), clinicians should additionally address negative emotions and lack of intentions.

In common with previous evidence syntheses, modifiable determinants were primarily barriers to adherence (Garcia et al., Reference Garcia, Martinez-Cengotitabengoa, Lopez-Zurbano, Zorrilla, Lopez, Vieta and Gonzalez-Pinto2016; Velligan et al., Reference Velligan, Weiden, Sajatovic, Scott, Carpenter and Ross2009) with few reported facilitators. This may be an artefact of the included studies focussing on the challenges experienced by patients, rather than seeking to explore potential solutions. This hypothesis is supported by a third of the included studies explicitly seeking only barriers to medication adherence. For the few studies exploring facilitators, determinants that are not the opposite of barriers, such as wanting to keep the mood stable and not wanting to be hospitalised, have also been reported (Clatworthy, Parham, Horne, Bowskill, & Rank, Reference Clatworthy, Parham, Horne, Bowskill and Rank2007; Darling, Olmstead, Lund, & Fairclough, Reference Darling, Olmstead, Lund and Fairclough2008). A strength of the present review is that we did not restrict the search to only adherence barriers; thus, we have identified a gap in the literature.

Current adherence interventions in BD focus mostly on education regarding medication and BD, cognitive therapy to address negative attitudes and beliefs, family therapy to encourage social support and technology to address forgetfulness (MacDonald, Reference MacDonald2017; Torres-Robles et al., Reference Torres-Robles, Wiecek, Tonin, Benrimoj, Fernandez-Llimos and Garcia-Cardenas2018). Furthermore, adherence support in the UK focusses on shared decision making regarding the choice of medication, side effects profile of medication, cost of medication and exploring patients beliefs [Care Quality Commission (CQC), 2018; National Institute of Healthand Care Excellence (NICE), 2009]. However, in this study, we found a broad range of other modifiable determinants that may be affecting medication adherence. This study provides clinicians with a comprehensive list of modifiable determinants of medication adherence, some of which are underappreciated by clinicians and unaddressed by existing adherence interventions.

Advantages of mapping modifiable determinants to the TDF

Mapping determinants to the TDF allows them to be linked to BCTs. Thus, this study provides a foundation for developing a complex adherence intervention tailored to patients' needs based on their predominant determinants of adherence. The most frequently reported TDF domains of ‘Beliefs about consequences’ and ‘Environmental context and resources’ indicate that working with the patient's belief system, medication acceptability and tolerability are vital to support medication adherence. However, other modifiable determinants, particularly in ‘Intentions’, ‘Memory, attention and decision process’ and ‘Emotion’ domains, presented in this study may be equally or more relevant to individual patients. Thus, identifying the modifiable determinants most pertinent to an individual patient is critical to providing patient-centred adherence support.

The most frequently reported domain ‘Environmental context and resources’ was primarily related to medication characteristics such as side effects, treatment regime, medication effectiveness or cost of medication, etc. This finding accords with previous studies (Garcia et al., Reference Garcia, Martinez-Cengotitabengoa, Lopez-Zurbano, Zorrilla, Lopez, Vieta and Gonzalez-Pinto2016; Kikkert et al., Reference Kikkert, Schene, Koeter, Robson, Born, Helm and Gray2006; Salzmann-Erikson & Sjodin, Reference Salzmann-Erikson and Sjodin2018; Velligan et al., Reference Velligan, Weiden, Sajatovic, Scott, Carpenter and Ross2009). Side effects were represented in the domains of both ‘Environmental context and resources’ and ‘Beliefs about consequences’. This was because patients reported non-adherence arising from both experiencing side effects and being concerned that side effects may result from taking the medication. Each requires a different BCT, for example, the former may be better addressed by ‘restructuring the physical environment,’ e.g. by changing medication with a lower propensity of a particular side effect that the patient is experiencing. In contrast, the latter aligns with BCTs such as ‘pros and cons,’ e.g. discussing the risk and benefit of taking and not taking the medication (The UCL Centre for Behaviour Change, 2019).

The dominance of ‘Beliefs about consequences’ on medication adherence in this review is supported by other studies using the TDF (Crayton et al., Reference Crayton, Fahey, Ashworth, Besser, Weinman and Wright2017; Easthall et al., Reference Easthall, Taylor and Bhattacharya2019). Belief about the necessity or concerns of medication were frequently reported determinants of adherence within this domain. As often reported in clinical practice, many people stop taking their medication once they feel better believing they no longer need them. On the contrary, some people believe they do not need medication at the start of the treatment and thus do not initiate them. Therefore, BCTs such as ‘pros and cons’ may play a vital role in medication adherence (The UCL Centre for Behaviour Change, 2019).

The absence of determinants mapped to the TDF domains ‘Optimism’, ‘Reinforcement’ and ‘Behavioural regulation’ does not necessarily mean that these three domains are unimportant to medication adherence in BD. Previous studies may not have explored these specific domains. Some adherence intervention studies suggest ‘Reinforcement’ using financial incentives may improve adherence (Priebe, Bremner, Lauber, Henderson, & Burns, Reference Priebe, Bremner, Lauber, Henderson and Burns2016). Similarly, optimism, as measured by the revised Life Orientation Test (Herzberg, Glaesmer, & Hoyer, Reference Herzberg, Glaesmer and Hoyer2006), was reported to lead to improved adherence in acute coronary syndrome (Millstein et al., Reference Millstein, Celano, Beale, Beach, Suarez, Belcher and Huffman2016). Revised Life Orientation Test includes statements such as ‘Overall, I expect more good things happen to me than bad’, ‘In uncertain times, I usually expect the best’ (Herzberg et al., Reference Herzberg, Glaesmer and Hoyer2006). However, these may not be modifiable. Future study should explicitly investigate the extent to which these unrepresented domains are relevant to non-adherence in this population and whether they are modifiable in the context of medication adherence.

