A randomized trial of a breast/ovarian cancer genetic testing decision aid used as a communication aid during genetic counseling

Psycho-OncologyPsycho-Oncology 17: 844–854 (2008)Published online 9 July 2008 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/pon.1353

A randomized trial of a breast/ovarian cancer genetictesting decision aid used as a communication aid duringgenetic counseling

Claire E. Wakefield1,2,3,�, Bettina Meiser2,4, Judi Homewood1, Alan Taylor1, Margaret Gleeson5, Rachel Williams6,the AGenDA Collaborative Group, and Kathy Tucker2,4

1Department of Psychology, Macquarie University, NSW, Australia2Department of Medical Oncology, Prince of Wales Hospital, Randwick, NSW, Australia3School of Psychiatry, University of New South Wales, Randwick, NSW, Australia4Prince of Wales Clinical School, University of NSW, Randwick, NSW, Australia5Hunter Family Cancer Service, Hunter New England Health, NSW, Australia6Family Cancer Clinic, St Vincent’s Hospital, Darlinghurst, NSW, Australia

Abstract

Objectives: To evaluate the impact of a decision aid for women considering genetic testing for

breast/ovarian cancer risk given during genetic counseling.

Methods: One hundred and forty-eight women were randomized to receive the decision aid or

a control pamphlet at the beginning of their first consultation with a genetic counselor. When

the patient received the decision aid, it was used to complement consultation discussions about

genetic testing. One hundred and ten (74.3%) women completed the first questionnaire

designed to elicit information about women’s levels of decisional conflict and knowledge about

genetic testing. Of these, 105 (70.9%) completed a second questionnaire to assess longer-term

outcomes, 6 months postconsultation.

Results: Results showed that women who received the decision aid felt more informed about

genetic testing (w2(1)5 8.69; P5 0.003), had clearer values (w2(1)5 6.90; P5 0.009) and had

higher knowledge levels (w2(2)5 6.49; P5 0.039) than women who received the control

pamphlet.

Conclusions: The developed decision aid improved patient outcomes better than a control

pamphlet when implemented during genetic counseling and given to the patient to take home.

Copyright r 2008 John Wiley & Sons, Ltd.

Keywords: cancer; oncology; decision aid; implementation; genetic testing; hereditary breast/

ovarian cancer

Introduction

Decision aids are patient education tools specifi-cally designed to improve patients’ understandingof the potential benefits and risks of their differentoptions, as well as to assist patients to considerthe personal importance they place on each ofthese options [1]. They typically include relevantinformation about a particular decision as well asmethods for clarifying and expressing the patient’svalues [2]. Many studies have demonstratedthat decision aids are acceptable to patients, reduceuncertainty, assist people to clarify values andmake decisions congruent with those values;assist those who are uncertain in making choices,reduce the time taken to make a decision andresult in greater adherence to, and satisfactionwith, the decision made [3,4]. Given the nowextensive evidence base documenting their effec-tiveness, decision aids are fast becoming oneof the most common strategies developed to assist

patients with health-related decisions of allkinds.

A decision aid for women considering genetictesting

Decision making about genetic testing forBRCA1/2 mutations can be complex [5], yet asystematic literature search revealed very fewdecision aids available for individuals consideringgenetic testing for cancer risk. A Dutch group haspreviously developed and evaluated a video-baseddecision aid to assist women with decision makingabout screening and prophylactic surgery 2 weeksafter undergoing genetic testing for breast/ovariancancer risk [6]. They reported that women whoreceived the decision aid felt better informed, weremore satisfied with the information and had moreaccurate risk perceptions than women who hadreceived standard care [6]. This group has also

* Correspondence to:Psychosocial Research Group(PRG), Dickinson 3,Department of MedicalOncology, Prince of WalesHospital, Randwick, NSW2031, Sydney, AustraliaE-mail: [email protected]

Received: 15 May 2007

Revised: 25 January 2008

Accepted: 12 February 2008

Copyright r 2008 John Wiley & Sons, Ltd.

