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. 2017 Feb 21;2017(2):CD012566. doi: 10.1002/14651858.CD012566

Rinse‐free hand wash for reducing absenteeism among school‐ and preschool‐aged children

Zachary Munn 1,✉, Catalin Tufanaru 1, Craig Lockwood 1, Cindy J Stern 1
PMCID: PMC6464072

Abstract

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

  1. To assess the effectiveness of rinse‐free hand washing for reducing absenteeism due to illness in preschool and school‐aged children compared to no hand washing, conventional hand washing with soap and water or other hand hygiene strategies.

  2. To determine which rinse‐free hand washing products are the most effective (if head‐to‐head comparisons exist) and what effect additional strategies in combination with rinse‐free hand washing have on the outcomes of interest.

Background

Description of the condition

Absenteeism due to sickness (particularly gastrointestinal or minor respiratory illness) is an important problem in schools in low‐, middle‐ and high‐income countries (Day 1993; Early 1998; Guinan 1997; Kimel 1996; Master 1997; Monsma 1992; Niffenegger 1997). The common cold alone has been shown to result in approximately 22 million absent days from school per year in the USA (Adams 1999), and young children are likely to have between six and eight colds per year, decreasing to between two and four colds per year in adults (Heikkinen 2003). Not only are children adversely affected by repeated respiratory infections, family members can also be affected due to infections transmitted by an infected child (Neuzil 2002). When a child is ill, this can result in industrial absence due to parental illness or due to the need to remain at home to care for their child (Neuzil 2002).

There are many interventions and methods that have been developed for reducing the spread of infectious diseases in children, such as hand washing (Lee 2010), education or training (Roberts 2000), (Lee 2010), safe water supply (Esrey 1985; Lee 2010), environmental cleaning (Harris 2010; Lee 2010), exclusion periods (Lee 2010; Richardson 2001), and vigilance during food preparation (Lee 2010). While conventional hand washing with soap and water is an effective method of hand hygiene for the prevention of the spread of infectious diseases, it is difficult to maintain compliance with conventional hand washing, and its consistency and effectiveness among preschool (three‐to‐five‐year olds) (Niffenegger 1997) and school‐aged students is variable (Day 1993; Early 1998; Guinan 2002; Kimel 1996; Monsma 1992).

Description of the intervention

Rinse‐free hand wash (also known as hand gel, hand foam, hand sanitiser or hand rub) is increasingly being used in both health care settings and the community as a measure to improve hand hygiene (Gould 2010; Harbarth 2002; Maury 2000). The active ingredients of the majority of rinse‐free hand wash products are alcohols (such as isopropanol, ethanol, or n‐propanol). Other rinse‐free antimicrobial hand washes exist, but are not as common (Boyce 2002; Meadows 2004; Morton 2004). There also appear to be only minimal adverse effects (e.g. dry skin or irritation) from the use of rinse‐free hand wash (Meadows 2004; Sandora 2005); rinse‐free hand wash has been shown to reduce skin irritation and dryness compared to traditional soap and water methods, and has been shown to be more acceptable than traditional methods (Boyce 2000). Rinse‐free hand wash with a concentration of ethanol between 60% and 95%, with a 3 mL to 5 mL application, are considered to be effective and safe for reducing the amount of bacteria present on the hand (Kampf 2008).

Rinse‐free hand wash can be considered as more convenient than traditional hand washing with soap and water for the following reasons: (1) it can be easily transported or carried on oneself; (2) it can be located within classroom or day‐care settings without the need for running water; (3) hands do not require ‘drying’ after use; and (4) it is quicker than traditional hand washing. As rinse‐free hand wash may be a simpler method for hand hygiene compared to conventional hand washing with soap and water, it may be more effective than traditional measures.

How the intervention might work

Respiratory‐tract viruses, such as influenza or rhinoviruses, are commonly spread between people through direct contact with droplets or aerosol containing the pathogen to the respiratory mucosa of another person (Heikkinen 2003; Musher 2003; Warren‐Gash 2013). Gastrointestinal illnesses and diarrhoea‐causing pathogens are transmitted via the faecal‐oral route, by exposure to faecal matter, direct contact with a person, or via ingestion of food and water contaminated with faecal matter (Warren‐Gash 2013).

Hand hygiene is commonly recommended as a decontamination measure to reduce transmission of gastrointestinal and respiratory infections and has been reported to be effective in community settings (Aiello 2008; Warren‐Gash 2013). Once the hands come into contact with a pathogen, this can be transferred to respiratory or oral mucosa when the person brings their hand to their face. Hand hygiene may reduce transmission through reducing and removing or eliminating pathogens from the hand (Ejemot‐Nwadiaro 2015; Warren‐Gash 2013).