Although there was a significant overlap between determinants reported by clinicians and patients, there were also notable distinctions. These distinctions may explain the limited progress made by clinicians in identifying and addressing non-adherence (Hartung et al., Reference Hartung, Low, Jindai, Mansoor, Judge, Mendelson and Kondo2017; Nieuwlaat et al., Reference Nieuwlaat, Wilczynski, Navarro, Hobson, Jeffery, Keepanasseril and Haynes2014). However, these distinctions may also have arisen due to the small number of studies exploring the clinician's perspective.

Clinician reported determinants mapped to less than half of the TDF domains, suggesting that clinicians may not be aware of the broad range of determinants affecting medication adherence or studies were not designed to elicit this information from clinicians. The influence of negative emotion evoked by taking medication and intentional non-adherence was the most notable omission from clinicians' perspectives. This incomplete picture may result in adherence support poorly reflecting patients' needs (Brown et al., Reference Brown, Twigg, Taylor, Easthall, Hartt, Budd and Bhattacharya2017). This is evident from current adherence support being focused on a very limited number of determinants (MacDonald, Reference MacDonald2017; National Institute of Healthand Care Excellence (NICE), 2009; Thompson, Kulkarni, & Sergejew, Reference Thompson, Kulkarni and Sergejew2000; Torres-Robles et al. Reference Torres-Robles, Wiecek, Tonin, Benrimoj, Fernandez-Llimos and Garcia-Cardenas2018).

Strengths and limitations

This study offers three novel aspects in the field of medication adherence research in BD. Firstly, the study focuses on potential adherence intervention targets by reporting only modifiable determinants. Secondly, as the application of theory is a core requirement for developing and implementing complex interventions, our use of a theoretical framework provides the foundations for developing future medication adherence interventions and their implementation. Finally, the comprehensive nature of a theoretical framework rather than an individual theory has enabled us to identify gaps in the literature.

Using the TDF as an a priori framework to organise modifiable determinants is a deductive approach. However, we did not constrain extraction of the determinants and mapping them to only the TDF domains as any determinants not aligned to the TDF would have been captured in the ‘Others’ category. The lack of detailed description of the determinants in some studies risked mapping them to incorrect TDF domains. For example, some studies described ‘hassle to acquire medication’ as a determinant of adherence. It could mean the patient has difficulty obtaining medication due to not knowing how to order their prescription or difficulty remembering to order a prescription or lack of transport/money/time to order prescription. Each interpretation would be mapped to a different TDF domain. Further qualitative study with patients will facilitate these further refinements in mapping.

We presented the modifiable determinants of adherence identified from a wide range of study designs. We recognise that the medium via which data are collected can influence the range of determinants captured. For example, interviews may elicit a greater range of determinants that are personal to the individual v. a structured survey of potentially relevant determinants (Lagard, Keegan, & Ward, Reference Lagard, Keegan, Ward, Ritchie and Lewis2003). This non-restrictive approach has contributed to identifying a list of modifiable determinants as comprehensively as possible which was one of the goals of this study.

Implications for practice

We provide theory and evidence-based modifiable determinants that influence a patient's ability to adhere to their prescribed medication. All these determinants should, therefore, be considered and potentially discussed with patients when initiating treatment and at every review. Currently, clinicians may not be providing adherence support tailored to patients' wide-ranging needs.

Implications for research

The application of a theoretical framework to the systematic review has enabled us to identify gaps in the literature where researchers have not sought to investigate the relevance of facilitators of adherence. Further research to explicitly capture the facilitators of adherence may help design future adherence interventions. The existing literature mostly represents the patient voice; absence of the carer voice is a notable gap given their role in supporting medication adherence in people with mental health problems (Deane, McAlpine, Byrne, Davis, & Mortimer, Reference Deane, McAlpine, Byrne, Davis and Mortimer2018). Future research exploring carers' views on modifiable determinants of medication adherence in BD is, therefore, needed.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721001446

Data

The data that support the findings of this study are available from the corresponding author, AP, upon a reasonable request.

Acknowledgements

We would like to thank members of the Collaborative Medication Adherence in Bipolar disorder (C-MAB) Research Advisory Board members for their support. We are also grateful to colleagues from NSFT and UEA libraries for help with the literature search and sourcing articles.

Author contributions

All authors contributed to the development of the protocol for this systematic review. AP led the literature search. AP, DB, GM, JW and SS screened the abstract and full text. AP, GM, JW and FS extracted data. AP, GM and FS quality assessed included studies. AP, AD, DB and SS extracted modifiable determinants and mapped to the TDF. AP and DB led manuscript preparation. All authors read and approved the final manuscript.