developed a decision aid for known BRCA1/2mutation carriers [7]. Similarly, a US-based grouphas evaluated an interactive computer programadministered before genetic counseling that edu-cates women (with and without a family historyof cancer) considering genetic testing for breast/ovarian cancer risk [8]. They found that using thecomputer program before counseling significantlyreduced the length of the counseling session,as well as shifting the focus of the consultationaway from basic education toward patients’individual risks and concerns. In terms of patientoutcomes, they found that use of the computerprogram increased knowledge about breast cancerand genetic testing in low-risk women [9]. Finally,another US-based group has developed severaldecision support booklets for women at increasedrisk for breast/ovarian cancer, including onedesigned specifically for women with AshkenaziJewish heritage [10] and another decision aidfor known BRCA1/2 mutation carriers consideringtheir risk management options [11]. Each ofthese studies has reported positive outcomesfrom decision aid use, including improved know-ledge [10,12] and reduced decisional conflict inwomen who were initially undecided aboutthe risk management strategies they wanted toadopt [11].Although the results from these studies are

positive, there are substantial differences betweenAustralia and the United States in the genetictesting process in terms of costs, time frames,access to predictive genetic testing and impacts onhealth insurance and employment. In addition,recent Australian research suggests that even whenbreast cancer patients have regular access to acomputer, many prefer written information to CD-ROM and videos [13]. Further advantages ofpaper-based tools include the fact that they arecheaper to produce and update, they are easier toshare with other family members, they can be usedeasily by patients who lack computer skills andthey are accessible to the patient at times whenaccess to a video recorder or computer would beinconvenient.We therefore developed a decision aid designed

specifically for Australian women consideringgenetic testing for breast/ovarian cancer risk, usingthe theoretical frameworks developed by O’Connorand colleagues [3,14,15]. The topics in the 40-pagedecision aid include background informationabout cancer and cancer-related genes, a descrip-tion of the testing process, possible test results anda discussion of the potential impact of testingon the individual and their family. A detaileddescription of the decision aid is provided inWakefield et al. [5].The effectiveness of the decision aid was first

evaluated using a randomized controlled trial inwhich the decision aid was given to the patient after

their first consultation at one of five participatingAustralian familial cancer clinics. The results ofthis trial are reported in Wakefield et al. [16].Briefly, the trial showed that women who receivedthe decision aid at the end of their first consultationhad higher knowledge levels (w2(2)5 6.82;P5 0.033) and felt more informed (w2(1)5 4.86;P5 0.028) about genetic testing than women whoreceived a control pamphlet.Although decision aids have proven effective in

experimental trials, few studies have evaluated‘when and how’ decision aids for different medicaldecisions are most effective in practice. Typically,once a decision aid is made available to clinicians,little is done in order to regulate their method ofuse, so that often clinicians adopt the use to suittheir own practice. This is of potential concernwhen different implementation strategies have notbeen properly evaluated. Indeed, O’Cathain andThomas showed that despite decision aids provingeffective in many randomized trials, some prag-matic, or real-life, trials have shown lower usage ofdecision aids than expected as well as muchreduced effectiveness [17]. They argue that moreconsideration of the barriers and challenges todecision aid implementation should be given whendeveloping and evaluating decision aids for clinicalpractice. In fact in our first study, several recruitingclinicians expressed frustration with not being ableto use the decision aid during their consultations.They reported preferring to use the decision aid toguide the patient through the information anddiagrams provided, entering tailored information(e.g. personalized risk estimates) in the appropriatesections and assisting patients to complete theirvalues clarification exercises. Given the dearth ofliterature regarding the effectiveness of differentdecision aid implementation methods, we decidedto conduct a second randomized controlled trial ofthe decision aid assessing the effectiveness of thedecision aid used as a communication aid duringcounseling.

Aims and hypotheses

This study was aimed at evaluating a decision aidfor women considering genetic testing for breast/ovarian cancer risk implemented during geneticcounseling, using a randomized controlled trial. Itwas hypothesized that compared with womenreceiving the standard best practice (a generaleducational pamphlet), those who received thedecision aid during the consultation would havethe following:

(a) decreased decisional conflict (i.e. uncertainty)about genetic testing (primary outcome);

(b) increased knowledge about genetic testing and

(c) an increased rate of informed choice.

Copyright r 2008 John Wiley & Sons, Ltd. Psycho-Oncology 17: 844–854 (2008)

DOI: 10.1002/pon

Randomized trial of a decision aid used during genetic counseling 845

Materials and methods

A detailed description of the materials andmethods utilized for this study is provided inWakefield et al. [16]. The study procedure wasidentical for the current trial, except that thedecision aid was given to women at the beginningof their first consultation with a genetic counselor,used during counseling, and then taken home bythe women. If the woman received the controlpamphlet, the clinician gave the pamphlet to her totake home and continued the consultation in thestandard manner.

Sample

The research sample included women (bothaffected and unaffected by cancer) who approachedone of five Australian familial cancer clinicsparticipating in this study between September2004 and September 2006. To be eligible for thestudy, women were

(i) eligible for genetic testing in Australia [18,19],(ii) able to give informed consent,(iii) able to read English and(iv) aged 18 years or older.

Males considering genetic testing were excludedfrom the study.