The active component of the vast majority of rinse‐free hand washes is alcohol. Alcohol has the ability to denature proteins and, therefore, acts as a skin disinfectant against viruses and bacteria (Bessonneau 2010).

Why it is important to do this review

When children acquire an illness, this can spread through the family and result in days lost from school and from work. Student attendance is positively related to improved performance on standardised tests (Lamdin 1996), whilst significant or chronic absence from schooling can have a detrimental effect on a student's academic achievement (Chang 2008). Although lost days to an infectious illness like the common cold or gastroenteritis are not likely to result in a significant amount of attendance days lost from school, as compared to a chronic illness, there may still be an effect on learning and academic achievement (Gottfried 2009).

A Cochrane systematic review, which evaluated hand washing with water and soap to reduce diarrhoea in children and adults in community settings (day‐care centres, schools, communities or hospitals) in both high‐income countries and low‐ and middle‐income countries (LMICs), found a reduction in diarrhoea episodes of "around one‐third (rate ratio (RR) 0.70; 95% confidence interval (CI) 0.58 to 0.85)" (Ejemot‐Nwadiaro 2015). However, this review explicitly excluded rinse‐free hand wash and respiratory illnesses (Ejemot‐Nwadiaro 2015). Another systematic review, published in 2004, evaluated the effectiveness of rinse‐free hand sanitisers for reducing absenteeism related to illness in elementary school children. The review authors found six trials of low quality and poor reporting (Meadows 2004). In the time since that review was published there have been a number of new studies published. A systematic review was published in 2015 on hand‐hygiene interventions for children in educational settings (Willmott 2016). The authors of this review concluded that the evidence is equivocal regarding the effectiveness of hand‐hygiene interventions although they may decrease respiratory tract infections amongst children. There are some important differences between our review inclusion criteria and the Willmott 2016 review, the main being that our proposed review focuses explicitly on rinse‐free interventions. Willmott 2016 state the following as one of the limitations of their review: this "review does not distinguish between handwashing with soap or hand sanitiser use even though these methods may have different resource implications and be differentially effective in eliminating certain pathogens.” Additionally, the search for the Willmott 2016 review was conducted in September 2014.

This systematic review will serve to provide an up‐to‐date examination of the effects of rinse‐free hand wash on illness‐related absenteeism amongst school‐ and preschool‐aged children in low‐, middle‐ and high‐income countries.

Objectives

  1. To assess the effectiveness of rinse‐free hand washing for reducing absenteeism due to illness in preschool and school‐aged children compared to no hand washing, conventional hand washing with soap and water or other hand hygiene strategies.

  2. To determine which rinse‐free hand washing products are the most effective (if head‐to‐head comparisons exist) and what effect additional strategies in combination with rinse‐free hand washing have on the outcomes of interest.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs), including cluster‐RCTs, irrespective of publication status. We will also include quasi‐RCTs, where allocation has been systematic but not random (for example, by days of the week).

Types of participants

Children aged between 2 and 18 years attending preschool (childcare, day care, kindergarten, etc.) or school (primary, secondary, elementary, etc.). We will include children attending preschool or school in urban or rural settings regardless of whether they reside in a low‐, middle‐ or high‐income country.

Types of interventions

Rinse‐free hand wash in any form (hand rub, hand sanitiser, gel), based on alcohol or another active ingredient, irrespective of dose or frequency of use. It may be used alone or as part of a comprehensive hand‐hygiene program. The rinse‐free hand wash may be applied by the child or by a helper (such as a childcare worker, caregiver or teacher) or under direction by the helper. We will consider education on rinse‐free hand wash an intervention.

Comparators may include conventional hand washing with soap and water, other hand‐hygiene programs (such as education alone), or no intervention.

Types of outcome measures

Primary outcomes

  1. Child or pupil absenteeism for any reason. Absenteeism is defined as time absent from school or preschool when the child is scheduled to be attending, and does not include planned holidays or leave, or pupil‐free days.

  2. Child or pupil absenteeism due to any illness.

  3. Adverse skin reactions (such as a rash or irritation) within the trial period.

Illness may be confirmed by a physician or by self‐report.

The outcome measures may be assessed on a per week, month, term, trial period, or year basis. These may be reported as average or median days absent per group, as total days absent within each group, or as an incidence rate (i.e. 2 absences per 100 child days) per group. This is not a time‐bound intervention and, as such, outcomes will not be reported in terms of short‐term, mid‐term and long‐term follow‐up.

