Implementation and Use of a Client-Facing Web-Based Shared Decision-Making System (MyCHOIS-CommonGround) in Two Specialty Mental Health Clinics

Supported decision-making interventions in mental healthcare: A systematic review of current evidence and implementation barriers

BACKGROUND

There is a growing momentum around the world to foster greater opportunities for the involvement of mental health service users in their care and treatment planning. In-principle support for this aim is widespread across mental healthcare professionals. Yet, progress in mental health services towards this objective has lagged in practice.

OBJECTIVES

We conducted a systematic review of quantitative, qualitative and mixed-method research on interventions to improve opportunities for the involvement of mental healthcare service users in treatment planning, to understand the current research evidence and the barriers to implementation.

METHODS

Seven databases were searched and 5137 articles were screened. Articles were included if they reported on an intervention for adult service users, were published between 2008 and October 2023 and were in English. Evidence in the 140 included articles was synthesised according to the JBI guidance on Mixed Methods Systematic Reviews.

RESULTS

Research in this field remains exploratory in nature, with a wide range of interventions investigated to date but little experimental replication. Overarching barriers to shared and supported decision-making in mental health treatment planning were (1) Organisational (resource limitations, culture barriers, risk management priorities and structure); (2) Process (lack of knowledge, time constraints, health-related concerns, problems completing and using plans); and (3) Relationship barriers (fear and distrust for both service users and clinicians).

CONCLUSIONS

On the basis of the barriers identified, recommendations are made to enable the implementation of new policies and programs, the designing of new tools and for clinicians seeking to practice shared and supported decision-making in the healthcare they offer.

PATIENT OR PUBLIC CONTRIBUTION

This systematic review has been guided at all stages by a researcher with experience of mental health service use, who does not wish to be identified at this point in time. The findings may inform organisations, researchers and practitioners on implementing supported decision-making, for the greater involvement of people with mental ill health in their healthcare.

Peer-Facilitated Decision Making in Mental Health: Promises, Pitfalls, and Recommendations for Research and Practice

Recognition has grown that peer support workers serve an important role in facilitating decision making about treatment and recovery among people with mental health conditions. This article provides examples of peer-facilitated decision support interventions in the literature, discusses promises and potential pitfalls associated with peers serving in decision support roles, and offers recommendations for research and practice. Examples were selected from the literature on decision support interventions for people with serious mental illnesses, such as schizophrenia, bipolar disorder, and major depression. Promises, pitfalls, and recommendations were informed by this research and by the literature on lived experience perspectives, the helper-therapy principle, and reported barriers to and facilitators of peers assisting with decision making. According to the included studies, peers may facilitate decision making in several ways (e.g., by asking service users about their goals or preferences, assisting them with using decision support tools, sharing stories, and facilitating access to information and resources). Peer-facilitated decision support may be associated with positive decision making and health outcomes for service users and peer support workers. However, providers need to carefully consider barriers to implementation of this support, such as inadequate resourcing, poor integration, and compromising of peer support values.

The Role of Moderators in Facilitating and Encouraging Peer-to-Peer Support in an Online Mental Health Community: A Qualitative Exploratory Study

Online peer support platforms have gained popularity as a potential way for people struggling with mental health problems to share information and provide support to each other. While these platforms can offer an open space to discuss emotionally difficult issues, unsafe or unmoderated communities can allow potential harm to users by spreading triggering content, misinformation or hostile interactions. The purpose of this study was to explore the role of moderators in these online communities, and how moderators can facilitate peer-to-peer support, while minimizing harms to users and amplifying potential benefits. Moderators of the Togetherall peer support platform were recruited to participate in qualitative interviews. The moderators, referred to as 'Wall Guides', were asked about their day-to-day responsibilities, positive and negative experiences they have witnessed on the platform and the strategies they employ when encountering problems such as lack of engagement or posting of inappropriate content. The data were then analyzed qualitatively using thematic content analysis and consensus codes were deduced and reviewed to reach final results and representative themes. In total, 20 moderators participated in this study, and described their experiences and efforts to follow a consistent and shared protocol for responding to common scenarios in the online community. Many reported the deep connections formed by the online community, the helpful and thoughtful responses that members give each other and the satisfaction of seeing progress in members' recovery. They also reported occasional aggressive, sensitive or inconsiderate comments and posts on the platform. They respond by removing or revising the hurtful post or reaching out to the affected member to maintain the 'house rules'. Lastly, many discussed strategies they elicit to promote engagement from members within the community and ensure each member is supported through their use of the platform. This study sheds light on the critical role of moderators of online peer support communities, and their ability to contribute to the potential benefits of digital peer support while minimizing risks to users. The findings reported here accentuate the importance of having well-trained moderators on online peer support platforms and can guide future efforts to effectively train and supervise prospective peer support moderators. Moderators can become an active 'shaping force' and bring a cohesive culture of expressed empathy, sensitivity and care. The delivery of a healthy and safe community contrasts starkly with non-moderated online forums, which can become unhealthy and unsafe as a result.

