Patterns of Consent in Epidemiologic Research: Evidence from Over 25,000 Responders

Kate M. Dunn , Kelvin Jordan, Rosie J. Lacey, Mark Shapley and Clare Jinks

From the Primary Care Sciences Research Centre, Keele University, Keele, Staffordshire, United Kingdom.

Received for publication July 21, 2003; accepted for publication December 16, 2003.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Ethical guidelines in the United Kingdom require written consent from participants in epidemiologic studies for follow-up or review of medical records. This may cause bias in samples used for follow-up or medical record review. The authors analyzed data from seven general population surveys conducted in the United Kingdom (1996–2002), to which over 25,000 people responded. Associations of age, gender, and symptom under investigation with consent to follow-up and consent to review of medical records were examined. Consent to follow-up was approximately 75–95% among survey responders under age 50 years but fell among older people, particularly females. Consent to follow-up was also higher among responders who had the symptom under investigation (pooled odds ratio = 1.61, 95% confidence interval: 1.36, 1.92). Consent to review of medical records followed a similar pattern. Patterns of consent were relatively consistent and represented a high proportion of responders. Males, younger people, and subjects reporting the symptom under investigation were more likely to give consent, and these groups may be overrepresented in follow-up samples or reviews of medical records. Although consent is high among responders, the additive effect of nonresponse and nonconsent can substantially reduce sample size and should be taken into account in epidemiologic study planning.

bias (epidemiology); consent forms; epidemiologic methods; informed consent; longitudinal studies; medical records; selection bias


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
National regulations in the United Kingdom require written consent from study participants for use of their individual data in research. Recent publication of the Governance Arrangements for Research Ethics Committees (1) has further clarified and enforced these regulations. Similar regulations have also been introduced in certain US states and in other countries. These regulations have implications for epidemiologic research, particularly the requirement for written consent when researchers wish to link survey results to medical records or to contact people at more than one time point.

There are a number of potential effects of "consent" regulations on epidemiologic research. First, asking study participants for consent to review their medical records, for example, may affect survey response rates. Investigators who have examined this have reported conflicting results (25). Second, there are implications for study design, particularly in increasing sample sizes to allow for nonconsent (6). Third, concerns have been raised about whether consent will be obtained uniformly among survey responders and, if some form of selection bias (or "consent bias") exists, how this affects the external validity of study findings (79).

Several studies have examined patterns of consent, but only a few studies have been carried out in samples considered to be representative of the general population, and these have only examined consent to review of medical records (2, 7, 10) or consent to medical examination (11). Other studies have evaluated patients using health services in the United States, either at hospitals (12, 13) or at family practice centers (9). Two studies in the United Kingdom evaluated specific samples of primary care patients (6, 14). A range of types of consent have been requested in these studies, the most common being consent to examination of medical records (2, 6, 7, 9, 10, 12, 13, 15). Other studies have requested consent to being videotaped for research purposes (16), consent to medication review (14), and consent to medical examination (11).

There is limited information available on patterns of consent in general population samples, particularly on consent to be followed up as part of a study. In this paper, we aim to describe and evaluate patterns of consent to follow-up and consent to review of primary-care medical records among patients responding to a number of large-scale epidemiologic surveys in the United Kingdom.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The Primary Care Sciences Research Centre at Keele University in North Staffordshire, United Kingdom, has carried out a number of large-scale epidemiologic surveys since 1996, many of which have included questions asking for permission to review primary-care medical records and/or permission to follow up responders in the future as part of the study. The Local Research Ethics Committee approved all of the studies. Table 1 shows the characteristics of the surveys included in this paper.


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TABLE 1. Characteristics of seven general population surveys, United Kingdom, 1996–2002
 
All of the studies used the general-practice age-sex register as the sampling frame for the study, either directly from the practice or indirectly through the North Staffordshire Health Authority. As indicated in table 1, either everyone registered with the general practices (four studies) or a random sample of all of those registered (three studies) were mailed the study questionnaires. The total population receiving the mailing across all studies was 42,812 people; table 1 shows the breakdown by study. In the United Kingdom, approximately 98 percent of the population are registered with a general practitioner (24), and the general-practice age-sex register is considered to be representative of the general population (25).

The studies had a mailing policy of a postcard sent to nonresponders 2 weeks after the baseline mailing and a reminder questionnaire sent to people who still had not responded 4 weeks after baseline. Two exceptions to this policy were study A, where reminder questionnaires were mailed at 4 weeks but postcards were not sent, and study C, where the reminder questionnaire was sent 5 weeks (instead of 4 weeks) after baseline.