Financial support

Asta Ratna Prajapati is funded by Health Education England (HEE)/National Institute for Health Research (NIHR) (Clinical Doctoral Research Fellowship) (NIHR reference number: ICA-CDRF-2017-03-054) for this research project. This paper presents independent research funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the HEE/NIHR, or the Department of Health and Social Care.

Conflict of interest

None.

References

Agyapong, V. I. O., Nwankwo, V., Bangaru, R., & Kirrane, R. (2009). Sources of patients' knowledge of the adverse effects of psychotropic medication and the perceived influence of adverse effects on compliance among service users attending community mental health services. Journal of Clinical Psychopharmacology, 29(6), 565570.CrossRefGoogle ScholarPubMed
Arvilommi, P., Suominen, K., Mantere, O., Valtonen, H., Isometsa, E., & Leppamaki, S. (2014). Predictors of adherence to psychopharmacological and psychosocial treatment in bipolar I or II disorders – An 18-month prospective study. Journal of Affective Disorders, 155(1), 110117.CrossRefGoogle ScholarPubMed
Atkins, L., Francis, J., Islam, R., O'Connor, D., Patey, A., Ivers, N., … Michie, S. (2017). A guide to using the theoretical domains framework of behaviour change to investigate implementation problems. Implementation Science, 12, 7795. doi: 10.1186/s13012-017-0605-9.CrossRefGoogle ScholarPubMed
Averous, P., Charbonnier, E., Lagouanelle-Simeoni, M. C., Dany, L., & Prosperi, A. (2018). Illness perceptions and adherence in bipolar disorder: An exploratory study. Comprehensive Psychiatry, 80, 109115.CrossRefGoogle ScholarPubMed
Baldessarini, R. J., Perry, R., & Pike, J. (2008). Factors associated with treatment nonadherence among US bipolar disorder patients. Human Psychopharmacology, 23(2), 95105.CrossRefGoogle ScholarPubMed
Bates, J. A., Whitehead, R., Bolge, S. C., & Kim, E. (2010). Correlates of medication adherence among patients with bipolar disorder: Results of the bipolar evaluation of satisfaction and tolerability (BEST) study: A nationwide cross-sectional study. Primary Care Companion to the Journal of Clinical Psychiatry, 12(5), E1E8. doi: 10.4088/PCC.09m00883yel.Google Scholar
Bauer, M., Glenn, T., Alda, M., Sagduyu, K., Marsh, W., Grof, P., … Whybrow, & P. C, . (2013). Regularity in daily mood stabilizer dosage taken by patients with bipolar disorder. Pharmacopsychiatry, 46(5), 163168.Google ScholarPubMed
Belzeaux, R., Correard, N., Azorin, J.-M., Etain, B., Loftus, J., Bellivier, F., … Boyer, L. (2013). Depressive residual symptoms are associated with lower adherence to medication in bipolar patients without substance use disorder: Results from the FACE-BD cohort. Journal of Affective Disorders, 151(3), 10091015.CrossRefGoogle ScholarPubMed
Bener, A., Dafeeah, E. E., & Salem, M. O. (2013). A study of reasons of non-compliance of psychiatric treatment and patients' attitudes towards illness and treatment in Qatar. Issues in Mental Health Nursing, 34(4), 273280.CrossRefGoogle ScholarPubMed
Brown, T., Twigg, M., Taylor, N., Easthall, C., Hartt, J., Budd, T., … Bhattacharya, D. (2017). Final report for the IMAB-Q study: Validation and feasibility testing of a novel questionnaire to identify barriers to medication adherence. London, UK. Retrieved May 5, 2020, from https://pharmacyresearchuk.org/wp-content/uploads/2017/01/IMAB-Q-validation-and-feasibility-testing-full-report.pdf.Google Scholar
Care Quality Commission (CQC). (2018). NHS patient survey programme: 2018 community mental health survey, Statistical release, 30-34. Retrieved May 5, 2020, from https://www.cqc.org.uk/sites/default/files/20181122_cmh18_statisticalrelease.pdf.Google Scholar
Center for Evidence Based Management. (2014). Critical Appraisal Checklists for a Qualitative Study. Retrieved May 10, 2020, from https://www.cebma.org.Google Scholar
Clatworthy, J., Bowskill, R., Parham, R., Rank, T., Scott, J., & Horne, R. (2009). Understanding medication non-adherence in bipolar disorders using a necessity-concerns framework. Journal of Affective Disorders, 116(1), 5155.CrossRefGoogle ScholarPubMed
Clatworthy, J., Parham, R., Horne, R., Bowskill, R., & Rank, T. (2007). Adherence to medication in bipolar disorder: A qualitative study exploring the role of patients' beliefs about the condition and its treatment. Bipolar Disorders, 9(6), 656664.CrossRefGoogle ScholarPubMed
Col, S. E., Caykoylu, A., Karakas, U. G., & Ugurlu, M. (2014). Factors affecting treatment compliance in patients with bipolar I disorder during prophylaxis: A study from Turkey. General Hospital Psychiatry, 36(2), 208213.CrossRefGoogle ScholarPubMed