Secondary outcomes

  1. Child or pupil absenteeism due to acute respiratory illness (an infection of the respiratory system such as influenza or rhinovirus).

  2. Child or pupil absenteeism due to acute gastrointestinal illness (an illness with gastrointestinal symptoms such as diarrhoea, vomiting and nausea).

  3. Compliance with the intervention or program.

  4. Perception of the hand‐hygiene strategy or satisfaction with the hand‐hygiene strategy.

Search methods for identification of studies

Electronic searches

We will search the electronic databases and trials registers listed below.

  1. Cochrane Central Register of Controlled Trials (CENTRAL; current issue) in the Cochrane Library, and which includes the Cochrane Developmental, Psychosocial and Learning Problems Specialised Register.

  2. MEDLINE Ovid (1946 onwards).

  3. MEDLINE In‐Process & Other Non‐Indexed Citations Ovid (current issue).

  4. MEDLINE Epub Ahead of Print Ovid (current issue).

  5. Embase Ovid (1974 onwards).

  6. CINAHLPlus EBSCOhost (Cumulative Index to Nursing and Allied Health Literature; 1937 onwards).

  7. ERIC EBSCOhost (Education Resources Information Center; 1966 onwards).

  8. Science Citation Index Web of Science (SCI; 1970 onwards).

  9. Social Sciences Citation Index Web of Science (SSCI; 1970 onwards).

  10. Conference Proceedings Citation Index ‐ Social Science & Humanities Web of Science (CPCI‐SS&H; 1990 onwards).

  11. Conference Proceedings Citation Index ‐ Science Web of Science (CPCI‐S; 1990 onwards).

  12. LILACS (Latin American and Caribbean Health Sciences Literature; lilacs.bvsalud.org/en).

  13. Cochrane Database of Systematic Reviews (CDSR; current issue) in the Cochrane Library.

  14. Database of Abstracts of Reviews of Effects (DARE; current issue) in the Cochrane Library.

  15. Database of Promoting Health Effectiveness Reviews (DoPHER; eppi.ioe.ac.uk/webdatabases4/Intro.aspx?ID=9).

  16. International Initiative for Impact Evaluation Systematic Reviews Database (3ie; www.3ieimpact.org/en/evidence/systematic‐reviews).

  17. ClinicalTrials.gov (clinicaltrials.gov).

  18. World Health Organization International Clinical Trials Registry Platform (WHO ICTRP; apps.who.int/trialsearch).

  19. Australian New Zealand Clinical Trials Registry (www.anzctr.org.au).

We will search Ovid MEDLINE using the search strategy in Appendix 1, which uses the sensitivity‐maximising version of the Cochrane Highly Sensitive Search Strategy for identifying randomised trials (Lefebvre 2008), and which we will adapt for other databases. We will not place any language restrictions on the search and we will assess non‐English studies for their need for translation on a case‐by‐case basis (Higgins 2011a).

Searching other resources

We will search the reference lists of studies selected for inclusion for additional references. We will also contact lead authors in this field for information about ongoing or unpublished studies.

Data collection and analysis

Selection of studies

We will collate and upload all identified citations to the review management software, Covidence (Covidence), removing any duplicates. Two review authors (from ZM, CT, CL, CJS) will then independently screen titles and abstracts for assessment against the inclusion criteria for the review (Criteria for considering studies for this review). We will obtain the full text of any paper that is clearly eligible for inclusion or where there is any doubt about eligibility. Two review authors (from ZM, CT, CL, CJS) will independently assess the full text against the inclusion criteria. We will exclude full‐text reports that do not meet the inclusion criteria and provide reasons for exclusion in the review and in the 'Characteristics of excluded studies' tables. Any disagreements that arise between the review authors will be resolved through discussion, or with a third, independent review author (from ZM, CT, CL, CJS). We will record our decisions in a study flow diagram (Moher 2009).

Data extraction and management

Two review authors from the review team (from ZM, CT, CL, CJS) will independently extract data from included studies using a standardised data extraction tool. This tool will be piloted and modified accordingly. We will extract specific data on the population, intervention, study methods and outcomes of significance to the review question and specific objectives, as listed below.

  1. Participants: number randomised (including the number of withdrawals and whether data were imputed and the imputation method), age distribution, gender, type of schooling, class sizes, time or months of the year (season), sociodemographics (race, ethnicity, language spoken), and country.