The number of questions on the questionnaires used in the studies ranged from 36 to 225 (see table 1), but all contained demographic, disease-specific, and generic items. Two studies surveyed subjects aged 50 years or more (studies B and F); one assessed young adults aged 18–25 years (study G); and one studied only females aged 18–54 years (study D).

Analysis
Information on age, gender, response, and consent to follow-up and/or consent to review of medical records was collated from all studies. Information on reporting of the symptom under investigation for each study (as specified in table 1) was also collated for survey responders.

The proportion of the total sample responding, the proportion of responders consenting to follow-up, and the proportion of responders consenting to review of medical records were calculated for each study separately and then across all studies. For each study, odds ratios for the effect of age (categorized into age groups) on response and consent were calculated separately for females under age 50 years, males under age 50 years, females aged 50 years or more, and males aged 50 years or more. The youngest age group in each category was used as the reference group (18–29 for those under age 50 years and 50–59 for those aged 50 years or more). This split by gender and age was used because of the nature of the studies, two of which only considered people aged 50 years or more (studies B and F) and one of which only considered females (study D). It also allows for easier interpretation by researchers considering studies of only one gender or only older or younger populations, but it gives the overall age-gender picture as well. We then pooled these odds ratios across the studies to obtain overall odds ratios with 95 percent confidence intervals for age within each of the four age-gender divisions given above. This was performed using random-effects models (26).

The effect on consent of reporting the symptom under investigation was assessed among survey responders in two ways. First, we performed separate multiple logistic regression analyses for follow-up and review of medical records for each study with age, gender, and self-report of the symptom under investigation entered jointly as predictors of consent. The effects on consent of interaction between age, gender, and the symptom under investigation were then assessed by the addition of three two-way interactions (age x gender, age x symptom, and gender x symptom) to these models. Finally, we pooled the age- and gender-adjusted odds ratios for the symptoms under investigation for each study to obtain an overall summary (a pooled odds ratio with 95 percent confidence interval) of the effect of self-reporting of the symptom under investigation on consent rates, again using a random-effects model.

Analyses were carried out using SPSS for Windows 11.0 (27) and Stata 7.0 (28).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The overall survey response across all seven studies was 65 percent, comprising 27,797 people (see table 1 for a breakdown by study). There was a wide range of response when data were stratified by age and gender, from 25 percent in young males (study E, age 18–29 years) to 90 percent in older males (study A, age 70–79 years). The patterns found were similar in the different studies. Table 2 shows that overall survey response was lowest in the youngest age group and that it increased with age until approximately age 70 years in women and 80 years in men; it was lower in men than in women until approximately age 70 years, after which lower proportions of women responded.


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TABLE 2. Response in seven general population surveys, by gender and age group, United Kingdom, 1996–2002
 
The patterns of consent to follow-up and review of medical records among responders were reasonably consistent across the different studies. Both types of consent were fairly stable among persons under age 50 years at approximately 75–95 percent of responders. However, the proportion consenting fell with advancing age in the older age groups, particularly in women.

The consent figures for responders pooled across all studies are shown in table 3. The odds ratios for consent to follow-up (pooled across studies C, D, E, F, and G) suggest an increase in the age group 30–49 years in comparison with the age group 18–29 years, though the figures are not significantly different. However, consent fell significantly with increasing age for both male and female responders over the age of 50 (when compared with the 50–59 age group). The proportions of responders consenting in the under-50 group were similar but slightly higher in females than in males, but in the 50-and-over group, higher proportions of male responders consented to follow-up. In particular, there were age-gender interactions in studies E (p = 0.005) and F (p = 0.07), where there were steeper falls in consent to follow-up among older female responders than among male responders. For example, consent fell to below 50 percent among women aged 80 years or more in study F.


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TABLE 3. Proportions of the total sample responding to seven general population surveys, and proportion of the total sample consenting, stratified by age and gender, United Kingdom, 1996–2002
 
Consent to review of medical records had a pattern fairly similar to that for consent to follow-up (table 3), with consent falling among responders over age 50 years. Again, the odds ratios (pooled across studies A, B, C, D, F, and G) show that consent to review of medical records increased from the youngest age group to a maximum at age 40–49 years. As with consent to follow-up, consent to record review fell continuously by age for both male and female responders over the age of 50. Consent to record review among persons under 50 was similar in females and males, but higher proportions of males consented among responders aged 50 years or more.

