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. 2019 Oct 19;2019(10):CD013454. doi: 10.1002/14651858.CD013454

Mobile phone text messaging for the prevention of sexually transmitted infections

Mohaddesseh Noura 1,✉, Azam Rahmani 2, Shayesteh Jahanfar 3, Ursula M Ellis 4
PMCID: PMC6800541

Abstract

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

To assess the effectiveness and safety of mobile phone text messaging for the prevention of sexually transmitted infections (STIs) and high‐risk sexual behavior.

Background

Description of the condition

Sexually transmitted infections (STIs) are defined as infections that are passed from one person to another via sexual contact (vaginal intercourse, oral sex, and anal sex). Examples of STIs are chlamydia, syphilis, trichomoniasis, gonorrhoea, herpes simplex virus (HSV), human papilloma virus (HPV), hepatitis B and human immunodeficency virus (HIV). Globally, STIs affect millions of young people between 15 and 24 years of age, as well as older people (United Nations Development Programme 2014). According to estimates by the World Health Organization, there are 357 million new cases of the following four STIs each year: chlamydia (131 million), gonorrhoea (78 million), syphilis (5.6 million) and trichomoniasis (143 million) (WHO 2016). At any point in time, more than 290 million women suffer from HPV infections, one of the most common types of STI (WHO 2015). The Centers for Disease Control and Prevention (CDC) reported that there are 20 million new cases of STIs annually that cost the USA approximately $16 billion in lifetime healthcare costs (Steiner 2014).

A substantial concern related to STIs is poor health outcomes for young people. Gonorrhoea and chlamydia could cause prostatitis and pelvic pain in men, whilst pelvic inflammatory disease and infertility are frequently seen in women. Syphilis can cause stillbirth and congenital malformations and is the main cause of neonatal mortality in newborns. HPV can lead to cancer in the uterine cervix, vulva, vagina, penis, anus and throat.

Because most of these infections are asymptomatic or unrecognized, young people who do not regularly access health services may miss out on proper diagnosis and management, and their sexual and reproductive health may be affected (Moodley 2000). In addition, young people with STI symptoms often do not seek treatment. Therefore, it is not surprising that young women in the reproductive age group have the greatest burden of STIs (Moodley 2000). This problem is more important in low‐ and middle‐income countries (LMICs) where STIs are more prevalent and access to healthcare is limited (Moodley 2000).

Young people have easy access to social media and text messaging in low‐ and middle‐income countries. Therefore, it seems logical to use Short Message Service (SMS) to deliver information and strategies aimed at preventing high‐risk sexual behavior and STIs (e.g. chlamydia, gonorrhoea) (Lunny 2014) to reduce the burden of adverse health outcomes among these individuals.

Description of the intervention

Digital media technology (DMT) is defined as digitalized content that can be transmitted over the internet or computer networks. It can include text, audio, video, and graphics. Use of mobile application as of DMT is the intervention of interest in this systematic review. Mobile technology, in particular SMS, facilitates a variety of communication methods which could provide an essential opportunity for health education and health promotion in general and for sexual health in particular (Bull 2012). Therefore, SMS can be viewed as an alternative approach to program delivery, instead of personal or group‐delivered programs. A telephone intervention has some advantages compared to face‐to‐face sessions. It can reduce costs, and it is faster and more convenient for users (Car 2003). Moreover, transport and infrastructure barriers can be overcome because young people do not have to visit their healthcare providers. They can decide whether they would be open to release their identity or avoid being intimidated by face‐to‐face communication (Bunn 2005) when seeking care to deal with STIs.

Mobile phone text messaging (MPTM), is the act of composing and sending brief, electronic messages between two or more mobile phones, or fixed or portable devices, over a phone network. The term originally referred to messages sent using SMS. Text messaging covers all 26 alphabetical letters and numerals. Alpha‐numeric messages or text messages can be sent by the texter or received by the textee (Lim 2012). Messaging could create an appropriate opportunity for breaking down geographic boundaries in sexual health education (Guse 2012). Mobile phones are used universally by some 6 billion people globally. There were approximately 3.8 billion mobile‐phone users in developing countries by 2011 (International Telecommunication Union 2010). Mobile phones are owned by 67% of the world’s population (Head 2013).

Short Message Service is commonly used by young people and may be a promising way to prevent STIs because it is widely available, inexpensive and instantly accessible (Lim 2012). It also demonstrates strong potential as a tool for healthcare improvement for several reasons: it is available on almost every model of mobile phone; it is quite cheap, popular, and easy to use; it also could be used for educational purposes applicable to various types of healthy behaviours or risky situations (Rice 2003). Text messaging also has the advantage of being asynchronous because it can be accessed at any time that is personally convenient (Fjeldsoe 2009). Moreover, if the phone is turned off, messages will be delivered once the phone is turned on. Additionally, text messaging is an mHealth (mobile health) innovation for which utility remains, even in resource‐poor settings in which people may not have access to expensive technology (Fjeldsoe 2009). This technology supports interactivity, which allows people to obtain extra help when needed. Motivational messages, monitoring, and behavior‐change tools used in face‐to‐face support can be modified for delivery via mobile phones (Free 2013). Messages commenced prior to quitting and were based on effective brief interventions including quitting advice and motivational messages. Interactive components included the ability to text in for more support (in the instance of cravings or lapses) and an optional "Quit Buddy" (Rodger 2005)

Text messaging is suitable for behavior change as it can deliver strong messages with powerful contents. It can be used for in‐the‐moment, personally‐tailored health communication, delivering prevention components based on theoretical models such as the theory of planned behavior and the health belief model (Glanz 2005). These new digital media have significantly modified the communication mode, particularly for young people benefiting from sexual health promotion interventions. SMS was used in a large clinical setting to improve knowledge, which in turn increased STI retesting (Bourne 2011). One study estimated that the numbers of young people being tested for chlamydia annually increased from 7% to 12% after SMS was used to deliver health messages (Gold 2011). Increasing the rate of chlamydia testing is important because it could reduce the duration, transmission and the risk of infection (Lim 2012). Previous studies showed text messaging as a positive method for improving the rate of STIs and their treatment (Reed 2014).