  2. Intervention: the rinse‐free hand wash manufacturer, composition, active ingredient, dosage or frequency, application (who delivered it) and, when possible, cost. Details around any education regarding the use of the rinse‐free hand wash such as who delivered the education and the format for delivery (online or in person) will be extracted.

  3. Outcomes: outcome definition and unit of measurement, the number of participants allocated to each group, the sample size for each outcome.

  4. Results: events per groups and subgroups.

Any disagreements that arise between the review authors will be resolved through discussion, or with a third review author (from ZM, CT, CL, CJS).

Assessment of risk of bias in included studies

Two independent review authors from the review team (from ZM, CT, CL, CJS) will critically appraise selected studies at the outcome level for risk of bias as detailed in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). This tool assesses the following domains of bias; selection (random sequence generation and allocation concealment), performance, detection, attrition, reporting and other sources of bias. We will assess the domains as high, low or unclear risk of bias, following the guidance in Table 8.5.d in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a), and as described in Appendix 2. Any disagreements that arise between the review authors will be resolved through discussion, or with a third, independent review author (from ZM, CT, CL, CJS). We will report the results of the assessment in narrative form, a graph and in a table.

Measures of treatment effect

We will pool studies, where possible, in a statistical meta‐analysis using Review Manager 5 (RevMan 5) (RevMan 2014).

Dichotomous data

We will collect dichotomous data such as reporting whether a student was absent or not. We will calculate effect sizes as odds ratios (OR) and present these with 95% confidence intervals (CIs). It is unlikely that there will be no events in a treatment arm, however, if this occurs, RevMan 2014 will add a fixed value of 0.5 to the empty cell. If there are no events in the study, we will exclude the study from the meta‐analysis (Higgins 2011b).

Time‐to‐event data

We will analyse time‐to‐event data (if relevant) as dichotomous data, if appropriate. If hazard ratios are reported and suitable for synthesis, we will compute risk ratios (RR) for other similar studies, so that a synthesis across studies can occur.

Continuous data

As absenteeism can occur on multiple occasions, it may be that the mean days absent is reported. We will calculate effect sizes as mean differences (MD) and present these with 95% CIs. If different scales are used, we will report effect sizes using standardised mean differences (SMD).

Unit of analysis issues

Cluster‐randomised trials

We are likely to encounter unit of analysis issues in this systematic review, as groups of individuals are likely to be randomised and assigned together (in clusters such as classrooms or schools) (Higgins 2011b). We will take appropriate measures to address unit of analysis issues such as using the generic inverse variance method in RevMan 2014 when studies have analysed their data accounting for their cluster design. If studies have not taken their cluster design into account in their initial analysis, we will analyse clusters as if the randomisation process was performed on the individuals rather than the clusters (Higgins 2011b). It is likely that authors will have taken steps to control for clustering in their analysis, however, if not, we will request the individual participant data to calculate an estimate of the intracluster correlation coefficient (ICC). If data are not available, we will obtain these estimates from external sources and use these to reanalyse the data to obtain the approximately correct analyses, which we will then enter into RevMan 2014 using the generic inverse variance method.

Dealing with missing data

We will request missing or additional data from authors of studies, when required. If authors cannot be contacted or do not respond to requests, we will highlight this in the Results and Discussion sections and Tables of included studies in the review. We will not impute missing data with replacement values. We will analyse only available data. We will address the potential impact of missing data in the Discussion section of the review (Higgins 2011a).

Assessment of heterogeneity

We will assess clinical and methodological heterogeneity by evaluating the similarities and differences across studies in terms of the population (including age ranges, urban or rural, country, (including low‐ and middle‐income countries compared to high‐income countries) and type of schooling), the intervention (dose and frequency), and study design (such as cluster trials compared to non‐cluster trials). We will assess statistical heterogeneity visually by inspection of the forest plot and statistically by Cochran's Q (P value ≤ 0.10), and by I², which is a statistic used for quantifying inconsistency in meta‐analysis. In a meta‐analysis, which uses a random‐effects model, we will also report tau², an estimate of between‐study variability. We will interpret the I² according to the guidance in theCochrane Handbook for Systematic Reviews of Interventions, bearing in mind the limitations of concrete thresholds for I² (Deeks 2011):

  1. 0% to 40%: might not be important;

  2. 30% to 60%: may represent moderate heterogeneity;

  3. 50% to 90%: may represent substantial heterogeneity; or

  4. 75% to 100%: considerable heterogeneity.

