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The Choice Project: Peer Workers Promoting Shared Decision Making at a Youth Mental Health Service

Abstract

Objective:

In youth mental health services, consumer participation is essential, but few implementation strategies exist to engage young consumers. This project evaluated an intervention implemented in an Australian youth mental health service that utilized peer workers to promote shared decision making via an online tool.

Methods:

All new clients ages 16–25 were invited to participate in this nonrandomized comparative study, which used a historical comparison group (N=80). Intervention participants (N=149) engaged with a peer worker and used the online tool before and during their intake assessment. Pre- and postintake data were collected for both groups; measures included decisional conflict, perceived shared decision making, and satisfaction. A series of paired t tests, analyses of variance, and multiple regressions were conducted to assess differences in scores across intervention and comparison groups and pre- and postintake assessments.

Results:

Ratings of perceived shared decision making with intake workers were higher in the intervention group than in the comparison group (p=.015). In both groups, decisional conflict scores were significantly lower after the intake assessment (p<.001 for both groups). Both perceived shared decision making and lower decisional conflict were associated with satisfaction (p<.015).

Conclusions:

Young people who participated in an intervention that combined peer work and shared decision making reported feeling more involved in their assessment. Feeling involved and having lower decisional conflict after seeing an intake worker were important for client satisfaction. These findings demonstrate the importance of both peer work and shared decision making for promoting optimal outcomes in youth mental health services.

Providing optimal care for young people with mental illness is essential given the prevalence and impact of mental disorders in this age group. Most mental disorders begin between the ages of 12 and 24, although help seeking is poor among young people, and those who visit a provider often do not stay long enough to receive adequate care (1). Working together with young people to understand and address these gaps is critical (2).

Over the past 20 years, consumer participation in mental health services has been recognized as essential for both service providers and consumers. Although several local and international strategies have been developed to promote consumer participation among recipients of adult mental health services (38), few strategies exist in youth mental health services (9,10).

The World Health Organization (11) and the United Nations (12) have both stipulated that young people have the right to make informed health care decisions. There is a clear responsibility to explore individual needs, values, and preferences for young people who seek care from mental health services. In addition to the emphasis on youth participation in service development and provision, there is also recent interest in strategies that promote the involvement of all clients in making decisions about their care (1317). The most commonly suggested strategy is shared decision making (SDM), a collaborative approach to treatment decision making that incorporates evidence-based practices and client preferences and values (18,19).

Despite the appeal of SDM, studies in general practice and adult mental health services demonstrate relatively low levels of SDM (2022). To date, trials of SDM interventions for mental health have been conducted among adults (4,2326) and among children for whom adults (for example, parents) are the decision makers (27). Although the results are promising, these interventions tend to support a specific treatment decision (for example, treatment for schizophrenia). Two interventions have taken a broader approach and can be used for any decision, regardless of presenting problem (26,28,29). One of these, CommonGround, is used in mental health clinics and inpatient settings. Based on the recovery model, CommonGround employs peer workers to help clients use an online decision support tool in the waiting room (28). This tool allows clients to explore their preferences and values in relation to treatment options, and a report is prepared and taken into the time-limited session with their clinician. In clinics that use this SDM tool, clients arrive 30 minutes before their appointment with the clinician and are invited by peer workers to use the tool. Following the consultation, peer workers are available for further support. The tool helps clients convey complex information in a report that can be quickly reviewed by clinicians. This program has been implemented in both adult and young adult settings (29).

This novel combination of SDM and peer work is yet to be tested in younger populations, such as adolescents. Peer work among young people needs to consider developmental stage, social and educational factors, and stage of mental illness when relevant. A small number of youth participation models have been described, and the models highlight facilitators and barriers to youth involvement in the context of delivering peer-led decision support. Monson and Thurley (30) described a youth peer work service largely driven by young people themselves. Peer workers are former clients of a specialized youth mental health service, who use their lived experience of mental illness to promote recovery for current clients of the service. One barrier related to the use of peer-led electronic decision support is the lack of availability of online tools, even though clinicians and clients want to use technology in youth mental health care (31).