Text messages could be about sexual health information, STIs (testing, simple treatment, STI clearance, condom use, motivation for retesting), protective and risky sexual behaviours, and abstinence (Lim 2012). Messages used for chlamydia infections include the following examples.

  • "Chlamydia: hard to spell, easy to catch. Use a condom."

  • "Chlamydia can cause infertility."

  • "Chlamydia can be diagnosed by a urine test."

  • "People infected with Chlamydia often don't have any symptoms and won't know they have the infection."

  • “Well before the Big Day Out, its time to clear Chlamydia out. Pap smears and blood tests are not the go, you need to pee in order to know.”

  • “Speak to your doctor about a Chlamydia test."

  • "I know you're hurting, feels like you're burning–but maybe not? Don’t be the biggest loser! Most STIs have no symptoms, only way to know is to get tested."

  • “Speak to your doctor about a Chlamydia test."

  • “Get those dancing shoes on, it takes two to tango! Pill for pregnancy, condoms for Chlamydia.”

  • “Don’t be fooled, Chlamydia testing and treatment is easy” (Gold 2011).

These messages could be sent at various times and on different days, and could be mostly sent on Friday and Saturday evenings, as described in the literature (Lim 2012). Also, text messages could be used as a reminder of a clinical appointment, for example "You are due for your next screening" (Bourne 2011).

How the intervention might work

In the field of sexual health services, SMS is usually used for reminders of appointments and rescreening, delivery of results, communication of information, sexual health promotion, and assistance with contact‐tracing (Lunny 2014). It has also been shown to decrease the amount of time from diagnosis to treatment among positive chlamydia patients, increase the rate of retesting among high‐risk groups, and reduce the amount of missed clinic appointments. STI preventional interventions, such as mobile phone messaging, can improve young people's knowledge, understanding and self‐efficacy. Thereby, SMS technology can encourage people to accept healthier behaviours. For instance, young people may learn not to engage in risky sexual behaviours, which could potentially reduce STI incidence rates (Car 2003). Studies have found that periodic prompts and reminders are effective methods to encourage and reinforce healthy behaviours (Fry 2009), and improve communication and a sense of responsibility to take care of one's health. Moreover, repeating messages via text messaging may increase the likelihood of reinforcing positive behavioral changes to prevent STIs (Fry 2009).

Text messaging can also be beneficial for those who dread facing healthcare professionals in person due to fear of lack of confidentiality, embarrassment or stigma associated with sexual activities. In such cases, consultation by telephone should be considered to minimize such limitations (Sokol 2006). Morevoer, evidence suggests that SMS is very popular and easy to measure. It can facilitate the delivery of healthcare, and is a cost‐effective form of communication for STI prevention (Brusamento 2013). It is important to note that using SMS for STI prevention could be limited by illiteracy and the short space available in a message (Head 2013).

Why it is important to do this review

Adolescents and young adults aged under 24 years have the highest incidence rates of STIs and a disproportionate number of new infections occur in this age group (Reed 2014). Increasing STI incidence rates strongly suggest the urgency of trying new ways to fight against STIs (Lim 2012). To our knowledge, no review has been done to investigate the impact of text messaging on preventing STIs. The purported benefits of SMS for preventing STIs remain controversial (Fjeldsoe 2009), as the data have been collected in studies with small sample sizes.

Objectives

To assess the effectiveness and safety of mobile phone text messaging for the prevention of sexually transmitted infections (STIs) and high‐risk sexual behavior.

Methods

Criteria for considering studies for this review

Types of studies

Randomized controlled trials (RCTs), cluster‐randomized trials and cross‐over trials.

Types of participants

All sexually active males and females, aged over 14 years.

Types of interventions

Experimental intervention

  • Mobile phone text messaging designed to prevent STIs

Comparators

  • Usual care

  • No intervention

  • Any other mobile phone options; software applications for STI prevention, diagnosis, behavior change, treatment, and retest

Types of outcome measures

Primary outcomes

  • Incidence of any STI during the first year of follow up and specific etiological incidence of STI (N gonorrhoeae, syphilis, C trchomatis, HPV or HS infection).

  • Detection rate of STI

  • Adverse effects of the intervention (e.g. emotional stress or couple break‐up) during the next three months

We will exclude the use of mobile phone text messaging for preventing HIV infection because this has been assessed in another Cochrane Review (van‐Velthoven 2013).