Procedure

The human research ethics committee of each clinicapproved the study and informed consent wasobtained from all participants. A randomizedcontrolled trial was used to compare the efficacyof the decision aid with an educational pamphletcurrently used in many clinics in Australia [20]. Thefour-page pamphlet is comparable to the decisionaid in describing hereditary breast/ovarian cancerand the general benefits and risks of genetic tests;however, it does not include characteristic decisionaid features, such as balanced information describ-ing different decision options, patient stories and avalues clarification exercise [21]. Throughout therecruitment process all recruiting clinicians for thestudy participated in bi-monthly teleconferences toaddress any administrative and methodologicalissues for the study and informally discuss theirexperiences recruiting participants and using thedecision aid during their consultations.

Recruitment of participants

Figure 1 presents a flowchart of the recruitmentprocess.Participants were randomized according to

family-wise randomization. That is, all womenwho were the first of their family to attend the

clinic were randomly allocated to the control ordecision aid condition. Subsequent members of thesame family attending the same clinic were thenassigned to the same condition as their other familymembers in order to prevent potential contamina-tion across groups.

Measures

Staff at familial cancer clinics provided the follow-ing data:

(1) Type of genetic test: Clinicians indicatedwhich type of test the woman was considering(mutation search or predictive testing). ‘Mu-tation search’ involves examining the BRCA1and BRCA2 genes for pathogenic mutationsin someone already affected by cancer. If acausative mutation is identified in an affectedfamily member, then other adult at-riskfamily members can be offered a ‘predictive’test to find out whether they carry the family-specific mutation.

(2) Participant’s disease status: Women wereclassified as affected or unaffected by breast/ovarian cancer, and if unaffected, their muta-tion carrier risk (MCR) was given.

At start of the consultation, the clinician invites patientto participate in the study.

Continue with standard care.

Clinician gives patient a randomized opaque envelope, and opens it in front of them.

Patient consentsPatient declines

If the envelope contains the DA,the clinician uses it as acommunication aid during theconsultation.

Some patients decide tohave blood drawn for genetic testing.

Most patients go home to consider their genetictesting decision.

Patients’ can re-read the information materials theyreceived, and complete andreturn questionnaire 1.

Questionnaire 2 is mailed to the patient 6 monthsafter the consultation.

Figure 1. Flowchart detailing the process of care andrecruitment

846 C. E. Wakefield et al.


DOI: 10.1002/pon

(3) Blood drawn: Clinic staff noted whether or notblood was drawn on the day of the firstconsultation.

(4) Participant’s decision: Clinicians reported thegenetic testing decision they felt was the bestchoice for the woman at the end of theconsultation (response options included: ‘Inmy opinion the best choice for this patientwould be to: ‘undergo genetic testing’, ‘notundergo genetic testing’ or ‘defer their deci-sion to a later date’). Concordance betweenclinician opinion and patient’s decision wasrated as a dichotomous variable (‘patient andclinician agreed’ and ‘patient and cliniciandisagreed’ on best decision).

The initial questionnaire for participants elicited:

(1) Demographic characteristics.(2) Reading the materials: Participants were asked

to rate how thoroughly they read the materi-als they received (‘from cover to cover’,‘thoroughly’, ‘briefly’, ‘just the relevant parts’and ‘not at all’).

(3) Decisional conflict: The Decisional ConflictScale (DCS) was used to assess uncertaintyabout choosing among alternatives [22]. Thereare three research versions of the DCS [23].The two traditional forms include 16 itemsand five subscales, however, given the lengthof the study questionnaires, the large numberof participants affected by cancer-relatedillness when completing the survey and themulticultural nature of the women attendingthe clinics, we administered the low literacyversion of the scale. The low literacy versionincludes 10 items and assesses four subscales.These include: the informed subscale (whichassesses perceived knowledge or feeling in-formed about the available options andpotential outcomes of these options); thevalues clarity subscale (which assesses unclearvalues, or being unable to define whichoutcomes are personally important to thedecision maker); the support subscale (whichassesses perceived emotional or practicalsupport from others); and the uncertaintysubscale (which assesses feelings of uncer-tainty about what is the right decision for thedecision maker) [14].

(4) Knowledge of genetic testing: Eight true–falseitems were purposively designed for thisstudy [16].

(5) Multidimensional measure of informed choice:This scale classifies respondents as havingmade an informed or uninformed choice. Aninformed choice is one based on relevantknowledge, consistent with the decision ma-ker’s values and behaviorally implemented[24]. The measure combines the 8-item knowl-

edge test described above, a 4-item attitudesscale and genetic testing decision (1-item). Asdescribed in the scale’s validated scoringinstructions, two groups were classified ashaving made an informed choice: those whoscored above the sample median on theknowledge scale, had a positive attitudetoward testing and decided to undergo testing,and those who had a good knowledge score, anegative attitude toward testing and did notundergo testing. All other women werecategorized as having made an uninformedchoice.