Table 3 also shows the proportions of the total sample (i.e., responders and nonresponders) consenting for each age and gender category, with figures ranging from 22 percent of men under age 30 consenting to follow-up to 67 percent of women aged 40–49 consenting to record review. The proportions consenting are higher for females than for males under the age of 50, fairly similar among persons aged 50–69 years, and higher for males in the oldest age groups.

Figures 1 and 2 display the effect of having the symptom under investigation on consent to follow-up and consent to review of medical records, respectively, among responders. The squares represent the odds ratio for each study, and the horizontal lines represent the corresponding 95 percent confidence intervals. The size of each square reflects the weight of that study in the pooled odds ratio. The diamonds represent the odds ratios pooled across studies, with associated 95 percent confidence intervals. The relation of age and gender with consent described above remained when it was included in the logistic regression models along with symptom reporting. The interactions of symptom reporting with age and gender were nonsignificant across all studies.



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FIGURE 1. Effect of having the symptom under investigation on consent to follow-up among responders to seven general population surveys, United Kingdom, 1996–2002. The squares represent the log odds ratio (adjusted for age and gender) for each study, and the horizontal lines represent the corresponding 95 percent confidence intervals. The size of each square reflects the weight of that study in the pooled odds ratio. The diamond represents the pooled odds ratio with its associated 95 percent confidence interval.

 


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FIGURE 2. Effect of having the symptom under investigation on consent to review of medical records among responders to seven general population surveys, United Kingdom, 1996–2002. The squares represent the log odds ratio (adjusted for age and gender) for each study, and the horizontal lines represent the corresponding 95 percent confidence intervals. The size of each square reflects the weight of that study in the pooled odds ratio. The diamond represents the pooled odds ratio with its associated 95 percent confidence interval.

 
For consent to follow-up, the odds ratio (pooled across studies) was 1.61 (95 percent confidence interval: 1.36, 1.92), indicating that responders who had the symptom being investigated were significantly more likely to consent to follow-up, independently of age and gender, than responders without the symptom under investigation. Figure 1 shows general consistency in the effect of positive reporting of the symptom under investigation on consent rates in the four studies (including studies C and D, which investigated symptoms different from those of the other studies). However, the effect appeared much larger among the younger adults in study G, which led to significant heterogeneity between the studies (test for heterogeneity: p = 0.007).

Figure 2 displays the effect of having the symptom under investigation on consent to review of medical records among survey responders. The results are very similar to those for consent to follow-up, with a pooled odds ratio of 1.44 (95 percent confidence interval: 1.34, 1.55). This indicates that responders who had the symptom being investigated had approximately 1.5 times’ the odds of consenting to review of their medical records as responders not reporting the symptom. There is consistency in the effect of reporting the symptom across the studies (test for heterogeneity: p = 0.43).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
We studied data from over 25,000 adults who returned postal questionnaires in seven surveys and have shown that approximately 70–90 percent of responders consented to review of their medical records or to being followed up. Patterns were similar for consent to follow-up and consent to review of medical records, but consent was not evenly distributed among survey responders. This provides evidence of a consent bias.

Among responders under 50 years of age, although consent was high (75–95 percent), persons in the youngest age group and males were slightly less likely to consent. Among responders aged 50 years or more, consent was slightly lower (50–80 percent), the proportions consenting declined with age, and male responders were more likely to consent than female responders. Another United Kingdom study also found that younger people were more likely to consent to medical examination (11), though two studies carried out in the United States found that older people were more likely to consent to record review (7, 9). The higher proportion of men consenting than women has been found in other studies evaluating consent to review of medical records (7, 9, 13), consent to medical examination (11), and consent to medication review (14). This pattern for consent contrasts with initial survey response, which this study and other studies (2, 25) have found to be lower in younger people and in men.

Survey responders reporting the symptoms under investigation were more likely to consent, even after adjustment for age and gender, than responders not reporting the symptom under investigation. Similar findings have been reported in other studies; for example, Woolf et al. (9) reported that people in poorer health were more likely to consent to review of medical records, and Petty et al. (14) found that people receiving more repeat prescriptions were more likely to consent to medication review.