Secondary outcomes

  • Use of alcohol in combination with unsafe sexual behavior (measured by self report)

  • Use of drugs in combination with unsafe sexual behavior (measured by self report)

  • Use of condom to prevent unsafe sexual behavior (measured by self report)

  • Unprotected intercourse (measured by self report)

  • Uptake of STI test (time to rescreening, time to positive test to treatment)

  • Acceptability and feasibility of the contraceptive method used (e.g. condom) measured either as a dichotomous variable (yes/no) or using a validated rating scale (eg VAS) (measured by self report)

  • Final microbiological diagnosis of STI test

  • Number of patients treated after diagnosis following STI testing

Where studies reported multiple time points, the secondary outcomes will be measured at 3 and 12 months after initiation of the intervention

Search methods for identification of studies

We will seek relevant studies irrespective of their language of publication, publication date and publication status (published, unpublished, in press, and in progress). We will use both electronic searching in bibliographic databases and handsearching, as described in theCochrane Handbook for Systematic Reviews of Interventions (Higgins 2016).

Electronic searches

We will contact the Information Specialist of Cochrane Sexually Transmitted Infections in order to implement a comprehensive search strategy to capture as many relevant RCTs as possible in electronic databases. For this purpose, we will use a combination of controlled vocabulary (MeSH, Emtree, DeCS, including exploded terms) and free‐text terms (considering spelling variants, synonyms, acronyms and truncation) for “mobile phone text messaging” and “prevention STI”, with field labels (title and abstract), proximity operators (adj) and boolean operators (OR, AND).

Mobile phones evolved from 1983, hence we start the search from this date.

The sensitivity of the search strategies will be improved by including key words from relevant RCTs that were detected by earlier searches. The search strategies can be found in Appendix 1.

Specifically, we will search the following electronic databases.

  • MEDLINE, MEDLINE In‐Process & Other Non‐Indexed Citations, Daily Update, Ovid platform: inception to present.

  • Embase, Ovid platform: inception to present.

  • Cochrane Central Register of Controlled Trials (CENTRAL), Ovid platform: inception to present.

  • LILACS, iAHx interface: inception to present.

For MEDLINE we will use the Cochrane highly sensitive search strategy for identifying RCTs: sensitivity and precision maximizing version (2008 revision), Ovid format (Higgins 2016). The LILACS search strategy will be combined with the RCT filter of the iAHx interface.

We will also consider searching the following resources.

  • Sexually Transmitted Infections Cochrane Review Group’s Specialized Register, which includes RCTs and controlled clinical trials from 1944 , located through electronic searching (MEDLINE, Embase and CENTRAL) and handsearching.

  • Trials registers

    • WHO International Clinical Trials Registry Platform ICTRP portal (apps.who.int/trialsearch/): inception to present.

    • ClinicalTrials.gov (clinicaltrials.gov/): inception to present.

  • Web of Science: inception to present.

  • PsycINFO: inception to present.

  • System for Information on Grey Literature in Europe “OpenGrey” (opengrey.eu/): inception to present.

These searches will be updated within six months before publication of the review.

Searching other resources

We will attempt to identify additional relevant RCTs by using the following methods.

  • Searching by contacting authors of all RCTs identified by other methods. A comprehensive list of RCTs included in the review, along with the inclusion criteria, will be sent to the first author of each included study and we will ask for any additional studies (published or unpublished) that might be relevant.

  • Handsearching in those journals not indexed in MEDLNE or Embase (according to the journals’ master list ‐ STI Cochrane Review Group) to identify relevant RCTs not covered by electronic searches: Anatolian Journal of Obstetrics & Gynecology, Current Medical Literature Gynecology & Obstetrics, Current Obstetrics and Gynecology Reports, ISRN Obstetrics and Gynecology, Journal of South Asian Federation of Obstetrics & Gynecology, Obstetrics and Gynecology International, Obstetrics Gynaecology and Reproductive Medicine, Sexual Science: the newsletter of the Society for the Scientific Study of Sexuality and Sexualities.

  • Handsearching conference proceeding abstracts for the following events.

    • The International Society for Sexually Transmitted Diseases Research ‐ ISSTDR (www.isstdr.org/): From 2007

    • The British Association for Sexual Health and HIV ‐ BASHH (www.bashh.org/): From 2004

    • International Congress on Infectious Diseases ‐ ICID (www.isid.org/): from 200

    • The International Union against Sexually Transmitted Infections ‐ IUSTI (www.iusti.org/): From 2011

    • International Society for Infectious Diseases ‐ ISID (www.isid.org/): From 2011From 20071

    • Interscience Conference on Antimicrobial Agents and Chemotherapy ‐ ICAAC (www.icaac.org/): From 2011

    • The International Federation of Gynecology and Obstetrics ‐ FIGO (www.figo2012.org/home/): from 2012

  • Handsearching within previous systematic reviews and other relevant publications on the same topic.

  • Handsearching the reference lists of all relevant RCTs identified by other methods.

  • Searching Google Scholar and other digital media technology journals.

Data collection and analysis

Selection of studies

Using a form with predefined inclusion criteria, two review authors (MN and AR), will independently assess all the titles and abstracts of the studies generated by the search, for eligibility. We will assess and obtain full‐text manuscripts for those studies that we agree are potentially eligible. Any disagreements will be resolved by discussion and in cases where no agreement is reached, the third review author (SJ) will resolve the conflict of opinion.

Data extraction and management

The data to be extracted will be organised according to the following five categories.

  1. Methods: authors and citation; start and end dates; location of service (rural, urban); location of study and setting (low‐, middle‐ or high‐income country), study design (RCTs, cluster‐RCTs and cross‐over trials); methods (duration, sequence generation, allocation sequence concealment, blinding), sample size, analysis.

  2. Population: inclusion and exclusion criteria, characteristics of study participants, number of participants enrolled, randomized, and excluded after randomization and analyzed; number of participants lost to follow‐up in the groups; baseline information of the participants in order to have comparable intervention groups at entry (age, sexually activity, contraceptive habits, history of STIs, sexual behavioral history); total number of intervention groups.