(6) Family involvement: Two ‘yes/no’ items as-sessed whether any other family member readthe information materials given to the patientand whether other family members contrib-uted to their decision-making process. Thosewho responded ‘yes’ were asked to indicate,using Likert-type scales separately for eachfamily member, the extent to which they hadread the materials (‘from cover to cover’through to ‘briefly’), and their level ofinvolvement in the decision-making process(‘extremely involved’ to ‘a little involved’).

(7) Impact of Event Scale (IES): The 15-item IESwas used to measure the frequency andseverity of intrusive and avoidant thoughtsabout being at risk of developing breast and/or ovarian cancer [25,26].

(8) Hospital Anxiety and Depression Scale(HADS): The HADS is a 14-item self-reportscale, which requires respondents to choosebetween four responses that most closelydescribe how they have been feeling in thepast week [27–29].

(9) Genetic testing decision: One item askedparticipants about their decision about genetictesting at this point in time. In order to reducethe demand for potentially sensitive informa-tion from participants, they were not askedabout any genetic testing results they hadreceived.

The second questionnaire collected data onmeasures 2–9 described above, as well as theDecision Regret Scale (DRS): The 5-item DRS

assesses level of health-care decision regret and hasgood internal consistency and validity [30].

Data analysis

Data were analyzed using SPSS 14.0 [31] andSTATA 9.2 [32] and data analysis techniques aredescribed in detail in Wakefield et al. [16]. Briefly,as DCS and regret scores were highly skewed, thesevariables were recoded into binary dichotomousvariables using a median split, with participantsgrouped into ‘low’ and ‘high’ DCS and regretgroups, respectively. Similarly, knowledge was



DOI: 10.1002/pon

recoded into a categorical variable with three levels(low, medium and high knowledge). The reason fortreating the dependent variables as categorical wasthat, apart from being highly skewed, they weremade up of relatively few distinct values, so thatother transformations would not be effective.Observations from the same family were treatedas clusters using the method described by Williams[33]. A Bonferroni adjustment for multiple testswas not employed, as we wanted to control forType 1 error at a 0.05 level of significance for eachdependent variable separately, rather than over alldependent variables considered together. Extensivedata analysis revealed no significant differencesbetween scores for women considering mutationsearch compared with predictive testing on any ofthe dependent variables.The analyses used w2 analyses and binary logistic

regression for dichotomous dependent variables(DCS, informed choice, family involvement andregret) and multinomial logistic regression forknowledge. All regression models were run sepa-rately for each dependent variable, and alwaysincluded time and the clinic the woman attended asfixed factors in the models. The correlationbetween the two observations (one at each time)for each subject was taken into account by treatingthem as a cluster, as for the observations formembers of the same family [33].

Statistical power

With the sample size recruited for this study, wehad 74% power to detect a medium-sized differencein decisional conflict scores between the decisionaid and control groups. The above power calcula-tion assumes a 0.05 significance level and an effectsize of half a standard deviation. This effect size isconsidered to be a medium effect size [34]. Thiseffect size is also considered clinically significant[35] and has been reported in other randomizedcontrolled trials of decision aids [21].

Results

Response rates and sample

Figure 2 presents the composition of the studyparticipants. Briefly, 156 women were invited toparticipate in the study, of whom 148 (95.5%)agreed to participate. Of these, 110 returned thefirst questionnaire (74.3%) and 105 returned thesecond questionnaire (70.9%). Table 1 presentstheir demographic characteristics. There were nosignificant group or clinic differences in neitherdemographic characteristics nor in any of theclinician reported data, indicating that randomiza-tion was successful in spreading potential con-founding variables equally between the groups andacross clinics.

Assessed for eligibility and invited to participate (n=156)

Declined (n=8)Too busy (n=6)Ill health (n=1)Already decided (n=1)

Allocated to control (n=75)Returned Questionnaire 1 (n=55)Did not return Q1 (n=20)

Withdrew before Q1 (n=6)Non-contactable (n=14)

Allocated to intervention (n=73)Returned Questionnaire 1 (n=55) Did not return Q1 (n=18)

Withdrew before Q1 (n=1) Non-contactable (n=17)

Returned Questionnaire 2 (n=56) Did not return Q2 (n=17)

Non-contactable (n=14)Withdrew after Q1 (n=3)

Returned Questionnaire 2 (n=49)Did not return Q2 (n=26)

Non-contactable (n=26)Withdrew after Q1 (n=0)

Randomized

Allocation

Enrolment (n=148)

