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Training and supportive programs for palliative care volunteers in community settings

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Abstract

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

To assess the effects of training and support strategies for palliative care volunteers on palliative care clients and their families, volunteers and service quality.

Background

Palliative care is specialised health care to support people living with a terminal illness and their families. The World Health Organisation defines palliative care as an approach that improves the quality of life of clients and their families facing life‐threatening illness (Sepúlveda 2002; WHO 2009). Palliative care aims to prevent and relieve suffering, to help people to live as well as possible until they die, and to support the processes of dying and bereavement. The involvement of volunteers in formal programs can extend the range of activities offered by palliative care services (Freeman 1998; Chittazhathu 2005; Baines 2010; Wittenberg‐Lyles 2010) and volunteers can comprise a considerable proportion of the palliative workforce headcount in some jurisdictions (DHS 2009). People in such volunteer roles are likely to need support, and this review seeks to determine the most effective way to provide support to palliative care volunteers without compromising the focus on quality palliative care services for clients and families.

Despite wide use of the term 'volunteer', there is no internationally recognised definition, but most existing definitions address four common issues: free will; availability and nature of remuneration; closeness of the recipient of volunteer services; and an affiliation with a formal agency (Hustinx 2010). This review defines a palliative care volunteer as someone who undertakes activities of benefit to the community of their own free will, with no financial payment (excluding reimbursements or nominal payments for expenses), in a designated volunteer position in a palliative care service or program in community settings.

A range of different service models for palliative care have developed (Higginson 2003; DoH 2008), which operate across a range of settings, including hospitals, hospices, homes, and residential aged care. The inclusion of bereavement within the scope of palliative care extends the reach to encompass resources for families after the death, in an attempt to minimise risks associated with complicated bereavement outcomes (O'Connor 2009). Multidisciplinary teams are common (Pastrana 2008) and many countries, both high and low income, include volunteers in their palliative care workforce (Igoe 1997; Francke 2000; Bollini 2004; Gorospe 2006; DHS 2009; Luijkx 2009; Block 2010; Di Sorbo 2010; McKee 2010; Sévigny 2010; Wittenberg‐Lyles 2010). The focus of this review is support for volunteers working with clients and their families in community settings, recognising that some clients may require inpatient palliative care services at some time. Community care is located in sites where people live or meet, as these contexts are where volunteers perform the broadest range of activities, are more likely to have more autonomy, and have less ready access to health professional support (Weeks 2008; Sévigny 2010).

The activities undertaken by palliative care volunteers in the community vary considerably across jurisdictions, and can be practical, social or emotional in nature. The involvement of palliative care volunteers can be directed to three main areas: the palliative patient; the patient's family or carers; and the palliative care organisation itself. This review is concerned with those palliative care volunteers working directly with clients and their families in their homes or community settings. These volunteers can be involved with clients in a number of ways. They can provide some form of practical basic patient care, such helping with feeding or grooming (Herbst‐Damm 2005). They can provide emotional support, by helping to discuss difficult issues (Luijkx 2009); social support, such as companionship (McKee 2010); or practical support, such as transporting clients and their families to and from appointments (Worthington 2008). Palliative care volunteers can provide similar types of support to families and carers before death (Luijkx 2009) and can also provide bereavement support (Weeks 2008).

There are practical reasons for including volunteers in palliative care teams and their widespread use means that it is not feasible to assess the effectiveness of their involvement in palliative care directly, however there is some indication that they contribute positively to palliative care goals. Small but significant positive benefits from palliative care teams for clients, in terms of reducing pain and relieving other symptoms, were shown in a review of 44 studies, particularly for those cared for at home, including at least three studies which had volunteers in the palliative care team (Higginson 2003). Assessing the impact of palliative care and subsequent volunteer involvement in other non‐symptom related goals of palliative care poses significant challenges (Wong 2004; Albers 2010; Hales 2010) as there is little agreement on the most appropriate measures to use (Aspinal 2003; Higginson 2003; Jocham 2009; Pastrana 2010). However two measures related to the palliative care goal of living as well as possible until death may be influenced by the availability of volunteers: length of survival (Herbst‐Damm 2005) and place of death (Gomes 2009).

