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. 2019 Jul 29;2019(7):CD013385. doi: 10.1002/14651858.CD013385

Decision coaching for people making healthcare decisions

Janet Jull 1,✉, Sascha Köpke 2, Laura Boland 3, Angela Coulter 4, Sandra Dunn 5, Ian D Graham 6, Brian Hutton 7, Jürgen Kasper 8, Simone Maria Kienlin 9,10, France Légaré 11, Krystina B Lewis 12, Anne Lyddiatt 13, Wakako Osaka 14, Tamara Rader 15, Anne C Rahn 16, Claudia Rutherford 17,18, Maureen Smith 19, Dawn Stacey 12
PMCID: PMC6662893

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To determine the effects of decision coaching when used to provide non‐directive support to help people prepare to make decisions related to their health care.

Background

This is a protocol for a Cochrane Review. The objective is to assess the effectiveness of decision coaching when used to provide non‐directive support to help people prepare to make decisions related to their health care.

Description of the condition

People who are patients in the healthcare system continuously report inadequate involvement in healthcare decisions, despite there being numerous opportunities for such involvement (Foot 2014). Healthcare systems around the world call for improved patient engagement and increased efforts to support those making healthcare decisions (e.g. ACSQHC 2018; Chow 2009; Frosch 2011; Härter 2011; NICE 2018; Oslo University Hospital 2018). There is a need to identify effective interventions to support health decision making. Patient involvement in healthcare decisions combines evidence‐based medicine and patient‐centred care (Hoffmann 2014).

Shared decision making (SDM) is a process by which patients and those who provide their health care (clinicians, or 'healthcare providers') work together to make decisions about tests, treatments, or management of chronic conditions (i.e. SDM concerns not just medical treatments but also support for people with long‐term or palliative conditions). SDM is based on the best available evidence on healthcare options and the patients' informed preferences (Coulter 2011). SDM has been shown to improve patient outcomes and experience (Stacey 2017); improve the experiences and effectiveness of health professionals in their communication with patients; and optimize costs in health care (Légaré 2012; Légaré 2014; Légaré 2018). Patient decision aids and decision coaching are interventions that may be used to facilitate SDM. Decision coaching is an intervention that is delivered by trained healthcare providers to patients who are facing a healthcare decision. In this protocol, we will use the definition of the World Health Organization (WHO). 'Healthcare provider', according to the WHO, refers to health support workers (e.g. peer support worker, lay health worker), or members of a healthcare profession (e.g. audiology and speech language pathology, dentistry, medicine, nursing, midwifery, occupational and physical therapy), or both (WHO 2018). Patient decision aids are tools that may be used alone or in a consultation with a healthcare provider. Healthcare providers who deliver decision coaching may or may not use a tool such as a patient decision aid as part of the decision coaching session. Despite the benefits and effectiveness of SDM, there have been low levels of uptake of SDM interventions such as decision coaching or patient decision aids. The use of patient decision aids in clinical practice remains limited (Couet 2013). While there is moderate‐quality evidence that patient decision aids increase patient participation in decision making (Stacey 2017), there is uncertainty about the effects of decision coaching as a preparatory intervention for supporting patients who are faced with making healthcare decisions.

Description of the intervention

Decision coaching is provided by a trained healthcare provider. Decision coaching is non‐directive guidance and support to help prepare patients who are making health decisions. The use of decision coaching aims to prepare patients to actively participate in making decisions with their healthcare provider (that is, SDM) and to achieve informed, values‐based decisions (i.e. decisions that are in accordance with the person's values). Decision coaching differs from patient decision aids; decision coaching supports patients who are preparing to make health decisions and decision coaches are trained to be non‐directive, to provide evidence, and to support patients rather than offer advice. The concept of decision coaching is that, as an approach, it is likely to lead to patients making choices consistent with their own values and beliefs. Decision coaching is a distinct process in that it is preparing patients to engage in the SDM process with the healthcare provider.