Shared decision-making interventions for people with mental health conditions

BACKGROUND

One person in every four will suffer from a diagnosable mental health condition during their life. Such conditions can have a devastating impact on the lives of the individual and their family, as well as society.  International healthcare policy makers have increasingly advocated and enshrined partnership models of mental health care. Shared decision-making (SDM) is one such partnership approach. Shared decision-making is a form of service user-provider communication where both parties are acknowledged to bring expertise to the process and work in partnership to make a decision.  This review assesses whether SDM interventions improve a range of outcomes. This is the first update of this Cochrane Review, first published in 2010.

OBJECTIVES

To assess the effects of SDM interventions for people of all ages with mental health conditions, directed at people with mental health conditions, carers, or healthcare professionals, on a range of outcomes including: clinical outcomes, participation/involvement in decision-making process (observations on the process of SDM; user-reported, SDM-specific outcomes of encounters), recovery, satisfaction, knowledge, treatment/medication continuation, health service outcomes, and adverse outcomes.

SEARCH METHODS

We ran searches in January 2020 in CENTRAL, MEDLINE, Embase, and PsycINFO (2009 to January 2020). We also searched trial registers and the bibliographies of relevant papers, and contacted authors of included studies.  We updated the searches in February 2022. When we identified studies as potentially relevant, we labelled these as studies awaiting classification.

SELECTION CRITERIA

Randomised controlled trials (RCTs), including cluster-randomised controlled trials, of SDM interventions in people with mental health conditions (by Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) criteria).

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. We used GRADE to assess the certainty of the evidence.

MAIN RESULTS

This updated review included 13 new studies, for a total of 15 RCTs. Most participants were adults with severe mental illnesses such as schizophrenia, depression, and bipolar disorder, in higher-income countries. None of the studies included children or adolescents.  Primary outcomes We are uncertain whether SDM interventions improve clinical outcomes, such as psychiatric symptoms, depression, anxiety, and readmission, compared with control due to very low-certainty evidence. For readmission, we conducted subgroup analysis between studies that used usual care and those that used cognitive training in the control group. There were no subgroup differences. Regarding participation (by the person with the mental health condition) or level of involvement in the decision-making process, we are uncertain if SDM interventions improve observations on the process of SDM compared with no intervention due to very low-certainty evidence. On the other hand, SDM interventions may improve SDM-specific user-reported outcomes from encounters immediately after intervention compared with no intervention (standardised mean difference (SMD) 0.63, 95% confidence interval (CI) 0.26 to 1.01; 3 studies, 534 participants; low-certainty evidence). However, there was insufficient evidence for sustained participation or involvement in the decision-making processes. Secondary outcomes We are uncertain whether SDM interventions improve recovery compared with no intervention due to very low-certainty evidence. We are uncertain if SDM interventions improve users' overall satisfaction. However, one study (241 participants) showed that SDM interventions probably improve some aspects of users' satisfaction with received information compared with no intervention: information given was rated as helpful (risk ratio (RR) 1.33, 95% CI 1.08 to 1.65); participants expressed a strong desire to receive information this way for other treatment decisions (RR 1.35, 95% CI 1.08 to 1.68); and strongly recommended the information be shared with others in this way (RR 1.32, 95% CI 1.11 to 1.58). The evidence was of moderate certainty for these outcomes. However, this same study reported there may be little or no effect on amount or clarity of information, while another small study reported there may be little or no change in carer satisfaction with the SDM intervention. The effects of healthcare professional satisfaction were mixed: SDM interventions may have little or no effect on healthcare professional satisfaction when measured continuously, but probably improve healthcare professional satisfaction when assessed categorically. We are uncertain whether SDM interventions improve knowledge, treatment continuation assessed through clinic visits, medication continuation, carer participation, and the relationship between users and healthcare professionals because of very low-certainty evidence. Regarding length of consultation, SDM interventions probably have little or no effect compared with no intervention (SDM 0.09, 95% CI -0.24 to 0.41; 2 studies, 282 participants; moderate-certainty evidence). On the other hand, we are uncertain whether SDM interventions improve length of hospital stay due to very low-certainty evidence. There were no adverse effects on health outcomes and no other adverse events reported.