6 mth follow up

Analysis

Analyzed (n=63)NB: A total of 48 women completedboth Q1 & Q2, 9 completed Q1 onlyand 7 completed Q2 only

Analyzed (n=60) NB: A total of 41 women completedboth Q1 & Q2, 14 completed Q1 onlyand 5 completed Q2 only

Clinic enrolment numbersPrince of Wales Hospital: 63 Westmead Hospital: 16Peter McCallum Cancer Inst: 7 St Vincent’s Hospital: 41Hunter Genetics: 21

Figure 2. Participant flow



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Clinician report

Type of genetic test: Overall, 62.6% of participantswere considering mutation search and 37.4% wereconsidering predictive genetic testing. Of thoseconsidering predictive testing, 76.1% were consid-ering predictive testing after a mutation had beenidentified in their family and 23.9% comprisedother types of predictive testing situations, such aswomen considering screening for founder muta-tions and those considering future predictivetesting in families where a mutation had not yetbeen identified. There were no significant differ-ences between women considering different types ofpredictive testing on any of the dependent vari-ables, so they were combined for further analysis.Participant disease status: Of the 77 participants

(62.6%) who had had a previous diagnosis ofcancer, 69 (89.6%) were affected with breast canceronly, 5 (6.5%) with ovarian cancer only, 2 (2.6%)with both breast and ovarian cancer and 1 (1.3%)with both breast and bowel cancer. Of the 46women who were unaffected by cancer, 36 (76.1%)had a 50% MCR, 7 (15.2%) had a 25% MCR, 1

(2.2%) woman had a 12.5% MCR and 2 (4.3%)had a 100% MCR as they were interveningrelatives.Blood drawn: Blood was drawn immediately after

the first consultation in 36 (29.3%) cases. Havingblood drawn was equally distributed in the studygroups, with 23.4% of women in the decision aidgroup having blood drawn after the consultation,compared with 35.0% of women in the controlgroup (w2(1)5 1.45; P5 0.229).Participant’s decision: In 102 (92.7%) cases, the

clinician’s opinion on the best decision for thepatient agreed with the participant’s decision 1week after the consultation, with only 8 (7.3%)cases in which the clinician’s opinion did not agreewith that of the participant.

Questionnaire 1

Reading the materials

Both the decision aid and the control pamphletwere read thoroughly before completing question-naire 1, with 63.9% of the decision aid group and75.0% of the control group reporting having readthe decision aid or the control pamphlet ‘fromcover to cover’ or ‘quite thoroughly’. These rateswere not significantly different between the groups(w2(5)5 4.65; P5 0.460). How thoroughly womenreported reading the decision aid or controlpamphlet was not related to participants’ decisio-nal conflict full-scale or subscale scores at baseline.However, reported thoroughness of reading thematerials was significantly and positively correlatedwith women’s knowledge scores at baseline, withwomen who reported reading the decision aid andthe control pamphlet more thoroughly being morelikely to have higher knowledge scale scores(r5 0.277, P5 0.04 and r5 0.351, P5 0.01, re-spectively). Women who had blood drawn on theday of their consultation were equally likely to readthe educational materials they received, comparedwith those who did not have blood drawn on theday (w2(5)5 3.01; P5 0.699).

Decisional conflict

All dependent variable mean scores and propor-tions are presented in Table 2.There was no significant difference between DCS

full-scale (w2(1)5 0.45; P5 0.500), Certainty(w2(1)5 1.77; P5 0.184) and supported(w2(1)5 0.17; P5 0.679) subscale scores in womenwho received the decision aid compared with thosewho received the control pamphlet. However,women who received the decision aid were sig-nificantly more likely to be in the ‘Informed’(w2(1)5 8.69; P5 0.003) and ‘Clear Values’(w2(1)5 6.90; P5 0.009) groups than women whoreceived the control pamphlet. There were no

Table 1. Demographic characteristics of participants(N 5 123)

DA group

(n 5 63)

Control group

(n 5 60)

N (%) N (%)

Age Mean: 49.2 years 48.2 years

Range: 24–73 years 22–75 years

Type of genetic test

Mutation search 39 (61.9%) 38 (63.3%)

Predictive testing—

mutation identified

19 (30.2%) 16 (26.7%)

Other predictive testinga 5 (7.9%) 6 (10.0%)

Disease status

Aected by cancer 39 (61.9%) 38 (63.3%)

Unaected by cancer 24 (38.1%) 22 (36.7%)

Education levelb

High school only 22 (34.9%) 20 (33.3%)

Certificate/diploma 16 (25.4%) 20 (33.3%)

Undergraduate degree 13 (20.6%) 9 (15.0%)

Postgraduate degree 12 (19.0%) 11 (18.3%)

Any medical/health train-

ing?