Key characteristics and components of decision coaching include the following:

  • delivered by a healthcare provider who provides non‐directive guidance and support that helps prepare patients to participate actively in making healthcare decisions;

  • supports the use of healthcare information, facilitates identification of patients' needs in health decisions, clarifies patients' values and beliefs, guides in deliberation, and encourages patients to communicate their preferences to others (family, clinicians);

  • interacts by using face‐to‐face, telephone or other communication media between the decision coach and patients (i.e. not automated electronically);

  • can be used alone or may include the use of other decision support tools such as patient decision aids; and

  • uses decision coaches who are trained in knowledge and skills for supporting patients in the process of health decision making.

An example of a decision coaching intervention can be found here: decisionaid.ohri.ca/docs/decision_coaching_script.pdf.

While evidence on the effects of decision coaching is limited to a sub‐analysis of 10 trials from an outdated systematic review of patient decision aids (Stacey 2012), the indicators for its potential effectiveness in facilitating patient involvement in SDM are promising. The sub‐analysis (Stacey 2012) showed that when used alone, decision coaching increased patient knowledge. Further, when decision coaching was combined with a patient decision aid, decision coaching increased patients’ understanding of, and participation in, their care (Stacey 2012). There were mixed results for other outcomes, but no harms were reported. In another example, a study on evidence‐based patient information and decision support in multiple sclerosis has shown that providing information or decision tools (or both) to patients may not be sufficient to achieve informed decision making about treatment (Kasper 2008). Instead, the addition of opportunities to discuss and process the treatment options may increase informed choice and participation (Köpke 2017). In addition, decision coaching has been purported to increase the effectiveness of consultations between patients and physicians (O'Connor 2008). Other studies have shown that populations who face barriers to participation in healthcare decisions may be helped when provided with non‐directive support in the form of decision coaching (Belkora 2013; Belkora 2015; Dartmouth‐Hitchcock 2018; Feenstra 2015; Jull 2015; Jull 2019; Rahn 2017). Decision coaching aligns well with the expected competencies of most healthcare providers who are expected to provide evidence‐based information and to support people’s chosen level of participation (Joseph‐Williams 2014; Politi 2013). Nevertheless, despite its promise, uncertainties exist about the effects of decision coaching as a preparatory intervention for supporting patients who are facing healthcare decisions. Therefore, it is essential to systematically assess the literature to determine the current evidence across studies evaluating decision coaching.

How the intervention might work

Decision coaching provides support and guidance in the process of decision making in order to increase patient participation and improve the quality of the outcome (e.g. decision quality) and the process. This is consistent with the Ottawa Decision Support Framework (ODSF), a theoretically‐based framework that describes how to support people facing health and social decisions and involves three key elements: decisional needs, decision support (e.g. counselling, decision coaching, patient decision aids), and decision‐making process and outcomes (O'Connor 2008). The ODSF is based on the construct of decisional conflict (NANDA 2005), and concepts from theories in general psychology (Tversky 1981), social psychology (Ajzen 1980), decision analysis (Keeney 1982), decisional conflict (Janis 1977), values (Fischoff 1980), social support (Norbeck 1988; Orem 1995), and self‐efficacy (Bandura 1982).

The ODSF asserts that decision making can be adversely affected by the following factors: decisional conflict (that is, uncertainty about the best course of action); inadequate knowledge and unrealistic expectations; unclear values; inadequate support or resources; complex decision type; urgent timing; unreceptive stage of decision making; polarized leaning toward an option; and participants' characteristics (e.g. patients' cognitive limitations, poverty, limited education, or physical incapacitation) (Stacey 2009). When used to assess patient and provider determinants of decisions to identify decision support needs, the ODSF hypothesizes that unresolved decisional needs may negatively influence decision quality, and that decision support, using counselling, decision tools or decision coaching, addresses unresolved decisional needs (Stacey 2009). The ODSF may also be used to evaluate the decision‐making process and outcomes (Stacey 2009).

Why it is important to do this review

The proposed review is focused on investigating the effect of decision coaching on multiple outcomes (e.g. preparation for decision making). There is no comprehensive synthesis of evidence on decision coaching.

