Anna Elizabeth Phillips
email: a.phillips05@ic.ac.uk

Gabriella B Gomez

Marie-Claude Boily

Geoffrey P Garnett

Phillips Ae

Gomez Gb

Boily Mc

Garnett Gp

A systematic review and meta-analysis of quantitative

Keywords: Interview, Quantitative, HIV risk behaviour, meta-analysis, systematic, low-and middle-income countries Interview, review, meta-analysis, bias

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Intervention programmes aimed at reducing HIV and STI incidence often rely on self-reported measures of behaviours because of the difficulties in directly measuring the infrequent occurrences of infection.

Such self-reports are subject to recall bias and social desirability bias [START_REF] Catania | Methodological problems in AIDS behaviour research: influences on measurement error and participation bias in studies of sex behaviour[END_REF]. Concerns over the accuracy of these measures have prompted efforts to improve data collection through the modification of interview modes [START_REF] Gribble | Interview mode and measurement of sexual behaviours: methodological issues[END_REF].

Different systematic and methodological reviews of research into sexual behaviour have been published in the last decade [START_REF] Catania | Methodological problems in AIDS behaviour research: influences on measurement error and participation bias in studies of sex behaviour[END_REF][START_REF] Gribble | Interview mode and measurement of sexual behaviours: methodological issues[END_REF][START_REF] Aral | Measuring outcomes of behavioural interventions for STD/HIV prevention[END_REF][START_REF] Weinhardt | Reliability and validity of self-report measures of HIV-related sexual behaviour: progress since 1990 and recommendations for research and practise[END_REF][START_REF] Fenton | Measuring sexual behaviour: methodological challenges in survey research[END_REF]. Most have been sceptical that the dominant mode of data collection -face-toface interviews (FTFI) -is the most effective means of gathering high quality data, and have urged the adoption of alternative methods [START_REF] Cleland | Monitoring sexual behaviour in general populations: a synthesis of lessons of the past decade[END_REF]. There are a number of reasons that may lead to inconsistencies between actual and self-reported behaviour such as poor recall and the desire to conceal socially prohibited behaviour. In general, intentional misreporting of sensitive behaviours is motivated either by a desire to underreport socially proscribed behaviour or a tendency to exaggerate socially desirable behaviour [START_REF] Catania | Methodological problems in AIDS behaviour research: influences on measurement error and participation bias in studies of sex behaviour[END_REF]. Examples are culturally dependent and may depend on intervention efforts.

Several studies suggest that improving the level of privacy and anonymity that an interview method affords can greatly enhance the accuracy of self-reporting, particularly stigmatising or illegal behaviour [START_REF] Catania | Methodological problems in AIDS behaviour research: influences on measurement error and participation bias in studies of sex behaviour[END_REF] [START_REF] Weinhardt | Reliability and validity of self-report measures of HIV-related sexual behaviour: progress since 1990 and recommendations for research and practise[END_REF]. As a result, researchers have developed alternatives to the FTFI such as self-administered questionnaires (SAQ). Whilst SAQs are thought to reduce biases associated with FTFI, variable literacy levels amongst respondents and difficulties in following complicated skip patterns mean that responses on SAQs may be less internally consistent [START_REF] Catania | Methodological problems in AIDS behaviour research: influences on measurement error and participation bias in studies of sex behaviour[END_REF]. Computerisation attempts to deal with these challenges, including computer-assisted personal interviewing (CAPI) which evolved into computer-assisted selfinterviewing (CASI). Computer-based responses were then amalgamated with tape-recorded questioning to create audio-CASI (ACASI).

A growing body of research in the United States indicates that computer-based interviews can dramatically increase reports of sensitive behaviour, such as multiple partners or injecting drug use, compared with interviewer-administered surveys [START_REF] Aquilino | Privacy effects on self-reported drug use: interactions with survey mode and respondents characteristics[END_REF][START_REF] Jarlais | Audio-computer interviewing to measure risk behaviour for HIV among injection drug users: a quasi-randomised trial[END_REF][START_REF] Ghanem | Audio computer assisted self interview and face to face interview modes in assessing response bias among STD clinic patients[END_REF][START_REF] Kissinger | Application of computer assisted interviews to sexual behavior research[END_REF][START_REF] Tourangeau | Survey research and societal change[END_REF][START_REF] Turner | Adolescent sexual behavior, drug use and violence: increased reporting with computer survey technology[END_REF]. However, relatively few studies have been conducted in low-and middle-income countries comparing ACASI with FTFI [START_REF] Van De Wijgert | Is audio computer-assisted self-interviewing a feasible method of surveying in Zimbabwe?[END_REF][START_REF] Simões | A randomised trial of audio computer and in-person interview to assess HIV risk among drug and alcohol users in Rio De Janeiro, Brazil[END_REF][START_REF] Simões | Acceptability of audio computerassisted self-interview (ACASI) among substance abusers seeking treatment in Rio de Janeiro, Brazil[END_REF][START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][START_REF] Nimh Collaborative | The feasibility of audio computerassisted self-interviewing in international settings[END_REF][START_REF] Hewett | Using sexually transmitted infection biomarkers to validate reporting of sexual behavior within a randomized, experimental evaluation of interviewing methods[END_REF][START_REF] Mensch | Consistency in the Reporting of Sensitive Behavior within an Interview Mode Experiment Conducted among Women in São Paulo, Brazil[END_REF][START_REF] Van Griensven | Palmtop-assisted self-interviewing for the collection of sensitive behavioural data: randomised trial with drug use urine testing[END_REF], and the results of these studies do not seem to be consistent across behaviours [START_REF] Rumakom | Obtaining accurate responses to sensitive questions among Thai students: a comparison of two data collection techniques[END_REF][START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][START_REF] Potdar | Does Audio-CASI improve reports of risky behavior? Evidence from a randomized field trial among young urban men in India[END_REF][26][START_REF] Minnis | Audio computer-assisted self-interviewing in reproductive health research: reliability assessment among women in Harare, Zimbabwe[END_REF][START_REF] Jaya | Differences in young people's reports of sexual behaviors according to interview methodology: a randomised trial in India[END_REF][START_REF] Guest | Fear, hope and social desirability bias among women at high risk for HIV in West Africa[END_REF][START_REF] Mensch | Sexual Behavior and STI/HIV Status among Adolescents in Rural Malawi: An Evaluation of the Effect of Interview Mode on reporting[END_REF][START_REF] Van Der Elst | Is Audio Computer-Assisted Self-Interview (ACASI) useful in risk behaviour assessment of female and male sex workers in Mombasa, Kenya?[END_REF]. More recently, handheld personal digital assistants (PDAs) have emerged as a tool for collecting risk behaviour data, due to the advantages of portability [START_REF] Bernabe-Ortiz | Handheld computers for self-administered sensitive data collection: A comparative study in Peru[END_REF][START_REF] Jaspan | Methods for collecting sexual behaviour information from South African adolescents -a comparison of paper versus personal digital assistant questionnaires[END_REF]. Such computerised methods may still pose some challenges for participants with low literacy and less experience with technology.

Non-computerised interview tools have also been developed for enhancing privacy among low literacy populations, these include tape-recorded interviews which were trialled in China [START_REF] Xia | A questionnaire-based survey on attitude and behaviour of sex among rural women in Hainan province. Zhonghua Liu Xing Bing Xue Za Zhi[END_REF], informal confidential voting interviews (ICVI) developed in Zimbabwe [START_REF] Gregson | Methods to reduce social desirability bias in sex surveys in low-development settings: experience in Zimbabwe[END_REF][START_REF] Gregson | Informal confidential voting interview methods and temporal changes in reported sexual risk behaviour for HIV transmission in sub-Saharan Africa[END_REF], polling booth surveys (PBS) in India [START_REF] Blanchard | Variability in the sexual structure in a rural Indian setting: implications for HIV prevention strategies[END_REF][START_REF] Hanck | Assessment of Self-Reported Sexual Behavior and Condom Use Among Female Sex Workers in India Using a Polling Box Approach: A Preliminary Report[END_REF], and assisted self-completion questionnaires in Tanzania (ASCQ) [START_REF] Plummer | Asking semi-literate adolescents about sexual behaviour: the validity of assisted self-completion questionnaire data in rural Tanzania[END_REF][START_REF] Plummer | A bit more truthful': the validity of adolescent sexual behaviour data in rural northern Tanzania using five methods[END_REF]. Interviewer bias aside, even highly motivated and uninhibited respondents may have trouble being able to recollect past sexual events [START_REF] Catania | Methodological problems in AIDS behaviour research: influences on measurement error and participation bias in studies of sex behaviour[END_REF]. In another strategy the introduction of coital diaries in several low-and middle-income countries has achieved some success in minimising recall bias [START_REF] Ramjee | Recording sexual behaviour: comparison of recall questionnaires with a coital diary[END_REF][START_REF] Allen | Validity of coital diaries in a feasibility study for the Microbicide Development Programme trial among women at high risk of HIV/AIDS in Mwanza, Tanzania[END_REF][START_REF] Pickering | Sexual behaviour in a fishing community on Lake Victoria, Uganda[END_REF][START_REF] Pickering | Prostitutes and their clients: a Gambian survey[END_REF][START_REF] Ferguson | Using diaries to measure parameters of transactional sex: an example from the Trans-Africa highway in Kenya[END_REF].