To investigate the usefulness of peer work and SDM with online decision support tools in a youth mental health setting, we took the basic principles of CommonGround (delivered by peer workers and completed in waiting rooms, with a report taken into clinical session and a focus on promoting SDM) and applied this to youth mental health care. The Choices About Healthcare Options Informed by Clients Experiences and Expectations Project (Choice Project) employed youth peer workers to support other young people to make informed decisions about treatment options. The purpose of this study was to evaluate this intervention, which included an online tool codesigned with peer workers to facilitate SDM.

Methods

Setting

The study took place at a youth mental health service in New South Wales, Australia, known as headspace Gosford. Young people ages 12–25 are assessed by the triage team—the Youth Access Team (YAT)—which is staffed by allied health professionals. A revised version of the HEADSS assessment instrument (Home, Education, Activities, Drug use and abuse, Sexual behavior, Suicidality and depression) (32) is used to determine client needs and the most appropriate treatment. Treatment options at the time of the study included one-on-one counseling with a clinical psychologist; an appointment with a general practitioner or nurse; a counseling service for cannabis use; a general support service, including housing assistance; a vocational support service; and a welfare service.

Intervention

The intervention has been described in detail elsewhere (Simmons MB, Coates D, Batchelor S, et al., unpublished manuscript, 2017). In summary, peer workers welcome clients before their appointment with the YAT. Peer workers use an online decision support tool delivered via electronic tablet (an iPad). The tool provides decision support based on the Ottawa decision support framework (33) and was designed in line with the International Patient Decision Aid Standards (34); however, the tool is not a traditional decision aid because it does not address a specific decision or disorder. Peer workers were involved in codesigning the tool to ensure quality, usefulness, and acceptability. [More information on the intervention is provided in an online supplement to this article.]

Peer workers use the tool with clients in the waiting room before their appointment with a YAT clinician. Clients complete the “What matters to you?” section, which explores their needs and preferences. A report based on this information is generated for the YAT clinician to view at the start of the appointment. The tool is also available for use during the appointment, with a section on treatment options (“What are my choices?”) to be discussed at the end of the session after the standard HEADSS assessment. The treatment options are described briefly in the tool and are complemented with three key questions that promote an SDM approach to treatment: “What are my options?” “What are the possible benefits and harms of those options?” “How likely are each of those benefits and harms to happen to me?” (35). After the appointment, clients can see a peer worker for further support.

Participants

Young people ages 16–25 years attending headspace Gosford for an appointment with the YAT were invited to participate in the study.

Outcome Measures

Before and after their assessment with the YAT clinician, participants completed the Decisional Conflict Scale (36), a self-report measure that assesses the degree to which a person is conflicted about a decision that he or she faces. Higher scores reflect higher decisional conflict, an undesirable outcome. After the assessment with the YAT clinician, participants completed the nine-item Shared Decision Making Questionnaire (37) and four items from the headspace Service Satisfaction Survey (38). Higher scores on these two instruments reflect higher perceived SDM and satisfaction, respectively. The nine-item Shared Decision Making Questionnaire was administered once to the comparison group (with reference to the YAT clinician only) and twice to the intervention group (with reference to the YAT clinician and the peer worker) to measure the level of perceived SDM. Participants were asked to cite one or more reasons that they were attending headspace Gosford. Six options were available, with an additional “other” option.

Design

To evaluate the intervention, a historical comparison group design was used. During the 26-week period between January 8 and June 23, 2014, all clients ages 16–25 attending headspace Gosford to see a YAT clinician (that is, for an initial assessment) were invited to complete study measures before and after this assessment. No additional interventions were used during this time, and YAT assessments were completed as usual. This group is referred to as the comparison group. Between June 24 and December 1, 2014, peer workers began to work at headspace Gosford and invited clients to use the SDM tool and complete the study measures. This group is referred to as the intervention group. Informed consent was obtained from all participants, and this study was approved by the New South Wales Human Research Ethics Committee (LNR/13/HNE/346).

