Summary
Introduction: Surveys are a useful tool in primary care. However, low response rates can introduce selection bias, impairing both external and internal validity. The aim of this study was to assess the average response rate in surveys with Portuguese general practitioners (GPs).
Method: We searched the Medline, Web of Science, Scopus, Embase, PsychInfo, SciELO, IndexRMP, RCAAP, Revista Portuguesa de Medicina Geral e Familiar, Acta Médica Portuguesa and the proceedings of conferences of general practice from incepton to December 2016. We included all postal, e-mail, telephone and personal surveys to primary care physicians without language restrictions. We did not assess risk of bias of included studies, since the main outcome was survey response rate. We performed planned subgroup analyses of the use of monetary incentives, the use of non-monetary incentives, survey delivery modes and prior contact with participants.
Results: A total of 1,094 papers were identified and 37 studies were included in this review. The response rate in surveys done to Portuguese GPs was 56% (95CI 47-64%). There was substantial heterogeneity among included studies (I2=99%), but subgroup analysis did not explain this heterogeneity.
Conclusion: Consistent with other published studies, the average response rate in surveys done with Portuguese GPs was 56%, with substantial variation among studies. Use of monetary incentives, one of the most effective strategies to increase response rates, was not present in any of the included studies.
Keywords: Physicians; Family Practice; Primary Health Care; Surveys and Questionnaires; Portugal
Resumo
Introdução: Questionários são úteis na investigação em cuidados de saúde primários. Contudo, baixas taxas de resposta podem introduzir um viés de seleção, prejudicando a validade externa e interna. O objetivo deste estudo foi identificar a taxa de resposta média a questionários aplicados a médicos de família (MF) portugueses.
Método: Foram pesquisadas as bases de dados Medline, Web of Science, Scopus, Embase, PsychInfo, SciELO, IndexRMP, RCAAP, Revista Portuguesa de Medicina Geral e Familiar, Acta Médica Portuguesa e resumos em conferências de medicina familiar do início até dezembro de 2016. Incluiram-se estudos realizados a médicos de família portugueses independentemente de sua tipologia, do tipo de entrega (correio, e-mail, pessoalmente e por telefone) e do idioma do artigo. Não foi avaliado o risco de viés dos artigos porque o principal resultado considerado foi a taxa de resposta. Foram efetuadas análises de subgrupos sobre a utilização de incentivos monetários, de incentivos não monetários, o modo de entrega e o contato prévio com os participantes.
Resultados: Foram identificados 1.094 artigos e incluídos 37 estudos. O número de participantes em cada estudo variou entre 13 e 2.815 participantes. A taxa de resposta média foi de 56% (IC95% 47-64%). Identificou-se uma heterogeneidade substancial (I2=99%) não explicável pela análise de subgrupos.
Conclusão: A taxa de resposta média a inquéritos realizados a MF portugueses foi de 56%, o que corresponde aos valores identificados em revisões internacionais, apesar da variação significativa entre os estudos englobados nesta revisão. O uso de incentivos monetários, uma das estratégias mais eficazes para aumentar as taxas de resposta, não foi identificado em qualquer dos estudos incluídos.
Palavras-chave: Médicos; Medicina de Família e Comunidade; Atenção Primária à Saúde; Inquéritos e Questionários; Portugal
Introduction
Surveys areuseful in medical research.1-3 They can provide insight on knowledge, attitudes and behaviors related to challenging conditions or complex patients. Furthermore, they can be used to assess needs, which can then guide interventions to improve care.4,5 Surveys are used by a wide range of professionals in primary care research as a standardized tool which is easily applicable.6
Low response rates can introduce important selection bias into survey results due to the extent to which non-responders may differ from the study population.7 Random sampling is done to ensure that the sample shares the same characteristics as the reference population. However, this may be compromised if there is a low number of non-respondents, as often non-respondents and respondents have different characteristics. For example, if respondents are more educated than non-respondents, the survey results may be representative of the most educated elements of the reference population, not the whole reference population. These differences can impair both external and internal validity.8 International studies report an average response rate of 61% (95CI 59-63%)9 for surveys in general practitioners (GPs).
GP survey response rates are influenced by monetary incentives, perceived value of the research, concerns about disrupting routine practice, time, confidentiality, volume of requests, questionnaire length and insufficient background information.10 Furthermore, non-responders in surveys involving GPs seem to be older and less likely to possess a postgraduate medical degree or belong to a practice that is involved with post- or undergraduate training.11
Monetary incentives seem to be the most successful strategy to increase physicians’ response rates to surveys.12,13 Other effective approaches include non-monetary incentives, shorter surveys and pre-contact (defined as contacting participants before delivering the survey in order to explain the aim and clarify any doubts).6,11,12 The survey delivery mode is also important, with postal surveys generally showing higher response rates when compared with telephone, e-mail, fax and online surveys.11,14 Nevertheless, despite increasing evidence regarding strategies to improve participation, GP response rates to postal surveys over the past decades remain relatively unchanged.9
In Portuguese speaking countries, despite growing interest in primary care research, no data is currently available regarding average response rates in general practice surveys. Synthesizing response rates from prior surveys will help researchers adequately plan sample sizes for future projects. Thus, the aim of this study was to assess the average response rate in surveys done with Portuguese GPs, as well as identify its potential influencing factors.