Copeland, L. A., Zeber, J. E., Salloum, I. M., Pincus, H. A., Fine, M. J., & Kilbourne, A. M. (2008). Treatment adherence and illness insight in veterans with bipolar disorder. The Journal of Nervous and Mental Disease, 196(1), 1621.CrossRefGoogle ScholarPubMed
Correard, N., Consoloni, J.-L., Azorin, J.-M., Belzeaux, R., Raust, A., Etain, B., … Beetz, E. (2017). Neuropsychological functioning, age, and medication adherence in bipolar disorder. PLoS ONE, 12(9), e0184313.CrossRefGoogle ScholarPubMed
Crayton, E., Fahey, M., Ashworth, M., Besser, S. J., Weinman, J., & Wright, A. J. (2017). Psychological determinants of medication adherence in stroke survivors: A systematic review of observational studies. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 51(6), 833845. doi: 10.1007/s12160-017-9906-0CrossRefGoogle ScholarPubMed
Critical Appraisal Skills Programme (CASP). (2018). 10 questions to help you make sense of qualitative research. CASP qual checkl. Oxford: UK. Retrieved May 5, 2020, from https://casp-uk.net/.Google Scholar
Darling, C. A., Olmstead, S. B., Lund, V. E., & Fairclough, J. F. (2008). Bipolar disorder: Medication adherence and life contentment. Archives of Psychiatric Nursing, 22(3), 113126.CrossRefGoogle ScholarPubMed
Deane, F. P., McAlpine, E., Byrne, M. K., Davis, E. L., & Mortimer, C. (2018). Are carer attitudes toward medications related to self-reported medication adherence amongst people with mental illness? Psychiatry Research, 260, 158163. doi: S0165-1781(17)30394-3CrossRefGoogle ScholarPubMed
Deegan, P. E. (2005). The importance of personal medicine: A qualitative study of resilience in people with psychiatric disabilities. Scandinavian Journal of Public Health, 33, 2935.CrossRefGoogle Scholar
De Las, C. C., Penate, W., & Cabrera, C. (2016). Perceived health control: A promising step forward in our understanding of treatment adherence in psychiatric care. Journal of Clinical Psychiatry, 77(10), e1233-e1239. doi: 10.4088/JCP.15m09769Google Scholar
De Las, C. C., Penate, W., & Sanz, E. J. (2014). Risk factors for non-adherence to antidepressant treatment in patients with mood disorders. European Journal of Clinical Pharmacology, 70(1), 8998.CrossRefGoogle Scholar
Devine, F., Edwards, T., & Feldman, S. R. (2018). Barriers to treatment: Describing them from a different perspective. Patient Preference and Adherence, 12, 129133. doi: 10.2147/PPA.S147420CrossRefGoogle ScholarPubMed
Easthall, C., Taylor, N., & Bhattacharya, D. (2019). Barriers to medication adherence in patients prescribed medicines for the prevention of cardiovascular disease: A conceptual framework. The International Journal of Pharmacy Practice, 27(3), 223231. doi: 10.1111/ijpp.12491CrossRefGoogle ScholarPubMed
Fleck, D.E., Corey, K.B., Strakowski, S.M., & Keck, P.E Jr.. (2005). Factors associated with medication adherence in African American and white patients with bipolar disorder. Journal of Clinical Psychiatry, 66(5), 646652.CrossRefGoogle ScholarPubMed
Frambach, J. M., van der Vleuten, C. P., & Durning, S. J. (2013). AM last page. Quality criteria in qualitative and quantitative research. Academic Medicine: Journal of the Association of American Medical Colleges, 88(4), 552. doi: 10.1097/ACM.0b013e31828abf7f.Google ScholarPubMed
Gale, N. K., Heath, G., Cameron, E., Rashid, S., & Redwood, S. (2013). Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Medical Research Methodology, 13, 117–2288-13-117. doi: 10.1186/1471-2288-13-117.CrossRefGoogle ScholarPubMed
Garcia, S., Martinez-Cengotitabengoa, M., Lopez-Zurbano, S., Zorrilla, I., Lopez, P., Vieta, E., & Gonzalez-Pinto, A. (2016). Adherence to antipsychotic medication in bipolar disorder and schizophrenic patients: A systematic review. Journal of Clinical Psychopharmacology, 36(4), 355371. doi: 10.1097/JCP.0000000000000523CrossRefGoogle ScholarPubMed
Gianfrancesco, F. D., Sajatovic, M., Tafesse, E., & Wang, R. H. (2009). Association between antipsychotic combination therapy and treatment adherence among individuals with bipolar disorder. Annals of Clinical Psychiatry, 21(1), 316.Google ScholarPubMed
Gonzalez-Pinto, A., Mosquera, F., Alonso, M., Lopez, P., Ramirez, F., Vieta, E., & Baldessarini, R. J. (2006). Suicidal risk in bipolar I disorder patients and adherence to long-term lithium treatment. Bipolar Disorders, 8(5), 618624.CrossRefGoogle ScholarPubMed
Grande, I., Berk, M., Birmaher, B., & Vieta, E. (2016). Bipolar disorder. Lancet (London, England), 387(10027), 15611572. doi: S0140-6736(15)00241-XCrossRefGoogle ScholarPubMed
Greene, M., Yan, T., Chang, E., Broder, M. S., Hartry, A., & Touya, M. (2018). Medication adherence and discontinuation of long-acting injectable versus oral antipsychotics in patients with schizophrenia or bipolar disorder. Journal of Medical Economics, 21(2), 127134.CrossRefGoogle ScholarPubMed