AUTHORS' CONCLUSIONS

This review update suggests that people exposed to SDM interventions may perceive greater levels of involvement immediately after an encounter compared with those in control groups. Moreover, SDM interventions probably have little or no effect on the length of consultations.  Overall we found that most evidence was of low or very low certainty, meaning there is a generally low level of certainty about the effects of SDM interventions based on the studies assembled thus far. There is a need for further research in this area.

A scoping review of implementation of health-focused interventions in vulnerable populations

Vulnerable populations face significant challenges in getting the healthcare they need. A growing body of implementation science literature has examined factors, including facilitators and barriers, relevant to accessing healthcare in these populations. The purpose of this scoping review was to identify themes relevant for improving implementation of healthcare practices and programs for vulnerable populations. This scoping review relied on the methodological framework set forth by Arksey and O’Malley, and the Consolidated Framework for Implementation Research (CFIR) to evaluate and structure our findings. A framework analytic approach was used to code studies. Of the five CFIR Domains, the Inner Setting and Outer Setting were the most frequently examined in the 81 studies included. Themes that were pertinent to each domain are as follows—Inner Setting: organizational culture, leadership engagement, and integration of the intervention; Outer Setting: networks, external policies, and patients’ needs and resources; Characteristics of the Individual: knowledge and beliefs about the intervention, self-efficacy, as well as stigma (i.e., other attributes); Intervention Characteristics: complexities with staffing, cost, and adaptations; and Process: staff and patient engagement, planning, and ongoing reflection and evaluation. Key themes, including barriers and facilitators, are highlighted here as relevant to implementation of practices for vulnerable populations. These findings can inform tailoring of implementation strategies and health policies for vulnerable populations, thereby supporting more equitable healthcare.

A Systematic Review of Shared Decision-Making Interventions for Service Users With Serious Mental Illnesses: State of the Science and Future Directions

OBJECTIVE

Shared decision making (SDM) is a health communication model that may be particularly appealing to service users with serious mental illnesses, who often want to be involved in making decisions about their mental health care. The purpose of this systematic review was to describe and evaluate participant, intervention, methodological, and outcome characteristics of SDM intervention studies conducted within this population.

METHODS

Systematic searches of the literature through April 2020 were conducted and supplemented by hand searching of reference lists of identified studies. A total of 53 independent studies of SDM interventions that were conducted with service users with serious mental illnesses and that included a quantitative or qualitative measure of the intervention were included in the review. Data were independently extracted by at least two authors.

RESULTS

Most studies were conducted with middle-age, male, White individuals from Western countries. Interventions fell into the following categories: decision support tools only, multicomponent interventions involving decision support tools, multicomponent interventions not involving decision support tools, and shared care planning and preference elicitation interventions. Most studies were randomized controlled trials with sufficient sample sizes. Outcomes assessed were diverse, spanning decision-making constructs, clinical and functional, treatment engagement or adherence, and other constructs.

CONCLUSIONS

Findings suggest important future directions for research, including the need to evaluate the impact of SDM in special populations (e.g., young adults and racial-ethnic minority groups); to expand interventions to a broader array of decisions, users, and contexts; and to establish consensus measures to assess intervention effectiveness.

Ethics codes and medical decision making

OBJECTIVE

The objective of this study is to analyze guidance about medical decision making contained in ethics codes. The primary question we address is which of the main decision-making models - informed decision making (IDM), shared decision making (SDM), or paternalism - is promoted by these codes.

METHODS

We manually searched codes of medical ethics for guidance on medical decision making. Our analysis focused on the major international code, the World Medical Association International Code of Medical Ethics (ICME), and national codes of the US, Canada, Australia, New Zealand, the UK, Ireland, Germany, France and Norway.

RESULTS

The ICME does not promote any specific model of medical decision making. 10 of the 11 analyzed national codes contain guidance about IDM, while only four refer to SDM. Some codes contain articles which are imprecise with regard to the question of medical decision making.

CONCLUSIONS

All of the analyzed national codes should be updated or amended. In particular, given the great importance of SDM in medicine, codes which do not contain relevant guidance should be updated.

PRACTICE IMPLICATIONS

Relevant amendments introduced to ethics codes could contribute to promoting of adequate standards of medical decision making (especially those regarding SDM) among doctors.

Shared decision making for adults with severe mental illness: A concept analysis

AIM

Shared decision making for adults with severe mental illness has increasingly attracted attention. However, this concept has not been comprehensively clarified. This review aimed to clarify a concept of shared decision making for adults with severe mental illness such as schizophrenia, depression, and bipolar disorder, and propose an adequate definition.