There are a number of published papers on alternative methods to collect sensitive information.

Although these studies provide insight, few quantitatively compare new tools with the traditional FTFI within one population. This paper aims to review the empirical data collected in low-and middleincome countries (since over 90% of HIV infections take place in these populations [START_REF] Fenton | Measuring sexual behaviour: methodological challenges in survey research[END_REF]) that compare FTFI with innovative interview tools for reporting HIV-risk behaviour, including sexual behaviour and injecting drug use (IDU). The purpose of this review is to determine if new non FTFI techniques reduce misreporting by reducing interviewer bias or otherwise.

Methods

Search strategy

A systematic review of existing literature on alternative interview tools was conducted in three stages.

Firstly electronic searches of PubMed, LILACS, Web of Knowledge and Embase were carried out from June 2008 to November 2008 (details of search terms are provided in the Appendix). The Pubmed search was updated in April 2009. Titles were evaluated and irrelevant articles discarded. Potentially relevant publications' abstracts were evaluated and the manuscripts were retrieved as PDFs or paper copies for evaluation. These searches were complemented with searches in general engines (for example, Google scholar). Finally the bibliographies of relevant papers identified for inclusion were also searched to identify additional relevant publications. Six authors were contacted, all of whom replied, to provide additional information that was not available from the published article [16][22][26] [31][35][39].

Two independent investigators (AEP and GBG) screened all the records to determine relevant records. A short list was then prepared by both and checked for compatibility.

Inclusion criteria

Types of study: We included any study (randomised control trial or observational studies) investigating the reporting of HIV risk behaviour, including sexual information or IDU, which compared interviewing tools with the paper-based FTFI.

Types of population:

We accepted all studies that took place in low-and middle-income countries (according to World Bank classification), in order to examine the feasibility of alternative interview methods in resource-poor settings. There was no restriction on date or language of publication. Only one paper was returned in Chinese and this was translated into English for the analysis.

Types of intervention:

There was no restriction by study design. The influence of study design was explored in the analysis. To simplify the comparison between methods, recall bias will not be explored in this review. Types of outcome: Four potentially sensitive outcomes available in all papers were identified and included for review: 1) 'Have you ever had sex': since many studies focused on adolescents, it was assumed that social desirability bias may be particularly great among school pupils concerned about peer stigma and adult punishment for pre-marital sex. For example, in Tanzania school pupils are severely punished if they are found to have had sex [START_REF] Wight | Divergent sexual norms for young people in rural Northern Tanzania[END_REF]. Therefore, according to our hypothesis a higher proportion should report ever having sex in the alternative interview method.

2) Non-condom use included a range of questions such as lifetime, last 6 months, last 2 weeks, and last sex act. Although there was no uniform question asked across all papers, it was assumed that it is socially undesirable to report non-condom use regardless of time frame, therefore respondents would be more likely to admit unprotected sex if the interviewer bias had been removed. In religious communities or where condom use is associated with risky behaviour, condom promotion might be frowned upon and it would be 'desirable' to deny condom use. Such as circumstance was not addressed in any of the papers in the review so we assume condom use is socially desirable.

3) 'Ever been forced to have sex': since this outcome was expected to have strong negative connotations, it was expected that in a more private interview setting an increased number of respondents would report forced sex in the alternative interview tool. 4) Number of partners: time over which partner numbers are elicited and the cut-off points between the categories for the number of partners categorical variable varied across studies. It was assumed that it would be socially undesirable to report a higher number of partners, independently of the categorisation used. In order to assess the impact of these variations, timeframe and partner cut-off points were included in the subgroup analyses.

Analysis

We hypothesised that innovative methods that bypass the interviewer will be more successful than FTFI in achieving self-reports of risky behaviour as the impact of interviewer bias has been removed. For this reason a comparison was made between alternative interviewing tools (mostly ACASI) and FTFI.

Sample size was defined as the number of people that took part in the questionnaire because the denominator for each of the four outcomes varied within and between papers. Crude odds ratios and the 95% confidence intervals (CIs) were calculated for each study and outcome using FTFI as the comparative group. We assume that if one interview method was really superior the direction of the association of most included studies would be in the same direction, thus relatively homogeneous even though the magnitude of the effect could vary by study characteristics (e.g. gender, region). The Cochran Q test and I-squared were used to assess heterogeneity across studies [START_REF] Kirkwood | Medical statistics[END_REF]. If there was significant heterogeneity and the studies were not considered combinable, no overall pooled estimate was provided, and sub-group analyses based on study or population characteristics such as gender, education, locale (urban/rural), region (Africa/South America/Europe/Asia) and study design (randomised control trials (RCTs)/cross-sectional) was undertaken to explore potential causes of heterogeneity.

Surveys that interviewed both male and female respondents were considered independent and treated as two separate studies in the meta-analysis, in order to examine the impact of gender. For instance it was anticipated that girls, for whom secrecy about sexual activity is the norm, would be particularly susceptible to report more premarital sex in a more private interview setting [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF]. However, boys may exaggerate their level of sexual activity in the FTFI. Regarding education level of the participants in the studies, we created an aggregate study-level variable: over or under 60% of the sample having received secondary school education. As a range of education levels had been reported across studies, a cut-off had to be determined that maximised the number of studies in two comparable groups for analysis. Summary estimates in the subgroup analyses were calculated using random effects models [START_REF] Egger | Systematic reviews in health care. Meta-analysis in context[END_REF], which take into account the within and between-study variance across studies. Forest plots were used to explore graphically the heterogeneity found between the studies and between the pooled estimates by subgroups [50].

The systematic review was undertaken following MOOSE guidelines for reviews of observational studies since all studies were not randomised trials [START_REF] Stroup | Meta-analysis of observational studies in epidemiology. A proposal for reporting[END_REF].

Results

Nearly 1700 articles were identified. Of these, 105 were selected to be reviewed in full. Twenty-one references satisfied the primary selection criteria, examining interviewing techniques in resource-poor settings. Eight additional papers were identified from the references. Of these 29 references, five were excluded because they did not contain quantitative results and four studies compared interviewing tools with SAQ only (the search results are summarised in Table S1). Of the remaining 20 references, five reported results from the same dataset and were combined together. As a result there were a final total of 15 studies, with a total of 20 references as some articles described the same study. The final 15 studies were divided by gender, interview mode and district to create 25 independent datasets to be included in the meta-analysis, the characteristics of which are described in Table 1. The flow chart summarising the results of the search on self-reported HIV and STI associated behaviour in low-and middle-income countries, by interview mode, is shown in Figure S1 (see Appendix).

Figures 1 to 4 show OR and 95% CI for reporting HIV risk behaviour by interview mode. An OR>1 meant respondents were more likely to report a risk behaviour using an alternative interview mode than by FTFI. The funnel plots in S2-S5 are reasonably symmetrical therefore we can be reasonably confident in assuming there is no publication bias for these outcomes.

Description of the characteristics of the studies included: Out of the total of 15 studies; six studies were carried out in Asia and Africa, two in South America and one in Europe. Among these, eight interviewed adolescents; three the general population; and two among IDU and sex workers. Most of the studies compared FTFI with ACASI (11 studies) and there was one study comparing with PASI, taperecorded interviews, ICVI, PBS, and ASCQ.

Since potential biases are likely to occur for non-randomised studies compared with randomised trials, the heterogeneity of the included studies by study design was investigated (see Figures S6-S9 in Appendix). Since the meta-analysis demonstrated no difference by study design, the results from the different study types were grouped together in the analysis. Study population, study design, gender, interviewing tool, age, study outcomes and total sample size are summarised in Table 1.