Greenhouse, W. J., Meyer, B., & Johnson, S. L. (2000). Coping and medication adherence in bipolar disorder. Journal of Affective Disorders, 59(3), 237241.CrossRefGoogle ScholarPubMed
Grover, S., Ghosh, A., Sarkar, S., Chakrabarti, S., & Avasthi, A. (2014). Sexual dysfunction in clinically stable patients with bipolar disorder receiving lithium. Journal of Clinical Psychopharmacology, 34(4), 475482.CrossRefGoogle ScholarPubMed
Grunze, H., Vieta, E., Goodwin, G. M., Bowden, C., Licht, R. W., Moller, H. J., … WFSBP Task Force on Treatment Guidelines for Bipolar Disorders. (2013). The world federation of societies of biological psychiatry (WFSBP) guidelines for the biological treatment of bipolar disorders: Update 2012 on the long-term treatment of bipolar disorder. The World Journal of Biological Psychiatry, 14(3), 154219. doi: 10.3109/15622975.2013.770551.CrossRefGoogle ScholarPubMed
Hajda, M., Kamaradova, D., Latalova, K., Prasko, J., Ociskova, M., Mainerova, B., … Tichackova, A. (2015). Self-stigma, treatment adherence, and medication discontinuation in patients with bipolar disorders in remission – A cross sectional study. Activitas Nervosa Superior Rediviva, 57(1), 611.Google Scholar
Hartung, D., Low, A., Jindai, K., Mansoor, D., Judge, M., Mendelson, A., … Kondo, K. (2017). Interventions to improve pharmacological adherence among adults with psychotic spectrum disorders and bipolar disorder: A systematic review. Psychosomatics, 58(2), 101112. doi: S0033-3182(16)30100-1CrossRefGoogle ScholarPubMed
Herzberg, P. Y., Glaesmer, H., & Hoyer, J. (2006). Separating optimism and pessimism: A robust psychometric analysis of the revised life orientation test (LOT-R). Psychological Assessment, 18(4), 433438. doi: 10.1037/1040-3590.18.4.433CrossRefGoogle ScholarPubMed
Hibdye, G., Bekan, L., Dessalegne, Y., Debero, N., & Sintayehu, M. (2015). Prevalence of drug non adherence and associated factors among patients with bipolar disorder at outpatient unit of Amanuel Hospital, Addis Ababa, Ethiopia, 2013. African Journal of Psychiatry (South Africa), 18, 17.Google Scholar
Hou, R., Cleak, V., & Peveler, R. (2010). Do treatment and illness beliefs influence adherence to medication in patients with bipolar affective disorder? A preliminary cross-sectional study. European Psychiatry, 25(4), 216219.CrossRefGoogle ScholarPubMed
IBM Corp. (2017). IBM SPSS statistics for windows. Armonk, NY: IBM Corp.Google Scholar
Inder, M., Lacey, C., & Crowe, M. (2019). Participation in decision-making about medication: A qualitative analysis of medication adherence. International Journal of Mental Health Nursing, 28(1), 181189. doi: 10.1111/inm.12516CrossRefGoogle ScholarPubMed
Johnson, F. R., Ozdemir, S., Manjunath, R., Hauber, A. B., Burch, S. P., & Thompson, T. R. (2007). Factors that affect adherence to bipolar disorder treatments: A stated-preference approach. Medical Care, 45(6), 545552.CrossRefGoogle ScholarPubMed
Johnston, M., Carey, R. N., Connell Bohlen, L., Johnston, D. W., Rothman, A., de Bruin, M., … Michie, S. (2020). Linking behavior change techniques and mechanisms of action: Triangulation of findings from literature synthesis and expert consensus. Translational Behavioral Medicine, ibaa050, 117. doi: 10.1093/tbm/ibaa050Google Scholar
Jonsdottir, H., Opjordsmoen, S., Birkenaes, A. B., Simonsen, C., Engh, J. A., Ringen, P. A., … Andreassen, O. A. (2013). Predictors of medication adherence in patients with schizophrenia and bipolar disorder. Acta Psychiatrica Scandinavica, 127(1), 2333.CrossRefGoogle ScholarPubMed
Jose, T. T., Bhaduri, A., & Mathew, B. (2003). A study of the factors associated with compliance or non-compliance to lithium therapy among the patients with bipolar affective disorder. Nursing Journal of India, 94(1), 911.CrossRefGoogle Scholar
Kamaradova, D., Latalova, K., Prasko, J., Kubinek, R., Vrbova, K., Mainerova, B., … Holubova, M. (2016). Connection between self-stigma, adherence to treatment, and discontinuation of medication. Patient Preference and Adherence, 10, 12891298.CrossRefGoogle ScholarPubMed
Keck, P. E., McElroy, S. L., Strakowski, S. M., Balistreri, T. M., Kizer, D. I., & West, S. A. (1996). Factors associated with maintenance antipsychotic treatment of patients with bipolar disorder. The Journal of Clinical Psychiatry, 57(4), 147151.Google ScholarPubMed
Keck, P. E., McElroy, S. L., Strakowski, S. M., Bourne, M. L., & West, S. A. (1997). Compliance with maintenance treatment in bipolar disorder. Psychopharmacology Bulletin, 33(1), 8791.Google ScholarPubMed