These findings mean that people reporting the symptom under investigation could be overrepresented in follow-up samples or reviews of medical records. This may not matter in situations where the focus of any subsequent study is subjects with the condition, since most of those people are likely to consent. However, where a representative sample of the general population is required in follow-up surveys or studies using review of medical records, bias may be a problem, particularly if consent is low. In studies such as these, standardization for the baseline distribution of the symptom or condition should be considered. However, the effect of consent bias may not be important, because consent is generally high—for example, in this study, the overall prevalence of the symptom under investigation was 63 percent, but symptom prevalence among people consenting only increased to 64 percent.

The effect of bias caused by requesting consent is likely to be lesser than the effect of bias caused by selective survey response, since the proportion of the sample responding to the study is generally lower than the proportion giving consent to review of medical records or follow-up. The interaction between consent bias and nonresponse bias is unknown (8, 9). This study has shown that, among survey responders, younger people and men in certain age groups are more likely to give consent, although the percentage of the total sample consenting is still low for younger age groups because of their lower levels of response. Even with a respectable initial response and a high level of consent among responders, these results suggest that only 30–60 percent of the original sample (depending on age and gender) will both respond and consent. This should be taken into account in sample size calculations for studies with a longitudinal or multistage design. However, consent is only one step in the study process. Not all people who consent to follow-up will actually go on to participate in follow-up, and biases related to attrition may still be present at later stages of longitudinal studies. Therefore, the percentages of the original sample agreeing to be contacted for follow-up can be viewed as the maximum achievable participation rate at later stages.

One limitation of this study is that only a few self-report symptoms were studied, namely knee, neck, upper limb, and joint pain, headache, and increased vaginal bleeding. However, the studies of these different symptoms all showed consistent patterns, and it seems likely that other questionnaire-based studies of self-reported symptoms would find similar results. In addition, all of the studies were carried out within one specific geographic area, and similar studies in other areas may help to confirm the generalizability of the results.

In this study, we evaluated seven large surveys of a number of symptoms and found consistent patterns of consent. Overall, consent was high among responders, but biases were found; the biases were consistent for different populations but largely different from nonresponse biases. In addition, the additive processes of response and consent mean that less than half of an initial sample may be included in follow-up samples, and not all of these persons will actually respond to follow-up. It is important for researchers conducting longitudinal studies or studies involving review of medical records to be aware that not everyone will consent, and consent may not be evenly distributed among study participants. This information is important in study planning and interpretation. For example, sample sizes should be increased to account for nonconsenters, and researchers may need to carry out sensitivity analyses for investigation of potential effects of bias. However, the potential for bias does not necessarily imply that bias will invalidate study results. Researchers need to investigate the impact that bias may have in their study and how this may alter interpretation of results. Further work is needed to explore methods of increasing the proportion consenting to follow-up or to review of medical records in surveys, particularly among groups in which consent is lower, in order to minimize this source of bias.


    ACKNOWLEDGMENTS
 
Sources of funding for the individual studies in this analysis included the Haywood Rheumatism Research and Development Foundation (North Staffordshire), the Medical Research Council, a National Health Service Executive (West Midlands) New Blood Research Training Fellowship, the North Staffordshire Medical Institute, the North Staffordshire Primary Care Research Consortium, and the Wolstanton Medical Practice.

Individual study investigators included Dr. H. Boardman, Dr. C. D. Mallen, R. W. McCarney, Dr. E. Thomas, and R. Wilkie.


    NOTES
 
Correspondence to Kate M. Dunn, Primary Care Sciences Research Centre, Keele University, Keele, Staffordshire ST5 5BG, United Kingdom (e-mail: k.m.dunn{at}cphc.keele.ac.uk). Back