'Ever had sex': There were a total of 17 studies reporting 'ever had sex'. As shown in Figure 1, there is significant heterogeneity between studies (I 2 =93.4%, p<0.001) preventing a summary estimate to be interpreted. However, in the subgroup analysis presented in Figure 2A, studies with a higher proportion of participants having finished secondary education had a significantly higher pooled estimate of reporting sex in non-FTFI methods. There were trends observed between region, locale and study design, with studies from Asia, those sampled in urban areas and through cross-sectional studies presenting significantly higher pooled OR. However, despite the fact that the CIs overlap for these subgroups and the difference in reporting was therefore not statistically significant, there is indication that the new tool elicited a greater risk-behaviour reporting in non-FTFI for the outcome 'ever had sex'. As a result of the distinctions emerging in Figure 2A, 'ever had sex' by study design, region, education, and locale were explored to examine heterogeneity between studies, as shown in Figures S6 andS10-S12 respectively. Reporting ever had sex was higher in all studies carried out in Asia and urban areas, with the exception of boys recruited in slums of India which is likely to be confounded by lack of education [START_REF] Potdar | Does Audio-CASI improve reports of risky behavior? Evidence from a randomized field trial among young urban men in India[END_REF].

'Non-condom use': There were 21 studies that reported on 'non-condom use'. As shown in the bottom part of Figure 1, there is also significant heterogeneity present across all studies for non-condom use (I 2 =89.3%, p<0.001) preventing us to quote a summary statistic. Subgroup analysis to explore the source of variation is included in Figure 2B. In contrast to 'ever had sex', there were fewer clear distinctions emerging. There was a trend to an increased reporting of non-condom use among non-FTFI participants in all regions except Africa. This effect was particularly pronounced regarding South America. We also observed a trend in urban areas towards a higher effect estimate, which supported the findings of 'ever had sex'. However, the CIs are large and overlap for these subgroups. 'Last sex act' seemed to show a greater increase in reporting of non-condom use with respect to questions asked with a longer time frame. In contrast to 'ever had sex', those sampled through RCTs presented with higher pooled OR and as a result this outcome was explore to examine heterogeneity between studies, as shown in Figure S7.

'Ever forced to have sex': There were a total of 10 studies reporting 'ever been forced to have sex'.

There was consistent increased reporting of coerced sex among non-FTFI participants in all studies with no significant heterogeneity between them (Figure 3: I 2 =0% p=0.55). Contrary to expectation, Figure 4A shows a trend towards less educated respondents as well as rural, African studies presenting a slightly higher pooled estimate of reporting forced sex in non-FTFI method, although the CIs overlap for these subgroups.

'Number of sexual partners':

There were a total of 12 studies reporting 'number of partners'. Nearly all studies demonstrated increased reporting of a higher number of sexual partners among non-FTFI participants (Figure 3), with significant heterogeneity observed between them (p<0.01). Figure 4B shows a higher reporting in non-FTFI among more educated respondents but contrary to the trends observed for 'ever had sex' and non-condom use, studies from rural areas presented the highest pooled OR in non-FTFI. We also observed a similar trend regarding studies in the African region and RCTs, but

F o r R e v i e w O n l y
10 in these subgroup analyses CIs overlap. Figure 4B also shows studies with a shorter reporting timeframe (last month) report higher numbers of partners in the non-FTFI. Furthermore, as the number of partner threshold increases (i.e. more stigmatised behaviour) the difference between the FTFI and alternative tool also tends to increase. As a result of the distinctions emerging in Figure 4B, the number of partners by region and timeframe were explored to examine heterogeneity between studies, as shown in Figure S13 and S14 respectively.

A comparison was also made between innovative interview tools and paper-based SAQ. Although the results have not been analysed in detail, the summary Table S1 outlines the similar estimates and lack of difference between SAQ and alternative interview methods for the outcome 'ever had sex' (OR: 1.07; 95% C.I 0.91, 1.25) and non-condom use (OR: 0.87; 95% C.I 0.67, 1.12). Although forced sex also demonstrated increased reporting in the non-FTFI/SAQ method, the difference was not as significant.

Discussion

This review evaluates the impact of innovative modes of data collection in low-and middle-income countries by collating studies that compare two or more interview tools on one population in reporting HIV-risk behaviour. The purpose of this meta-analysis was to identify patterns and sources of disagreement among the results. With no gold standard in sexual behaviour research it is difficult to determine whether modification of interview mode (e.g. self-administered vs. interviewer-administered) increases the accuracy of reporting sensitive behaviour. However, the results showed that alternatives to FTFIs do not always yield higher estimates of risky behaviour.

Our hypothesis was based upon previous research indicating that a method providing greater anonymity and privacy than conventional interviewer-administered methods was more likely to yield higher affirmative response rates to sensitive questions [START_REF] Gregson | Methods to reduce social desirability bias in sex surveys in low-development settings: experience in Zimbabwe[END_REF]. This theory was based upon the assumption that a respondents' perception of social norms, and their own notions of acceptable behaviour, influence their willingness to respond truthfully to interview questions. It was further believed that differences in reporting would be greater among females and those with higher education. This hypothesis was not confirmed for the reporting of 'ever had sex', where there was no significant difference between FTFI and non-interviewer administered tools, and little difference between gender.

However, more educated respondents did have a higher pooled estimate for reporting sex in the non-

F o r R e v i e w O n l y
11 FTFI methods. Moreover a trend was observed in Asian, urban and cross-sectional studies suggesting an increase for reporting 'ever had sex' in the non-FTFI method, although the summary effect did not reach statistical significance. Overall, the results imply that FTFI may not be inferior to innovative interview tools in eliciting this behaviour. One possibility is that having started sexual intercourse was not perceived as particularly stigmatised. A second reason is that respondents had become more comfortable in the presence of an interviewer, or in the case of computerised methods inhibited by the technology.

There was no significant difference by interview tool in the reporting of non-condom use. However, higher levels of non-condom use were reported in non-FTFI studies in South America, and a similar trend was observed for studies in Asia, urban areas, those sampled through RCTs, and, unexpectedly, among respondents with less than 60% education. As mentioned previously, the variability of the results may be attributed to the impact of stigma in (religious) communities where condom use is associated with risky behaviour and therefore it would be 'desirable' to deny condom use. The timeframe of the question seems to have been important, with questions using a shorter recall period such as "condom use at last sex" resulting in increased reporting of non-condom use.

There was a significant increase in the reporting of forced sex in the non-interviewer administered tools.

Rural and African studies as well as those less educated reported more forced sex by non-FTFI, although the effect was not significant. Subgroup analysis for number of partners also showed that studies in Africa and rural areas were higher in non-FTFI. However, participants with a secondary education and asking the question within a recent timeframe showed an increase in the reporting of higher number of sexual partners in the non-interviewer administered tools.

There are limitations to the results of the meta-analysis. Firstly, not all of the studies identified asked about every behaviour, for example those sampling adult sex workers did not asked if the respondents had ever had sex. Secondly, question phrasing did vary across studies for example the time frame for non-condom use and the number of sexual partners. A third reason points to bias that could not be attenuated even with increased privacy and anonymity. For example Hewett et al suggested STI positive participants were more likely than STI negative participants to misreport their behaviour in the FTFI [START_REF] Hewett | Using sexually transmitted infection biomarkers to validate reporting of sexual behavior within a randomized, experimental evaluation of interviewing methods[END_REF]. Finally the response rate was not available for all studies so it was difficult to know if it was a factor influencing the performance of the different methods [START_REF] Gregson | Informal confidential voting interview methods and temporal changes in reported sexual risk behaviour for HIV transmission in sub-Saharan Africa[END_REF].

F o r R e v i e w O n l y 12
Any interpretation of these results is based on two sets of assumptions. Firstly, as outlined above, no self-report tool can be proven to be more accurate than another given no gold standard exists with which to compare alternative methods. Secondly, many assumptions are made about people's social desires when answering questions which may not always go in the direction expected.

In further developing methods for collecting HIV and STI risk behaviour data, multiple methods assessing self-reported behavioural risks should be complemented with the appropriate biological markers of sexual activity, as appropriate depending on the type of study. Although these tests may provide evidence of the validity of self-reported behaviours, their application is limited because the exposure period captured by a biomarker may not be the relevant exposure period for the study.

