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How social representations of sexually transmitted infections influence experiences of genito-urinary symptoms and care-seeking in Britain: mixed methods study protocol.

Mapp F, Hickson F, Mercer CH, Wellings K - BMC Public Health (2016)

Bottom Line: Social understandings of sexually transmitted infections and associated symptoms and care-seeking behaviour continue to lag behind advancements in biomedical diagnostics and treatment, perpetuating the burden of disease.It adds explanatory potential to existing national survey data and is likely to inform future surveys about sexual health.Given the current uncertainty around service provision in Britain, this study provides timely data about symptom experiences and care-seeking behaviour which may inform future commissioning of sexual healthcare.

View Article: PubMed Central - PubMed

Affiliation: Department of Social and Environmental Health Research, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK. Fiona.Mapp@lshtm.ac.uk.

ABSTRACT

Background: Social understandings of sexually transmitted infections and associated symptoms and care-seeking behaviour continue to lag behind advancements in biomedical diagnostics and treatment, perpetuating the burden of disease. There is a lack of research linking perceptions, experiences and care-seeking for sexual health issues, especially research conducted outside of medical settings. We aim to explore lay perceptions of STIs and how these influence experiences of genito-urinary symptoms and associated care-seeking behaviour, in women and men in Britain.

Methods and design: This study adopts a participant-selection variant of the explanatory sequential mixed methods design to incorporate quantitative and qualitative strands. We use data from Britain's third National Survey of Sexual Attitudes and Lifestyles (n = 15,162) to analyse national patterns of symptom experience and care-seeking, and to identify a purposive qualitative sample. Semi-structured interviews (n = 27) following up with survey participants include a novel flash card activity providing qualitative data about infection perceptions, symptom experiences and decisions about healthcare. Quantitative and qualitative data are analysed separately using complex survey analyses and principles of Interpretative Phenomenological Analysis respectively. Data are then integrated in a subsequent phase of analysis using matrices to compare, contrast and identify silences from each method.

Discussion: This is an ongoing mixed methods study collecting, analysing and synthesising linked data from a national survey and follow-up semi-structured interviews. It adds explanatory potential to existing national survey data and is likely to inform future surveys about sexual health. Given the current uncertainty around service provision in Britain, this study provides timely data about symptom experiences and care-seeking behaviour which may inform future commissioning of sexual healthcare.

No MeSH data available.


Related in: MedlinePlus

Derivation of sub-groups for quantitative analyses
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Fig2: Derivation of sub-groups for quantitative analyses

Mentions: This study uses data from a sub-sample of Natsal-3 participants (Fig. 2) who were aged 16–44 years and sexually experienced, defined as those who reported having had at least one sexual partner (n = 8947). We want to capture and compare patterns of symptoms and care-seeking across a greater age range than those at highest risk. After initial data exploration involving cross-tabulations of key variables and basic summary statistics to facilitate choosing the sampling frame for the qualitative strand, data analysis was delayed to coincide with analysis of the qualitative data. This approach enables us to move between each dataset, using findings from one to inform analyses of the other, and vice versa, whilst maintaining analytical distinction between data types. We conduct statistical analyses on variables derived from the survey questions [30] “In the last month, that is since (date one month ago), have you had any of the following symptoms?” and “Have you ever attended a sexual health clinic (GUM clinic)?” The primary dependent variables are reported symptom experience and non-attendance at a sexual health clinic. Table 1 shows the symptoms that the Natsal-3 questions asked about. Independent variables included in the quantitative analyses are informed by qualitative findings and relevant literature. Participants with missing data for either the independent and/or the dependent variables are excluded from analysis as there are generally low levels of missing data in Natsal-3, often between 1 and 3 % [28]. We are using the survey commands in Stata V.14.1 to account for stratification, clustering and weighting of the dataset. Prevalence estimates of reported symptoms and non-attendance at sexual health clinics are calculated with 95 % confidence intervals for women and men, stratified by age-group. We are using logistic regression to examine associations between reporting symptoms and not having attended a sexual health clinic in the past year to produce crude and age-adjusted odds ratios. Analyses are stratified by sex to reflect differences in male and female anatomy, physiology and epidemiology of genito-urinary infections [29, 31, 32] and reported gender differences in care-seeking behaviour [33–35].Fig. 2


How social representations of sexually transmitted infections influence experiences of genito-urinary symptoms and care-seeking in Britain: mixed methods study protocol.

