Types of studies

We will include randomised controlled trials (RCTs), non‐randomised controlled trials (NRCTs), controlled before‐after (CBA) studies, interrupted time series (ITS) studies and repeated measures studies (RMSs).

For the economic analysis part of this review, we will include all previous study designs having conducted full economic evaluations (cost‐effectiveness analyses, cost‐utility analyses and cost‐benefit analyses), cost analyses or comparative resource utilisation studies.

Types of participants

We will consider healthcare stakeholders such as healthcare professionals, decision makers, researchers and patients. We will include studies enrolling single groups of stakeholders (e.g., patients) as the only target of a collaborative writing application intervention only if the ultimate goal is to improve professional practices (e.g., involving patients in the development of clinical practice guidelines using a collaborative writing application). Moreover, we will include studies enrolling healthcare students as long as the majority of the participants are certified health professionals.

Types of interventions

We will consider studies that evaluated any collaborative writing application intervention aimed at improving processes of care, patient outcomes and healthcare costs. Our definition of a collaborative writing application intervention includes all of the following elements:

• content that is collaboratively created;

• a web page that allows the joint and/or simultaneous editing accessed by a group of authors;

• a web based software to keep track of the revisions to the original document;

• a public or private access.

Since we will compare the specific effects of wikis compared to other collaborative writing applications, we will include wiki interventions if they contain all the following elements:

• a web page or a collection of interlinked web pages designed to enable anyone who accesses it to easily contribute or modify its content using a web browser;

• a wiki software that keeps track of all changes and all the authors (and their internet protocol addresses) making the changes (e.g., MediaWiki and Tiki Wiki CMS Groupware);

• a collaboratively created content;

• a public access (e.g., Wikipedia, community websites) or a private access (e.g., corporate intranets, knowledge management systems).

We will exclude blogs, microblogs (e.g., Twitter), online communities of practice, discussion forums, media sharing websites and social bookmarking websites that do not include any collaborative writing feature defined as a common page that allows the joint and/or simultaneous editing by more than one person.

We will conduct the following comparisons:

• collaborative writing application intervention compared to no intervention;

• collaborative writing application intervention versus any single intervention (e.g., a static web page);

• collaborative writing application intervention compared to a wiki intervention;

• multifaceted intervention where a collaborative writing application is included versus any multifaceted intervention without a collaborative writing application; and

• a collaborative writing application with an implementation strategy compared to a wiki/collaborative writing application without an implementation strategy.

A single intervention would be any static resource (e.g., a traditional web page) intervention where users do not have the capability in editing the content of the page. A multifaceted intervention would be any intervention where a collaborative writing application is a part of the intervention but is not the only active ingredient. For example, a study could explore the impact of a virtual learning environment that contains a wiki and other applications (e.g., discussion boards, social networks, live virtual classroom meetings) compared to traditional teacher‐led classroom meetings or other educational interventions like problem‐based learning groups.

Types of outcome measures

Electronic searches

A draft search strategy for MEDLINE and additional databases based on the MEDLINE strategy has been developed by the Cochrane Effectice Practice and Organisation of Care (EPOC) Group Trials Search Co‐ordinator in consultation with the authors (Appendix 1). A second information specialist peer‐reviewed this strategy using the Peer Review of Electronic Search Strategies (PRESS) criteria (Sampson 2008). We will search the Cochrane Database of Systematic Reviews (CDSR) and the Database of Abstracts of Reviews of Effects (DARE) for related systematic reviews.

In addition, we will search the following databases for primary studies:

• MEDLINE (In‐Process and other non‐indexed citations) (1946‐present) (OvidSP);

• EMBASE (1947‐present) (OvidSP);

• CINAHL (Cumulative Index to Nursing and Allied Health Literature) (1980‐) (EBSCOhost);

• PubMed;

• Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library);

• Health Technology Assessment (HTA) Database (The Cochrane Library);

• National Health Service (NHS) Economic Evaluation Database (The Cochrane Library);

• Health Economic Evaluations Database (1994‐present);

• Dissertations and Theses Full Text (1861‐present) (ProQuest);

• Education Resources Information Center (ERIC);

• Science Citation Index Expanded (SCI‐EXPANDED) (1900‐present);

• Social Sciences Citation Index (SSCI) (1900‐present);

• Conference Proceedings Citation Index‐ Science (CPCI‐S) (1990‐present);

• Conference Proceedings Citation Index‐ Social Science & Humanities (CPCI‐SSH) (1990‐present).