  3. Intervention: frequency of text messaging; content of text messaging; period of intervention; duration, type of outcomes collected, methodologies for prevention.

  4. Comparison group: usual care, no intervention or any other mobile phone options; software applications for STI prevention, diagnosis, behavior change, treatment, and retest; primary and secondary outcomes, and how they were defined and measured; differences between groups for outcome assessment.

  5. Other: source of funds, ethical approval.

Using Covidence, we will screen the titles and abstracts. We will keep an electronic record stating the reasons for excluding potentially eligible studies.

We will then use a data extraction form to extract data from selected studies. Two review authors (MN, AR) will extract data from the included studies and any disagreement will be discussed with the third review author (SJ).

Assessment of risk of bias in included studies

Two review authors (MN, AR) will independently assess the risk of bias for each included study using the tool Risk of Bias II for parallel clinical trials and for cross‐over trials (Higgins 2016). Those who will assess risk of bias are methodology and content experts. When we need to obtain missing information, we will contact the study investigators using open‐ended questions. We will assess risk of bias in the included trials and collected information in data extraction forms. We then added the information to Review Manager 5 (Review Manager 2014) (RevMan)

Two review authors (AMP‐L and AMT‐C) will independently assess the included studies for risk of bias using the Cochrane 'Risk of bias' assessment tool (Higgins 2016) to assess:

  1. Bias arising from the randomization process

  2. Bias due to deviations from intended interventions

  3. Bias due to missing outcome data

  4. Bias in measurement of the outcome

  5. Bias in selection of the reported result

  6. other bias.

Judgments will be assigned as recommended in section 8.5 of the Cochrane Handbook (Higgins 2016). Disagreements will be resolved by discussion. We will describe all judgments fully and present the conclusions in the 'Risk of bias' table, which will be incorporated into the interpretation of review findings by means of sensitivity analyses (see below).

Overall risk of bias

We will also apply the criteria defined by Tramacere 2015 (Tramacere 2015) for assessing the risk of bias. To summarize the quality of the evidence we will consider the domains of: Bias arising from the allocation concealment process, blinding of outcome assessors or bias due to incomplete outcome data in order to classify each study as having either: low risk of bias (where we judge all of the three domains as being at low risk of bias); high risk of bias (where we judge at least one of the three domains as being at high risk of bias); unclear risk of bias (where we judge all of the three domains as being at unclear risk of bias); and moderate risk of bias in the remaining cases.

Measures of treatment effect

For dichotomous data, we will present the results as risk ratios (RRs) with 95% confidence intervals (CIs). For continuous data, we will use the mean difference (MD) if outcomes were measured in the same way between trials. We will use the standardized mean difference to combine trials that measured the same outcome but used different units of measurement.

Risk ratios and MDs will be derived from Mantel‐Haenszel and inverse variance methods respectively. We are planning to use a fixed‐effect model, where possible, to pool the results. We will switch to the random‐effects model if the heterogeneity is high and cannot be explained by sensitivity analysis or subgroup analysis.

Unit of analysis issues

We will include parallel randomized trials as well cluster‐randomized and cross‐over trials. The unit of analysis will be individual participants. In addition, we expect that eligible studies will collect and analyze a single measurement for each outcome from each participant

For cluster‐randomized trials, we will estimate the intraclass correlation coefficient (ICC) derived from a similar trial or from a study with similar population. The effect of variation in the ICC will be tested using sensitivity analysis.

Where trials with multiple arms are analyzed, we will determine which arm is the intervention group and relevant for analysis. To avoid confusion for the reader, we will include all the intervention groups of the study in the 'Characteristics of included studies’ table (in the notes cell), and provide a detailed description only of the intervention groups relevant to this review. Only these groups will be used in analyses. Finally, in order to overcome a unit of analysis error for a study that could contribute multiple, correlated comparisons, we will combine all relevant experimental intervention groups of the studies into a single group and combine all relevant control intervention groups into a single control group, in order to create a single pair‐wise comparison (Higgins 2016).

We will consider combining the results from both cluster‐RCTs and individual RCTs in one analysis, given there would be little heterogeneity between the study designs, and there would be no interaction between the effect of the intervention and the choice of randomization.

When analyzing a cross‐over trial, we will consider all participants as recipients of all interventions in sequence. Therefore, individuals are considered randomized to an ordering of interventions, acting as their own control. If is considered that there is any carry‐over only data of the first period will be included. Incorprating cross over trials data into the meta‐ analysis will be done following the Cocharne Hhandbook (Higgins 2016 section 16.4.5)

Dealing with missing data

If data are missing, or if the methods are not clear, we will contact the original investigators for clarification. We will report the percentage of observations with missing data in each included trial. As far as possible, we will carry out analyses on an intention‐to‐treat basis for all outcomes (i.e. we will attempt to include all participants randomized to each group in the analyses, and all participants will be analyzed in the group to which they were allocated, regardless of whether or not they received the allocated intervention).