The types of support provided to palliative care volunteers are likely to affect their effectiveness in their role and influence the quality of care provided to palliative clients and their families.

Description of the intervention

Almost all organisations or agencies providing a palliative care volunteer program offer an orientation program to new recruits, which can be considered to be 'usual care'. This review is concerned with training and additional forms of support. The purpose of programs can be threefold: to develop skills in specific tasks to be undertaken; to enhance capacity to cope with the dying process and subsequent death; and to maintain service quality.

The focus of skill development is the specific needs of people who are dying and their families (Kumar 2007; Rolls 2008; Berry 2009). It can include communication training (Herbst‐Damm 2005; Worthington 2008), or training on how to provide bereavement support (Weeks 2008).

Strategies to enhance coping seek to address the needs of volunteers, most commonly to help them to cope with death, and include screening for suitability for particular roles (Caidwell 1994; McCallum 1989), help with anxieties around death (Claxton‐Oldfield 2007), and offering peer or mentor support (Seibold 1987).

Support programs with an organisational focus on service quality may involve team‐building or emphasise harm minimisation, for example by introducing codes of conduct (Fusco‐Karmann 1998) or volunteer standards (DHS 2009), or by raising awareness of ethical issues (Freeman 1998; Gorospe 2006; Berry 2009).

How the intervention might work

Skill development programs for palliative care volunteers are similar to other training programs and are likely to work by increasing the knowledge, confidence and competence of palliative care volunteers to undertake their roles.

Strategies to support coping are likely to work by increasing volunteers' resilience to manage emotionally‐demanding situations. Four reasons have been identified for high attrition among palliative care volunteers in some services: under‐utilisation of volunteers by palliative care teams; late placement with patients; feelings of being undervalued by other palliative care team members; and restrictions in what can be done in the volunteer role (Claxton‐Oldfield 2008). These are all unrelated to the capacity of volunteers to cope with dying people, or the skills needed for the role, and suggest that strategies that promote organisational support, such as involvement in palliative care team meetings, may be relevant.

Organisation support strategies may make better use of volunteers and may also improve the quality of palliative care. One study suggests four ways that volunteer visits might lead to longer survival (Herbst‐Damm 2005). Volunteers may directly influence clients by increasing clients’ feelings of control; by enhancing clients’ emotional well‐being; or by enhancing clients’ appreciation for loved ones by helping them to find meaning (Mackay 2010). These three activities have potential to strengthen immune function. The fourth mechanism is indirect; through providing support to family caregivers, volunteers may relieve the burden of caring and so improve caregivers’ well‐being, which in turn may improve quality of care and support for clients.

Why it is important to do this review

While documenting the experiences of palliative care volunteers is important, the primary reason to invest in palliative care volunteers is to ensure the provision of quality palliative care for clients and families, while enhancing the volunteer experience. The provision of support to palliative care volunteers can have considerable resource implications for palliative care organisations, and while volunteers can extend the reach of a service considerably it is important that any support provided to them is as effective as possible.

The role of volunteers is likely to grow. While palliative care was traditionally associated with cancer care, noticeable changes have occurred in the client population accessing such services (Addington‐Hall 2002), in a manner consistent with the ageing demographic profile found in high‐income countries, and the growing life spans in mid‐ and low‐income countries. Demand has also been fuelled by equity expectations that quality dying is available to all, not just people with cancer; this is echoed internationally in population‐based government policies (DoH 2008; Gomez‐Batiste 2008; DoHA 2009).