Assessment of reporting biases

To address publication bias, we will seek both published and unpublished literature. Additionally, if there is an adequate number of studies (at least 10), we will create funnel plots to investigate reporting bias (Sterne 2011). In the case of 10 or more studies, for continuous data, we will use Egger's test (Egger 1997). If effect sizes appear to depend on the size of the trial, we will explore whether this association is due to heterogeneity or publication bias.

Data synthesis

Regardless of how the data are reported in the included studies (such as average or median days absent per group, as total days absent within each group, or as an incidence rate (e.g. 2 absences per 100 child days) per group), we will transform the data to a common effect size, when possible, to facilitate meta‐analysis.

As we intend to generalise the results beyond the included studies, we will use the random‐effects model as the default model, as this is a more appropriate approach than the fixed‐effect model for this purpose (Tufanaru 2015). We will use the inverse variance method, available in RevMan 2014, for both dichotomous and continuous data. We will only use the fixed‐effect model if it is not appropriate to use the random‐effects model (for example, if fewer than five studies are included in the meta‐analysis) (Cooper 1994; Guolo 2015; Murad 2015; Tufanaru 2015). We will synthesise the data in meta‐analysis and present them in forest plots using RevMan 2014, when possible. When synthesis in a meta‐analysis is not possible, due to significant clinical or methodological heterogeneity, we will provide a narrative description of the results.

Summary of findings

We will create a 'Summary of findings' table using GRADEPro GDT software (GRADEpro GDT 2016), based on review data exported from RevMan 2014. Following the GRADE approach (Schünemann 2011; Schünemann 2013), two authors from the review team (ZM, CT, CL, CJS) will assess the quality of the evidence for both the primary and secondary outcomes, based on the risk of bias, directness, heterogeneity, precision and risk of publication bias. We will present the following information in the 'Summary of findings' table, when appropriate: absolute risks for the treatment and control, estimates of relative risk, and a ranking of the quality of the evidence.

Subgroup analysis and investigation of heterogeneity

We intend to explore heterogeneity by conducting the subgroup analyses listed below.

  1. Age, coinciding with facility type (approximately 2 to 5 years of age (preschool), 6 to 12 years of age (primary school), and 13 to 18 years of age (secondary school)).

  2. The frequency of the intervention (i.e. only after meals, before and after meals and toilet breaks, on arrival at preschool or school, etc.).

  3. The person delivering the intervention or responsible for the intervention (teachers or caregivers compared to a child‐initiated intervention).

  4. The means of recording absence (teacher reported compared to other measures).

  5. The provision of hand wash alone versus the provision of hand wash plus additional strategies (such as education).

  6. By gross national income per capita, based on World Bank classifications of low‐, middle‐ and high‐income countries.

Sensitivity analysis

We intend to carry out sensitivity analyses, when necessary, to assess the robustness of our results to the:

  1. choice of model (fixed‐effect versus random‐effects models); and

  2. exclusion of studies at high risk of bias (determined by both the allocation concealment and blinding of outcome assessment 'Risk of bias' criteria being rated as high).

Acknowledgements

The review authors acknowledge the support of the Cochrane Developmental, Psychosocial and Learning Problems Review Group and feedback from the editors of the Group.

Appendices

Appendix 1. Ovid MEDLINE search strategy

1 hand sanitizers/ 2 hand hygiene/ 3 hand disinfection/ 4 (hand$ adj3 (hygiene or wash$ or wipe$ or gel$ or rub$ or foam$ or disinfect$)).tw. 5 ((antimicrobial$ or anti‐microbial$ or antiseptic$ or anti‐septic$ or anti‐infect$ or antiinfect$ or antiviral$ or anti‐viral$ or alcohol$ or ethanol$) adj5 (hand$ or wash$ or wipe$ or gel$ or rub$ or foam$)).tw. 6 (sanitis$ or sanitiz$).tw. 7 (handwash$ or handrub$ or handgel$ or handfoam$ or handsaniti$).tw. 8 (rinse‐free$ or rinsefree$ or rinseless or rinse‐less or non‐rinse$).tw. 9 or/1‐8 10 Anti‐infective agents, local/ 11 exp Communicable Diseases/ 12 Community‐Acquired Infections/ 13 Hygiene/ 14 Infection Control/ 15 Alcohols/ 16 Ethanol/ 17 or/10‐16 18 Hands/ 19 17 and 18 20 9 or 19 21 Child, Preschool/ 22 Child/ 23 Adolescent/ 24 Students/ 25 School/ 26 Schools, Nursery/ 27 Child Day Care Centers/ 28 (preschool$ or pre‐school$ or toddler$ or child$ or pre‐teen$ or adolescen$ or boy$ or girl$ or teen$or pre‐teen$ or young person$ or young people).tw. 29 (daycare$ or day care$ or nurser$ or kindergarten$ or kinder‐garten$ or pupil$ or student$ or school$ or college$).tw. 30 Absenteeism/ 31 absentee$.tw. 32 or/21‐31 33 20 and 32 34 randomized controlled trial.pt. 35 controlled clinical trial.pt. 36 randomi#ed.ab. 37 placebo$.ab. 38 drug therapy.fs. 39 randomly.ab. 40 trial.ab. 41 groups.ab. 42 or/34‐41 43 exp animals/ not humans.sh. 44 42 not 43 45 33 and 44