We will employ two methodological filters: the 'Cochrane Highly Sensitive Search Strategy (sensitivity‐ and precision‐maximizing version ‐ 2008 revision) to identify randomized trials' (Higgins 2011), and a Cochrane EPOC Group methodology filter to identify non‐RCT designs. We will not apply any limits on language or date of publication. However, in emerging technology areas, database controlled vocabulary, such as Medical Subject Headings (MeSH) found in MEDLINE and PubMed, lags behind. Thus, in MEDLINE, papers about wikis may be indexed using very general terms such as "Internet" or "Online Software." In the draft Medline strategy published here, the number of results found by these broad terms is not excessive and no date limit has been used. In other databases, depending on the search terms, a date limit corresponding to the emergence of wiki technology may be used for practical reasons.

We will search for economic analysis reviews in MEDLINE and EMBASE using the filter strategies developed by the Canadian Agency for Drugs and Technologies in Health (Glanville 2009).

Searching other resources

Selection of studies

Two independent authors (PA,AP) will assess the eligibility of papers identified. We will screen all titles and abstracts according to pre‐established inclusion criteria. We will obtain the full‐text copies of papers in order to fully assess their eligibility. Any disagreements will be resolved by discussion between the two authors, and where consensus is not reached, we will consult a third author (TvdB). We will document the selection process in a Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) flow diagram (Moher 2009), and also illustrate our findings in a 'Characteristics of excluded studies' table. This table will only present the excluded studies with the reasons of exclusion.

We will describe characteristics of ongoing studies such as the primary author, research question(s), methods and outcome measures together with an estimate of the reporting date.

Data extraction and management

Two review authors (PA,AP) will independently undertake data extraction from all included studies using a modified version of the Cochrane EPOC Group data extraction template. Any discrepancies in judgement will be resolved by discussion and consensus, or by consulting a third review author (TvdB) if necessary. Where information is missing, we will attempt to contact the study authors, and if data are not available the study will be recorded as an 'Included study without data.

In addition to standardized data extraction for EPOC interventions, we will use collect the following characteristics of the intervention.

• Clinical area addressed.

• Type of healthcare professional (e.g., physician, nurse, physiotherapist, student nurse, resident).

• Pre‐licensure healthcare professionals (student nurses, residents).

• Type of healthcare stakeholder (e.g., patients, consumer, decision maker, researcher).

• Conceptual or theoretical underpinnings of the intervention (i.e., part of a theory based intervention).

• Known effectiveness of the intervention for changing of healthcare professional behaviours (e.g., evidence‐based intervention).

• Number of components included in the intervention.

• Source and authors of the intervention (e.g., professional organisation, governmental agency, health professionals training schools).

• Mode of delivery (e.g., individuals or groups).

• Frequency/timing of the intervention and its duration.

• Type of collaborative writing application (i.e., Wiki, Google Knol, Google Docs, Google Wave).

• Presence of a moderator.

• Presence of a pre‐existing community of practice or community of learners.

• Open versus closed wiki or collaborative writing application.

• Authorship clearly stated.

• Type of conversational features integrated with the collaborative writing application (e.g., discussion pages, email, comment page).

• Format of knowledge being shared within the collaborative writing application (e.g., reminders, care pathways, textbook format).

• Formal teaching about how to use a wiki.

For economic analysis data extraction, we will develop a data collection form specifically for use with health economic studies, based on the template used to produce the National Health Service (NHS) Economic Evaluation Database (EED) structured abstracts (Craig 2007).

Assessment of risk of bias in included studies

Two review authors (PA,AP) will independently assess the risk of bias of included studies, with disagreements resolved by discussion and consensus. The two authors will assess and report on the risk of bias of included RCTs, NRCTs, and CBA studies in accordance with the suggested nine risk of bias criteria for Cochrane EPOC Group reviews (Cochrane EPOC Group 2014):

1. adequate sequence generation;

2. allocation concealment;

3. blinding;

4. incomplete outcome data addressed;

5. free of selective reporting;

6. free of other bias;

7. baseline outcomes similar;

8. free of contamination; and

9. baseline characteristics similar.

For ITS studies and RMSs, we will use the seven risk of bias criteria for Cochrane EPOC Group reviews (Cochrane EPOC Group 2014):

1. independence from other changes in time;

2. shape of the intervention effect pre‐specified;

3. intervention unlikely to affect data collection;

4. blinding;

5. incomplete data outcome;

6. free from selective outcome reporting; and

7. free from other biases.

For all study types, we will assess each risk of bias criterion as "High risk", "Low risk", or "Unclear risk", and also present a table describing these assessments of the risk of bias for each study and outcome. We will also prepare a summary table presenting an assessment of the risk of bias within and across studies for important outcomes.

We will assign an overall assessment of the risk of bias (high, moderate or low risk of bias) to each of the included studies using the approach suggested in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). Studies with low risk of bias for all key domains or where it seems unlikely for bias to seriously alter the results will be considered to have a low risk of bias. Studies where risk of bias in at least one domain is unclear or judged to have some bias that could plausibly raise doubts about the conclusions will be considered to have an unclear risk of bias. Studies with a high risk of bias in at least one domain or judged to have serious bias that decreased the certainty of the conclusions will be considered to have a high risk of bias.