Socio‐cultural and demographic changes will affect the future of palliative care in two main ways. First, demand will be higher as the call for a 'good death' becomes more common, and second, the proportion of the population available for the health workforce overall will decrease, and are likely to be prioritised to areas concerned with managing chronicity and maintaining life, rather than quality of care at the end of life. Service models for palliative care already use volunteers throughout the world, and this trend is likely to increase with many groups of people who have traditionally been volunteers becoming older and more frail. As palliative care extends its reach across social, cultural and economic boundaries, volunteers who match the socio‐cultural attributes of the palliative care client group will need to be recruited (Jovanovic 2011).

One other Cochrane review addresses similar issues to this review. Candy 2011 is concerned with informal caregivers of people with terminal illness, who are unpaid and provide "physical, practical and/or emotional care and support to a relative or friend." Our review differs in that participants will usually not have any prior relationship with the palliative care patient, and will be associated with a formal volunteer program.

A second Cochrane review touches some common ground with this review as it is concerned with trained non‐professionals carrying out healthcare functions (Lewin 2010), While our review is interested in support of a broader scope of palliative care volunteer activities than direct patient care, training in this aspect of care is a potential strategy to support palliative care volunteers.

This review aims to assess the impact of training and supporting palliative care volunteers, on the clients of palliative care services, palliative care organisations and on the volunteers themselves. It will also alert us to international differences in the use of volunteers and whether there are any reliable tools to measure effectiveness or determine impact,

Objectives

To assess the effects of training and support strategies for palliative care volunteers on palliative care clients and their families, volunteers and service quality.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomised controlled trials, quasi‐randomised controlled trials, controlled before‐and‐after (CBA) studies and interrupted time series (ITS) studies.

CBAs will be included if they have at least two intervention sites and two appropriate control sites, and contemporaneous data collection. ITS will be included if they have a clear time point when the intervention occurred and at least three data points before and three after the intervention is introduced. We anticipate the inclusion of cluster RCTs as interventions to support palliative care volunteers are commonly group‐based.

We will also include any qualitative studies conducted concurrently with included trials for additional narrative analysis related to the acceptability of the intervention and issues related to its feasibility.

Types of participants

We will include studies that involve participants either as volunteers through a formal volunteer program in services offering palliative care in people's homes, residential aged care facilities or other settings in the community; or studies that involve palliative care clients or their families receiving the services of such volunteers not in hospital.

We will exclude studies involving informal carers and other volunteers not associated with a formal program. We will also exclude studies involving people described as lay health workers or trained health professionals working without pay.

Types of interventions

We will include all formal training and support programs for palliative care volunteers. We will classify programs or strategies in included studies according to any stated or implied purpose; that is, whether they are intended to build skills for the volunteer’s role, to enhance their coping, or to maintain service standards.

We will classify interventions to train or support palliative care volunteers in included studies according to any stated or implied purpose that addresses skills, coping or service quality. If necessary, we will give programs that do not fit these classifications a post hoc categorisation.

Training to develop skills may include active listening, advance care planning, or providing bereavement support. Strategies to support coping could include screening for specific roles, mentorship, or linking with volunteer networks. Strategies to maintain service quality may introduce codes of conduct or raise awareness of ethical issues.

We will consider orientation programs that provide information about the palliative care service, but do not aim to build capacity in the volunteers in terms of skills, coping capacity or with a specific purpose of maintaining service quality to be 'usual care'. We will include any comparison group in included studies.

Types of outcome measures

Primary outcomes

The primary outcomes will address the main focus of this review; the impact on clients and families. These outcomes will include: evaluations of care (such as perceptions and ratings of volunteers by clients, families and other palliative care staff), psychological outcomes (such as anxiety, well‐being, confidence, grief, compassion fatigue and resilience), pain‐related outcomes, and care outcomes (such as place of death, preferences met).