Moreover, infection probabilities are moderated by other factors irrelevant to the particular risk behaviour, including prevalence in the general population, partner status, biological susceptibility of the respondents, and availability of STI testing and treatment [START_REF] Hewett | Using sexually transmitted infection biomarkers to validate reporting of sexual behavior within a randomized, experimental evaluation of interviewing methods[END_REF]. Only a few studies have attempted to validate the reporting of behaviour with STI biological markers within an interview mode experiment in a resource-poor setting [START_REF] Hewett | Using sexually transmitted infection biomarkers to validate reporting of sexual behavior within a randomized, experimental evaluation of interviewing methods[END_REF][20] [START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF].

In conclusion, the findings of the review have important implications for research design and data interpretation. The results of this review show that the relationship and success of novel interviewing methods has proved complex in a low-and middle-income country context. The results suggest that strongly stigmatised behaviour such as forced sex was significantly more likely to be reported in a non-FTFI setting, whereas other outcomes such as 'ever had sex' and non-condom use did not vary by Outcome: n: the number of respondents who answered positively to the question in each interview tool and N-n: the number of respondents who answered negatively to the question in each interview tool, **n and N-n may not always add up to the total sample population as some respondents may not have answered the outcome question, OR were then derived by [Odds of reporting behaviour in non-FTFI]/[Odds of reporting behaviour in FTFI]; ‡ the results in these papers were given as percentages, these were then re-calculated using the total sample size to calculate absolute numbers; § The mean number of partners were given by interview type in this study, as a result they were not included in the meta-analysis. Note: Some outcomes are blank as not every question was asked in each paper. Non-condom use: ***These papers did not report a time-frame of condom use but whether the respondent reported "inconsistent" condom use. We assume therefore that it is not desirable to deny condom use. Number of partners: The threshold of partner number varied across the studies, the odds ratio was calculated as above using the absolute number of respondents that had reported above the threshold in the non-FTFI method/the number of respondents that had reported over the threshold in the FTFI. * Plummer et al reported number of partners for several thresholds, those reporting over 2 and 4 partners have been included in the meta analysis for ASCQ data in 1998 only. ΣN = number of subjects that participated in the study by interview tool. Please note that the number of respondents answering each question may vary for example those that had never had sex would not answer a question on non-condom use. The total number of respondents answering each question can be calculated by adding together the number answering by alternative interview type plus FTFI 1 summarises the 17 studies that report 'ever had sex', where the summary effect was more favourable for the FTFI than the alternative interview mode (I 2 =93.4% p<0.001). Figure 1 also summarised the 21 studies that reported on 'non-condom use', some of which were included in the 'ever had sex' analysis. Respondents were more likely to report non-condom use in the FTFI, although the difference was not statistically significant (I 2 =89.3% p<0.001).

Figure 2A:

Since there is significant heterogeneity across all studies for ever had sex (I 2 =93.4% p<0.001), the source of variation was explored by grouping the studies according to study level characteristics. Figure 2A shows more educated respondents had a significantly higher pooled estimate of reporting sex in non-FTFI methods as well as studies from Asia and those sampled in urban areas presenting higher pooled OR.

Figure 2B:

Since there is significant heterogeneity across all studies for non-condom use (I 2 =89.3% p<0.001), pooled estimates were calculated. Figure 2B no statistically significant differences by study characteristics for reporting non-condom use by interview mode. (not identical) reporting 'number of partners'. There was statistically significant and consistent increased reporting of coerced sex (I 2 =0% p=0.55) and higher number of partners (I 2 =75.3% p<0.001) among non-FTFI participants.

Figure 4A:

Although there is homogeneity across all studies for forced sex (I 2 =0% p=0.972), pooled estimates were calculated to examine trends in reported forced sex by study characteristics. Figure 4A shows those sampled in African, rural areas and studies where less than 60% of the sample had secondary education presented higher pooled OR. The difference between subgroups, however, was not significant.

Figure 4B:

Since there is significant heterogeneity across all studies for number of partners (I 2 =78.8% p<0.001), pooled estimates were calculated. Figure 4B shows those sampled in rural areas presented higher pooled OR. There was also a significant difference in the time frame of the question, with a higher number of partners reported in the last month compared with the last six months or over a lifetime.

F

Region

Asia [START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][20] [START_REF] Potdar | Does Audio-CASI improve reports of risky behavior? Evidence from a randomized field trial among young urban men in India[END_REF][28] [START_REF] Xia | A questionnaire-based survey on attitude and behaviour of sex among rural women in Hainan province. Zhonghua Liu Xing Bing Xue Za Zhi[END_REF] Africa [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][30] [START_REF] Plummer | Asking semi-literate adolescents about sexual behaviour: the validity of assisted self-completion questionnaire data in rural Tanzania[END_REF][START_REF] Plummer | A bit more truthful': the validity of adolescent sexual behaviour data in rural northern Tanzania using five methods[END_REF] South America [START_REF] Simões | A randomised trial of audio computer and in-person interview to assess HIV risk among drug and alcohol users in Rio De Janeiro, Brazil[END_REF][START_REF] Simões | Acceptability of audio computerassisted self-interview (ACASI) among substance abusers seeking treatment in Rio de Janeiro, Brazil[END_REF] Education 60% less than secondary [14-15][22-25][28][30] [START_REF] Xia | A questionnaire-based survey on attitude and behaviour of sex among rural women in Hainan province. Zhonghua Liu Xing Bing Xue Za Zhi[END_REF] 60% more than secondary [START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][20] [25][39-40] Locale Urban [START_REF] Simões | Acceptability of audio computerassisted self-interview (ACASI) among substance abusers seeking treatment in Rio de Janeiro, Brazil[END_REF][START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][20][25] [START_REF] Jaya | Differences in young people's reports of sexual behaviors according to interview methodology: a randomised trial in India[END_REF] Rural [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][30] [START_REF] Plummer | Asking semi-literate adolescents about sexual behaviour: the validity of assisted self-completion questionnaire data in rural Tanzania[END_REF][START_REF] Plummer | A bit more truthful': the validity of adolescent sexual behaviour data in rural northern Tanzania using five methods[END_REF] Design RCT [START_REF] Simões | A randomised trial of audio computer and in-person interview to assess HIV risk among drug and alcohol users in Rio De Janeiro, Brazil[END_REF][START_REF] Simões | Acceptability of audio computerassisted self-interview (ACASI) among substance abusers seeking treatment in Rio de Janeiro, Brazil[END_REF][START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF] Asia [START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][25] [START_REF] Jaya | Differences in young people's reports of sexual behaviors according to interview methodology: a randomised trial in India[END_REF] Africa [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][31] [START_REF] Plummer | Asking semi-literate adolescents about sexual behaviour: the validity of assisted self-completion questionnaire data in rural Tanzania[END_REF][START_REF] Plummer | A bit more truthful': the validity of adolescent sexual behaviour data in rural northern Tanzania using five methods[END_REF] 60% less than secondary [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][START_REF] Potdar | Does Audio-CASI improve reports of risky behavior? Evidence from a randomized field trial among young urban men in India[END_REF][28] 60% more than secondary [START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][25] [START_REF] Plummer | Asking semi-literate adolescents about sexual behaviour: the validity of assisted self-completion questionnaire data in rural Tanzania[END_REF][START_REF] Plummer | A bit more truthful': the validity of adolescent sexual behaviour data in rural northern Tanzania using five methods[END_REF] Urban [START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][25][28] [START_REF] Van Der Elst | Is Audio Computer-Assisted Self-Interview (ACASI) useful in risk behaviour assessment of female and male sex workers in Mombasa, Kenya?[END_REF] Rural [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][ [START_REF] Plummer | Asking semi-literate adolescents about sexual behaviour: the validity of assisted self-completion questionnaire data in rural Tanzania[END_REF][START_REF] Plummer | A bit more truthful': the validity of adolescent sexual behaviour data in rural northern Tanzania using five methods[END_REF] Odds Ratio (OR) (log scale)

F o r R e v i

Region

Asia [START_REF] Potdar | Does Audio-CASI improve reports of risky behavior? Evidence from a randomized field trial among young urban men in India[END_REF] Africa [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF] (horizontal axis) against measure of study size (vertical axis). A funnel plot is a scatter plot which reflects how the estimates of the interview tool vary as sample size increases. In the absence of bias therefore, results from small studies are expected to scatter widely at the bottom of the graph, with the spread narrowing among larger studies. Publication bias (the association of publication probability with the statistical significance of the results), the use of the wrong measure of association, etc, may lead to asymmetrical funnel plots. The funnel plots in Figure S2-5 are reasonably symmetrical so we can assume that there is no publication bias for these variables.