Existing reviews have captured aspects of decision coaching (Coulter 2015; Légaré 2018; Stacey 2017); yet none have specifically focused on decision coaching as an intervention and have not clearly described and analyzed the interventions used in primary studies. The Cochrane Review of interventions to improve adoption of SDM is focused on the effects of any intervention on the outcome of SDM (Légaré 2018). The review of interventions to improve adoption of SDM may include decision coaching, however the only outcome reported on is SDM: if decision coaching is included, it is part of multiple interventions, which makes it difficult to determine the effect of coaching on various outcomes. The Cochrane Review of patient decision aids by Stacey and colleagues focused on what effect the intervention (patient decision aids) has on multiple outcomes related to SDM (e.g. decision quality and decision‐making process) (Stacey 2017). In the review of patient decision aids, some studies have included decision coaching as part of the intervention in one arm but the effect of decision coaching is not the focus of the review and so the effects are not reported. In the Cochrane Review about personalized care planning by Coulter and colleagues, the focus is on finding out whether a personalized approach, in which patients are encouraged to participate in setting goals and action plans and determine their support needs, leads to better outcomes than when these decisions are made by health professionals alone (Coulter 2015). While Coulter 2015 has a focus on interventions to support collaborative care, it is not focused on elements of decision coaching, nor does it focus on behaviours of decision coaching that are demonstrated by a trained healthcare provider but instead on behaviours of patients. In addition, decision coaching, shared decision making, patient decision aids, and personalized care planning have conceptually different definitions, and so there is a need to separately synthesize the evidence to support these different interventions.

In summary, none of the previously conducted reviews explicitly measured effectiveness of decision coaching. Decision coaching is an intervention that has the potential to facilitate patient participation in decision making and to achieve quality decisions. This review will be of interest to various stakeholders, given the increased focus on engagement of patients in healthcare. Policy makers and decision makers are seeking an innovative approach to advance consumer engagement and enhance health literacy (Coulter 2008). Healthcare consumers and providers will be interested in approaches that are likely to enhance or better support the active participation of people making healthcare decisions (Chen 2016; Coulter 2015; Krist 2017). Decision coaching has the potential to support these outcomes.

Objectives

To determine the effects of decision coaching when used to provide non‐directive support to help people prepare to make decisions related to their health care.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomized controlled trials (RCTs) with any kind of allocation method, e.g. individual, cluster, or stepped‐wedge. We will exclude studies other than RCTs.

Types of participants

We will include adults and children preparing to make a healthcare decision regarding treatment, screening, or diagnosis. The decision can be for themselves or a family member and may include the option to do nothing. We will exclude anyone who is making a lifestyle decision only, a decision about participation in research, a decision that is hypothetical, or a decision where there is only one option. We will exclude studies conducted using simulated patients (e.g. a healthy person who is trained to realistically reproduce a medical scenario, to provide learning opportunities for faculty and students). 

Types of interventions

To be included in the review, the decision coaching intervention must meet the following criteria as a minimum:

  • be delivered by a healthcare provider who is trained in decision coaching;

  • helps to prepare the patient to make a health decision;

  • comprise non‐directive support in preparation for decision making; and

  • be delivered person‐to‐person (i.e. not automated but in a person‐to‐person manner, whether face‐to‐face, by telephone, or via the internet).

Different terms may be used in place of 'decision coaching', such as 'health counselling', 'support', and 'navigation' (Stacey 2013).

We will exclude articles that describe healthcare providers who: are making the decision with, or on behalf of, the patient; are not trained in decision coaching; are recommending a specific treatment; or are not described as having direct interests in providing decision coaching (e.g. family members/substitute decision‐maker of the person making the decision). We will also exclude articles that describe automated support.

Any comparison will be included, i.e.:

  • decision coaching compared with any usual care or other control;

  • decision coaching compared with another intervention type, such as a patient decision aid;

  • decision coaching plus a patient decision aid, compared with the patient decision aid alone; or

  • decision coaching plus another decision tool, compared with the decision tool alone.

Types of outcome measures

We will take the following steps before including primary outcomes in the 'Results' and 'Summary of findings' tables.