The assessment of quality of life in palliative care is important but problematic at this stage, as there is a lack of consensus on what quality of life comprises and how it might be measured. None of the large number of tools used to measure quality of life in palliative care are validated. They also incorporate a broad spectrum of domains, few of which are common (Albers 2010). This would make it difficult to interpret pooled results across studies when different quality of life measures are used. Quality of life outcomes will be included with caution as a psychological outcome, when identified as a primary outcome in any included study.

Secondary outcomes

The secondary outcomes will address outcomes related to volunteers and palliative care services.

Outcomes related to palliative care volunteers are: evaluations of support, skill acquisition, and psychological outcomes (such as satisfaction with reciprocity, anxiety, well‐being, confidence, grief, compassion fatigue and resilience).

Outcomes related to health services are: cost; volunteer recruitment (such as rate and attrition); and adverse events (such as complaints).

Search methods for identification of studies

Electronic searches

We will search the following electronic databases:

  • The Cochrane Consumers and Communications Review Group Specialised Register;

  • The Cochrane Specialised Register of Controlled Trials (CENTRAL, The Cochrane Library, Latest Issue);

  • MEDLINE (OvidSP) (inception to present);

  • EMBASE (OvidSP) (inception to present);

  • PsycINFO (OvidSP) (inception to present);

  • CINAHL (EbscoHOST) (inception to present);

  • ProQuest Dissertations and Theses (inception to present).

We will also search the Database of Abstracts of Reviews of Effects (DARE, The Cochrane Library) to identify potentially relevant reviews.

We will use the strategy in Appendix 1 to search MEDLINE, and will adapt the strategy for other databases, using the most appropriate controlled vocabulary for each. The strategy combines two components: effects of programs to support needs of palliative care volunteers, and impact on clients, families, health services and volunteers.

Searching other resources

For all included studies, we will search reference lists and conduct author and citation searches in Science Citation Index database.

Grey literature

We will undertake an extensive search for evaluations published in government reports and other grey literature. We (M O'C and SL) will search the CareSearch database (www.caresearch.com.au from inception to present) and websites of relevant organisations for unpublished and ongoing studies. These will include: The National Gold Standards Framework (UK) (http://www.goldstandardsframework.nhs.uk); International Association for Hospice and Palliative Care (www.hospicecare.com); NHS UK (www.nhs.uk); International Observatory on End of Life Care (www.lancs.ac.uk/shm/research/ioelc/); Help the Hospices UK (www.helpthehospices.org.uk); National Institute for Health and Clinical Excellence UK (www.nice.org.uk); Asia Pacific Hospice Palliative Care Network (www.aphn.org); Worldwide Palliative Care Alliance (http://www.thewpca.org); Family Health International (www.fhi.org/en/index.htm); Red Cross (www.redcross.int); WHO (www.who.int); International Volunteer Programs Association (www.volunteerinternational.org); Oxford International Centre for Palliative Care (www.sobellhospiceoxford.org); Volunteering Australia (www.volunteeringaustralia.org). We will also search the websites of national and regional palliative care peak bodies including: African Palliative Care Association (www.apca.org.ug); Palliative Care Australia (www.palliativecare.org.au); Canadian Hospice Palliative Care Association (www.chpca.net); Indian Association of Palliative Care (www.palliativecare.in); Japan Hospice Palliative Care Foundation (www.hospat.org/english/future.html); National Hospice and Palliative Care Organization (www.nhpco.org).

International trials registers

We will search the following trial registry platforms to identify unpublished and ongoing studies using the terms 'palliative' and 'volunteer': Current Controlled Trials metaRegister of Controlled Trials (www.controlled‐trials.com) and the International Clinical Trials Registry Platform Search Portal (www.who.int/trialsearch).

Correspondence

We will write to corresponding authors of all included studies and relevant reviews to seek their help to identify unpublished and ongoing studies.

Data collection and analysis

Selection of studies

One review author (DH) will screen all titles identified by the search to exclude clearly irrelevant references. All other review authors will independently screen a randomly selected subset of studies to ensure consistent application of inclusion criteria. Any discrepancies will be discussed among authors and inclusion will be based on consensus.