Method
Selection criteria
We included studies that involved primary care physicians (family medicine specialists, non-specialists and residents), using all types of survey delivery modes (e.g., postal, e-mail, online, and telephone), and both validated and non-validated questionnaires, regardless of sponsor and knowledge field (e.g., clinical, public health, economics, management, marketing). Both published (journal article, report, thesis) and unpublished studies were considered. No language restriction was applied. Included studies needed to report the percentage of individuals contacted that completed the survey. Excluded studies included surveys directed mostly to public health specialists, physicians not involved with clinical practice (e.g., researchers or managers) or healthcare professionals other than doctors.
Search methods for the identification of studies
We searched international databases (Medline, Web of Science, Scopus, Embase, PsychInfo and SciELO) and Portuguese repositories (IndexRMP, RCAAP); the last search date was December 2016. The search combined free terms and, when supported, controlled vocabulary (full search strategy available in Supplement I). We hand-searched the table of contents of the Revista Portuguesa de Medicina Geral e Familiar (RPMGF) (Portuguese Journal of General Practice with previous title: Revista Portuguesa de Clínica Geral) and the Acta Médica Portuguesa (AMP), as well as the reference lists of eligible articles. We also searched for grey literature in the conference proceedings of Portuguese family medicine conferences.
Study selection
Two authors (NB, SC) independently scanned titles and abstracts from the references retrieved. When the title or abstract did not provide sufficient data to rule out eligibility, full text was obtained and eligibility was assessed independently by the same two authors. Disagreements were solved through discussion with a third author (BH or LL). Reasons for excluding a study were recorded and added to the PRISMA flowchart (Figure 1).
Data extraction, synthesis and analysis
A standardized extraction form with all variables was developed and an identification tag was attributed to each publication. NB and SC abstracted the data for each study and both records were compared for data entry or coding errors; disagreements were solved through consensus. The following variables were collected: first/contact author, title, year when the first participant was recruited, type of publication and study research question. Our main outcome was survey response rate, defined as the number of physicians who provided valid data per number of physicians contacted. We also tried to identify potential explanatory variables to response rate: monetary and non-monetary incentive use, survey delivery mode (postal, telephone, e-mail, online, other) and existence of pre-contact (i.e., whether researchers contacted participants before the survey). Missing data was retrieved, when possible, through e-mail contact with the main author or the corresponding author of the study. As we were exclusively interested in survey participation rates, risk of bias assessment of individual studies was not assessed.
Categorical variables and participation rates were described as proportions. Categorical variables were described with frequencies and percentages. Assessment of publication bias was performed through visual inspection of funnel plots. Meta-analysis of the participation rates was performed using a random effects model (DerSimonian and Laird inverse variance method). Planned subgroup analyses included use of monetary incentives, use of non-monetary incentives, survey delivery modes and contact with participants prior to the survey. Heterogeneity was assessed visually and using I2.
Results
A total of 1,010 papers were identified through database searching and 84 through a manual search of Portuguese journals, as well as from grey literature sources (Figure 1). Study characteristics are shown in Table 1. The smallest study had a total of 13 participants15 and the largest had 2,81516 (mean number of participants approximately 473 per study). The majority of studies addressed clinical practice issues, such as clinical diagnosis or treatment, and work satisfaction. Half of the included studies were developed in primary healthcare units. We also retrieved studies from Portuguese academic institutions, regulatory institutions related to health and pharmaceutics. Twelve (12) studies involved a national sample of physicians; 13 studies were conducted in the region of Lisbon and nine in the northern region of Portugal.
On average, the response rate in surveys done with Portuguese GPs was 56% (95CI 47-64%). There was substantial heterogeneity among included studies (I2=99%) (Figure 2) and subgroup analyses did not explain this heterogeneity.
Four different delivery modes were used in the included studies: e-mail,17-22 postal,16,23-36 personal contact (i.e., researchers delivered the questionnaire directly to the potential respondent)15,37-50 and telephone-based surveys.51 Subgroup analysis suggests that response rates differed in studies which used different survey delivery modes (interaction test p<0.0001). The highest response rate (96%) was seen in the single study that was based on a telephone survey51 (95CI 92-98%) and, on average, studies in which researchers handed out survey forms personally had higher response rates than those using e-mail or postal surveys. Nevertheless, study heterogeneity among subgroups defined by survey delivery mode remained high (I2=99% for e-mail surveys, I2=98% for personal delivery, and I2=99% for postal surveys). Subgroup analysis also suggests that response rates differ in studies using non-monetary incentives (interaction test p=0.04). Only two studies used this kind of incentive and both with postal reply-paid surveys,32,50 but response rate was lower compared to no use of incentives. In both subgroups, heterogeneity remained high (I2=85% and 99%, respectively). We found no evidence of an interaction between contacting study participants beforehand and response rates (interaction test p=0.27). We were unable to perform one of our main pre-specified subgroup analyses, since we found no studies using monetary incentives.