No 46 (73.0%) 43 (71.7%)

Yes 17 (27.0%) 17 (28.3%)

Marital status

Never married 7 (11.1%) 10 (16.7%)

Married/de facto 43 (68.3%) 39 (65%)

Widowed 4 (6.3%) 2 (3.3%)

Separated/divorced 9 (14.3%) 7 (11.7%)

Biological children

No children 18 (28.6%) 18 (30.0%)

Yes 45 (71.4%) 42 (70.0%)

DA 5 Decision aid.aThis group comprises unaffected women considering predictive testing for Jewish

founder mutations or predictive testing where a family-specific mutation has not

yet been identified.bOne participant did not answer the educational level question in the

questionnaire.



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significant interactions between choosing to haveblood drawn on the day of the consultation and theeffect of the decision aid on any of the decisionalconflict full-scale or subscale scores.

Knowledge scores

The main effects model showed that the decisionaid significantly improved knowledge at both timepoints (w2(2)5 6.49; P5 0.039). More specifically,the odds of women who received a decision aidbeing in the high knowledge group (relative to thelow-knowledge group) were more than twice thosefor women in the control group (OR5 2.42;P5 0.016) (see Figure 3). There was no significantinteraction between choosing to have blood drawn

on the day of the consultation and the effect of thedecision aid on knowledge score (w2(2)5 0.69;P5 0.707).

Informed choice

The effect of the decision aid on the measure ofinformed choice was neither significant(w2(1)5 0.01; P5 0.919) nor was there any sig-nificant interaction effect of having blood drawn onthe day of the consultation (w2(1)5 0.01;P5 0.917).

Family involvement

The majority of women reported sharing theinformation materials they received with otherfamily members by 6 months after their consulta-tion (see Table 2). Logistic regression with thedichotomous variable (‘information shared withany family member’ versus ‘not shared with anyfamily member’) showed that women who receiveda decision aid were equally likely to share thematerials they received, relative to women whoreceived the control pamphlet (w2(1)5 0.53;P5 0.389). There was also no significant groupdifference in the level of perceived family involve-ment in decision making (w2(1)5 1.12; P5 0.289).Participants named their spouse or partner most

often as the family member who had read theinformation materials they received and hadcontributed to their decision-making process. Sixmonths after their consultation, 20.9% of womenin the decision aid group and 20.5% of women inthe control group reported that their spouse orpartner had read the information materials theyhad received at their consultation. A noteworthyproportion of participants also reported that theirpartner had contributed to their decision makingabout genetic testing, with 25.6% of women in

Table 2. Dependent variable mean scores and proportions(SD in brackets)

N DA group

Control

group

Knowledge of genetic testing

Time 1 109 7.05 (1.04)� 6.68 (1.30)�

Time 2 105 7.16 (1.06)� 6.63 (1.15)�

Decisional Conflict Scale (DCS)

Time 1 106 1.60 (0.21) 1.69 (0.36)

Time 2 102 1.56 (0.14) 1.62 (0.24)

DCS: Informed Subscale

Time 1 106 1.55 (0.15)� 1.71 (0.44)�

Time 2 102 1.51 (0.68)� 1.65 (0.37)�

DCS: Clear Values Subscale

Time 1 109 1.68 (0.46)� 1.88 (0.66)�

Time 2 104 1.57 (0.26)� 1.71 (0.43)�

DCS: Supported Subscale

Time 1 109 1.59 (0.26) 1.61 (0.37)

Time 2 104 1.56 (0.22) 1.56 (0.24)

DCS: Certainty Subscale

Time 1 107 1.60 (0.33) 1.60 (0.46)

Time 2 102 1.64 (0.41) 1.55 (0.26)

Decisional Regret Scale (DRS) a

Time 2 85 9.78 (14.49) 5.13 (10.16)

Proportional data for dichotomous variables

Multidimensional Measure of In-

formed Choice (MMIC)

Time 1 104 26.4% ‘informed’ 35.3% ‘informed’

Time 2 103 36.4% ‘informed’ 29.2% ‘informed’

Did any family member read the

information materials?

Time 1 109 29.6% ‘yes’� 40.0% ‘yes’�

Time 2 94 52.6% ‘yes’� 54.5% ‘yes’�

Did any family member contri-

bute to decision making?

Time 1 109 46.3% ‘yes’ 65.5% ‘yes’

Time 2 94 52.6% ‘yes’ 45.5% ‘yes’

Genetic testing uptake a

Time 1 102 92.0% ‘yes’ 94.2% ‘yes’

Time 2 101 90.2% ‘yes’ 96.0 % ‘yes’

�Po0.05.aSome women did not answer the Regret Scale or uptake questions because they

either remained undecided about genetic testing, or were awaiting the results of a

relative’s genetic test and were therefore unable to undergo testing at this point.