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. United Kingdom Department of Health. Governance arrangements for NHS Research Ethics Committees (GAfREC). London, United Kingdom: United Kingdom Department of Health, 2001. (World Wide Web URL: http://www.dh.gov.uk/assetRoot/04/05/86/09/04058609.pdf). (Last accessed March 29, 2004).
  2. Korkeila K, Suominen S, Ahvenainen J, et al. Non-response and related factors in a nation-wide health survey. Eur J Epidemiol 2001;17:991–9.[CrossRef][ISI][Medline]
  3. Nelson K, Garcia RE, Brown J, et al. Do patient consent procedures affect participation rates in health services research? Med Care 2002;40:283–8.[CrossRef][ISI][Medline]
  4. Shah S, Harris TJ, Rink E, et al. Do income questions and seeking consent to link medical records reduce survey response rates? A randomised controlled trial among older people. Br J Gen Pract 2001;51:223–5.[ISI][Medline]
  5. Silva MS, Smith WT, Bammer G. The effect of timing when seeking permission to access personal health services utilization records. Ann Epidemiol 2002;12:326–30.[CrossRef][ISI][Medline]
  6. Baker R, Shiels C, Stevenson K, et al. What proportion of patients refuse consent to data collection from their records for research purposes? Br J Gen Pract 2000;50:655–6.[ISI][Medline]
  7. Jacobsen SJ, Xia Z, Campion ME, et al. Potential effect of authorization bias on medical record research. Mayo Clin Proc 1999;74:330–8.[ISI][Medline]
  8. Robling M, Hood K. Postal survey responses and questions about income and seeking consent for linkage to medical records. (Letter). Br J Gen Pract 2001;51:494.
  9. Woolf SH, Rothemich SF, Johnson RE, et al. Selection bias from requiring patients to give consent to examine data for health services research. Arch Fam Med 2000;9:1111–18.[Abstract/Free Full Text]
  10. Young AF, Dobson AJ, Byles JE. Health services research using linked records: who consents and what is the gain? Aust N Z J Public Health 2001;25:417–20.[ISI][Medline]
  11. Pullen E, Nutbeam D, Moore L. Demographic characteristics and health behaviours of consenters to medical examination: results from the Welsh Heart Health Survey. J Epidemiol Community Health 1992;46:455–9.[Abstract]
  12. Merz JF, Spina BJ, Sankar P. Patient consent for release of sensitive information from their medical records: an exploratory study. Behav Sci Law 1999;17:445–54.[CrossRef][ISI][Medline]
  13. Yawn BP, Yawn RA, Geier GR, et al. The impact of requiring patient authorization for use of data in medical records research. J Fam Pract 1998;47:361–5.[ISI][Medline]
  14. Petty DR, Zermansky AG, Raynor DK, et al. "No thank you": why elderly patients declined to participate in a research study. Pharm World Sci 2001;23:22–7.[CrossRef][ISI][Medline]
  15. Cleary PD, Jette AM. The validity of self-reported physician utilization measures. Med Care 1984;22:796–803.[ISI][Medline]
  16. Howe A. Refusal of videorecording: what factors may influence patient consent? Fam Pract 1997;14:233–7.[Abstract/Free Full Text]
  17. McCarney RW. The epidemiology of knee pain in primary care: prevalence, health care utilisation and disability. (Master’s thesis). Keele, United Kingdom: Keele University, 1998.
  18. Jinks C, Jordan K, Ong BN, et al. A brief screening tool for knee pain in primary care (KNEST). 2. Results from a survey in the general population aged 50 and over. Rheumatology 2004;43:55–61.[Abstract/Free Full Text]
  19. Boardman HF, Thomas E, Croft PR, et al. Epidemiology of headache in an English district. Cephalalgia 2003;23:129–37.[CrossRef][ISI][Medline]
  20. Shapley M, Jordan K, Croft PR. Increased vaginal bleeding and psychological distress: a longitudinal study of their relationship in the community. Br J Obstet Gynecol 2003;110:548–54.
  21. Sim J, Lacey RJ, Lewis M. Neck and upper limb pain in pottery workers in North Staffordshire, United Kingdom. (Abstract). Rheumatology 2003;42(suppl 1):35.
  22. Wilkie R, Thomas E, Peat G, et al. Population-based prevalence of participation restriction in older adults, and its association with joint pain. (Abstract). Rheumatology 2003;42(suppl 1):61.
  23. Mallen CD. The prevalence of chronic pain in young adults: a cross-sectional survey. (Master’s thesis). Keele, United Kingdom: Keele University, 2004.
  24. Bowling A, Bond M, Jenkinson C, et al. Short Form 36 (SF-36) Health Survey questionnaire: which normative data should be used? Comparisons between the norms provided by the Omnibus Survey in Britain, the Health Survey for England and the Oxford Healthy Life Survey. J Public Health Med 1999;21:255–70.[Abstract/Free Full Text]
  25. Walsh K. Evaluation of the use of general practice age-sex registers in epidemiological research. Br J Gen Pract 1994;44:118–22.[ISI][Medline]
  26. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177–88.[CrossRef][ISI][Medline]
  27. SPSS, Inc. SPSS for Windows. Release 11.0. Chicago, IL: SPSS, Inc, 2001.
  28. Stata Corporation. Stata statistical software. Release 7.0. College Station, TX: Stata Corporation, 2002.