1. We will categorize outcomes. Where no primary outcomes are identified in the article, we will select the outcome(s) specified in the sample size calculation. Where an article reports more than one outcome within an outcome category, we will report all of them and make a decision about which is most relevant to patients. Two review authors will independently assign the outcomes reported in each included study to the review's outcome categories and resolve any differences in categorization by the involvement of a third author.

2. We will select outcome measures with which to report data in both the 'Results' and 'Summary of findings' tables. If the outcomes of interest are reported with only one measure by the article then no further action is needed. If reported with more than one measure in the same trial, the outcome measures for each article will be listed and two review authors will independently make decisions about what is most relevant to patients; any differences will be resolved by the involvement of a third author.

Primary outcomes

  • Preparation for health decision making (patient reported). Outcomes may include any of the following: recognize that a decision needs to be made, feels prepared to make decision, helped to consider advantages and disadvantages, consider which advantages and disadvantages matter the most, organize thoughts about the decision, think about how involved they want to be in the decision, prepare to talk with a healthcare provider about the decision, and identify questions to ask (Graham 1995).

  • Resolution of modifiable decisional needs (patient reported). Modifiable decisional needs according to the ODSF include: decisional conflict; uniformed, unrealistic expectations; unclear values; inadequate support/resources (O'Connor 2008).

  • Quality of decision coaching (observer reported). To be included, this outcome has to be reported by an observer or measured by an observer with an instrument, such as the Decision Support Analysis Tool (DSAT‐10) (Guimond 2003; Stacey 2008).

  • Any reports of adverse effects on patient or decision coach, including worsening decisional needs, and/or effects reported in the primary studies, e.g. increased anxiety (see items in second bullet point, above).

Secondary outcomes

  • Patient‐reported satisfaction with decision coaching, and health systems resources (e.g. length of time and cost, quality of life, SDM).

Main outcomes for the ‘Summary of findings’ table

  • Preparation for health decision making (patient reported).

  • Resolution of modifiable decisional needs (patient reported).

  • Quality of decision coaching (observer reported).

  • Any reports of adverse effects on patient or decision coach, including worsening decisional needs, and/or effects reported in the primary studies, e.g. increased anxiety.

If multiple outcomes are reported in a given outcome category, we will collect information on all relevant outcomes. If the same outcome is assessed by two or more outcome measures in the same trial, two review authors will: select the primary outcome measure that has been identified by the publication authors; select the one specified in the sample size calculation when no primary outcome measure has been identified; and rank effect estimates (i.e. list them in order from largest to smallest) and select the median effect estimate if no sample size calculations are reported. When an even number of outcome measures is reported, the outcome measure whose effect estimate is ranked n/2, where n is the number of outcome measures, will be selected.

Search methods for identification of studies

Electronic searches

We will conduct a comprehensive search strategy with a librarian (AP), which has been peer reviewed by a second librarian (TR), according to the Peer Reviewed Electronic Search Strategy (PRESS) guidelines (McGowan 2016). We will search from database inception to current search date. To identify relevant studies, we will search the following databases: the Cochrane Library (Wiley), Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid), Embase (Ovid), PsycINFO (Ovid), CINAHL (Ebsco), and Nursing and Allied Health Source (ProQuest). We present the strategy for MEDLINE (Ovid) in Appendix 2. We will tailor strategies to other databases and report them in the review. We will not restrict the search by publication type or language.

Citation searching

We will perform a cited reference search in Web of Science, PubMed, using the related articles function with known, relevant papers.

We will search online trial registers for ongoing and recently completed studies, including the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP), and ClinicalTrials.gov.

Searching other resources

We will search the following grey literature sources.

  • Cochrane Effective Practice and Organization of Care (EPOC) Group Specialized Register.

  • Society for Medical Decision Making.

  • Center for Shared Decision Making.

  • International Patient Decision Aid Standards (IPDAS) Collaboration list serve archive.

  • International Shared Decision Making conference proceedings.

  • ProQuest Dissertation Theses database.

  • TRIP Database ‐ Clinical Search Engine.