ControlDecision Aid

Per

cent

100.0%

80.0%

60.0%

40.0%

20.0%

0.0%

High knowledgeMedium knowledgeLow knowledge

Knowledge group

Figure 3. Percentage of women in each of the threeknowledge groups according to their randomization status



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both groups reporting that their partner had beeninvolved in their decision-making process.

Psychological variables

The decision aid did not appear to affect women’sreported levels of psychological distress, with nosignificant group differences in intrusive andavoidant thoughts, anxiety or depression.

Regret

Logistic regression revealed no significant groupdifferences in women’s reported regret about theirgenetic testing decision 6 months after theirconsultation (w2(1)5 0.69; P5 0.406).

Genetic testing uptake

Genetic testing uptake was high, with 94 out of 101(93.1%) participants able to undergo genetictesting after their first consultation deciding toundergo testing. Receipt of the decision aid had noeffect on genetic testing decision (w2(1)5 4.29;P5 0.232).

Clinician feedback

Despite initial enthusiasm for using the decision aidduring their consultations, approximately half ofall recruiting clinicians revealed during the study’sscheduled bimonthly teleconferences that they werereluctant to continue using this implementationstyle at the conclusion of the research study. Theyreported that their main concerns with the decisionaid were that (i) it had the potential to increaseconsultation times; (ii) it ‘stilted’ the consultationand (iii) that given years of experience in the field,some clinicians still preferred to use their ownmethods during their consultations.

Discussion

This randomized trial revealed three significanteffects of a decision aid for women consideringgenetic testing for breast/ovarian cancer risk. Usedduring genetic counseling, women who received thedecision aid felt more informed and had clearervalues (as assessed using the DCS) and hadsignificantly higher knowledge scores than womenwho received the control pamphlet. These resultsare consistent with many previous reports ofdecision aid effectiveness in which knowledge andthe same two subscales of the DCS (feelinginformed and clear values) are most likely to bebeneficially affected by administration of a decisionaid [21]. As has been reported previously [16], thefamily member most likely to be named as havingread the materials given to the participant during

their consultation and having contributed to thegenetic testing decision-making process was theparticipant’s spouse or partner. These data againemphasize the importance of considering thespouse within the familial cancer setting, eventhough they are not blood relatives of the patient[36,37].Consistent with previous research, there was

neither evidence of an effect of the decision aid onwomen’s psychological functioning, genetic testingdecisions, scores of informed choice nor theirscores on the certainty and feeling supportedsubscales of the DCS [21, 38]. With regards to thelack of significance of the informed choice measure,the results may have been affected by ceiling effects,in that most participants had high knowledge levelsat baseline, and more than 90% of participantschose to undergo genetic testing after counseling.The scoring rules for this scale require a mediansplit for knowledge, such that 50% of participantsare categorized as having poor knowledge, despiteoften relatively high knowledge scores. If they thenchose to undergo genetic testing (as the largemajority did), they were categorized as havingmade an uninformed choice, despite obtainingrelatively high knowledge scores. This measure-ment issue is discussed in more detail in Rowe et al.[39] and Kasparian et al. [40].With regards to the timing and method of

decision aid use, our findings show that using thedecision aid during genetic counseling, rather thansimply giving it to women to take home after theirconsultation, may be a more effective means ofassisting women to clarify their values with regardsto genetic testing for cancer risk. Although both ouroriginal trial (in which women were given thedecision aid at the end of the consultation) and thecurrent trial (in which clinicians used the decisionaid during the consultation) showed that thedecision aid improved knowledge and the numbersof women feeling informed about genetic testing,this current trial showed that using the decision aidduring the consultation also significantly improvedthe numbers of women reporting that they hadclearer values when it came to the genetic testingdecision. This finding may reflect the women’sincreased exposure to the decision aid, as well as thefact that all women in this trial were exposed to thedecision aid before having blood drawn for testing.As well, it is possible that having a clinician workthrough the decision aid during the consultationimplied a stronger endorsement of the decision aidby the clinician and thereby elevated its perceivedrelevance and importance with women. Unfortu-nately, the current study design did not allow directcomparisons between the results of the two trials.Future research comparing implementation styleswithin the one study would be valuable to provide astronger evidence base as to the optimum timingand method of decision aid use in this context.



