Types of studies

We will include parallel‐group randomised controlled trials (RCTs) including the first period of cross‐over studies and cluster‐RCTs if there are 10 or more clusters. We will include studies reported as full text, those published as abstracts only, and unpublished data. We will restrict our review to placebo‐controlled trials. The common cold is a subjective experience, and there can be great variation among people in how they classify their symptoms and when they consider themselves to have recovered. However, as such subjective variation applies similarly to both intervention and placebo group participants, it should not lead to any bias. Subjectivity in the assessment of common cold symptoms can increase inaccuracy, which can lead to false‐negative findings, but is unlikely to lead to false‐positive findings in studies with adequate blinding.

Types of participants

We will include adults and children of either gender and any age. We will define children as people aged up to 18 years and adults as those aged 18 years and over. We will define older adults as those aged 65 years and over. We will not exclude studies with participants who have comorbidities.

We will include prevention trials that involved participants who did not have common cold symptoms before the intervention started.

We will include treatment trials that involved participants who had cold symptoms before the intervention started.

We will include studies in which participants had either natural common colds or induced common colds. We will analyse prevention trials and treatment trials data separately. We will also analyse natural common colds and induced common colds separately.

Types of interventions

We will include trials investigating oral zinc (tablets and syrups but not lozenges) versus placebo, zinc lozenges versus placebo, and nasal zinc administration versus placebo.

There will be no limitation on zinc dose administered by any route or duration of therapy.

We will not exclude studies with co‐interventions.

Types of outcome measures

Because common cold is not a precisely defined disease, we will describe the definitions for the common cold applied in the included studies in 'Characteristics of included studies' tables in the review.

Electronic searches

We will search the following databases from inception to present:

• Cochrane Central Register of Controlled Trials (CENTRAL), which contains the Cochrane Acute Respiratory Infection Group Specialised Register;

• PubMed; and

• Embase (Elsevier).

We will use the search strategy described in Appendix 1 to search PubMed. We will modify this search appropriately for other databases and clinical trials registers.

We will also search ClinicalTrials.gov (www.clinicaltrials.gov) and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (apps.who.int/trialsearch/).

Searching other resources

We will check reference lists of all primary studies and review articles for additional references. We will contact experts in the field to identify additional unpublished material.

Selection of studies

Two review authors (HH, EC) will independently screen titles and abstracts identified as a result of the searches to select potentially eligible trials). We will retrieve the full‐text study reports/publications, and two review authors (HH, EC) will independently screen the full texts and identify studies for inclusion, and identify and record reasons for exclusion of the ineligible studies. Any disagreements will be resolved through discussion. We will identify and exclude duplicates and collate multiple reports of the same study so that each study rather than each report is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table (Moher 2009). We will include studies reported as full text, those published as abstract only, and unpublished data. We will not impose any language restrictions.

Data extraction and management

We will use a data collection form for study characteristics and outcome data that has been piloted on at least one study in the review. One review author (HH) will extract the following study characteristics from the included studies.

1. Methods: study design, total duration of study, details of any 'run in' period, number of study centres and location, study setting, withdrawals, and date of study.

2. Participants: N, mean age, age range, gender, diagnostic criteria, inclusion criteria, and exclusion criteria.

3. Interventions: intervention, comparison, concomitant medications, and excluded medications.

4. Outcomes: primary and secondary outcomes specified and collected, and time points reported.

5. Notes: funding for trial, and notable conflicts of interest of trial authors.

Two review authors (HH, EC) will independently extract outcome data from the included studies. We will note in the 'Characteristics of included studies' table if outcome data are not reported in a usable format. We will resolve disagreements by consensus. One review author (HH) will transfer data into the Review Manager 5 file (Review Manager 2014). Both review authors (HH, EC) will double check that data are entered correctly by comparing the data presented in the systematic review with those in the study reports, and they will check study characteristics against the trial reports and data collection forms for accuracy.

Assessment of risk of bias in included studies

Two review authors (HH, EC) will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). Any disagreements will be resolved by discussion. We will assess the risk of bias according to the following domains.