METHODS

Rodgers' evolutionary concept analysis was used. MEDLINE, PsychINFO, and CINAHL were searched for articles written in English and published between 2010 and November 2019. The search terms were "psychiatr*" or "mental" or "schizophren*" or "depression" or "bipolar disorder", combined with "shared decision making". In total, 70 articles met the inclusion criteria. An inductive approach was used to identify themes and sub-themes related to shared decision making for adults with severe mental illness. Surrogate terms and a definition of the concept were also described.

RESULTS

Four key attributes were identified: user-professional relationship, communication process, user-friendly visualization, and broader stakeholder approach. Communication process was the densest attribute, which consisted of five phases: goal sharing, information sharing, deliberation, mutual agreement, and follow-up. The antecedents as prominent predisposing factors were long-term complex illness, power imbalance, global trend, users' desire, concerns, and stigma. The consequences included decision-related outcomes, users' changes, professionals' changes, and enhanced relationship.

CONCLUSIONS

Shared decision making for adults with severe mental illness is a communication process, involving both user-friendly visualization techniques and broader stakeholders. The process may overcome traditional power imbalance and encourage changes among both users and professionals that could enhance the dyadic relationship.

Digital Peer Support Mental Health Interventions for People With a Lived Experience of a Serious Mental Illness: Systematic Review

BACKGROUND

Peer support is recognized globally as an essential recovery service for people with mental health conditions. With the influx of digital mental health services changing the way mental health care is delivered, peer supporters are increasingly using technology to deliver peer support. In light of these technological advances, there is a need to review and synthesize the emergent evidence for peer-supported digital health interventions for adults with mental health conditions.

OBJECTIVE

The aim of this study was to identify and review the evidence of digital peer support interventions for people with a lived experience of a serious mental illness.

METHODS

This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedures. The PubMed, Embase, Web of Science, Cochrane Central, CINAHL, and PsycINFO databases were searched for peer-reviewed articles published between 1946 and December 2018 that examined digital peer support interventions for people with a lived experience of a serious mental illness. Additional articles were found by searching the reference lists from the 27 articles that met the inclusion criteria and a Google Scholar search in June 2019. Participants, interventions, comparisons, outcomes, and study design (PICOS) criteria were used to assess study eligibility. Two authors independently screened titles and abstracts, and reviewed all full-text articles meeting the inclusion criteria. Discrepancies were discussed and resolved. All included studies were assessed for methodological quality using the Methodological Quality Rating Scale.

RESULTS

A total of 30 studies (11 randomized controlled trials, 2 quasiexperimental, 15 pre-post designs, and 2 qualitative studies) were included that reported on 24 interventions. Most of the studies demonstrated feasibility, acceptability, and preliminary effectiveness of peer-to-peer networks, peer-delivered interventions supported with technology, and use of asynchronous and synchronous technologies.

CONCLUSIONS

Digital peer support interventions appear to be feasible and acceptable, with strong potential for clinical effectiveness. However, the field is in the early stages of development and requires well-powered efficacy and clinical effectiveness trials.

TRIAL REGISTRATION

PROSPERO CRD42020139037; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID= 139037.

Peer Support: a Human Factor to Enhance Engagement in Digital Health Behavior Change Interventions

The purpose of this report is to develop a theoretical model based on empirical evidence that can serve as a foundation for the science of peer-support factors that facilitate engagement in digital health interventions for people with serious mental illness (SMI). A review of the literature on how peer-support specialist interaction with consumers with SMI in digital health behavior change interventions enhances engagement. Unlike relationships with other health providers, peer-to-consumer relationships are based on reciprocal accountability -meaning that peer-support specialists and consumer mutually help and learn from each other. Under the recovery model of mental illness, reciprocal accountability suggests autonomy, flexible expectations, shared lived experience, and bonding influence engagement in digital interventions. Separate yet related components of reciprocal accountability in the context of digital health intervention engagement include (1) goal setting, (2) task agreement, and (3) bonding. Hope and sense of belonging are hypothesized moderators of peer-support factors in digital health interventions. Peer-support factors help people with SMI learn to live sucessfully both in the clinic and community. Peer-support specialists add value and complement traditional mental health treatment through their professional training and lived experience with a mental illness. The proposed model is a pioneering step towards understanding how peer-support factors impact engagement in digital health behavior change interventions among people with a lived experience of SMI. The model presents proposed factors underlying the reciprocal accountability processes in the context of digital health intervention engagement. This model and related support factors can be used to examine or identify research questions and hypotheses.