Kikkert, M. J., Schene, A. H., Koeter, M. W., Robson, D., Born, A., Helm, H., … Gray, R. J. (2006). Medication adherence in schizophrenia: Exploring patients', carers' and professionals' views. Schizophrenia Bulletin, 32(4), 786794. doi: 10.1093/schbul/sbl011CrossRefGoogle ScholarPubMed
Kraemer, S., Minarzyk, A., Eppendorfer, S., Henneges, C., Hundemer, H.-P., Wilhelm, S., & Grunze, H. (2013). Comparably high retention and low relapse rates in different subpopulations of bipolar patients in a German non-interventional study. BMC Psychiatry, 13, 193.CrossRefGoogle Scholar
Kutzelnigg, A., Kasper, S., Kopeinig, M., Chen, C.-K., Fabian, A., Pujol-Luna, M. G., … Doby, D. (2014). Compliance as a stable function in the treatment course of bipolar disorder in patients stabilized on olanzapine: Results from a 24-month observational study. Clinical and Translational Imaging, 2(1), 114.Google ScholarPubMed
Lagard, R., Keegan, J., & Ward, K. (2003). In-depth interviews. In Ritchie, J., & Lewis, J. (Eds.), Qualitative research practice: A guide for social science students and researchers (pp. 138139). London, UK: Sage.Google Scholar
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159174.CrossRefGoogle ScholarPubMed
Lingam, R., & Scott, J. (2002). Treatment non-adherence in affective disorders. Acta Psychiatrica Scandinavica, 105(3), 164172. doi: 10.1034/j.1600–0447.2002.1r084.xCrossRefGoogle ScholarPubMed
MacDonald, L. (2017) Medication adherence in bipolar disorder: Understanding patients’ perspectives to inform intervention development. PhD thesis, University College London, UK. 2017. Retrieved May 5, 2020. from https://discovery.ucl.ac.uk/id/eprint/1543201/1/MacDonald_LA_PhD_Thesis_2017.pdf.Google Scholar
Maczka, G., Siwek, M., Skalski, M., Grabski, B., & Dudek, D. (2010). Patients' and doctors' attitudes towards bipolar disorder – Do we share our beliefs? Archives of Psychiatry and Psychotherapy, 12(2), 4350.Google Scholar
Manwani, S. G., Szilagyi, K. A., Griffin, M. L., Weiss, R. D., Hennen, J., & Zablotsky, B. (2007). Adherence to pharmacotherapy in bipolar disorder patients with and without co-occurring substance use disorders. Journal of Clinical Psychiatry, 68(8), 11721176.CrossRefGoogle ScholarPubMed
Michie, S., Johnston, M., Abraham, C., Lawton, R., Parker, D., Walker, A., & ‘Psychological Theory’ Group. (2005). Making psychological theory useful for implementing evidence based practice: A consensus approach. Quality & Safety in Health Care, 14(1), 2633. doi: 10.1136/qshc.2004.011155.CrossRefGoogle ScholarPubMed
Michie, S., Johnston, M., Francis, J., & Hardeman, W. (2008). From theory to intervention: Mapping theoretically derived behavioural determinants to behaviour change techniques. Applied Psychology, 57(4), 660680.CrossRefGoogle Scholar
Millstein, R. A., Celano, C. M., Beale, E. E., Beach, S. R., Suarez, L., Belcher, A. M., … Huffman, J. C. (2016). The effects of optimism and gratitude on adherence, functioning and mental health following an acute coronary syndrome. General Hospital Psychiatry, 43, 1722. doi: 10.1016/j.genhosppsych.2016.08.006CrossRefGoogle ScholarPubMed
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. doi:10.1371/journal.pmed1000097.CrossRefGoogle ScholarPubMed
Morselli, P. L., & Elgie, R. (2003). GAMIAN-Europe*/BEAM survey I – Global analysis of a patient questionnaire circulated to 3450 members of 12 European advocacy groups operating in the field of mood disorders. Bipolar Disorders, 5(4), 265278.CrossRefGoogle ScholarPubMed
Nagesh, H. N., Kishore, M. S., & Raveesh, B. N. (2016). Assessment of adherence to psychotropic medications in a psychiatric unit of district hospital. National Journal of Physiology, Pharmacy and Pharmacology, 6(6), 581585.CrossRefGoogle Scholar
National Institute of Health. (2014). Quality assessment tool for observational cohort and cross sectional studies. Retrieved May 5, 2020, from https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools.Google Scholar
National Institute of Health and Care Excellence (NICE). (2009). Medicines adherence: Involving patients in decisions about prescribed medicines and supporting adherence. London: NICE.Google Scholar
National Institute of Health and Care Excellence (NICE). (2014). Bipolar disorder: Assessment and management (clinical guideline, CG 185). London: nice.Google Scholar
Nieuwlaat, R., Wilczynski, N., Navarro, T., Hobson, N., Jeffery, R., Keepanasseril, A., … Haynes, R. B. (2014). Interventions for enhancing medication adherence. The Cochrane Database of Systematic Reviews, 2014(11), CD000011. doi: 10.1002/14651858.CD000011.pub4.CrossRefGoogle ScholarPubMed
Novick, D., Montgomery, W., Treuer, T., Koyanagi, A., Aguado, J., Haro, J. M., et al. (2017). Comparison of clinical outcomes with orodispersible versus standard oral olanzapine tablets in nonadherent patients with schizophrenia or bipolar disorder. Patient Preference and Adherence, 11, 10191025.CrossRefGoogle ScholarPubMed
