Impact of an informed choice invitation on uptake of screening for diabetes in primary care (DICISION): trial protocol

Enhancing informed choice to undergo health screening: a systematic review

OBJECTIVE

To assess the effectiveness of health screening interventions aimed at enhancing informed choice.

METHODS

Studies were selected if (1) they were randomized controlled trials conducted between January 1, 2000, and March 30, 2010, (2) participants in one arm underwent a prescreening intervention aimed at improving informed choice, and (3) informed choice was the primary outcome.

RESULTS

Eight studies that met the inclusion criteria involved screening for prostate, colorectal and breast cancer, and diabetes. Five of the 8 prescreening interventions led to greater informed choice.

CONCLUSIONS

With researchers mindful of the limited number of studies, findings were encouraging, but conclusions regarding the most effective ways of facilitating informed choice for screening are at best tentative.

Non-participation in population-based disease prevention programs in general practice

BACKGROUND

The number of people with a chronic disease will strongly increase in the next decades. Therefore, prevention of disease becomes increasingly important. The aim of this systematic review was to identify factors that negatively influence participation in population-based disease prevention programs in General Practice and to establish whether the program type is related to non-participation levels.

METHODS

We conducted a systematic review in Pubmed, EMBASE, CINAHL and PsycINFO, covering 2000 through July 6th 2012, to identify publications including information about characteristics of non-participants or reasons for non-participation in population-based disease prevention programs in General Practice.

RESULTS

A total of 24 original studies met our criteria, seven of which focused on vaccination, eleven on screening aimed at early detection of disease, and six on screening aimed at identifying high risk of a disease, targeting a variety of diseases and conditions. Lack of personal relevance of the program, younger age, higher social deprivation and former non-participation were related to actual non-participation. No differences were found in non-participation levels or factors related to non-participation between the three program types. The large variation in non-participation levels within the program types may be partly due to differences in recruitment strategies, with more active, personalized strategies resulting in higher participation levels compared to an invitation letter.

CONCLUSIONS

There is still much to be gained by tailoring strategies to improve participation in those who are less likely to do so, namely younger individuals, those living in a deprived area and former non-participants. Participation may increase by applying more active recruitment strategies.

Non-participation in population-based disease prevention programs in general practice

Background

The number of people with a chronic disease will strongly increase in the next decades. Therefore, prevention of disease becomes increasingly important. The aim of this systematic review was to identify factors that negatively influence participation in population-based disease prevention programs in General Practice and to establish whether the program type is related to non-participation levels.

Methods

We conducted a systematic review in Pubmed, EMBASE, CINAHL and PsycINFO, covering 2000 through July 6th 2012, to identify publications including information about characteristics of non-participants or reasons for non-participation in population-based disease prevention programs in General Practice.

Results

A total of 24 original studies met our criteria, seven of which focused on vaccination, eleven on screening aimed at early detection of disease, and six on screening aimed at identifying high risk of a disease, targeting a variety of diseases and conditions. Lack of personal relevance of the program, younger age, higher social deprivation and former non-participation were related to actual non-participation. No differences were found in non-participation levels or factors related to non-participation between the three program types. The large variation in non-participation levels within the program types may be partly due to differences in recruitment strategies, with more active, personalized strategies resulting in higher participation levels compared to an invitation letter.

Conclusions

There is still much to be gained by tailoring strategies to improve participation in those who are less likely to do so, namely younger individuals, those living in a deprived area and former non-participants. Participation may increase by applying more active recruitment strategies.

Decision aids for people facing health treatment or screening decisions

BACKGROUND

Decision aids prepare people to participate in decisions that involve weighing benefits, harms, and scientific uncertainty.

OBJECTIVES

To evaluate the effectiveness of decision aids for people facing treatment or screening decisions.

SEARCH STRATEGY

For this update, we searched from January 2006 to December 2009 in MEDLINE (Ovid); Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, issue 4 2009); CINAHL (Ovid) (to September 2008 only); EMBASE (Ovid); PsycINFO (Ovid); and grey literature. Cumulatively, we have searched each database since its start date.

SELECTION CRITERIA

We included published randomised controlled trials (RCTs) of decision aids, which are interventions designed to support patients' decision making by providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies in which participants were not making an active treatment or screening decision.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened abstracts for inclusion, extracted data, and assessed potential risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards, were:A) decision attributes;B) decision making process attributes.Secondary outcomes were behavioral, health, and health system effects. We pooled results of RCTs using mean differences (MD) and relative risks (RR), applying a random effects model.