  • National Institute for Health and Care Excellence (NICE). Evidence search: Health and Social Care.

  • PROSPERO: international prospective register of systematic reviews.

We will contact experts in the field and authors of included studies for advice as to other relevant studies. We will also search reference lists of relevant studies and add other sources (e.g. personal collections of articles).

Data collection and analysis

Selection of studies

At least two members of the author team, randomly allocated, will independently screen titles and abstracts identified from searches to determine which meet the inclusion criteria. Citations will be reviewed against clearly identified and pre‐tested inclusion and exclusion eligibility criteria using an online systematic review software package, Covidence 2018. We will retrieve the full text of any studies identified as potentially relevant by at least one author. Two review authors will be randomly allocated to screen full‐text studies for inclusion or exclusion, with discrepancies resolved by discussion with a third review author to reach consensus. All studies excluded from the review at this stage will be listed as excluded, with reasons.

To mitigate differences between reviewers in the screening process, team members who are involved with screening will perform pilot calibration exercises on a random sample of 100 references. They will apply the inclusion and exclusion criteria to a common set of titles and abstracts. The level of agreement (whether the article was included or excluded) will then be calculated; the aim is to reach at least 90% agreement on the rating of a sample of references. This process of calibration on 100 articles will be repeated until the goal of at least 90% is reached. The screening and selection process will be documented in sufficient detail to complete a PRISMA flow chart (Liberati 2009) and ‘Characteristics of excluded studies’ tables. We will also provide citation details and any available information about ongoing studies, and collate and report details of multiple study publications that report on one study, so that each study (rather than each report) is the unit of interest in the review.

Data extraction and management

Two review authors will independently extract data from included studies and will use Covidence 2018. Any discrepancies will be resolved by discussion until consensus is reached, or through consultation with a third review author, when necessary. Review authors will not extract data from their own studies. We will develop and pilot a data extraction form using the Cochrane Consumers and Communication Review Group Data Extraction Template (available at: cccrg.cochrane.org/author‐resources) and including criteria from PRISMA Equity (Welch 2015). The Data Extraction Template includes criteria from the template for intervention description and replication (TIDieR) (Hoffmann 2014) to clearly describe intervention components and specific aspects, e.g. mode of delivery or intensity ('dose') of support. Should the authors report the costs and resource use, data on economic evaluations, or a combination of these, then we will report on these items (i.e. as secondary outcomes). The extracted data will include the following items.

  • General review information (journal, study contacts, year, country where the study was conducted).

  • Methods of the study (aim of study, design, involvement of others who may use the review — for example, the study funder or a member of a decision‐making body — and whether there are ethical approvals).

  • Information relating to the 'Risk of bias' assessment (Higgins 2011a).

  • Characteristics of participants (recipients of decision coaching), for example, using a social determinants of health framework such as "PROGRESS‐Plus". "PROGRESS" is an acronym for place of residence; race/ethnicity/culture/language; occupation; gender/sex; religion; education; socioeconomic status; and social capital (Evans 2003). "Plus" provides additional context‐specific personal or setting characteristics that may be associated with health  and are relevant to our study. These include 1) individual characteristics (e.g. disability, age), 2) features of relationships between people and their settings or other people (e.g. being excluded from school), and 3) time‐dependent transitions, (e.g. migration and/or refugee status) (Gough 2012; Oliver 2008). We will include numbers involved (identify included, excluded groups, randomized to which group, withdrawn etc.) and also includes details (e.g. health issues).

  • Characteristics of the decision coaching intervention and any other intervention(s) used alongside or in comparison with decision coaching. For example, theoretical basis, implementation strategy, duration, dose, etc. This includes characteristics of decision coaches (using a social determinants of health framework such as PROGRESS Plus, see above) and reported using the TIDieR framework criteria, 12 items that report on name, why, what (materials), what (procedure), who provided, how, where, when and how much, tailoring, modifications, how well (planned), how well (actual) (Hoffmann 2014). Decision coaching is a complex intervention and the use of TIDieR criteria will structure reporting of intervention characteristics, and that includes any training or preparation for delivering the intervention, as well as fidelity for delivery of the intervention and fidelity to the decision coaching process. Characteristics of the comparators will also be described in this manner.