Oxford English Dictionary online: Oxford university press. (2017). Retrieved March 2, 2017, from https://en.oxforddictionaries.com/definition/barrier.Google Scholar
Perron, B. E., Zeber, J. E., Kilbourne, A. M., & Bauer, M. S. (2009). A brief measure of perceived clinician support by patients with bipolar spectrum disorders. Journal of Nervous & Mental Disease, 197(8), 574579.CrossRefGoogle ScholarPubMed
Pope, M., & Scott, J. (2003). Do clinicians understand why individuals stop taking lithium? Journal of Affective Disorders, 74(3), 287291.CrossRefGoogle ScholarPubMed
Prajapati, A. R., Dima, A., Clark, A. B., Gant, C., Gibbons, C., Gorrod, R., … Bhattacharya, D. (2019). Mapping of modifiable barriers and facilitators of medication adherence in bipolar disorder to the theoretical domains framework: A systematic review protocol. BMJ Open, 9(2), e026980. doi: 10.1136/bmjopen-2018-026980CrossRefGoogle Scholar
Priebe, S., Bremner, S. A., Lauber, C., Henderson, C., & Burns, T. (2016). Financial incentives to improve adherence to antipsychotic maintenance medication in non-adherent patients: A cluster randomised controlled trial. Health Technology Assessment, 20(70), 121121.CrossRefGoogle ScholarPubMed
QSR International Pty Ltd. (2018). Nvivo 12 for windows. NVivo qualitative data analysis software (computer software).Google Scholar
Ralat, S. I., Depp, C. A., & Bernal, G. (2018). Reasons for nonadherence to psychiatric medication and cardiovascular risk factors treatment among Latino bipolar disorder patients living in Puerto Rico: A qualitative study. Community Mental Health Journal, 54(6), 707716. doi: 10.1007/s10597-017-0202-zCrossRefGoogle ScholarPubMed
Roe, D., Goldblatt, H., Baloush-Klienman, V., Swarbrick, M., & Davidson, L. (2009). Why and how people decide to stop taking prescribed psychiatric medication: Exploring the subjective process of choice. Psychiatric Rehabilitation Journal, 33(1), 3846.CrossRefGoogle ScholarPubMed
Rosa, A. R., Marco, M., Fachel, J. M. G., Kapczinski, F., Stein, A. T., & Barros, H. M. T. (2007). Correlation between drug treatment adherence and lithium treatment attitudes and knowledge by bipolar patients. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 31(1), 217224.CrossRefGoogle ScholarPubMed
Rosenblat, J. D., Simon, G. E., Sachs, G. S., Deetz, I., Doederlein, A., DePeralta, D., … McIntyre, R. S. (2018). Factors that impact treatment decisions: Results from an online survey of individuals with bipolar and unipolar depression. The Primary Care Companion for CNS Disorders, 20(6), 18m02340. doi: 10.4088/PCC.18m02340.CrossRefGoogle ScholarPubMed
Rowland, T. A., & Marwaha, S. (2018). Epidemiology and risk factors for bipolar disorder. Therapeutic Advances in Psychopharmacology, 8(9), 251269. doi: 10.1177/2045125318769235CrossRefGoogle ScholarPubMed
Sajatovic, M., Bauer, M. S., Kilbourne, A. M., Vertrees, J. E., & Williford, W. (2006). Self-reported medication treatment adherence among veterans with bipolar disorder. Psychiatric Services (Washington, D.C.), 57(1), 5662.CrossRefGoogle ScholarPubMed
Sajatovic, M., Ignacio, R. V., West, J. A., Cassidy, K. A., Safavi, R., Kilbourne, A. M., & Blow, F. C. (2009). Predictors of nonadherence among individuals with bipolar disorder receiving treatment in a community mental health clinic. Comprehensive Psychiatry, 50(2), 100107.CrossRefGoogle Scholar
Sajatovic, M., Levin, J., Fuentes-Casiano, E., Cassidy, K. A., Tatsuoka, C., & Jenkins, J. H. (2011). Illness experience and reasons for nonadherence among individuals with bipolar disorder who are poorly adherent with medication. Comprehensive Psychiatry, 52(3), 280287.CrossRefGoogle ScholarPubMed
Salzmann-Erikson, M., & Sjodin, M. (2018). A narrative meta-synthesis of how people with schizophrenia experience facilitators and barriers in using antipsychotic medication: Implications for healthcare professionals. International Journal of Nursing Studies, 85, 718. doi: S0020-7489(18)30115-9CrossRefGoogle ScholarPubMed
Scott, J., & Pope, M. (2002). Self-reported adherence to treatment with mood stabilizers, plasma levels, and psychiatric hospitalization. The American Journal of Psychiatry, 159(11), 19271929.CrossRefGoogle ScholarPubMed
Sharma, S., Kumar, N., Chakraborti, S., Sinha, S., Kumari, S., & Gajendragad, J. M. (2012). Prevalence and factors associated with medication compliance in Indian patients suffering from mental disorders. Tropical Doctor, 42(1), 2831.CrossRefGoogle ScholarPubMed