DOI: 10.1002/pon

Finally, clinicians’ reluctance to use the decisionaid during their consultations warrants furtherdiscussion. Other evidence also suggests thatclinicians may indeed resist using decision aids intheir everyday practice, and that extensive trainingof health professionals in the use of decision aids iscritical for them to be able integrate decision aidsinto routine practice. For example, O’Cathain andThomas reported similar clinician reluctance whenevaluating decision aids in the maternity caresetting, despite reporting that they approved ofthe decision aids before the commencement of thetrial [17]. Similarly, O’Donnell et al. listed thefollowing possible clinician-related barriers todecision aid implementation: lack of clinicianawareness, lack of knowledge and skills in the useof decision aids and a perceived lack of suitabilityof decision aids to meet the needs of participantswith diverse needs [41]. In addition, there areorganizational barriers to decision aid implementa-tion, including the organization’s culture andpriorities, structural issues that make it difficult toincorporate decision aids into the workflow, andthe costs of purchasing and updating decision aids[41]. Given the disparity between positive evalua-tions of decision aids by consumers [16] andpublished [17,42] and anecdotal reports that ourexperiences of clinician reluctance are not unusual,research into how to successfully implement deci-sion aids in a real-world setting is urgently needed.Previous researchers have recommended adopt-

ing a flexible approach to decision aid use in orderto increase overall use of tools that have consumedmany resources in their development, as well asthorough training and support of clinicians usingthe tools in the clinical setting [17,43]. Silvia andSepucha [42] also recommend integrating thedecision aids into the flow of patients throughclinics and having informed clinicians who recom-mend the decision aid directly to patients [42]. Thedecision aid developed for this trial has now beendistributed for general use in some clinics inAustralia, and these clinics are collecting basicdata on the numbers of decision aids distributed,and to whom, and how they are being used. It ishoped that by collecting a small amount of data onimplementation in the clinic setting, we mightobtain some data as to the extent of the potentiallylimiting factors in the usefulness of decision aids.The limitations of this study include (i) baseline

(i.e. precounseling) data collection was not possiblebecause eligibility for genetic testing in Australia istypically only determined during a patient’s firstconsultation at a clinic (however, given that theparticipants were randomized, any precounselingcharacteristics in patients should have been evenlydistributed across both groups), (ii) clinicians werenot blinded to the randomization status of theparticipants because the decision aid was usedduring the clinic consultation, (iii) women in this

study tended to have a higher education level thanthe general population, with 67% having a post-school qualification, compared with 52% of thegeneral population [44]. Finally, clinicians wereallowed to informally discuss their experiences usingthe decision aid during the trial and this may havemodified and biased the results of the ongoing study.This situation was difficult to avoid in a small andtight-knit medical community such as the Australianfamilial cancer clinics, so we instead chose to beinvolved in, and monitor, these discussions. Furtherstudies would benefit from encouraging clinicians tonot discuss their experiences in the trial until datacollection has been completed.To conclude, this study showed a clear benefit

for using a decision aid to assist women consider-ing genetic testing for breast/ovarian cancer riskduring genetic counseling. However, barriers todecision aid implementation need to be overcomeusing a flexible approach and we therefore suggestthat clinicians adopt the implementation style thatbest suits their own implementation style prefer-ence, the needs of the individual patient and theconstraints of the familial cancer clinic in whichthey work.

Acknowledgements

We would like to thank all the women who completed thequestionnaires for this study. We would also like to thankour consumer representative, Sandra Tanner, as well as eachof the clinicians who reviewed numerous drafts of thedecision aids and recruited their patients. The study wasfunded by a project grant from The Cancer Council of NewSouth Wales (Project Grant 300441). Claire Wakefield issupported by an Australian Postgraduate Award. BettinaMeiser is supported by a career development award from theNational Health and Medical Research Council of Australia(ID 350989). The authors have no conflicts of interest todeclare.

AGenDA Collaborative Group

The additional members of the Australian GENetic testingDecision Aid Collaborative Group are in alphabetical orderof group or institution: Centre for Genetics Education,Sydney (K. Barlow-Stewart); Familial Cancer Service,Westmead Hospital, Sydney (G. Fenton, A. Goodwin, J.Kirk, P. Zodgekar); Hereditary Cancer Clinic, Prince ofWales Hospital, Sydney (L. Andrews, J. Koehler, A.Overkov, M. Peate, J. Tyler, B. Warner); Hunter Genetics,Newcastle (T. Dudding, C. Groombridge, S. O’Donnell, A.Spigelman); Macquarie University (C. McMahon); PeterMcCallum Cancer Institute, Melbourne (L. Hossack, M.Kentwell, M. Young); Royal Melbourne Hospital, Mel-bourne (C. Aragona, R. D’Souza, C. Gaff, L. Hodgkin); StVincent’s Hospital, Sydney (R. Ward), University of Sydney(P. Butow, E. Lobb).

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A randomized trial of a breast/ovarian cancer genetic testing decision aid used as a communication aid during genetic counseling