Assessment of heterogeneity

We will make an assessment of whether to conduct a meta‐analysis by assessing for heterogeneity between the included studies. We will conduct a visual inspection of the forest plots and use the Chi2 test and I2 statistic to measure the level of heterogeneity. Heterogeneity levels of less than 40% will be considered low heterogeneity, between 40% to 70% will be investigated by subgroup analysis to discover the sources of variation, and levels of higher than 70% and the subgroup analysis does not explain the heterogeneity sources we will not pool the data

Assessment of reporting biases

We will use funnel plots to assess publication bias where at least 10 studies are available for meta‐analysis. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it. For continuous outcomes we will use the test proposed by Egger 1997, and for dichotomous outcomes we will use the test proposed by Harbord 2006. If we detect asymmetry in any of these tests or by a visual assessment, we will perform exploratory analyses to investigate and report it.

Data synthesis

We will carry out statistical analysis using Review Manager 5.3 software. We will use a fixed‐effect model to estimate the effect size of study outcomes where results are clinically and statistically homogenous, assuming that studies are estimating the same underlying treatment effect (i.e. where trials are examining the same intervention, and the trials’ populations and methods are judged adequately comparable).

If there is clinical and statistical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if we detect substantial statistical heterogeneity, we will use random‐effects meta‐analysis to produce an overall summary. We will treat the random‐effects summary as the average range of possible treatment effects and we will investigate the clinical implications of treatment effects.

Subgroup analysis and investigation of heterogeneity

In order to explore differences between subgroups for outcomes with statistical heterogeneity, and to explore the effects of any assumptions made (such as the value of the ICC used for RCTs), we will conduct subgroup analyses according to:

  1. Gender

  2. STI type

  3. Geographical area (low‐ and middle‐income countries versus high‐income countries)

  4. Number of sexual partners (single or multiple)

  5. Age group (adolescents and adult)

  6. Type of SMS.

We plan to assess subgroup differences by interaction tests available within Review Manager 5 and to report the results of subgroup analyses quoting the Chi² statistic and P value.

Sensitivity analysis

We plan to carry out sensitivity analyses to explore the effect of low and high risk of bias, assessed by both concealment of allocation and high attrition rates, for example 20% of missing data or 10 % difference between arms and no explanation about the difference (Tramacere method), with high risk studies being excluded from the analyses in order to assess whether this makes any difference to the overall result. Where cluster‐randomized studies are included we will also perform a sensitivity analysis based on the unit of randomization.

Overall quality of the body of evidence: 'Summary of findings' table

We will prepare a 'Summary of findings' table using GRADEpro GDT(GRADEpro GDT) and Cochrane methods. This table will evaluate the overall quality of the body of evidence for the primary outcomes — incidence of STI, detection rate of STI, and adverse effects of the intervention (e.g. emotional stress or couple break‐up) — for the the following comparisons

  1. mobile phone text messaging versus usual care

  2. mobile phone text messaging versus No intervention

  3. mobile phone text messaging versus any other mobile phone options; software applications for STI prevention, diagnosis, behavior change, treatment, and retest).

We will assess the quality of the evidence using GRADE criteria: risk of bias, consistency of effect, imprecision, indirectness and publication bias). Judgments about evidence quality (high, moderate, low or very low) will be made by two review authors working independently, with disagreements resolved by discussion. Judgments will be justified, documented, and incorporated into reporting of results for each outcome.We plan to extract study data, format our comparisons in data tables and prepare the 'Summary of findings' table before writing the results and conclusions of our review.

Acknowledgements

Many thanks for the information specialist for search strategies, and to editors and reviewers at Cochrane who have supported this protocol.