Figure S6-9

The forest plots in Figures S6-9 show crude OR and 95% CI for reporting HIV risk behaviour for each study by study design, using FTFI as the comparative group. The Cochran Q test and I-squared were used to assess heterogeneity across studies. Figure S6-9 show significant heterogeneity between studies for all for outcomes preventing a summary estimate to be interpreted. As a result study design has been added to all subgroup analysis in the main text of the paper. nearly all studies carried out in Asia and urban areas, with the exception of boys recruited in slums of India which was likely to be confounded by lack of education.

Figure S13-14

The forest plots in Figures S13 and S14 examine heterogeneity between individual studies for reporting number of partners by region and timeframe. A higher number of partners was more likely to be reported in Africa and if the question was asked over a shorter time frame, although this difference was not significant.

Table S1

A comparison was also made between innovative interview tools and paper-based SAQ. TOTAL included studies in review: N=29

Excluded studies: N=5 (because they did not include quantitative data for the meta-analysis [14][18][30] [START_REF] Allen | Validity of coital diaries in a feasibility study for the Microbicide Development Programme trial among women at high risk of HIV/AIDS in Mwanza, Tanzania[END_REF][START_REF] Pickering | Sexual behaviour in a fishing community on Lake Victoria, Uganda[END_REF]) TOTAL studies included in the meta-analysis: N=15

(5 studies were combined as they reported results from the same sample [18&19] [START_REF] Mensch | The reporting of sensitive behaviour by adolescents: a methodological experiment in Kenya[END_REF][START_REF] Hewett | Consistency in the reporting of sexual behaviour by adolescent girls in Kenya: a comparison of interviewing methods[END_REF][START_REF] Hewett | The feasibility of computer-assisted survey interviewing in Africa -Experience from two rural districts in Kenya[END_REF][ 35-36][39-40])

Excluded studies: N=4 (because they compared only with SAQthese results are summarised in Table S3) TOTAL datasets analysed in the meta-analysis: N=25 5 studies were divided into two separate studies by gender [START_REF] Linh | A pilot of audio computer-assisted selfinterview for youth reproductive health research in Vietnam[END_REF][28] [31][35-36][39-40] 1 study was divided into two separate studies by college students and slum population [START_REF] Potdar | Does Audio-CASI improve reports of risky behavior? Evidence from a randomized field trial among young urban men in India[END_REF] 1 study was divided into four separate studies by gender and district [22-24] 1 study was divided into two separate studies by ACASI and PASI vs. FTFI [START_REF] Van Griensven | Palmtop-assisted self-interviewing for the collection of sensitive behavioural data: randomised trial with drug use urine testing[END_REF]

  and meta-analysis of quantitative interviewing tools to investigate self-reported HIV and STI associated behaviours in low-and middle-income countries

  interview mode. Further research efforts to understand factors affecting the degree of measurement error obtained with different interview methods are required, as different tools may generate very different conclusions about what should constitute essential elements of HIV prevention programmes.

  SG, Higgins JP. How should meta-regression analyses be undertaken and interpreted? Stat Med 2002: 21; 1559-1573 51. Wang YC, Ching-Mei L, Lew-Ting CY, Hsiao CK, Chen DR, Chen WJ. Survey of substance use among high school students in Taipei: web-based questionnaire versus paper-and-pencil questionnaire. J Adolescent Health 2005: 37; 289-295

22 FigureFigure 1 :

 221 FigureLegend [note all figures are on a log scale]

Figure 3 :

 3 Figure 3: Figure 2 summarises the 12 studies reporting 'ever been forced to have sex' and 12 studies

  The literature search to June 2008 was conducted using the following search terms and Boolean operators, for matches under any field: (("HIV risk behaviour" OR "Sexual*" OR "Injecting drug use") AND terms associated with different interviewing tools (Self-administered questionnaire OR SAQ; Assisted selfadministered questionnaire OR ASCQ; Audio computer-assisted self-interview OR ACASI; Computer-assisted personal interview OR CAPI; Handheld OR Pocket PC OR Pocket-PC; Palm-top OR Palmtop; Personal digital assistant OR PDA; Palm assisted self-interview OR PASI; Informal confidential voting interview OR ICVI; Polling (booth OR box) survey OR PBS; Coital diaries)).

Figure S1

 S1 Figure S1Flowchart summarising the results of the search on alternative quantitative interviewing tools to

Figure S2- 5

 5 Figure S2-5 The funnel plot in Figure S2-5 show the interview mode effect from individual studies

Figure S10- 12

 12 Figure S10-12The forest plots in Figures S10, S11 and S12 examine heterogeneity between individual studies for reporting 'ever had sex' by region, education and locale respectively. Reporting ever had sex was higher in

Figure S4 :Figure S6 :

 S4S6 Figure S2 Funnel plot, with pseudo 95% confidence limits, investigating publication bias for 'Ever had sex'

Figure S11 :

 S11 Figure S11: Heterogeneity & homogeneity for 'ever had sex' by education (reference group: FTFI)

Figure S12 :

 S12 Figure S12: Heterogeneity for 'ever had sex' by locale (reference group: FTFI)

Figure S13 :Figure S14 :

 S13S14 Figure S13: Heterogeneity for 'number of sexual partners' by region (reference group: FTFI)

Table 1 : Summary of selected studies comparing alternative quantitative interview tools with FTFI in low-middle income countries

 1

	Study	Design Gender	Tool	ΣN	Age	Ever had	Non	Timeframe of	Forced	Number	No. of	Timeframe
	population						sex	Condom	Non-Condom	Sex	of	partners	number of
	(grey) and						n (N-n)**	n (N-n)**	use question	n (N-n)**	partners	cut-off	partners
	reporting										n (N-n)**
	estimates (white)
	Simoes 14-15 , Urban Brazil, Injecting Drug Users 2003
	Simoes (2005) 14-15	RCT	C	ACASI 367 FTFI 368	18+	260 (35) 338 (30)	279 (88) 260 (108)	Inconsistent***		67 (300) 40 (328)	2+ 2+	6 months
	LeLC 16 , Urban Vietnam, Adolescents
	LeLC (2006) 16	RCT	M	ACASI 378	15-24	69 (309)	50 (22)	Last sex act	1 (375)	3.46 §	[Mean]	Lifetime
			M	FTFI	356		54 (302)	47 (14)		0 (352)	1.46 §
			F	ACASI 393		29 (364)	50 (22)		2 (385)	1.92 §
			F	FTFI	465		24 (441)	47 (14)		0 (461)	1.06 §
	Hewett 18 and Mensch 19 , Urban Brazil, Adolescents
	Hewett 18 (2004)	RCT	F	ACASI 409	15-21		243 (68)	Last sex act		1.6 §	[Mean]	Last 6
				FTFI	409			254 (94)	(vaginal sex)		1.3 §		months
	Van Griensven 20 , Urban Thailand, Adolescents
	Van Griensven	RCT	C	PASI	328	15-21	192 (136)	238 (90)	Last sex act
	(2005) 20			FTFI	317		180 (137)	184 (133)
				ACASI 325		183 (142)	259 (66)
				FTFI	317		180 (137)	184 (133)
	Mensch 22 & Hewett 23-24 , Rural Kenya, Adolescents -data taken from
	Mensch (2003) 22	RCT	M (K)	ACASI 405	15-21	193 (212)	250 (109)	Lifetime	17 (83)	45 (55) ‡	1+	Lifetime
	& Hewett (2004) 23-24		M (K) F (K) F (K)	FTFI ACASI 343 361 FTFI 349		217 (142) 146 (197) 168 (180)	262 (99) 256 (69) 275 (74)		9 (91) 31 (69) 13 (87)	41 (59) ‡ 21 (79) ‡ 35 (65) ‡	1+ 1+ 1+ 1+
			M (N)	ACASI 688		271 (417)	111 (160)
			M (N)	FTFI	821		548 (273)	182 (365)
			F (N)	ACASI 603		138 (465)	79 (48)
			F (N)	FTFI	721		335 (386)	178 (155)

Study population: ¤ Gregson et al Round 1 data has been analysed only. Design of sampling method: RCT: randomised control trial (i.e. respondents were randomly allocated to either innovative interview tool or FTFI), XSect: Cross-sectional survey where respondents answered both interview tools; Male and female results were combined together and it was not possible to analyse separately; Gender: C; Combined male and female studies; M: Male data was reported and analysed independently; F: Female data was reported and analysed independently; Mensch

23

(2003) & Hewett 24-25 (2004) have been divided by gender and location of study -Kisumu and Nyeri districts (K) and (N) respectively; Potdar (2005) 26 has been divided by population type College students (C) and slum swelling adolescents (S);