Statistical Analysis

We present frequencies and percentages of responses to binary variables and means, standard deviations, and nonparametric statistics for continuous outcomes. One-way analyses of variance (ANOVAs) were used to compare demographic variables. Paired t tests were used to test for change in continuous outcomes over time within the intervention group; repeated-measures analysis of covariance tested for change in continuous outcomes over time between the comparison and intervention groups. A multiple linear regression tested for factors that were associated with a continuous outcome. When significant differences were found, effect sizes (Cohen's d, η2, and Cohen’s f2) were calculated to assess the magnitude of the difference between groups. Statistical analyses were conducted with IBM SPSS Statistics, version 22.0 (39).

Results

Participants

In total, 229 young people participated in the study, with 80 participants in the comparison group and 149 in the intervention group, although response rates for each measure varied. The groups did not differ significantly in age, gender, or reasons for coming to headspace (Table 1).

TABLE 1. Age, gender, and reason for attendance among participants in the comparison and intervention groupsa

Comparison (N=79)bIntervention (N=145)b
VariableN%N%
Age (M±SD)18.36±2.5117.83±2.89
Gender
 Female44569263
 Male35445337
Reason for attendancec
 Problems with how I feel698612987
 Problems with relationships34428255
 Problems at school or work26325336
 Problems with alcohol or other drugs17212517
 Problems with my physical health16202819
 Vocational assistance911117
 Otherd101396

aMeans were compared by t tests, and proportions were compared by chi-square tests. No significant between-group differences were found.

bSample sizes reflect missing data for the group.

cParticipants could endorse more than one reason.

dIn the comparison group, seven participants listed one “other” reason, and three participants listed two. In the intervention group, nine participants listed one “other” reason.

TABLE 1. Age, gender, and reason for attendance among participants in the comparison and intervention groupsa

Enlarge table

Perceived SDM

Participants’ scores on the Shared Decision Making Questionnaire for the YAT clinician were significantly higher in the intervention group than in the comparison group (p=.015). For individual SDM items, scores were significantly higher in the intervention group on four of the nine items (Table 2).

TABLE 2. Ratings of involvement in decision making with the Youth Access Team (YAT) clinician by all participants and with the YAT peer worker (PW) by intervention group participants

Rating for YAT clinician
Intervention group (N=78)aComparison group (N=61)aIntervention group rating for PW (N=78)a
Item from SDMQ-9bMSDMSDpMSDpc
[YAT/PW] made it clear that a decision needs to be made about getting help4.47.714.33.79.2514.40.86.330
[YAT/PW] wanted to know exactly how I want to be involved in making the decision4.56.594.13.83.0014.36.83.006
[YAT/PW] told me that there are different options for getting help4.52.704.34.81.1554.39.92.083
[YAT/PW] precisely explained the advantages and disadvantages of the options4.42.764.07.91.0124.23.94.031
[YAT/PW] helped me understand all the information4.55.684.36.75.1214.44.77.105
[YAT/PW] asked me which option I prefer4.50.704.30.86.1184.37.94.107
[YAT/PW] and I thoroughly weighed up the pros and cons of the different options4.39.803.971.0.0064.181.03.017
[YAT/PW] and I selected an option together4.43.824.08.99.0234.121.17.007
[YAT/PW] and I reached an agreement on how to proceed4.55.684.39.78.1924.211.12.002
Total SDMQ-9 score40.325.2237.975.98.01538.817.41.015

aSample sizes reflect missing data for the group.

bInvolvement in decision making was measured with the nine-item Shared Decision Making Questionnaire (SDMQ-9). Possible item scores range from 1 to 6 (total possible score of 54), with higher scores indicating higher perceived involvement in decision making.

cThe p values in this column are for intervention group differences between ratings for the YAT clinician and the PW.