At least two review authors (DH and AS) will independently screen all remaining titles and abstracts to identify potentially relevant papers. Full text copies of all potentially relevant papers will be retrieved, including those where description of the intervention, study design, participants, or outcomes is insufficient for a decision about inclusion. One review author will collate retrieved papers (AS) and two review authors will independently apply inclusion criteria (DH and LP). Disagreement will be resolved by discussion between all review authors.

Data extraction and management

It is anticipated that the heterogenous nature of the studies in this area will limit the opportunity for meta‐analysis and it is likely a narrative synthesis will be necessary.

At least two review authors (DH and LP) will extract data independently for each included study using a data collection checklist based on the Cochrane Consumers and Communication Data Extraction template, which will be pre‐determined and piloted by all review authors. Discrepancies in data extraction will be resolved by discussion between all review authors.

Details of included studies

We will extract the following data from included studies: aim of study, study design, method of recruitment, inclusion criteria, exclusion criteria, attrition, informed consent obtained (yes/no/unclear), ethical approval (yes/no/unclear), funding (including source and amount), consumer involvement in study design (yes/no/unclear).

Characteristics of palliative care volunteers

We will extract data from all included studies on the following characteristics of the palliative care volunteers: definition of volunteers (including any reference to free will, financial payment and relationship to volunteer service recipients); criteria for palliative care selection; setting (home‐based only, home and hospice, other); type(s) of care provided (direct patient care, direct patient support, family or carer support, bereavement support, unclear); descriptions of volunteer care; involvement of health professionals and retired health professionals as volunteers (yes/no/unclear), descriptions of such involvement.

Where details are not included in the published study, or are unclear, we will contact authors requesting further information.

Characteristics of palliative care clients and families

We will extract data from all included studies on the following characteristics of the palliative care clients and families: proportion with cancer; diagnosis; proportion with spouse or live‐in carer; gender; how service funded.

Characteristics of training or support programs 

We will extract data from all included studies that will allow comparison of different types of programs to support palliative care volunteers. Two authors (DH, AS) will independently classify the aims of programs (to train skills; to enhance capacity to cope; to maintain service quality; other purpose; or unclear) and whether programs are single or multi‐purpose. These classifications will be compared and differences resolved through consultation with all authors if consensus is not reached. If the aim of a program cannot be determined it will be categorised as unclear. All information about such classifications will be reported. If an alternate purpose for a volunteer support program emerges from the descriptions in the included studies, an appropriate category will be determined and post hoc analyses performed.

We will extract data to describe the following characteristics of any support program: aim of the support; number of components present; classification of components (skill development, coping enhancement, service quality, unclear); description of components; outcomes assessed; how outcomes were measured including details of any measurement tools used; frequency of support; duration; cost.

Where details are not included in the published study, or are unclear, we will contact study authors requesting further information and report when information is not available.

Assessment of risk of bias in included studies

Two review authors (DH, LP) will assess the risk of bias for each included study independently, using the ‘Risk of bias’ tool described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

We will assess risk of bias associated with RCTs. quasi‐RCTs and CBAs for seven domains from the ‘Risk of bias’ tool: random sequence generation; allocation concealment; blinding of participants and personnel; blinding of outcome assessment; incomplete outcome data; selective reporting; and other sources of bias (Higgins 2011). For clustered studies, we will assess the risk of bias associated with an additional domain: selective recruitment of participants.

We will assess risk of bias associated with ITS studies for the following seven domains: intervention independent of other changes; shape of intervention effect pre‐specified; intervention unlikely to affect data collection; blinding of outcome assessors to intervention allocation; incomplete outcome data; selective outcome reporting; and other sources of bias (EPOC 2009).