Appendices

Appendix 1. Electronic search strategies

MEDLINE and CENTRAL (Ovid platform) 1.exp Cell Phones/ 2.(mobile adj5 phone$).tw. 3.(mobile adj5 telephone$).tw. 4.(cell$ adj5 phone$).tw. 5.(cell$ adj5 telephone$).tw. 6.smartphone$.tw. 7.(smart adj5 phone$).tw. 8.(car adj5 phone$).tw. 9.(portable adj5 phone$).tw. 10.or/1‐9 11.text$.tw. 12.messag$.tw. 13.SMS.tw. 14.mHealth.tw. 15.or/11‐13 16.10 and 14 17.exp Sexually Transmitted Diseases/ 18.exp Sexually Transmitted Diseases, Bacterial/ 19.exp Sexually Transmitted Diseases, Viral/ 20.(sex$ adj5 transmi$ adj5 disease$).tw. 21.(sex$ adj5 transmi$ adj5 infectio$).tw. 22.(sex$ adj5 transmi$ adj5 disorder$).tw. 23.(vener$ adj5 disease$).tw. 24.(vener$ adj5 infectio$).tw. 25.(vener$ adj5 disorder$).tw. 26.(genital adj5 disease$).tw. 27.(genital adj5 infectio$).tw. 28.(genital adj5 disorder$).tw. 29.STI$.tw. 30.STD$.tw. 31.VD.tw. 32.or/16‐31 33.exp Chancroid/ 34.exp Chlamydia infections/ 35.exp Lymphogranuloma venereum/ 36.exp Gonorrhea/ 37.exp Granuloma inguinale/ 38.exp Syphilis/ 39.exp Neurosyphilis/ 40.exp Tabes dorsalis/ 41.exp Syphilis, cardiovascular/ 42.exp Syphilis, cutaneous/ 43.exp Syphilis, latent/ 44.exp Condylomata acuminata/ 45.exp Herpes genitalis/ 46.exp Vaginitis/ 47.exp Trichomonas vaginitis/ 48.exp Trichomonas vaginalis/ 49.exp Vulvovaginitis/ 50.(vagin$ or trichomoniasis).tw. 51.exp Vaginosis, bacterial/ 52.exp Gardnerella vaginalis/ 53.exp Candidiasis/ 54.exp Candidiasis, vulvovaginal/ 55.exp Candidiasis, invasive/ 56.exp Candidemia/ 57.exp Candida albicans/ 58.(candidiasis or (vulvovagina$ adj5 candidosis)).tw. 59.exp Mobiluncus/ 60.mobiluncus.tw. 61.exp Chlamydia/ 62.exp Chlamydia trachomatis/ 63.chlamydia$.tw. 64.exp Neisseria gonorrhoeae/ 65.(gonorrh?ea$ or gonococc$).tw. 66.(lymphogranuloma venereum or lymphogranuloma inguinale).tw. 67.exp Uterine cervicitis/ 68.exp Urethritis/ 69.cervicitis.tw. 70.urethritis.tw. 71.(nongonococcal urethritis or non‐gonococcal urethritis or ngu).tw. 72.exp Mycoplasma genitalium/ 73.(mycoplasma adj5 genital$).tw. 74.exp Ureaplasma urealyticum/ 75.exp Chancre/ 76.chancre$.tw. 77.exp Treponema pallidum/ or 78.treponema pallidum.tw. 79.condylom$.tw. 80.syphili$.tw. 81.exp Haemophilus ducreyi/ 82.h?emophilus ducreyi.tw. 83.(chancroid$ or ulcus molle).tw. 84.exp Calymmatobacterium/ 85.calymmatobacterium.tw. 86.klebsiella granulomatis.tw. 87.(granuloma inguinale or granuloma venereum or donovan$).tw. 88.exp Herpesvirus 1, human/ 89.exp Herpesvirus 2, human/ 90.(hsv1 or hsv‐1 or hsv2 or hsv‐2 or (herpes adj5 genital$)).tw. 91.(human cytomegalovirus or human herpesvirus‐5 or hhv‐5 or hcmv).tw. 92.exp Infectious mononucleosis/ 93.mononucleosis.tw. 94.cmv infection$.tw. 95.exp Alphapapillomavirus/ 96.exp Human papillomavirus 6/ 97.exp Human papillomavirus 11/ 98.exp Human papillomavirus 16/ 99.exp Human papillomavirus 18/ 100.exp Human papillomavirus 31/ 101.exp Betapapillomavirus/ 102.exp Gammapapillomavirus/ 103.(human papillomavirus$ or hpv or recurrent respiratory papillomatosis or condyloma$).tw. 104.((venereal adj5 ulcer$) or (venereal adj5 wart$)).tw. 105.((genital$ adj5 ulcer$) or (anogenital adj5 ulcer$) or (anorectal adj5 ulcer$) or (penile adj5 ulcer$) or (penis adj5 ulcer$)).tw 106.((genital$ adj5 wart$) or (anogenital adj5 wart$) or (anorectal adj5 wart$) or (penile adj5 wart$) or (penis adj5 wart$)).tw. 107.((genital$ adj5 lesion$) or (anogenital$ adj5 lesion$) or (cerv$ adj3 lesion$) or (cerv$ adj3 ulcer$) or (cerv$ adj3 wart$)).tw. 108.Bowen's Disease/ 109.(bowen$ adj5 disease$).tw. 110.bowenoid papulosis.tw. 111.erythroplasia of queyrat.tw. 112.exp Pediculus/ 113.exp Phthirus/ 114.(pubic lice or phthirius pubis or pediculosis pubis).tw. 115.exp Pelvic infection/ 116.exp Pelvic inflammatory disease/ 117.((pelvic adj5 infectio$) or (pelvic adj5 inflamm$) or PID).tw. 118.exp Salpingitis/ 119.exp Prostatitis/ 120.exp Epididymitis/ 121.prostitis.tw. 122.exp Balanitis/ 123.exp Balanitis xerotica obliterans/ 124.balanoposthitis.tw. 125.exp Molluscum contagiosum virus/ 126.molluscum contagiosum.tw. 127.MCV‐2.tw. 128.or/ 32‐127 129.randomized controlled trial.pt. 130.controlled clinical trial.pt. 131.randomized.ab. 132.placebo.ab. 133.clinical trials as topic.sh. 134.randomly.ab. 135.trial.ti. 136.or/129‐135 137.exp animals/ not humans.sh. 138.136 not 137 139.15 and 128 and 138

Note: the CENTRAL search strategy does not include the terms #138 to #139. Embase (embase.com platform)