TABLE 2. Ratings of involvement in decision making with the Youth Access Team (YAT) clinician by all participants and with the YAT peer worker (PW) by intervention group participants

Enlarge table

In the intervention group, SDM ratings were significantly higher for the YAT clinician than for the peer worker (p=.015). Significantly higher ratings for the YAT clinician were observed on five of the nine items (Table 2).

Decisional Conflict

Across both groups, a significant decrease in decisional conflict was observed from before the YAT assessment to after the assessment, with significant changes observed on each of the decisional conflict subscales (Table 3). However, no difference in the decrease of decisional conflict scores was observed between the intervention and comparison groups.

TABLE 3. Scores on the Decisional Conflict Scale for the comparison and intervention groups before and after assessment by the Youth Access Team cliniciana

Comparison group (N=63)bIntervention group (N=82)b
PreassessmentPostassessmentPreassessmentPostassessment
SubscaleMSDMSDpMSDMSDp
Uncertainty 48.8123.0127.2423.01<.00144.0425.5224.5519.82<.001
Informed 41.5620.8421.2115.96<.00137.3221.8418.1215.99<.001
Values clarity 41.6720.6022.5117.65<.00137.8622.9820.2517.48<.001
Support 37.3917.9219.5316.51<.00132.8619.8717.3015.34<.001
Effective decision 37.0819.0722.3517.23<.00135.3019.6320.2616.09<.001
Total score40.9916.6222.0015.52<.00135.2118.5719.3014.53<.001

aPossible scores range from 0 to 100, with higher scores indicating higher decisional conflict (an unwanted outcome).

bSample sizes reflect missing data in each group.

TABLE 3. Scores on the Decisional Conflict Scale for the comparison and intervention groups before and after assessment by the Youth Access Team cliniciana

Enlarge table

Satisfaction

Overall, both the comparison and intervention groups reported high satisfaction levels, and no participant endorsed “disagree” or “strongly disagree” on any of the individual items (Table 4). For the comparison group, the total score (sum for the four individual items) ranged from 5 to 20 (maximum possible score of 20), with a mean score of 18.07±2.61. For the intervention group, the total score ranged from 15 to 20, with a mean score of 18.56±1.76. No significant between-group differences were found in satisfaction levels (Table 4).

TABLE 4. Scores on the Service Satisfaction Scale for the comparison and intervention groupsa

Comparison group (N=61)bIntervention group (N=84)b
ItemMSDMSD
I was given enough information about headspace4.56.594.65.50
I got help for the things I wanted to get help with4.40.694.50.63
I was generally satisfied with headspace4.61.584.67.50
If a friend needed this sort of help, I would suggest headspace4.72.554.74.44

aPossible scores on each item range from 1 to 5, with higher scores indicating higher levels of satisfaction. No significant between-group differences were found.

bSample sizes reflect missing data in each group.

TABLE 4. Scores on the Service Satisfaction Scale for the comparison and intervention groupsa

Enlarge table

Factors Associated With Satisfaction

A model for measuring associations with satisfaction (total satisfaction score) was developed by using the level of SDM (total score on the nine-item Shared Decision Making Questionnaire) and the level of decisional conflict (total score on the Decisional Conflict Scale after intake appointment with YAT clinician). The final model was statistically significant (F=14.21, df=2 and 71, p<.015, R2=.286, f2=.40), with results indicating that higher SDM scores (β=.333, t=2.86, df=130, p=.006) and lower postassessment decisional conflict (β=–.295, t=−2.54, df=130, p=.013) were significantly associated with higher satisfaction.

Discussion

This study demonstrated the feasibility of implementing a peer worker intervention promoting SDM in a youth mental health setting. Clients actively engaged in the intervention, demonstrating a willingness to connect with peers in this setting. Clients in the intervention group reported feeling more involved than those in the comparison group in making treatment decisions with their YAT clinician, although the magnitude of the effect was small. However, this finding is of critical importance to services that seek to promote client-centered care, as well as to youth mental health services in general, where help seeking and clinical engagement are significant barriers to timely treatment of mental illness (40).