Pooled estimates for subgroup analysis for 'Ever had sex' (reference group: FTFI)

	Figure 1 Ever Sex Jaya (F) Jaya (M) LeLC (F) Author Figure 2A: Gender			2.73 (0.71, 10.41) 1.35 (0.92, 1.98) 1.46 (0.84, 2.56) OR (95% CI) 2.73 (0.71, 10.41) 1.35 (0.92, 1.98) 1.46 (0.84, 2.56)
	LeLC (M) Male & Female [14-15][20]		1.25 (0.85, 1.84) 1.25 (0.85, 1.84)
	Mensch (FK) Female [16][22-24][28][30][34][39-40]		0.79 (0.59, 1.07)
	Mensch (FN) Male [16][22-25]28][39-40]		0.34 (0.27, 0.43) 0.34 (0.27, 0.43)
	Mensch (MK)			0.60 (0.45, 0.79) 0.60 (0.45, 0.79)
	Mensch (MN)			0.32 (0.26, 0.40) 0.32 (0.26, 0.40)
	Mensch (Mal)			0.58 (0.41, 0.84) 0.58 (0.41, 0.84)
	Plummer (F)			0.98 (0.85, 1.13) 0.98 (0.85, 1.13)
	Plummer (M) Potdar (C) Potdar (S) Simoes	o F o		1.17 (1.05, 1.31) 1.68 (0.78, 3.61) 0.23 (0.15, 0.35) 0.66 (0.39, 1.10) 1.17 (1.05, 1.31) 1.68 (0.78, 3.61) 0.23 (0.15, 0.35) 0.66 (0.39, 1.10)
	Van Grievensen (A) Van Grievensen (P)	r r		0.98 (0.72, 1.34) 1.07 (0.79, 1.47) 0.98 (0.72, 1.34) 1.07 (0.79, 1.47)
	Xia Non Condom use Edwards Gregson (F) Gregson (M) Hanck Hewett LeLC (F) LeLC (M) Mensch (FK)	R e v i e w R e v i e w	0.94 (0.59, 1.48) 1.17 (0.77, 1.78) 0.68 (0.51, 0.91) 0.97 (0.76, 1.25) 1.33 (0.90, 1.97) 1.32 (0.92, 1.89) 4.26 (0.86, 21.07) 0.68 (0.31, 1.48) 1.00 (0.69, 1.44) 0.94 (0.59, 1.48) 1.17 (0.77, 1.78) 0.68 (0.51, 0.91) 0.97 (0.76, 1.25) 1.33 (0.90, 1.97) 1.32 (0.92, 1.89) 0.68 (0.31, 1.48) 1.00 (0.69, 1.44)
	Mensch (FN) Mensch (MK) Mensch (MN) Minnis Plummer (F) Plummer (M) Potdar (C) Potdar (S) Simoes		O n l y O n l y	1.43 (0.94, 2.18) 0.87 (0.63, 1.20) 1.39 (1.03, 1.88) 1.11 (0.81, 1.54) 0.27 (0.20, 0.37) 0.43 (0.28, 0.67) 0.51 (0.35, 0.74) 0.58 (0.42, 0.81) 1.32 (0.95, 1.83) 1.43 (0.94, 2.18) 0.87 (0.63, 1.20) 1.39 (1.03, 1.88) 1.11 (0.81, 1.54) 0.27 (0.20, 0.37) 0.43 (0.28, 0.67) 0.51 (0.35, 0.74) 0.58 (0.42, 0.81) 1.32 (0.95, 1.83)
	Van Grievensen (A)			2.84 (2.00, 4.03) 2.84 (2.00, 4.03)
	Van Grievensen (P)			1.91 (1.37, 2.66) 1.91 (1.37, 2.66)
	VanderElst (M)			1.94 (1.15, 3.26) 1.94 (1.15, 3.26)
	VanderElst (F)			0.58 (0.35, 0.96) 0.58 (0.35, 0.96)
		.1	1	10
		Odds Ratio (OR) (log scale)
		23 24

* : Odds Ratio for 'Ever had sex' and 'Non-condom use' (reference group: FTFI) * Four papers were divided into separate studies by gender (M) =Male and (F)=Female as the data was reported by individual sex. Potdar & Koenig analysed slum-dwelling (S) and college (C) youth individually and so have been divided into two separate studies. Van Grievensen reported individual comparisons between ACASI (A) and PASI (P) with FTFI. Mensch sampled into two regions in Kenya (Kisumu and Nyeri) where samples were further divided by gender, therefore the data has been split into four: Kisumu Female (FK) and male (MK) and Nyeri Female (FN) and male (MN).

.

Pooled estimates for subgroup analysis for 'Non-condom use' (reference group: FTFI)

	Subgroup Figure 2B: Gender Subgroup		OR (95% CI) OR (95% CI) OR (95% CI)
	Male & Female [14-15][20][26]		1.71 (1.17, 2.51) 1.71 (1.17, 2.51)
	Female [18-19][22-24][27][24-25][38-40] Male [16][18][25][34-35][39-40]		0.95 (0.75, 1.20) 0.74 (0.54, 1.01) 0.74 (0.54, 1.01) 0.95 (0.75, 1.20) 0.98 (0.62, 1.55) 0.98 (0.62, 1.55)
			0.82 (0.54, 1.24) 0.82 (0.54, 1.24)
	Region		0.75 (0.43, 1.29) 0.75 (0.43, 1.29)
	Asia [17][21][26][38]		1.19 (0.67, 2.12) 1.19 (0.67, 2.12)
	Africa [23-25][28][35-36][39-40]		0.81 (0.57, 1.15) 0.81 (0.57, 1.15)
	South America [14-15][19-20] F o r Europe [26] Education 60% less than secondary [14-15][18-19][22-25][35-36][38] 60% more than secondary [16][20][25-27][39-40] F o r	1.03 (0.70, 1.52) 0.62 (0.41, 0.94) 0.66 (0.39, 1.10) 0.60 (0.42, 0.85) 1.32 (1.04, 1.68) 1.32 (1.04, 1.68) 1.03 (0.70, 1.52) 0.62 (0.41, 0.94) 0.66 (0.39, 1.10) 0.60 (0.42, 0.85) 1.17 (0.77, 1.78) 1.08 (0.83, 1.41) 0.91 (0.59, 1.40) 1.17 (0.77, 1.78) 1.08 (0.83, 1.41) 0.91 (0.59, 1.40)
	[20][22-25][30][34][39-40] Urban [14-16][18-20][25-27] XSect [28] Locale Rural [22-24][35-36][38-40] Timeframe of question Last sex act [16][18-20][38] Last 2 weeks [35-36] Last 6 months [26] Lifetime [22-25][27][39-40] Design XSect [26][31][38] RCT [14-16][18][20][22-25][27][35-36][39-40] R e v i e w R e v i e w	1.10 (1.00, 1.21) 0.99 (0.66, 1.49) 0.65 (0.44, 0.96) 0.70 (0.51, 0.96) 1.13 (0.95, 1.34) 1.10 (1.00, 1.21) 0.99 (0.66, 1.49) 0.65 (0.44, 0.96) 0.70 (0.51, 0.96) 1.13 (0.95, 1.34) 1.18 (0.82, 1.70) 0.82 (0.58, 1.16) 1.64 (1.13, 2.38) 0.91 (0.60, 1.38) 1.17 (0.77, 1.78) 0.74 (0.51, 1.07) 0.66 (0.29, 1.50) 1.12 (0.88, 1.43) 1.18 (0.82, 1.70) 0.82 (0.58, 1.16) 1.64 (1.13, 2.38) 0.91 (0.60, 1.38) 1.17 (0.77, 1.78) 0.74 (0.51, 1.07) 0.66 (0.29, 1.50) 1.12 (0.88, 1.43)
	.394 .29	1 1 Odds Ratio (OR) (log scale) O n 2.54 l y 1 1 3.45 O n Odds Ratio (OR) (log scale) l y
		25