We will judge whether a study has a low, high, or unclear risk of bias for each domain using the criteria specified in the Cochrane Handbook for Systematic Reviews of Interventions and Cochrane EPOC Group guidance. We will report our assessment of risk of bias for each domain for each included study with a descriptive summary our judgment.

Measures of treatment effect

Continous outcomes

We will extract or generate the mean difference (MD) from the means and standard deviations for continuous outcomes. These include:

  • Three patient outcome categories: evaluations of care; psychological outcomes; and pain‐related outcomes.

  • Two volunteer outcomes: evaluations of support; and psychological outcomes

  • Three palliative care service outcomes: cost; volunteer recruitment, adverse events.

Dichotomous outcomes

We will extract or generate odds ratios (ORs) and their 95% confidence intervals (CIs) for dichotomous outcomes. Two outcome categories will be treated as dichotomous outcomes. Categorical data will be collapsed:

  • The patient outcome category, care outcomes: for example place of death will be [home, not at home] or [consistent with preferences, not consistent with preferences] where more than two places of death are recorded.

  • The volunteer outcome category: skill acquisition. Any categorical data will be collapsed [Skills acquired, skills partly or not acquired].

We will adopt the approach to the selection of measures of treatment effect as outlined by Brennan and colleagues (Brennan 2009) and include any primary outcome identified by study authors that falls within each of our outcome categories. We will also report any common outcomes within these categories, but these results will be additional findings.

If multiple primary outcomes are identified within any category, we will rank the reported effect estimates for each of these outcomes and select the outcome with the median effect estimate.

If no primary outcome within our categories is specified, we will adopt the following strategy. First we will use any outcome within our categories specified in sample size calculations; then, if necessary, we will rank relevant intervention effect estimates, as reported, and select the median effect estimate. If the number of outcomes is even (n), we will include the outcome whose effect estimate is ranked n/2.

We will report whether we have used the primary outcome or the outcome with the median effect estimate in the results tables. We will also verify whether the specified primary outcomes in included studies are consistent with those identified in trial protocols and/or trial registry entries. This will be possible for RCTs only.

Measures of treatment effect for RCTs, quasi‐RCTs, and CBAs

We will extract the intervention effect estimate reported for all included outcomes with their associated P value and confidence intervals (CIs), and the method of statistical analyses used to calculate them. If an inappropriate statistical method has been used, we will present only re‐analysed data, if this is possible, with the P value annotated 're‐analysed'.

We will follow the approach described by Brennan 2009 (see Table 1 and Table 2) to calculate the effect estimates for:

Open in table viewer
Table 1. Effect estimators for dichotomous outcomes from RCTs, cluster‐RCTs, quasi‐RCTs and CBAs

Dichotomous outcomes

Relative risk*

RR=RPost,I/RPost, C

Relative risk adjusted for baseline*

RRAdj=(RPost,I/RPost, C)/(RPre,I/RPre, C)

Where RPost,I and RPost, C are defined above, and RPre,I and RPre, C are the respective risk of the outcome in the intervention and comparator groups pre‐intervention.

Risk difference*

RD=RPost,I ‐ RPost, C where RPost,I and RPost, C are defined as above.

RPost,I= risk of the outcome in the post‐intervention group.

RPost, C =risk of the outcome in the comparator group post intervention.

RPre,I is the risk of the outcome in the intervention group pre‐intervention.

RPre, C is the risk of the outcome in the comparator groups pre‐intervention.

Open in table viewer
Table 2. Effect estimators for continuous outcomes from RCTs, cluster RCTs, quasi‐RCTs and CBAs

Continuous outcomes

Standardised mean difference*

SMD=(Mean Post,I Mean Post,C )/SD Pre,pooled

Relative percentage change post intervention*

RPC=((Mean Post,I Mean Post,C )/Mean Post,C )X100

Difference in means post‐intervention*

DM=(Mean Post,I Mean Post,C )

Difference in mean change*

DMC=(Mean Post,I Mean Post,C )‐(Mean Pret,I Mean Pre,C )

*Mean Post,I is mean of post‐intervention groups.