Mapp F, Hickson F, Mercer CH, Wellings K - BMC Public Health (2016)

Derivation of sub-groups for quantitative analyses
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4940703&req=5

Fig2: Derivation of sub-groups for quantitative analyses
Mentions: This study uses data from a sub-sample of Natsal-3 participants (Fig. 2) who were aged 16–44 years and sexually experienced, defined as those who reported having had at least one sexual partner (n = 8947). We want to capture and compare patterns of symptoms and care-seeking across a greater age range than those at highest risk. After initial data exploration involving cross-tabulations of key variables and basic summary statistics to facilitate choosing the sampling frame for the qualitative strand, data analysis was delayed to coincide with analysis of the qualitative data. This approach enables us to move between each dataset, using findings from one to inform analyses of the other, and vice versa, whilst maintaining analytical distinction between data types. We conduct statistical analyses on variables derived from the survey questions [30] “In the last month, that is since (date one month ago), have you had any of the following symptoms?” and “Have you ever attended a sexual health clinic (GUM clinic)?” The primary dependent variables are reported symptom experience and non-attendance at a sexual health clinic. Table 1 shows the symptoms that the Natsal-3 questions asked about. Independent variables included in the quantitative analyses are informed by qualitative findings and relevant literature. Participants with missing data for either the independent and/or the dependent variables are excluded from analysis as there are generally low levels of missing data in Natsal-3, often between 1 and 3 % [28]. We are using the survey commands in Stata V.14.1 to account for stratification, clustering and weighting of the dataset. Prevalence estimates of reported symptoms and non-attendance at sexual health clinics are calculated with 95 % confidence intervals for women and men, stratified by age-group. We are using logistic regression to examine associations between reporting symptoms and not having attended a sexual health clinic in the past year to produce crude and age-adjusted odds ratios. Analyses are stratified by sex to reflect differences in male and female anatomy, physiology and epidemiology of genito-urinary infections [29, 31, 32] and reported gender differences in care-seeking behaviour [33–35].Fig. 2

Bottom Line: Social understandings of sexually transmitted infections and associated symptoms and care-seeking behaviour continue to lag behind advancements in biomedical diagnostics and treatment, perpetuating the burden of disease.It adds explanatory potential to existing national survey data and is likely to inform future surveys about sexual health.Given the current uncertainty around service provision in Britain, this study provides timely data about symptom experiences and care-seeking behaviour which may inform future commissioning of sexual healthcare.

View Article: PubMed Central - PubMed

Affiliation: Department of Social and Environmental Health Research, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK. Fiona.Mapp@lshtm.ac.uk.

ABSTRACT

Background: Social understandings of sexually transmitted infections and associated symptoms and care-seeking behaviour continue to lag behind advancements in biomedical diagnostics and treatment, perpetuating the burden of disease. There is a lack of research linking perceptions, experiences and care-seeking for sexual health issues, especially research conducted outside of medical settings. We aim to explore lay perceptions of STIs and how these influence experiences of genito-urinary symptoms and associated care-seeking behaviour, in women and men in Britain.

Methods and design: This study adopts a participant-selection variant of the explanatory sequential mixed methods design to incorporate quantitative and qualitative strands. We use data from Britain's third National Survey of Sexual Attitudes and Lifestyles (n = 15,162) to analyse national patterns of symptom experience and care-seeking, and to identify a purposive qualitative sample. Semi-structured interviews (n = 27) following up with survey participants include a novel flash card activity providing qualitative data about infection perceptions, symptom experiences and decisions about healthcare. Quantitative and qualitative data are analysed separately using complex survey analyses and principles of Interpretative Phenomenological Analysis respectively. Data are then integrated in a subsequent phase of analysis using matrices to compare, contrast and identify silences from each method.

Discussion: This is an ongoing mixed methods study collecting, analysing and synthesising linked data from a national survey and follow-up semi-structured interviews. It adds explanatory potential to existing national survey data and is likely to inform future surveys about sexual health. Given the current uncertainty around service provision in Britain, this study provides timely data about symptom experiences and care-seeking behaviour which may inform future commissioning of sexual healthcare.

No MeSH data available.


Related in: MedlinePlus