MAIN RESULTS

Of 34,316 unique citations, 86 studies involving 20,209 participants met the eligibility criteria and were included. Thirty-one of these studies are new in this update. Twenty-nine trials are ongoing. There was variability in potential risk of bias across studies. The two criteria that were most problematic were lack of blinding and the potential for selective outcome reporting, given that most of the earlier trials were not registered.Of 86 included studies, 63 (73%) used at least one measure that mapped onto an IPDAS effectiveness criterion: A) criteria involving decision attributes: knowledge scores (51 studies); accurate risk perceptions (16 studies); and informed value-based choice (12 studies); and B) criteria involving decision process attributes: feeling informed (30 studies) and feeling clear about values (18 studies).A) Criteria involving decision attributes:Decision aids performed better than usual care interventions by increasing knowledge (MD 13.77 out of 100; 95% confidence interval (CI) 11.40 to 16.15; n = 26). When more detailed decision aids were compared to simpler decision aids, the relative improvement in knowledge was significant (MD 4.97 out of 100; 95% CI 3.22 to 6.72; n = 15). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.74; 95% CI 1.46 to 2.08; n = 14). The effect was stronger when probabilities were expressed in numbers (RR 1.93; 95% CI 1.58 to 2.37; n = 11) rather than words (RR 1.27; 95% CI 1.09 to 1.48; n = 3). Exposure to a decision aid with explicit values clarification compared to those without explicit values clarification resulted in a higher proportion of patients achieving decisions that were informed and consistent with their values (RR 1.25; 95% CI 1.03 to 1.52; n = 8).B) Criteria involving decision process attributes:Decision aids compared to usual care interventions resulted in: a) lower decisional conflict related to feeling uninformed (MD -6.43 of 100; 95% CI -9.16 to -3.70; n = 17); b) lower decisional conflict related to feeling unclear about personal values (MD -4.81; 95% CI -7.23 to -2.40; n = 14); c) reduced the proportions of people who were passive in decision making (RR 0.61; 95% CI 0.49 to 0.77; n = 11); and d) reduced proportions of people who remained undecided post-intervention (RR 0.57; 95% CI 0.44 to 0.74; n = 9). Decision aids appear to have a positive effect on patient-practitioner communication in the four studies that measured this outcome. For satisfaction with the decision (n = 12) and/or the decision making process (n = 12), those exposed to a decision aid were either more satisfied or there was no difference between the decision aid versus comparison interventions. There were no studies evaluating the decision process attributes relating to helping patients to recognize that a decision needs to be made or understand that values affect the choice.C) Secondary outcomesExposure to decision aids compared to usual care continued to demonstrate reduced choice of: major elective invasive surgery in favour of conservative options (RR 0.80; 95% CI 0.64 to 1.00; n = 11). Exposure to decision aids compared to usual care also resulted in reduced choice of PSA screening (RR 0.85; 95% CI 0.74 to 0.98; n = 7). When detailed compared to simple decision aids were used, there was reduced choice of menopausal hormones (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable. The effect of decision aids on length of consultation varied from -8 minutes to +23 minutes (median 2.5 minutes). Decision aids do not appear to be different from comparisons in terms of anxiety (n = 20), and general health outcomes (n = 7), and condition specific health outcomes (n = 9). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive.

AUTHORS' CONCLUSIONS

New for this updated review is evidence that: decision aids with explicit values clarification exercises improve informed values-based choices; decision aids appear to have a positive effect on patient-practitioner communication; and decision aids have a variable effect on length of consultation.Consistent with findings from the previous review, which had included studies up to 2006: decision aids increase people's involvement, and improve knowledge and realistic perception of outcomes; however, the size of the effect varies across studies. Decision aids have a variable effect on choices. They reduce the choice of discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, patient-practitioner communication, cost-effectiveness, and use with developing and/or lower literacy populations need further evaluation. Little is known about the degree of detail that decision aids need in order to have positive effects on attributes of the decision or decision-making process.

Impact of informed-choice invitations on diabetes screening knowledge, attitude and intentions: an analogue study

Background

Despite concerns that facilitating informed choice would decrease diabetes screening uptake, 'informed choice' invitations that increased knowledge did not affect attendance (the DICISION trial). We explored possible reasons using data from an experimental analogue study undertaken to develop the invitations. We tested a model of the impact on knowledge, attitude and intentions of a diabetes screening invitation designed to facilitate informed choices.