Stentzel, U., van den, B. N., Schwaneberg, T., Radicke, F., Hoffmann, W., Schulze, L. N., … Langosch, J. M. (2018). Predictors of medication adherence among patients with severe psychiatric disorders: Findings from the baseline assessment of a randomized controlled trial (TECLA). BMC Psychiatry, 18(1), 155.CrossRefGoogle ScholarPubMed
Strakowski, S. M., Keck, P. E. Jr, McElroy, S. L., West, S. A., Sax, K. W., Hawkins, J. M., … Bourne, M. L. (1998). Twelve-month outcome after a first hospitalization for affective psychosis. Archives of General Psychiatry, 55(1), 4955. doi: 10.1001/archpsyc.55.1.49.CrossRefGoogle ScholarPubMed
Teter, C. J., Falone, A. E., Weiss, R. D., Bakaian, A. M., Tu, C., & Ongur, D. (2011). Medication adherence and attitudes in patients with bipolar disorder and current versus past substance use disorder. Psychiatry Research, 190(2), 253258.CrossRefGoogle ScholarPubMed
Thompson, K., Kulkarni, J., & Sergejew, A. A. (2000). Reliability and validity of a new medication adherence rating scale (MARS) for the psychoses. Schizophrenia Research, 42(3), 241247. doi: S0920-9964(99)00130-9CrossRefGoogle ScholarPubMed
Torres-Robles, A., Wiecek, E., Tonin, F. S., Benrimoj, S. I., Fernandez-Llimos, F., & Garcia-Cardenas, V. (2018). Comparison of interventions to improve long-term medication adherence across different clinical conditions: A systematic review with network meta-analysis. Frontiers in Pharmacology, 9, 1454. doi: 10.3389/fphar.2018.01454CrossRefGoogle ScholarPubMed
The UCL Centre for Behaviour Change. (2019). The behaviour change taxonomy v1. Retrieved May 5, 2020, from https://www.bct-taxonomy.com/interventions.Google Scholar
Vargas-Huicochea, I., Huicochea, L., Berlanga, C., & Fresan, A. (2014). Taking or not taking medications: Psychiatric treatment perceptions in patients diagnosed with bipolar disorder. Journal of Clinical Pharmacy and Therapeutics, 39(6), 673679.CrossRefGoogle ScholarPubMed
Vazquez, G. H., Holtzman, J. N., Lolich, M., Ketter, T. A., & Baldessarini, R. J. (2015). Recurrence rates in bipolar disorder: Systematic comparison of long-term prospective, naturalistic studies versus randomized controlled trials. European Neuropsychopharmacology: The Journal of the European College of Neuropsychopharmacology, 25(10), 15011512. doi: 10.1016/j.euroneuro.2015.07.013CrossRefGoogle ScholarPubMed
Velligan, D. I., Weiden, P. J., Sajatovic, M., Scott, J., Carpenter, D., Ross, R., … Expert Consensus Panel on Adherence Problems in Serious and Persistent Mental Illness. (2009). The expert consensus guideline series: Adherence problems in patients with serious and persistent mental illness. The Journal of Clinical Psychiatry, 70(Suppl 4), 146.Google ScholarPubMed
Vieta, E., Azorin, J. M., Bauer, M., Frangou, S., Perugi, G., Martinez, G., & Schreiner, A. (2012). Psychiatrists' perceptions of potential reasons for non- and partial adherence to medication: Results of a survey in bipolar disorder from eight European countries. Journal of Affective Disorders, 143(1–3), 125130.CrossRefGoogle ScholarPubMed
Weiss, R. D., Greenfield, S. F., Najavits, L. M., Soto, J. A., Wyner, D., Tohen, M., & Griffin, M. L. (1998). Medication compliance among patients with bipolar disorder and substance use disorder. Journal of Clinical Psychiatry, 59(4), 172174.CrossRefGoogle ScholarPubMed
Younas, M., Bradley, E., Holmes, N., Sud, D., & Maidment, I. D. (2016). Mental health pharmacists views on shared decision-making for antipsychotics in serious mental illness. International Journal of Clinical Pharmacy, 38(5), 11911199.CrossRefGoogle ScholarPubMed
Zeber, J. E., Copeland, L. A., Good, C. B., Fine, M. J., Bauer, M. S., & Kilbourne, A. M. (2008). Therapeutic alliance perceptions and medication adherence in patients with bipolar disorder. Journal of Affective Disorders, 107(1–3), 5362.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. PRISMA flow diagram.PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Figure 1

Table 1. Summary of included studies

Figure 2

Table 2. Quality of included studies

Figure 3

Table 3. TDF domains, themes of determinants and examples of determinants (barriers and facilitators)

Figure 4

Fig. 2. Comparison of TDF domains reported by patients and clinicians. No. of patients only studies = 50; no. of clinicians only studies = 2; no. of studies including patients and clinicians = 3. Two studies exploring researchers' perspectives were not included in this graph.

Supplementary material: File

Prajapati et al. supplementary material

Prajapati et al. supplementary material 1

Download Prajapati et al. supplementary material(File)
File 73.1 KB
Supplementary material: File

Prajapati et al. supplementary material

Prajapati et al. supplementary material 2

Download Prajapati et al. supplementary material(File)
File 81.9 KB