1.'mobile phone'/exp 2.(mobile NEAR/5 phone*):ab,ti 3.(mobile NEAR/5 telephone*):ab,ti 4.(cell* near/5 phone*):ab,ti 5.(cell* NEAR/5 telephone*):ab,ti 6.smartphone*:ab,ti 7.(smart NEAR/5 phone*):ab,ti 8.(car NEAR/5 phone*):ab,ti 9.(portable NEAR/5 phone*):ab,ti 10.#1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8 OR #9 11.text*:ab,ti 12.messag*:ab,ti 13.SMS:ab,ti 14.mHealth:ab,ti 15.#11 OR #12 OR #13 OR #14 16.'sexually transmitted disease'/exp 17.(sex* NEAR/5 transmi*):ab,ti AND disease*:ab,ti 18.(sex* NEAR/5 transmi*):ab,ti AND infectio*:ab,ti 19.(sex* NEAR/5 transmi*):ab,ti AND disorder*:ab,ti 20.(vener* NEAR/5 disease*):ab,ti 21.(vener* NEAR/5 infectio*):ab,ti 22.(vener* NEAR/5 disorder*):ab,ti 23.(genital NEAR/5 disease*):ab,ti 24.(genital NEAR/5 infectio*):ab,ti 25.(genital NEAR/5 disorder*):ab,ti 26.sti*:ab,ti 27.std*:ab,ti 28.vd:ab,ti 29.'chlamydiasis'/exp 30.'condyloma'/exp 31.'condyloma acuminatum'/exp 32.'condyloma latum'/exp 33.'genital herpes'/exp 34.'gonorrhea'/e 35.'granuloma inguinale'/exp 36.'lymphogranuloma venereum'/exp 37.''syphilis'/exp 38.‘secondary syphilis'/exp 39.'tabes dorsalis'/exp 40.'ulcus molle'/exp 41.'vaginitis'/exp 42.'vulvovaginitis'/exp 43.'trichomoniasis'/exp 44.'trichomonas vaginalis'/exp 45.vagin*:ab,ti 46.trichomoniasis:ab,ti 47.'gardnerella infection'/exp 48.'gardnerella vaginalis'/exp 49.(vaginosis NEAR/5 bacterial):ab,ti 50.'candidiasis'/exp 51.'vagina candidiasis'/exp 52.'genital candidiasis'/exp 53.'invasive candidiasis'/exp 54.'candidemia'/exp 55.'candida albicans'/exp 56.candidiasis:ab,ti 57.(vulvovagina* NEAR/5 candidosis):ab,ti 58.'mobiluncus'/exp OR 'mobiluncus curtisii'/exp OR 'mobiluncus mulieris'/exp OR mobiluncus:ab,ti 59.'chlamydia'/exp 60.'chlamydia trachomatis'/exp 61.chlamydia*:ab,ti 62.'neisseria gonorrhoeae'/exp 63.gonorrh*:ab,ti 64.gonococc*:ab,ti 65.'lymphogranuloma venereum':ab,ti 66.'lymphogranuloma inguinale':ab,ti 67.'uterine cervicitis'/exp 68.'urethritis'/exp 69.'chlamydial urethritis'/exp 70.'gonococcal urethritis'/exp 71.cervicitis:ab,ti 72.urethritis:ab,ti 73.'nongonococcal urethritis'/exp 74.(nongonococcal:ab,ti AND urethritis:ab,ti OR 'non gonococcal':ab,ti AND urethritis:ab,ti) OR ngu:ab,ti 75.'mycoplasma genitalium'/exp 76.(mycoplasma NEAR/5 genital*):ab,ti 77.'ureaplasma urealyticum'/exp 78.'treponema pallidum'/exp 79.treponema:ab,ti 80.pallidum:ab,ti 81.syphili*:ab,ti 82.chancre*:ab,ti 83.condylom*:ab,ti 84.'haemophilus ducreyi'/exp 85.'haemophilus ducreyi':ab,ti 86.chancroid*:ab,ti OR 'ulcus molle':ab,ti 87.'calymmatobacterium'/exp 88.'calymmatobacterium granulomatis'/exp 89.calymmatobacterium:ab,ti 90.'klebsiella granulomatis':ab,ti 91.'granuloma inguinale':ab,ti 92.'granuloma venereum':ab,ti 93.donovan*:ab,ti 94.'herpes simplex virus 1'/exp 95.'herpes simplex virus 2'/exp 96.hsv1:ab,ti 97.'hsv 1':ab,ti 98.hsv2:ab,ti 99.'hsv 2':ab,ti 100.(herpes NEAR/5 genital*):ab,ti 101.human:ab,ti 102.cytomegalovirus:ab,ti 103.human:ab,ti 104.'herpesvirus 5':ab,ti 105.'hhv 5':ab,ti 106.hcmv:ab,ti 107.'infectious mononucleosis'/exp 108.mononucleosis:ab,ti 109.'cmv infection':ab,ti 110.'alphapapillomavirus'/exp 111.'human papillomavirus type 11'/exp 112.'human papillomavirus type 16'/exp 113.'human papillomavirus type 18'/exp 114.'human papillomavirus type 31'/exp 115.'human papillomavirus type 6'/exp 116.'betapapillomavirus'/exp 117.'gammapapillomavirus'/exp 118.'human papillomavirus':ab,ti OR 119.hpv:ab,ti 120.(venereal NEAR/5 ulcer*):ab,ti 121.(venereal NEAR/5 wart*):ab,ti 122.(genital* NEAR/5 ulcer*):ab,ti 123.(anogenital NEAR/5 ulcer*):ab,ti 124.(anorectal NEAR/5 ulcer*):ab,ti 125.(penile NEAR/5 ulcer*):ab,ti 126.(penis NEAR/5 ulcer*):ab,ti 127.(genital* NEAR/5 wart*):ab,ti 128.(anogenital NEAR/5 wart*):ab,ti 129.(anorectal NEAR/5 wart*):ab,ti 130.(penile NEAR/5 wart*):ab,ti 131.(penis NEAR/5 wart*):ab,ti 132.(anogenital* NEAR/5 lesion*):ab,ti 133.(cerv* NEAR/5 lesion*):ab,ti 134.(cerv* NEAR/5 ulcer*):ab,ti 135.(cerv* NEAR/5 wart*):ab,ti 136.(genital* NEAR/5 lesion*):ab,ti 137.'bowen disease'/exp 138.(bowen* NEAR/5 disease*):ab,ti 139.'bowenoid papulosis':ab,ti 140.'erythroplasia of queyrat':ab,ti 141.'pediculus'/exp 142.'phthirus'/exp 143.'pubic lice':ab,ti 144.'phthirius pubis':ab,ti 145.'pediculosis pubis':ab,ti 146.'pelvic inflammatory disease'/exp 147.(pelvic NEAR/5 infectio*):ab,ti 148.(pelvic NEAR/5 inflamm*):ab,ti 149.pid:ab,ti 150.'salpingitis'/exp 151.'prostatitis'/exp 152.'epididymitis'/exp 153.prostitis:ab,ti 154.'balanitis'/exp 155.'balanitis xerotica obliterans'/exp 156.balanoposthitis:ab,ti 157.'molluscipoxvirus'/exp 158.'molluscum contagiosum':ab,ti 159.'mcv‐2':ab,ti 160.#16 OR #17 OR #18 OR #19 OR #20 OR #21 OR #22 OR #23 OR #24 OR #25 OR #26 OR #27 OR #28 OR #29 OR #30 OR #31 OR #32 OR #33 OR #34 OR #35 OR #36 OR #37 OR #38 OR #39 OR #40 OR #41 OR #42 OR #43 OR #44 OR #45 OR #46 OR #47 OR #48 OR #49 OR #50 OR #51 OR #53 OR #54 OR #55 OR #56 OR #57 OR #58 OR #59 OR #60 OR #61 OR #62 OR #63 OR #64 OR #65 OR #66 OR #67 OR #68 OR #69 OR #70 OR #71 OR #72 OR #73 OR #74 OR #75 OR #76 OR #77 OR #78 OR #79 OR #80 OR #81 OR #82 OR #83 OR #84 OR #85 OR #86 OR #87 OR #88 OR #89 OR #90 OR #91 OR #92 OR #93 OR #94 OR #95 OR #96 OR #97 OR #98 OR #99 OR #100 OR #101 OR #102 OR #103 OR #104 OR #105 OR #106 OR #107 OR #108 OR #109 OR #110 OR #111 OR #112 OR #113 OR #114 OR #115 OR #116 OR #117 OR #118 OR #119 OR #120 OR #121 OR #122 OR #123 OR #124 OR #125 OR #126 OR #127 OR #128 OR #129 OR #130 OR #131 OR #132 OR #133 OR #134 OR #135 OR #136 OR #137 OR #138 OR #139 OR #140 OR #141 OR #142 OR #143 OR #144 OR #145 OR #146 OR #147 OR #148 OR #149 OR #150 OR #151 OR #152 OR #153 OR #154 OR #155 OR #156 OR #157 OR #158 OR #159 161."randomized controlled trial"/de 162."controlled clinical study"/de 163.random*:ti,ab 164.randomization/de 165."intermethod comparison"/de 166.placebo:ti,ab 167.(compare OR compared OR comparison):ti 168.((evaluated OR evaluate OR evaluating OR assessed OR assess) AND (compare OR compared OR comparing OR comparison)):ab 169.(open NEAR/1 label):ti,ab 170.((double OR single OR doubly OR singly) NEAR/1 (blind OR blinded OR blindly)):ti,ab 171."double blind procedure"/de 172.(parallel NEXT/1 group*):ti,ab 173.(crossover OR "cross over"):ti,ab 174.((assign* OR match OR matched OR allocation) NEAR/5 (alternate OR group* OR intervention* OR patient* OR subject* OR participant*)):ti,ab 175.(assigned or allocated):ti,ab 176.(controlled NEAR/7 (study OR design OR trial)):ti,ab 177.(volunteer OR volunteers):ti,ab 178.trial:ti 179."human experiment"/de 180.#161 OR #1622 OR #163 OR #164 OR #165 OR #166 OR #167 OR #168 OR #169 OR #170 OR #171 OR #172 OR #173 OR #174 OR #175 OR #176 OR #177 OR #178 OR #179 181.#10 AND # 15 AND #180 AND [embase]/lim