  • Primary and secondary outcomes, as stated in Types of outcome measures.

  • Outcome measures for both primary and secondary outcomes (i.e. method of assessment, follow‐up for non‐respondents, timing of outcome measures, information on validity and reliability of instruments used).

All extracted data will be entered into Covidence 2018 and transferred into Review Manager 2014 by one review author, and will be independently checked for accuracy against the data extraction sheets by a second review author.

Assessment of risk of bias in included studies

We will assess and report on the methodological risk of bias of included studies, in accordance with the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a) and the Cochrane Consumers and Communication guidelines (Ryan 2013), which recommend the explicit reporting of the following individual elements for RCTs: random sequence generation; allocation sequence concealment; blinding (participants, personnel, and outcome assessment); completeness of outcome data, selective outcome reporting; and other sources of bias (such as whether the same healthcare provider delivered the decision coaching intervention and the comparator, whether clustering was accounted for in the analysis, and other potential sources of bias reported by the study authors). We will consider blinding separately for different outcomes where appropriate (for example, blinding may have the potential to differently affect subjective versus objective outcome measures). Completeness of outcome data (avoidance of attrition bias) will be considered separately for different lengths of follow‐up (shorter and longer follow‐up). We will consider the outcomes in terms of timing of assessment. For example, if multiple time points are reported, then the ones immediately post‐intervention and then at longest‐follow up will be reported. We will judge each item as being at high, low, or unclear risk of bias, as set out in the criteria provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will provide a quote from the study report and a justification for our judgement for each item in the 'Risk of bias' table.

We will consider studies to be at high risk of bias if they are judged as having high or unclear risk of bias regarding sequence generation or allocation concealment, based on growing empirical evidence that these factors are particularly important potential sources of bias (Higgins 2011a). For cluster‐RCTs we will also assess and report the risk of bias associated with an additional domain: selective recruitment of cluster participants. In all cases, two review authors will independently assess the risk of bias of included studies, with any disagreements resolved by discussion with a third author to reach consensus. We will contact study authors for additional information about the included studies, or for clarification of the study methods as required.

Measures of treatment effect

We will use Review Manager 5 for analysis (Review Manager 2014). For dichotomous outcomes, we will analyze data based on the number of events and the number of people assessed in the intervention and comparison groups. We will use these to calculate the risk ratio (RR) and 95% confidence interval (CI). For continuous measures, we will analyze data based on the mean, standard deviation (SD) and number of people assessed for both the intervention and comparison groups to calculate mean difference (MD) and 95% CI. If the MD is reported without individual group data, we will use this to report the study results. If more than one study measures the same outcome using different tools, we will calculate the standardized mean difference (SMD) and 95% CI using the inverse variance method in Review Manager 5.

Unit of analysis issues

If we include cluster‐RCTs or studies with multiple treatment groups we will apply the methods recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2017). Specifically, we will check for unit‐of‐analysis errors. If errors are found, and sufficient information is available, we will re‐analyze the data using the appropriate unit of analysis, by taking account of the intra‐cluster correlation coefficient (ICC). We will obtain estimates of the ICC by contacting authors of included studies, or impute them using estimates from external sources. If it is not possible to obtain sufficient information to re‐analyze the data we will not include studies in meta‐analysis. In case of a narrative summary the unit of analysis error will be annotated.

Studies with multiple treatment groups

If a study compares two or more eligible intervention groups to one eligible control group, we will split the sample size for the shared comparator group, as outlined in chapter 16.5 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We will compare the decision coaching intervention to usual care or to other interventions (e.g. the use of patient decision aids).

Dealing with missing data

We will attempt to contact study authors to obtain missing data. For participant data, we will, where possible, conduct analysis on an intention‐to‐treat basis; otherwise data will be analyzed as reported. We will report on the levels of loss to follow‐up and assess this as a source of potential bias. For missing outcome or summary data we will impute missing data where possible and report any assumptions in the review. We will investigate, through sensitivity analyses, the effects of any imputed data on pooled effect estimates.