We also performed two non-pre-specified subgroup analyses to further explore the sources of heterogeneity. Firstly, we divided studies into small and large studies using an arbitrary cutoff of 500 participants, adjusted to our mean number of participants per study. Larger studies had lower response rates compared with smaller studies (interaction test p<0.0001), although there was still substantial heterogeneity in the two subgroups (I2=95.1% for smaller studies, and I2=99.3% for larger studies). We also analyzed the impact of different affiliations on response rate but we found no evidence supporting this influence (interaction test p<0.01). Twenty-one (21) studies were affiliated to healthcare provider,15,17-19,22-26,28,31,34,35,37-39,41,42,44,46,48 fourteen to academic institutions,21,27,29,30,32,33,36,40,43,45,47,49-51 one related to regulatory institution16 and other to the pharmaceutical industry.20 Heterogeneity could not be explained by this subgroup analysis (I2=99% for academic institution affiliation and I2=98% for healthcare provider affiliation).
Discussion
On average, the response rate in surveys done to Portuguese GPs was 56%, but we found substantial heterogeneity (I2=99%). Our search did not retrieve any studies using monetary incentives, which is a strategy known to increase response rates.
The funnel plot is very asymmetric, suggesting that smaller studies were more likely to be published or presented at conferences if they had higher response rates.
Strengths and limitations
The main strength of this study is our attempt to reduce bias by following systematic review guidelines.52 Given that survey response rates may be related to publication status, we have made an effort to identify other surveys through conference proceedings, databases of MSc and PhD theses, and by contacting relevant authors. Yet, it is likely that small studies with low response rates were never published or presented at conferences, which means that the estimated average of 56% for response rates may be optimistic.
The major weakness of the study was the substantial heterogeneity that remains largely unexplained. It is reasonable to question whether a summary measure should be obtained when heterogeneity is high. However, we agree with the view that researchers and clinicians still need a best estimate to inform their decisions53 and that it is licit to pool the primary studies’ estimates together as long as their limitations are acknowledged. In our main meta-analysis, heterogeneity was very high (I2=99%), and within our pre-specified and post-hoc subgroup analyses heterogeneity was also high (I2>75.0%). The main factors described in the literature as having an influence in response rates do not explain the variation we found between studies.11 In hindsight, we could have explored the topic of the survey or its length. Clinicians may be more inclined to reply to a survey if they think the topic is more interesting and if the questionnaire is short.11
Interpretation in the context of the available literature
So far, surveys in Portugal have not used monetary incentives to increase GP participation rates. According to the international literature,11,12 monetary incentives are the most effective method to increase survey participation. However, most of the studies we found were conducted by family medicine residents and the vast majority seemed to be self-funded. Yet, it shows that there is potential for increasing participation rates in Portuguese studies if there is more funding for research in general practice.
Our estimate of 56% response rate is consistent with the average response rate of 61% (95CI 59-63%) found in international studies.8 We were surprised to find that pre-contact strategies were not associated with increased response rates (75% vs. 52%, p=0.27 for the interaction test), contrary to what has been previously described.8 It is possible that this result is due to the small number of studies which described contacting participants before sending the questionnaires (n=6). We found that there were differences according to delivery mode. There was a single study surveying GPs by telephone,51 which yielded the highest response rate in our review. However, it is impossible to say whether such high response rate is associated with this specific delivery mode or if it was due to other characteristics of this particular study. Personal delivery also seems to produce higher response rates (75%) compared to postal questionnaires (37%); e-mail questionnaires seem to have intermediate response rates (48%). A possible explanation is that in small surveys it is feasible to hand-in questionnaires personally, and that there is often some sort of personal relationship with the researcher (often a co-worker) that may contribute to increase the participation rate. In fact, it is clear in our data that smaller studies have higher response rates than larger studies. Whether this is a true association or just an artifact of publication bias (small studies with low response rates not being considered for publication or presentation) is unclear to us.
Conclusion
Researchers wanting to conduct surveys with Portuguese general practitioners should anticipate response rates of 56% or lower. There is substantial variation in response rates in this target population, which remains unexplained. Monetary incentives should be considered by researchers in future studies, as this has been shown in the international literature to be an effective strategy in increasing response rates.
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Study conducted at Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisboa, Portugal
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Publication Dates
-
Publication in this collection
Mar 2018
History
-
Received
13 July 2017 -
Accepted
23 Aug 2017