LILACS (iAHx interface) (tw:(phone$)) AND (tw:(text$)) AND db:("LILACS") AND type_of_study:("clinical_trials") RCTs filter: ((PT:"ensayo clinico controlado aleatorio" OR PT:"ensayo clinico controlado" OR PT:"estudio multicéntrico" OR MH:"ensayos clinicos controlados aleatorios como asunto" OR MH:"ensayos clinicos controlados como asunto" OR MH:"estudios multicéntricos como asunto" OR MH:"distribución aleatoria" OR MH:"método doble ciego" OR MH:"metodo simple‐ciego") OR ((ensaio$ OR ensayo$ OR trial$) AND (azar OR acaso OR placebo OR control$ OR aleat$ OR random$ OR enmascarado$ OR simpleciego OR ((simple$ OR single OR duplo$ OR doble$ OR double$) AND (cego OR ciego OR blind OR mask))) AND clinic$)) AND NOT (MH:animales OR MH:conejos OR MH:ratones OR MH:ratas OR MH:primates OR MH:perros OR MH:gatos OR MH:porcinos OR PT:"in vitro") WHO International Clinical Trials Registry Platform ICTRP portal phone* AND text* ClinicalTrials.gov phone* AND text*

Contributions of authors

Mohaddesseh Noura, Azam Rahmani and Shayesteh Jahnfar drafted the protocol. All authors approved the final version of the protocol.

Sources of support

Internal sources

  • Workshop of Dr Shayesteh Jahnafar, Other.

External sources

  • None, Other.

Declarations of interest

None of the authors (MN, AR, SJ, UE) have anything to declare.

New

References

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