Mean Post,C is mean of post‐comparator groups.

SD Pre,pooled is the pooled standard deviation of the two groups pre‐intervention.

Mean Pret,I is mean of pre‐intervention groups.

Mean Pre,C is mean of pre‐comparator groups.

  • Dichotomous outcomes (relative risks adjusted for baseline or risk differences)

  • Continuous outcomes (standardised mean difference, relative percentage change post intervention, mean differences post intervention, and difference in mean change).

P values for these effect estimates will be calculated. Effect estimates will be standardised so that scales and other outcome measures are concordant. Ratios greater than one, and differences between the intervention and comparator groups greater than zero will indicate benefit for the intervention group, so effect estimates will be multiplied by minus one where necessary.

Measures of treatment effect for ITS and repeated measures ITS

We plan to report the following estimates and their P values from ITS studies from regression analyses that adjust for autocorrelation: immediate effect of the intervention (change in level of the outcome at the first point after the introduction of the intervention); and long‐term effect of the intervention (post‐intervention slope minus the pre‐intervention slope).

Unit of analysis issues

Clustering

Studies where clusters of individuals are randomised (cluster‐RCTs, quasi‐RCTs) or allocated (CBAs) to intervention groups, but where inference is intended at the level of the individual, data need to be analysed taking account of intra‐cluster correlation (ICC). Estimates of ICC will be obtained from contacting authors, or imputed using external estimates. If this is not possible we will report effect estimates and annotate 'unit of analysis error'.

ITS studies

Where ITS studies do not account for the autocorrelation of data points we plan to re‐analyse results if we are able to obtain the data from the authors, or from data presented in graphs or tables in the publication. We will use time series regression analysis accounting for first order autocorrelation and estimate changes in level of each outcome at the first point after the intervention was introduced and for post intervention slope minus the pre‐intervention slope. We will calculate confidence intervals for these effect estimates.

Dealing with missing data

We do not plan to undertake any imputation for missing outcome data but we will impute missing summary data where possible and report any assumptions in the results tables. We will investigate the effect of our choice of ICCs on the pooled effect estimate in any meta‐analysis through sensitivity analyses.

Assessment of heterogeneity

If there is substantial heterogeneity in the types of training or support for palliative care volunteers across included studies, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random‐effects analysis to produce it. Explanation of these assessments will be recorded. We will assess statistical heterogeneity in any meta‐analyses by visually inspecting the scatter of effect estimates on forest plots and by the calculated I2 statistic (Higgins 2003).

Assessment of reporting biases

In addition to an extensive search of the published and grey literature, we will search the International Clinical Trials Registry Platform Search Portal and Current Controlled Trials metaRegister of Controlled Trials to identify other trials that may not be published or are currently underway and contact the relevant investigators for further information. As stated above we will include all retrieved trials from this search in the review, and note those for which we cannot get further information. If we find sufficient RCTs (at least ten) we will use funnel plots and formal statistical tests to investigate funnel plot asymmetry. We anticipate heterogeneity in effect estimates because of variability in the interventions. We plan to use the approach identified by Brennan 2009, and developed by Rücker and colleagues, which proposes a statistical test for when substantial between‐study heterogeneity exists when data points are proportions (Rücker 2008).

Data synthesis

We will report summary statistics for each comparison from the included studies (RCTs, quasi‐RCTs, CBAs) including: baseline and follow‐up summary statistics; effect estimates and their statistical significance; and information on effect modifiers and study design. We will summarise effect estimates for dichotomous outcomes within each comparison and study design. This will include the median effect estimate, inter‐quartile range, and range. We will use graphs to display data graphically.