Methods

417 men and women aged 40-69 recruited from town centres in the UK were randomised to receive either an invitation for diabetes screening designed to facilitate informed choice or a standard type of invitation. Knowledge of the invitation, attitude towards diabetes screening, and intention to attend for diabetes screening were assessed two weeks later.

Results

Attitude was a strong predictor of screening intentions (β = .64, p = .001). Knowledge added to the model but was a weak predictor of intentions (β = .13, p = .005). However, invitation type did not predict attitudes towards screening but did predict knowledge (β = -.45, p = .001), which mediated a small effect of invitation type on intention (indirect β = -.06, p = .017).

Conclusions

These findings may explain why information about the benefits and harms of screening did not reduce diabetes screening attendance in the DICISION trial.

Screening for type 2 diabetes: an update of the evidence

A growing body of evidence on diabetes screening has been published during the last 10 years. Type 2 diabetes meets many but not all of the criteria for screening. Concerns about potential harms of screening have largely been resolved. Screening identifies a high-risk population with the potential to gain from widely available interventions. However, in spite of the findings of modelling studies, the size of the benefit of earlier initiation of treatment and the overall cost-effectiveness remains uncertain, in contrast to other screening programmes (such as for abdominal aortic aneurysms) that are yet to be fully implemented. There is also uncertainty about optimal specifications and implementation of a screening programme, and further work to complete concerning development and delivery of individual- and population-level preventive strategies. While there is growing evidence of the net benefit of earlier detection of individuals with prevalent but undiagnosed diabetes, there remains limited justification for a policy of universal population-based screening for type 2 diabetes at the present time. Data from ongoing studies should inform the key assumptions in existing modelling studies and further reduce uncertainty.

Impact of an informed choice invitation on uptake of screening for diabetes in primary care (DICISION): randomised trial

OBJECTIVE

To compare the effect of an invitation promoting informed choice for screening with a standard invitation on attendance and motivation to engage in preventive action.

DESIGN

Randomised controlled trial.

SETTING

Four English general practices.

PARTICIPANTS

1272 people aged 40-69 years, at risk for diabetes, identified from practice registers using a validated risk score and invited to attend for screening.

INTERVENTION

Intervention was a previously validated invitation to inform the decision to attend screening, presenting diabetes as a serious potential problem, and providing details of possible costs and benefits of screening and treatment in text and pie charts. This was compared with a brief, standard invitation simply describing diabetes as a serious potential problem.

MAIN OUTCOME MEASURES

The primary end point was attendance for screening. The secondary outcome measures were intention to make changes to lifestyle and satisfaction with decisions made among attenders.

RESULTS

The primary end point was analysed for all 1272 participants. 55.8% (353/633) of those in the informed choice group attended for screening, compared with 57.6% (368/639) in the standard invitation group (mean difference -1.8%, 95% confidence interval -7.3% to 3.6%; P=0.51). Attendance was lower among the more deprived group (most deprived third 47.5% v least deprived third 64.3%; P<0.001). Interaction between deprivation and effect of invitation type on attendance was not significant. Among attenders, intention to change behaviour was strong and unaffected by invitation type.

CONCLUSIONS

Providing information to support choice did not adversely affect attendance for screening for diabetes. Those from more socially deprived groups were, however, less likely to attend, regardless of the type of invitation received. Further attention to invitation content alone is unlikely to achieve equity in uptake of preventive services.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN 73125647.

Trials in primary care: statistical issues in the design, conduct and evaluation of complex interventions

Trials carried out in primary care typically involve complex interventions that require considerable planning if they are to be implemented successfully. The role of the statistician in promoting both robust study design and appropriate statistical analysis is an important contribution to a multi-disciplinary primary care research group. Issues in the design of complex interventions have been addressed in the Medical Research Council's new guidance document and over the past 7 years by the Royal Statistical Society's Primary Health Care Study Group. With the aim of raising the profile of statistics and building research capability in this area, particularly with respect to methodological issues, the study group meetings have covered a wide range of topics that have been of interest to statisticians and non-statisticians alike. The aim of this article is to provide an overview of the statistical issues that have arisen over the years related to the design and evaluation of trials in primary care, to provide useful examples and references for further study and ultimately to promote good practice in the conduct of complex interventions carried out in primary care and other health care settings. Throughout we have given particular emphasis to statistical issues related to the design of cluster randomised trials.