Types of studies

Randomised controlled trials (RCTs), quasi‐randomised controlled trials (QRCTs), controlled before and after studies (CBAs), and interrupted time series (ITS) with at least three time points before and after the intervention.

We consider including QRCT, CBA and ITS designs, as preliminary literature searching indicates a scarcity of RCTs of text messaging interventions. However, if a sufficient number of well‐conducted RCTs is identified (upon which we can draw reliable conclusions), we will exclude other study designs during the review stage. If all study designs are included, we will perform a sensitivity analysis to assess whether the results change by including non‐RCT designs.

Types of participants

We will consider all study participants regardless of age, gender and ethnicity, as well as all types and stages of diseases. We will include studies in all settings, i.e. primary care settings (services of primary health care), outpatient settings (outpatient clinics), community settings (public health services) and hospital settings. We will not exclude studies according to the type of healthcare provider (e.g. nurse, doctor, allied staff).

Types of interventions

We will include interventions that use Short Messaging Service (SMS or 'text messaging) or Multimedia Message Service (MMS) messaging in communicating results of all medical tests, regardless of the purpose of the test (screening, diagnostic, guide to treatment, monitoring etc.). The SMS or MMS messaging needs to be between a healthcare provider (either in person or automated) or a 'treatment buddy' and patient, regardless of who sends the first SMS.

The review will not include interventions communicating results to people other than those for whom the medical investigation has been performed (e.g. partner notifications) or between two healthcare providers, such as from a laboratory to a rural health clinic. We will exclude studies in which SMS/MMS is a part of a multifaceted intervention, as it will not be possible to separate the effects of messaging alone.

We will make comparisons between outcomes of mobile phone messaging and no intervention, as well as other modes of communication such as face‐to‐face, postal letters, calls to landline or mobile telephones, e‐mail or via electronic health records; and if applicable, automated versus personal text messaging.

Types of outcome measures

A number of processes and outcomes may be affected by interventions that aim to enhance and/or facilitate the communication between patients and healthcare providers using mobile phone messaging.

Primary outcomes of interest are whether the text message has been understood and acted upon correctly by the patient as meant by the healthcare provider and whether text messaging was an appropriate mode of communication.

To evaluate whether the text message was acted upon correctly, outcomes regarding patients' health status and well‐being (including physiological measures, e.g. blood pressure; biomarkers or clinical progression; clinical assessments, e.g. wound healing; patient self‐reports of symptom resolution or quality of life; patient self‐esteem; adoption of lifestyle behaviours) are relevant. Short term responses to the test result and intervention, including actions taken by the patients to improve their health status and well‐being (such as making a follow‐up appointment), are also included as primary outcome measures.

To evaluate whether text messaging was an appropriate mode of communication, the outcomes listed below are relevant:

• Patient / healthcare consumer / carer's or healthcare providers' evaluation of the communication mode (including impact on self‐efficacy and support, satisfaction, availability, convenience, readiness to use and timeliness);

• Patient and/or healthcare providers' use of resources following intervention (including time, health care or monetary resources);

• Harm or adverse effects regarding the communication mode (e.g. breach of confidentiality, failure or delays in message delivery);

• Costs and cost‐effectiveness.

We will also record data related to the medical setting and clinical context of patients to assess any changes in outcomes within that context.

Measurement of effect of the intervention

We will use risk ratios (RR) as effect measures for dichotomous outcomes and standardised mean differences (SMD) for continuous outcomes (Deeks 2001). We will report confidence intervals with all measures of effect.

Unit of analysis issues

We will take into account unit of analysis issues resulting from cluster‐randomised trials, repeated measurements and studies with more than two treatment groups. If applicable, the data will be analysed using the recommendations in Cochrane Collaboration Open Learning Module on issues related to the unit of analysis (Alderson 2002a).