Assessment of heterogeneity

Where studies are considered similar enough (based on consideration of populations, interventions, outcomes) to allow pooling of data using meta‐analysis, we will assess the degree of heterogeneity by visual inspection of forest plots and by examining the Chi² test and the I² statistic for heterogeneity for each outcome (Gentles 2013; Hatala 2005). An I² value of 50% or more will be considered to represent substantial levels of heterogeneity, but this value will be interpreted in relation to the size and direction of effects and the strength of the evidence for heterogeneity, based on the P value from the Chi² test (Deeks 2017). Reasons for deciding that studies were similar enough to pool statistically will be reported. Where we detect substantial clinical, methodological or statistical heterogeneity across included studies we will not report pooled results from meta‐analysis but will instead use a narrative approach to data synthesis (Hatala 2005). In this event, we will clearly report reasons for deciding that studies were too dissimilar to meta‐analyze. We will also attempt to explore possible clinical or methodological reasons for this variation by grouping studies that are similar in terms of populations, intervention, and outcome measures to explore differences in intervention effects.

Assessment of reporting biases

In order to minimize language bias, we will include studies in any language. We will assess reporting bias qualitatively, based on the characteristics of the included studies (e.g. if only small studies that indicate positive findings are identified for inclusion), and if information that we obtain from contacting experts and authors of studies suggests that there are relevant unpublished studies. We will link to registered protocols to determine whether studies report what was originally planned. If we identify sufficient studies (at least 10) for inclusion in the review, we will construct a funnel plot to investigate small‐study effects, which may indicate the presence of publication bias. We will formally test for funnel plot asymmetry, with the choice of test made based on advice in the Cochrane Handbook for Systematic Reviews of Interventions (Sterne 2011), bearing in mind that there may be several reasons for funnel plot asymmetry when interpreting the results.

Data synthesis

Meta‐analysis of primary and secondary outcomes will be conducted, where possible, based on whether the interventions in the included trials are similar enough in terms of participants, settings, intervention, comparison and outcome measures to ensure meaningful conclusions from a statistically pooled result. Due to the anticipated variability in the populations and interventions, we will use a random‐effects model for meta‐analysis.

Subgroup analysis and investigation of heterogeneity

Where heterogeneity is present in pooled effect estimates, we will explore possible reasons for variability by conducting subgroup analysis. The following subgroup analyses are proposed, based on the ODSF theory and the expertise of members of the author team who are active in the development, implementation, and evaluation of decision coaching:

  • types of decisions (treatment, screening, diagnostic);

  • method of intervention delivery (in person, by telephone, internet‐based); and

  • characteristics of participants who are recipients of the intervention and who delivered the intervention, i.e. sex and/or gender, education, socioeconomic status, occupation of decision coaches (healthcare providers who are health support workers versus healthcare professionals).

Sensitivity analysis

Sensitivity analyses will be used to assess the robustness of the results, for example, to examine the effect of including compared to excluding studies at high risk of bias (that is, if different decisions are made about the analysis, how much does this affect the results?). Sensitivity analyses will also be used to assess the effects of any imputed data on pooled effect estimates.

'Summary of findings' table

We will prepare a 'Summary of findings' table to present the results of meta‐analyses or narrative syntheses (or both) for the major comparisons of the review, for each of the primary markers (e.g. preparation in health decision making), including potential harms, outlined in Types of outcome measures (Ryan 2016). We will provide a source and rationale for each assumed risk cited in the table(s), and will use the GRADE criteria to rank the quality of the evidence based on the methods described in chapter 11 of the Cochrane Handbook for Systematic Reviews of Interventions, using GRADEpro GDT software (GRADEpro GDT 2015; Schünemann 2011). If meta‐analysis is not possible, we will present results in a narrative ‘Summary of findings’ table format.

Ensuring relevance to decisions in health care

The protocol and review will receive feedback from at least one consumer referee, in addition to a health professional, as part of Cochrane Consumers and Communication’s standard editorial process.