For included health economic studies, we will assess their risk of bias using the Cochrane Collaboration’s tool for assessing risk of bias as well as the Consolidated health economic evaluation reporting standards (CHEERS) developed by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) (Higgins 2011; Husereau 2013).

Measures of treatment effect

Unit of analysis issues

Dealing with missing data

All efforts will be made to contact the original authors if missing data is present in an included study. If this is impossible, we will clearly state if the data seems to be ‘missing at random’. If this is the case, we will analyse only the available data and ignore the missing data (Higgins 2011). If data seems ‘not to be missing at random’, we will clearly state our assumptions and we will either impute the missing data with replacement values, and treat these as if they were observed (e.g., last observation carried forward, imputing an assumed outcome such as assessing all were poor outcomes, imputing the mean, imputing based on predicted values from a regression analysis). We will also explore the impact of missing values on our results with the use of statistical models to allow for missing data, making clearly stated assumptions about their relationship with the available data. We will perform sensitivity analyses to assess how sensitive our results are to reasonable changes in the stated assumptions (Sensitivity analysis). Finally, we will address the potential of missing data on the findings of our review in our discussion section.

Assessment of heterogeneity

We will analyse included studies to determine whether there are studies sufficiently similar in participants characteristics (e.g., age, gender), study design, type of collaborative writing application (e.g., wiki, Google Docs), type of knowledge contained in collaborative writing application (e.g., wikis sharing reminders), environmental setting (e.g., critical care), health condition (e.g., acute disease) and outcome measurement to allow for a meta‐analysis of their combined data using a random‐effects model. If studies are too heterogeneous, we will present a descriptive review of included studies using a narrative summary along with extracted data in tables and figures.

Where meta‐analysis is possible, we will assess statistical heterogeneity between trials using the Chi² test and the I² statistic (a Chi² P value of less than 0.05 or an I² value equal to or more than 50% will be considered to indicate substantial heterogeneity). If heterogeneity is identified, we will undertake subgroup analysis to investigate its possible sources (Subgroup analysis and investigation of heterogeneity). We will also conduct a meta‐regression if there are enough studies to assess the effect of the possible sources of heterogeneity.

Assessment of reporting biases

If sufficient studies are found, we will assess for publication bias graphically using funnel plots and statistically using Begg and Egger tests (Egger 1997). While funnel plot asymmetry may indicate publication bias, this is not always the case. We will consider all possible explanations for this asymmetry and discuss them in the review.

Data synthesis

We expect to find statistical heterogeneity, given the range of disparate settings where wikis and collaborative writing applications will be tested and the difference of content within these different collaborative writing applications. This makes it unlikely that statistical pooling will be feasible, but if there appears to be a body of studies amenable to meta‐analysis, then we will display their results graphically, and view them to assess heterogeneity. It is unlikely that this review will find many studies for inclusion in a meta‐analysis, and so statistical tests for heterogeneity will be insensitive. We will nevertheless carry out these tests. We will conduct any subsequent meta‐analyses using a random‐effects model. In comparisons of homogeneous groups of studies with different outcome measures, we will consider using a single effect size measure (standardised mean differences).

We will provide narrative and qualitative summaries. We will group studies by criteria included in this protocol (e.g., type of collaborative writing application), and vote counts made of studies grouped according to simple trichotomies on outcome: effective/no difference/harm. We will perform formal qualitative textual analysis for each of these groups of studies, looking for common themes in the description of the intervention within each outcome group, and systematic differences between groups of studies with different outcomes.

We will produce a 'Summary of findings' table with selected studies according to the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

We will list all the outcomes that are important to patients and other decision makers. Consultation and feedback with the current decision makers on our team have identified that all the primary outcomes of our review will be included in this Summary of findings table. In addition, we will list all negative outcomes identified (e.g., quality of content, adverse events related to collaborative writing application knowledge use).

Subgroup analysis and investigation of heterogeneity

We will prepare tables and bubble plots comparing effect sizes of studies grouped according to potential effect modifiers to investigate heterogeneity. For example, the following variables will guide our exploration of heterogeneity: the type of collaborative writing application (wikis compared to Google Docs), the age of wiki users/editors (‘internet generation’ (born between 1976 and 1994) compared to participants born before the ‘internet generation’). We will consider the following subgroups to explore the following effect modifiers of the intervention on the magnitude of effects observed across studies:

• open versus closed collaborative writing applications;

• clear authorship identification;

• the presence of a moderator; and

• being part of a theory‐based intervention.

Sensitivity analysis

We will undertake sensitivity analyses for the allocation of missing data by best and worst case analysis and will also undertake sensitivity analysis on the basis of our evaluation of the risk of bias of each study. Since studies will not be blinded and already contain one domain with high risk of bias, our sensitivity analyses will include studies with at least two high risk of bias domains.