Dealing with missing data

We will obtain relevant missing data from study authors, if feasible. We will carefully evaluate important numerical data such as screened, eligible and randomised patients as well as intention‐to‐treat and per‐protocol population. With incomplete outcome data (such as drop‐outs, misses to follow‐up and withdrawn study participants), we will assess and report the risk of bias as 'low' or 'high' as guided by the Cochrane Handbook (Higgins 2008) and identify the numbers as well as the reasons for incomplete data (requesting for additional information from the study authors if necessary). Issues of last‐observation‐carried‐forward (LOCF) will be critically appraised and compared to specifications of primary outcome parameters and power calculation.

Assessment of reporting biases

We will assess reporting biases statistically and using funnel plots in RevMan 5. We will assess selection bias, performance bias, attrition bias and detection bias in the included studies using the checklist provided in Ryan 2007.

Data synthesis

We will present a narrative overview of the findings, including tabular summaries of extracted data. We aim to structure the narrative primarily according to the intended purpose of the message. We will consider whether it is appropriate to combine the studies quantitatively once we have completed the search. The decision is likely to rest on the diversity of interventions and outcome measures used in the studies. Studies will be classified on the following issues:

• Study design: RCTs, QRCTs, CBAs, ITS;

• Outcome measures used, as described at Types of outcome measures.

If quantitative analysis is undertaken, the meta‐analysis will depend on the outcomes reported. For continuous data, where outcomes have been measured in a standard way across studies, we will report the SMD and confidence intervals (Alderson 2002b). For dichotomous data, when outcomes have been measured in a standard way, we will report the RR. In such cases, a cautious approach will be taken to combining results, and the rationale will be detailed. We will conduct statistical analysis according to the guidelines in the Cochrane Handbook (Higgins 2008).

Assessment of heterogeneity

In the event of substantial clinical, methodological or statistical heterogeneity, we will not combine study results in meta‐analysis. We will identify heterogeneity by visual inspection of the forest plots, by using a standard Chi² test and a significance level of alpha = 0.1, in view of the low power of such tests. We will also examine heterogeneity with I², where I² values of 50% or more indicate a substantial level of heterogeneity (Higgins 2003). When heterogeneity is found, we will attempt to determine potential reasons for it by examining individual study characteristics and those of subgroups of the main body of evidence.

Subgroup analysis

If there are sufficient trial data, and if appropriate, we will analyse subgroups according to age, as mobile phone messaging usage and general healthcare utilisation patterns are different across age groups. We will distribute patients into three subgroups; 0 to 18, 18 to 55, over 55. The distribution was made on the basis of a survey by MORI in 2005 (MORI 2005). The use of text messaging by different age groups varied, but was significant and consistently high except in the over 55 age group where around only 40% of users had communicated by text messaging.

Sensitivity analysis

We will perform sensitivity analyses where appropriate in order to explore the influence of the following factors on effect size:

• excluding unpublished studies;

• taking account of risk of bias of included studies, as specified above;

• excluding any large studies to establish how they impact on the results;

• excluding studies using the following filters: criteria used for clinical diagnosis and eligibility for intervention, language of publication, source of funding (industry versus other), country;

• the length of the interval between delivery of the intervention and measurement of the effect.

We may also test the robustness of the results by repeating the analysis using different measures of effects size (risk difference, odds ratio etc.) and different statistical models (fixed effect and random effects models).

Consumer participation

The draft review will be circulated for peer review by consumers in the Cochrane Collaboration. We will examine whether consumers were involved in the design and implementation of each included study. We also aim to receive consumer feedback from organisations that may represent consumers/patients who would be affected by the interventions identified in our review.

Dissemination plans

We will aim to promote and disseminate the findings of our review through publication of the review in peer‐reviewed journal(s), by presenting the findings at conferences and scientific meetings and by giving talks on the topic of the review for broad audiences varying from public and policy‐makers to healthcare providers. We will also promote and disseminate the findings of the review through organisations representing consumers ‐ as described above.