Appendix 2. 'Risk of bias' assessment

1. Random sequence generation (selection bias)

This refers to whether a random process was used to allocate participants to study groups (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: use of the term 'random' and particularly referring to a random number table or computer‐generated random numbers, in addition to the guidance in Table 8.5.d in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a).

  2. High risk of bias: if it is clear that a pseudo‐random or a systematic, non‐random approach was taken, such as allocation by location or date.

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

2. Allocation concealment (selection bias)

This refers to whether foreknowledge of forthcoming allocations was prevented (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: when methods such as central allocation or sequentially‐numbered, opaque, sealed envelopes are used. In cluster trials, clusters are often randomised and allocated at the same time, meaning there is a low risk of bias (Higgins 2011a).

  2. High risk of bias: when an open, random allocation schedule is used or alternate allocation, or any other method where allocators may potentially foresee assignments (Higgins 2011a).

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

3. Blinding of participants and personnel (performance bias)

This can be present when study participants and personnel are aware of the group to which they have been allocated (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: when participants and personnel are unable to determine the treatment group to which they have been allocated.

  2. High risk of bias: when participants and personnel are aware of the group to which they have been allocated.

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

4. Blinding of outcome assessment (detection bias)

This can be present when outcome assessors are aware of the groups to which participants are allocated (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: when outcome assessors are unable to determine treatment allocation.

  2. High risk of bias: when outcome assessors are not blinded to treatment allocation.

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

5. Incomplete outcome data (attrition bias)

This can be present when there is incomplete data for each main outcome, including attrition and exclusions (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: no missing outcome data, or the amount of missing data is balanced across groups, or missing data have been imputed appropriately (Higgins 2011a).

  2. High risk of bias: missing outcome data, which may be related to the intervention or outcome; or imbalance in missing data across groups.

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

6. Selective outcome reporting (reporting bias)

This can be present when there are differences between reported and unreported findings (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: in reviewing the study protocol it is clear that all prespecified outcomes were collected and reported on.

  2. High risk of bias: when not all of the study's prespecified outcomes or outcome measurements are reported, or expected outcomes (such as absenteeism) are clearly lacking.

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

7. Other bias

This refers to other types of bias that may occur, such as those that can occur with cluster trials (Higgins 2011a). We will assess included studies to be at low, high or unclear risk of bias on this domain as follows.

  1. Low risk of bias: when none of the issues reported below are present.

  2. High risk of bias: when there is clear imbalance in baseline characteristics between groups, loss of clusters in cluster trials, incorrect analysis (such as not accounting for clustering), or evidence of individuals being preferentially recruited to clusters following the randomisation of clusters (Higgins 2011a).

  3. Unclear risk of bias: insufficient information to make a judgement of high or low risk of bias.

Contributions of authors

All authors contributed to the development and review of this protocol.

Zachary Munn (ZM) — drafted the protocol and incorporated feedback from other group members. ZM is the guarantor for the review. Catalin Tufanaru — assisted with searching for literature and writing, including methodological guidance. Craig Lockwood — conceptualised the idea and focus of the review and assisted with the draft. Cindy J Stern — contributed to the draft of the protocol and provided feedback.

Sources of support

Internal sources

  • Joanna Briggs Institute, Australia.

    Employer of all four authors

External sources

  • No sources of support supplied

Declarations of interest

Zachary Munn — none known. Catalin Tufanaru (CT) — received royalties from WK Lippincott Williams and Wilkins for two books 'Statistics for Systematic Review Authors' and 'Synthesizing Economic Evidence'. CT declares that the contents of these books are not related to the review and that there is no information in either book about the interventions investigated in this review. Craig Lockwood — none known. Cindy J Stern — none known.

New

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