1. Random sequence generation.

2. Allocation concealment.

3. Blinding of participants and personnel.

4. Blinding of outcome assessment.

5. Incomplete outcome data.

6. Selective outcome reporting.

7. Other bias.

We will grade each potential source of bias as high, low, or unclear and provide a quote from the study report together with a justification for our judgement in the 'Risk of bias' table. We will summarise the 'Risk of bias' judgements across different studies for each of the domains listed. We will consider blinding separately for different key outcomes, where necessary. Where information on risk of bias relates to unpublished data or correspondence with a trialist, we will note this in the 'Risk of bias' table.

When considering treatment effects, we will take into account the risk of bias for the studies that contribute to that outcome.

Measures of treatment effect

We will enter the outcome data for each study into the data tables in Review Manager 5 to calculate the treatment effects (Review Manager 2014).

We will calculate the risk ratio (RR) for dichotomous outcomes. We will calculate the effect of zinc on common cold duration in days, and we will calculate the pooled mean difference (MD) estimate. Because duration is a time‐related outcome, we will also conduct survival analysis in accordance with guidance in Section 9.2.6 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). Survival analysis enables visual inspection and formal analysis of possible time‐dependent variations in treatment effects. Survival analysis is not confounded by censored data or outlier participants who had particularly long colds. In contrast, outliers may decrease the statistical power of a t‐test when examining cold duration, because these data inflate the standard deviation estimates.

Unit of analysis issues

If there are several zinc arms for a single placebo group, we will divide the placebo group for the zinc arms if we show several zinc arms in the same analysis table. If we find cross‐over trials, we will include data for the first observation period. Because the common cold is contagious and different groups of people have different levels of incidence, we will include cluster‐randomised trials only if there are 10 or more clusters. In such cases, we will conduct the analysis at the same level as the allocation, using a summary measurement from each cluster.

Dealing with missing data

We will contact investigators or study sponsors to verify key study characteristics and to obtain missing numerical outcome data where possible (e.g. when a study is identified as abstract only). Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of excluding such studies in the overall assessment of results by a sensitivity analysis.

If numerical outcome data such as standard deviations or correlation coefficients are missing and cannot be obtained from the authors, we will calculate them from other available statistics such as P values according to the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

Assessment of heterogeneity

We will use the I² statistic to estimate heterogeneity among the trials in each analysis. We will also use the Chi² test to calculate the P value for the heterogeneity. We will consider an I² value of 50% or more to represent a substantial level of heterogeneity, though heterogeneity is not a dichotomous issue (Higgins 2003).

If we identify substantial heterogeneity, we will report this and explore possible causes in prespecified subgroup analyses.

Assessment of reporting biases

We will construct funnel plots, but will interpret them cautiously, since there are a number of problems with the use of funnel plots in the assessment of publication bias (Ioannidis 2007; Lau 2006; Sterne 2011; Terrin 2005). We will also narratively consider the possibility of publication bias in the Discussion section.

Data synthesis

We will pool data from studies judged to be clinically homogeneous using Review Manager 5 software (Review Manager 2014). If more than one study provides usable data for any single comparison, we will perform fixed‐effect meta‐analysis.

Subgroup analysis and investigation of heterogeneity

We plan to conduct subgroup analysis to investigate the preventive effects of zinc for people in low‐income countries compared with those in middle‐ and high‐income countries. We will use the World Bank 2017 classification to determine countries' income status.

In the analysis of treatment effects, we intend to perform subgroup analyses for children, adults, and older adults where possible.

We will also explore the effects of zinc lozenges for:

1. dose of elemental zinc per day: < 75 mg versus ≥ 75 mg; and

2. zinc acetate lozenges versus zinc gluconate lozenges in zinc lozenge trials with doses ≥ 75 mg/day.

We will use the Chi² test to test for subgroup interactions in Review Manager 5 (Review Manager 2014).

If there are several studies that are clinically so similar that they can be considered to measure the same effect, we may consider carrying out meta‐regression to simultaneously analyse several subgroup variables. However, meta‐regression is not a valid approach if there are fewer than 10 trials, as described in Section 9.6.4 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

Sensitivity analysis

We plan to perform sensitivity analyses excluding trials:

• with methodological shortcomings leading to inadequate randomisation or blinding; and

• those with missing data that required imputation.