26 Figure 3: Odds Ratio estimates for 'Forced sex' and 'Number of partners' (reference group: FTFI)

	Figure 4A:
	Author			OR (95% CI)
	Forced sex
	Jaya (F)			2.73 (0.71, 10.41)
	Jaya (M)			1.49 (0.85, 2.61)
	LeLC (F)			5.99 (0.29, 125.05)
	LeLC (M)			2.82 (0.11, 69.36)
	Mensch (FK)			3.01 (1.46, 6.18)
	Mensch (MK)			2.07 (0.88, 4.90)
	Potdar (C) Potdar (S) VanderElst (M) VanderElst (F) Number of partners Gregson (F) Gregson (M) Edwards Mensch (FK) Mensch (MK) Mensch (Mal) Plummer (F) Plummer (M) Potdar (C) Potdar (S) Simoes Minnis	F o r R e v i e w	1.92 (0.96, 3.85) 10.07 (2.33, 43.65) 2.43 (1.13, 5.21) 3.07 (0.81, 11.60) 2.02 (0.93, 4.39) 1.71 (1.06, 2.77) 0.90 (0.48, 1.69) 1.18 (0.67, 2.06) 1.83 (0.92, 3.62) 1.76 (1.10, 2.80) 2.68 (2.10, 3.42) 2.01 (1.01, 4.00) 1.00 (0.73, 1.38) 0.96 (0.55, 1.67) 2.03 (1.08, 3.81) 0.90 (0.62, 1.29)
		1 1 Odds Ratio (OR) (log scale) .1 10	O n
				l y
		27

Pooled estimates for subgroup analysis for 'Ever forced to have sex' (reference group: FTFI)

	Subgroup		OR (95% CI) OR (95% CI)
	Gender
	Female [16][22-24][28][31][39-40]		3.04 (1.73, 5.34) 3.04 (1.73, 5.34)
	Male [16][22-25][28][31][39-40]		2.11 (1.43, 3.11) 2.11 (1.43, 3.11)
	Region
			2.28 (1.34, 3.88) 2.28 (1.34, 3.88)
			2.58 (1.69, 3.94) 2.58 (1.69, 3.94)
	Education
			2.39 (1.67, 3.42) 2.39 (1.67, 3.42)
			2.06 (1.06, 4.00) 2.06 (1.06, 4.00)
	Locale
			2.16 (1.53, 3.05) 2.16 (1.53, 3.05)
			2.58 (1.48, 4.50) 2.58 (1.48, 4.50)
	Design
	Xsect [28][31]		1.94 (1.29, 2.92) 1.94 (1.29, 2.92)
	RCT [16][22-25][39-40]		2.63 (1.69, 4.09) 2.63 (1.69, 4.09)
	.187	1 1	5.34

Pooled estimates for subgroup analysis for 'Number of partners' † (reference group: FTFI

  ) † Note Plummer et al have reported number of partners over +2 and +4 threshold, therefore the sample was divided into two in order to explore the sensitivity of the two cut-off points. It is important to note that the same individuals were not included in both the 2+ and 4+ groups. Given the small sample size in the Plummer analysis, the OR was calculated without the Plummer et al results included and were as follows:

	e w O n l y Figure 4B: Gender: Female 1.63 (1.22-2.18) and Male 1.33 (0.96-1.85); Region: Gender Male & Female [14-15][26] Female [22-24][27][30][35-36][39-40] Male [22-25][35-36][39-40]
	Africa 1.49 (1.13-1.94); Education: 60% more than secondary 1,34 (0.95-1.91); Locale: Rural 1.69 (1.34-2.13); Timeframe
	of question: Last month 1.78 (1.31-2.42).
	28

Table S1

 S1

	Figure S1: Systematic review search results
	Identified citations: N=1696
	Pubmed, n=598
	Web of knowledge, n=343
	Ovid Embase, n=231
	LILACS, n=524
	Excluded studies: N=1592
	(not relevant as they did not include
	interview data or information about HIV-risk
	behaviour)
	Potentially relevant papers retrieved:
	N= 105
	Excluded studies: N=85 summarises the similar estimates and lack of difference between SAQ and alternative interview methods for Based in developed countries, n=52
	Duplicates, n=19 the outcome 'ever had sex' (OR: 1.07; 95% C.I 0.91, 1.25); non-condom use (OR: 0.87; 95% C.I 0.67, 1.12); and forced sex (OR: 1.31; 95% C.I 0.84, 2.06). Not comparing two interview modes, n=14 F references of r Studies included from Studies relevant for review: o N=21
	w e i v e R	included studies: N=8
	O n
	l y

Heterogeneity for "non condom use" by study design (reference group: FTFI)

	F o r R e v i e w Overall (I-squared = 90.5%, p = 0.000) . Gregson (F) RCT Mensch (MN) XSect Mensch (MK) Van Grievensen (P) Minnis Subtotal (I-squared = 95.0%, p = 0.000) Mensch (FN) Hewett Potdar (C) Mensch (FK) Simoes Hanck Gregson (M) Potdar (S) Plummer (M) Plummer (F) Van Grievensen (A) LeLC (M) Edwards Subtotal (I-squared = 85.8%, p = 0.000) Author 1 .196 1 F o r R e v w e i Figure S7: . Figure S8:	1.07 (0.79, 1.47) 2.73 (0.71, 10.41) 0.66 (0.39, 1.10) 0.60 (0.45, 0.79) 1.68 (0.78, 3.61) 0.34 (0.27, 0.43) 1.17 (1.05, 1.31) 0.32 (0.26, 0.40) 0.94 (0.59, 1.48) 0.79 (0.59, 1.07) 0.98 (0.72, 1.34) 0.58 (0.41, 0.84) 0.98 (0.85, 1.13) 1.25 (0.85, 1.84) 1.13 (0.95, 1.34) 1.46 (0.84, 2.56) OR (95% CI) 0.80 (0.61, 1.04) 0.23 (0.15, 0.35) 0.70 (0.51, 0.96) 1.35 (0.92, 1.98) 1.07 (0.79, 1.47) 2.73 (0.71, 10.41) 0.66 (0.39, 1.10) 0.60 (0.45, 0.79) 1.68 (0.78, 3.61) 0.34 (0.27, 0.43) 1.17 (1.05, 1.31) 0.32 (0.26, 0.40) 0.94 (0.59, 1.48) 0.79 (0.59, 1.07) 0.98 (0.72, 1.34) 0.58 (0.41, 0.84) 0.98 (0.85, 1.13) 1.25 (0.85, 1.84) 1.13 (0.95, 1.34) 1.46 (0.84, 2.56) OR (95% CI) 1.00 (0.77, 1.30) 0.68 (0.51, 0.91) 1.39 (1.03, 1.88) 0.87 (0.63, 1.20) 1.91 (1.37, 2.66) 1.11 (0.81, 1.54) 0.66 (0.29, 1.54) 1.43 (0.94, 2.18) 1.38 (1.01, 1.88) 0.51 (0.35, 0.74) 1.00 (0.69, 1.44) 1.32 (0.95, 1.83) 1.43 (1.02, 2.01) 0.97 (0.76, 1.25) 0.58 (0.42, 0.81) 0.43 (0.28, 0.67) 0.27 (0.20, 0.37) 2.84 (2.00, 4.03) 1.48 (0.68, 3.22) 1.17 (0.77, 1.78) 1.12 (0.88, 1.42) OR (95% CI) 1.00 (0.77, 1.30) 0.68 (0.51, 0.91) 1.39 (1.03, 1.88) 0.87 (0.63, 1.20) 1.91 (1.37, 2.66) 1.11 (0.81, 1.54) 0.66 (0.29, 1.54) 1.43 (0.94, 2.18) 1.38 (1.01, 1.88) 0.51 (0.35, 0.74) 1.00 (0.69, 1.44) 1.32 (0.95, 1.83) 1.43 (1.02, 2.01) 0.97 (0.76, 1.25) 0.58 (0.42, 0.81) 0.43 (0.28, 0.67) 0.27 (0.20, 0.37) 2.84 (2.00, 4.03) 1.48 (0.68, 3.22) 1.17 (0.77, 1.78) 1.12 (0.88, 1.42) OR (95% CI) 5.11
	.0961	1 1 'Non condom use' by study design 10.4 O n O n 'Ever had sex' by study design l y l y

Heterogeneity (homogeneity for XSect) for "forced sex" by study design (reference group: FTFI)