If possible, we plan to use meta‐analytical methods to pool relative risks measuring the effectiveness of different strategies to support palliative care volunteers focused on skill development and/or coping enhancement and/or service quality using orientation programs as the comparator. Random‐effects meta‐analysis will be used to pool intervention effects because of anticipated clinical and methodological diversity. We plan to report an approximate 95% range of underlying effect estimates, based on the between‐study variance estimate, to provide some information on the spread of effect estimates (Higgins 2009). We will prepare a 'Summary of findings' table from the results of the meta‐analysis using the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2008).

We will present results from ITS studies in tables for each comparison, with summary statistics for each of the included studies, change in level of the outcome at the first point after the introduction of the intervention, post‐intervention slope minus the pre‐intervention slope, and information on effect modifiers. This will also be presented graphically using, for example, scatter plots of change in level versus change in slope with combinations of statistical significance denoted by different symbols.

Subgroup analysis and investigation of heterogeneity

We plan to carry out sub‐group analyses based on differences in the focus of interventions (skill development, coping enhancement or service standards) and to compare single purpose programs with multipurpose programs (for example, we will compare training for skill development only with programs that combine skill development and coping enhancement and/or service standard issues). If there are sufficient trials we will use random‐effects meta‐regression to estimate the relative change in the intervention effect (and 95% CI) for each.

Sensitivity analysis

We plan to undertake sensitivity analyses based on the risk of bias assessment. If possible studies at the greatest risk of bias, as described in the risk of bias tables, will be removed from the analysis.

Consumer participation

Two important potential users of this review are people who are palliative care volunteers themselves, and people who may use their services. We will involve these two groups by using an existing network of palliative care volunteers in Victoria and members of the Cochrane Consumer Network. The draft protocol and draft review will be circulated to these groups for consumer peer review. The review team sent the draft protocol to two palliative care volunteers working in community settings, and the editorial team of the Cochrane Consumers and Communication Review Group involved members of the Cochrane Consumer Network in commenting on the protocol, and will do so again for the review.

Table 1. Effect estimators for dichotomous outcomes from RCTs, cluster‐RCTs, quasi‐RCTs and CBAs

Dichotomous outcomes

Relative risk*

RR=RPost,I/RPost, C

Relative risk adjusted for baseline*

RRAdj=(RPost,I/RPost, C)/(RPre,I/RPre, C)

Where RPost,I and RPost, C are defined above, and RPre,I and RPre, C are the respective risk of the outcome in the intervention and comparator groups pre‐intervention.

Risk difference*

RD=RPost,I ‐ RPost, C where RPost,I and RPost, C are defined as above.

RPost,I= risk of the outcome in the post‐intervention group.

RPost, C =risk of the outcome in the comparator group post intervention.

RPre,I is the risk of the outcome in the intervention group pre‐intervention.

RPre, C is the risk of the outcome in the comparator groups pre‐intervention.

Figuras y tablas -
Table 1. Effect estimators for dichotomous outcomes from RCTs, cluster‐RCTs, quasi‐RCTs and CBAs
Table 2. Effect estimators for continuous outcomes from RCTs, cluster RCTs, quasi‐RCTs and CBAs

Continuous outcomes

Standardised mean difference*

SMD=(Mean Post,I Mean Post,C )/SD Pre,pooled

Relative percentage change post intervention*

RPC=((Mean Post,I Mean Post,C )/Mean Post,C )X100

Difference in means post‐intervention*

DM=(Mean Post,I Mean Post,C )

Difference in mean change*

DMC=(Mean Post,I Mean Post,C )‐(Mean Pret,I Mean Pre,C )

*Mean Post,I is mean of post‐intervention groups.

Mean Post,C is mean of post‐comparator groups.

SD Pre,pooled is the pooled standard deviation of the two groups pre‐intervention.

Mean Pret,I is mean of pre‐intervention groups.

Mean Pre,C is mean of pre‐comparator groups.

Figuras y tablas -
Table 2. Effect estimators for continuous outcomes from RCTs, cluster RCTs, quasi‐RCTs and CBAs