Acknowledgements

We thank the editors and staff of Cochrane Consumers and Communication, particularly the Managing Editor, Bronwen Merner, for their input to this protocol.

We thank Anne Parkhill for the Information Specialist support.

Appendices

Appendix 1. MEDLINE search strategy

Ovid MEDLINE® In‐Process & Other Non‐Indexed Citations and Ovid MEDLINE® 1946 to Present:

‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐

Jull_Medline_final 1. *Decision Making/ 2. decision support techniques/ 3. (decision* or decid* or choice or choose or prefer*).ti. 4. (informed adj (choice* or decision*)).tw. 5. or/1‐4 6. Directive Counseling/ or *Counseling/ 7. *Health Education/ 8. Patient Education as Topic/ 9. *Patient Participation/ 10. *Physician‐Patient Relations/ 11. "Referral and Consultation"/ 12. (assess* or coach* or guidance or counsel* or prepar*).ti. 13. or/6‐12 14. and/5,13 15. randomized controlled trial.pt. 16. controlled clinical trial.pt. 17. randomized.ab. 18. placebo.ab. 19. drug therapy.fs. 20. randomly.ab. 21. trial.ab. 22. groups.ab. 23. or/15‐22 24. exp animals/ not humans.sh. 25. 23 not 24 26. and/14,25

What's new

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30 July 2019 Amended Updated affiliations
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Contributions of authors

The work presented here is the result of shared interests of an international network of healthcare consumers, providers, decision makers, and researchers with expertise in the topics of SDM, research methodology, Cochrane Reviews, and knowledge translation ('knowledge users'), and who are all authors on this review. All authors have discussed and agreed upon their roles in this review, as follows.

Contributions

JJ wrote and co‐ordinated the protocol development.

JJ, SK, LB, AC, SD, IG, BH, JK, SK, FL, KL, AL, WO, TR, AR, CR, MS, DS contributed to the decisions leading to the design of the protocol and agreed to the final version of the protocol.

Roles for this review

Consumers on this review: AL, MS.

Team leaders: JJ, SK, DS, MS.

Project co‐ordinator: JJ.

International collaborative research group: CR, LB, AC, SD, IG, BH, JK, SK, FL, KL, WO, TR, AR.

JJ is the guarantor for this review. JJ will be responsible for conducting the review update.

Sources of support

Internal sources

  • No sources of support, Other.

    None

External sources

  • No sources of support, Other.

    None

Declarations of interest

Janet Jull: none known. Sascha Köpke: has received fees for lectures and presentations on shared decision making. Laura Boland: none known. Angela Coulter: none known. Sandra Dunn: none known. Ian D Graham: none known.

Brian Hutton: none known.

Jürgen Kasper: none known. Simone Maria Kienlin: none known. France Légaré: none known. Krystina B Lewis: none known. Anne Lyddiatt: none known. Wakako Osaka: none known. Tamara Rader: none known.

Anne C Rahn: none known.

Claudia Rutherford: none known. Maureen Smith: receives honoraria from the Ontario Ministry of Health and Long‐Term Care to attend meetings, has received travel scholarships to attend conferences as a consumer, and receives an honorarium for roles as a co‐investigator and a knowledge user on two Canadian Institute of Health Research grants. Dawn Stacey: is a Professor in the School of Nursing at the University of Ottawa and Senior Scientist at the Ottawa Hospital Research Institute where she conducts funded studies to evaluate the effectiveness of patient decision aids and decision coaching, evaluate use of cancer symptom management tools, and evaluate implementation of knowledge tools in clinical practice. The institution where she is employed, the University of Ottawa, has received funding to support her research studies from national granting agencies and cancer programs. She has received funding for consultation with the Washington State Health Care Authority for the development and implementation of criteria for certifying patient decision aids. She received funding from the Oncology Nursing Society for providing a presentation as part of a panel focused on implementation science. Finally she received funding to travel to the Shared Decision Making Advisory Board Meeting in Vejle, Denmark.

Notes

This protocol is based on standard text and guidance provided by Cochrane Consumers and Communication (CCCG 2016).

Edited (no change to conclusions)

References

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