	Figure S9:
	Author		OR (95% CI)
	XSect
	Jaya (F)		2.73 (0.71, 10.41) 2.73 (0.71, 10.41)
	Jaya (M)		1.35 (0.92, 1.98) 1.35 (0.92, 1.98)
	Plummer (F)		0.98 (0.85, 1.13) 0.98 (0.85, 1.13)
	Plummer (M)		1.17 (1.05, 1.31) 1.17 (1.05, 1.31)
	Subtotal (I-squared = 55.6%, p = 0.080)	1.13 (0.95, 1.34) 1.13 (0.95, 1.34)
	.
	Mensch (MK) Mensch (FK) RCT	F o	0.60 (0.45, 0.79) 0.79 (0.59, 1.07) 0.60 (0.45, 0.79) 0.79 (0.59, 1.07)
	Potdar (C)	r	1.68 (0.78, 3.61) 1.68 (0.78, 3.61)
	Potdar (S)		0.23 (0.15, 0.35) 0.23 (0.15, 0.35)
	. Overall (I-squared = 90.5%, p = 0.000) Subtotal (I-squared = 89.7%, p = 0.000) .0961 'Forced sex' by study design 1 1 R e v i e w	0.86 (0.63, 1.18) 0.62 (0.34, 1.15) 0.86 (0.63, 1.18) 0.62 (0.34, 1.15) 10.4
		O n
			l y

Heterogeneity for "number of partners" by study design (reference group: FTFI)

	Figure S10:
	Author	OR (95% CI) OR (95% CI)
	RCT
	Gregson (F)	2.02 (0.93, 4.39) 2.02 (0.93, 4.39)
	Gregson (M)	1.71 (1.06, 2.77) 1.71 (1.06, 2.77)
	Mensch (FK)	2.03 (1.08, 3.81) 2.03 (1.08, 3.81)
	Mensch (MK)	1.18 (0.67, 2.06) 1.18 (0.67, 2.06)
	Mensch (Mal)	1.83 (0.92, 3.62) 1.83 (0.92, 3.62)
	Potdar (C)	2.01 (1.01, 4.00) 2.01 (1.01, 4.00)
	. Subtotal (I-squared = 51.3%, p = 0.037) Minnis Simoes Potdar (S) F o r	1.29 (1.03, 1.63) 0.90 (0.62, 1.29) 0.94 (0.70, 1.26) 1.00 (0.73, 1.38) 0.90 (0.62, 1.29) 0.94 (0.70, 1.26) 1.00 (0.73, 1.38) 1.29 (1.03, 1.63)
	. Overall (I-squared = 78.8%, p = 0.000) Edwards XSect Plummer (M) Subtotal (I-squared = 82.2%, p = 0.004) Plummer (F) R e v i e w	1.45 (1.10, 1.92) 0.90 (0.48, 1.69) 2.68 (2.10, 3.42) 1.72 (0.95, 3.09) 1.76 (1.10, 2.80) 1.45 (1.10, 1.92) 0.90 (0.48, 1.69) 2.68 (2.10, 3.42) 1.72 (0.95, 3.09) 1.76 (1.10, 2.80)
	1 1 'Number of partners' by study design .228 4.39 O n
		l y

Heterogeneity for 'ever had sex' by region (reference group: FTFI)

	Author		OR (95% CI)
	Asia
	Jaya (F)		2.73 (0.71, 10.41) 2.73 (0.71, 10.41)
	Jaya (M)		1.35 (0.92, 1.98) 1.35 (0.92, 1.98)
	LeLC (F)		1.46 (0.84, 2.56) 1.46 (0.84, 2.56)
	LeLC (M)		1.25 (0.85, 1.84) 1.25 (0.85, 1.84)
	Potdar (C)		1.68 (0.78, 3.61) 1.68 (0.78, 3.61)
	Potdar (S)		0.23 (0.15, 0.35) 0.23 (0.15, 0.35)
	Van Grievensen (A)		0.98 (0.72, 1.34) 0.98 (0.72, 1.34)
	Van Grievensen (P)		1.07 (0.79, 1.47) 1.07 (0.79, 1.47)
	Xia		0.94 (0.59, 1.48) 0.94 (0.59, 1.48)
	Subtotal (I-squared = 85.2%, p = 0.000)		1.03 (0.70, 1.53) 1.03 (0.70, 1.53)
	.
	Africa
	Mensch (FK)		0.79 (0.59, 1.07) 0.79 (0.59, 1.07)
	Mensch (FN)		0.34 (0.27, 0.43) 0.34 (0.27, 0.43)
	Mensch (MK)		0.60 (0.45, 0.79) 0.60 (0.45, 0.79)
	Mensch (MN)		0.32 (0.26, 0.40) 0.32 (0.26, 0.40)
	Mensch (Mal)		0.58 (0.41, 0.84) 0.58 (0.41, 0.84)
	Plummer (F)		0.98 (0.85, 1.13) 0.98 (0.85, 1.13)
	Plummer (M)		1.17 (1.05, 1.31) 1.17 (1.05, 1.31)
	Subtotal (I-squared = 96.7%, p = 0.000)		0.62 (0.41, 0.94) 0.62 (0.41, 0.94)
	.
	South America
	Simoes		0.66 (0.39, 1.10) 0.66 (0.39, 1.10)
	Subtotal (I-squared = .%, p = .)		0.66 (0.39, 1.10) 0.66 (0.39, 1.10)
	.
	Overall (I-squared = 93.4%, p = 0.000)		0.80 (0.61, 1.04) 0.80 (0.61, 1.04)
	.1	1 1	10
	Odds ratio (OR) (log scale)

Table S1 : Summary odd ratios by outcome for meta-analyses of SAQ versus alternative interview tool (reference group: SAQ)

 S1 Alternative interview methods compared to self-administered questionnaire(SAQ)

	Author		OR (95% CI)
	Africa
	Gregson (F)		2.02 (0.93, 4.39) 2.02 (0.93, 4.39)
	Gregson (M)		1.71 (1.06, 2.77) 1.71 (1.06, 2.77)
	Mensch (FK)		2.03 (1.08, 3.81) 2.03 (1.08, 3.81)
	Mensch (MK)		1.18 (0.67, 2.06) 1.18 (0.67, 2.06)
	Mensch (Mal)		1.83 (0.92, 3.62) 1.83 (0.92, 3.62)
	Plummer (F)		1.76 (1.10, 2.80) 1.76 (1.10, 2.80)
	Plummer (M)		2.68 (2.10, 3.42) 2.68 (2.10, 3.42)
	Minnis		0.90 (0.62, 1.29) 0.90 (0.62, 1.29)
	.
	Europe
	Edwards		0.90 (0.48, 1.69) 0.90 (0.48, 1.69)
	.
	Asia
	Potdar (C)		2.01 (1.01, 4.00) 2.01 (1.01, 4.00)
	Potdar (S)		1.00 (0.73, 1.38) 1.00 (0.73, 1.38)
	. . Overall (I-squared = 78.8%, p = 0.000) Simoes S.America F o	1.45 (1.10, 1.92) 0.94 (0.70, 1.26) 1.45 (1.10, 1.92) 0.94 (0.70, 1.26)
		r
	2.02 (0.93, 4.39) 1.71 (1.06, 2.77) OR (95% CI) 1.76 (1.10, 2.80) 2.02 (0.93, 4.39) 1.71 (1.06, 2.77) 1.76 (1.10, 2.80) v 10 Odds ratio estimates 'Number of partners' 1 .5 1 R e i e w
			0.94 (0.70, 1.26) 0.90 (0.48, 1.69) 2.68 (2.10, 3.42) 2.03 (1.08, 3.81) 0.90 (0.48, 1.69) 2.68 (2.10, 3.42) O n 0.94 (0.70, 1.26) 2.03 (1.08, 3.81) l y
			1.18 (0.67, 2.06) 1.18 (0.67, 2.06)
			1.83 (0.92, 3.62) 1.83 (0.92, 3.62)
			2.01 (1.01, 4.00) 2.01 (1.01, 4.00)
			1.00 (0.73, 1.38) 1.00 (0.73, 1.38)
			0.90 (0.62, 1.29) 0.90 (0.62, 1.29)
			1.45 (1.10, 1.92)
	.5	1 1	10
	Odds ratio estimates 'Number of partners'

Acknowledgements

We would like to thank the following people for their contribution in providing raw data for the analysis: Barbara Mensch, Paul Hewett, Joanna Rankin and Barbara Miller at the Population Council; Simon Gregson and Ide Cremin from Imperial College; Mary Plummer; Erica Edwards, Le Cu Linh; and Eduard Sanders. We would also like to acknowledge Isaac Fung for helping to access the Chinese language paper [35] and also for his help in translating the results into English.

Funding

AE Phillips and GB Gomez were funded by the Medical Research Council, UK.

Competing Interests

All authors declare no conflicts of interest exist.

Contributors

AE Phillips, MC Boily and GB Gomez designed the study; AE Phillips and GB Gomez performed the searches, data extraction and analysis. All authors contributed to the interpretation of results and write up.

Outcome