In the intervention group, clients felt significantly more involved with their YAT clinician than with their peer worker in making decisions about treatment. Given that clients make treatment decisions with the YAT clinician rather than with the peer worker, this finding supports the proposition that peer work, SDM, or the combination of peer work and SDM result in clients’ feeling more involved in treatment decision making with their clinician. The role of the peer worker was to focus on promoting involvement and engagement in the service, and thus it was possible for clients to feel just as involved, or more involved, with peer workers and to have blurred perceptions of the roles of peer workers and clinicians. Had clients in the intervention group felt equally as involved in treatment decision making with peer workers as they had with YAT clinicians, uncertainty would remain about whether clients merely felt more involved in the service in general rather than at the critical point when decisions about treatment are made. However, it is also possible that peer workers primed clients to feel more involved by promoting SDM through both the tool and motivational support directly before their appointment with the YAT clinician.

Clients in both the comparison and the intervention groups were highly satisfied with their care, and no difference in satisfaction was found, possibly because of either a ceiling effect or the fact that only four items measured client satisfaction. A validated measure of client satisfaction specifically designed for youth mental health services has since been developed based on the items used in the current study, and the full version should be considered for future studies (38,41). Similarly, both groups experienced a significant reduction in decisional conflict after their appointment with the YAT clinician, and no differences in this reduction were found between the groups. However, regression analysis showed the importance for client satisfaction of both perceived involvement in decision making and lower decisional conflict directly after the decision assessment, which represented a small-medium effect. This finding highlights the importance of interventions that promote SDM and focus on increasing client satisfaction, such as by use of decision support tools.

These findings add to the growing fields of SDM and peer work in mental health, which have largely omitted young people. The intervention resulted in clients feeling more involved in making decisions, which is consistent with SDM interventions for adults diagnosed as having depression (42,43) and schizophrenia (4,44). However, studies in adult populations have also demonstrated effectiveness in terms of reducing decisional conflict (42,45,46), increasing client satisfaction (42,43,47), and improving knowledge (an outcome that we did not examine in this study because of the diversity of treatment decisions that we were seeking to support) (4,42). Most important, this study demonstrated that the combination of peer work and SDM can play an important role in a youth mental health service with a focus on early intervention, as it has in adult medication clinics for individuals with severe mental illness (26,28,29).

This study also contributes to the understanding of how technology can be used in youth mental health services. Both young people (48) and clinicians (49) are enthusiastic about the use of technology to promote mental health and well-being; however, there are few well-tested tools for this purpose, particularly tools for use in the clinical consultation (31). With the increased use of smartphone technology, mental health clinicians need evidence-based Web sites and applications to fully engage digitally connected young people and maximize the chances of providing appropriate treatment in a timely manner (50).

The study had several limitations. The design was not randomized; funding limitations precluded our undertaking a large cluster randomized or stepped-wedge randomized trial. More clients in the intervention group than in the comparison group participated in the evaluation component, and there were missing data for several measures. It is likely that the presence of peer workers made the service more welcoming and that clients were less likely to participate in the research if asked by reception staff, with whom they may not have built a relationship. This was the first large research study at headspace Gosford, and data collection procedures became more refined during the intervention period. Also, it was not possible to tease apart the impacts of the two main components of the intervention—SDM and peer work. Finally, there was no formal measure of fidelity to ensure that the decision support tool was used in full or that it facilitated SDM as measured by audio-recording sessions or by use of an observed rating scale (51).

A considerable strength of the study was the real-world nature of the design, which showed that the intervention can be readily adapted by other services. In addition, both the peer work roles and online tool were codesigned with young people, ensuring acceptability and integrity.

Future research should focus on the adaptation and effectiveness of a combined SDM and peer work intervention for tertiary youth mental health services, where the effects are likely to be more profound. It is also vital to better understand the mechanisms by which SDM interventions lead to improved outcomes. Determining the role of mediating and moderating factors related to more positive experiences of services, better engagement, and improved clinical outcomes will help define the role that SDM and peer work can play in youth mental health services. By involving young people in multiple ways, it may be possible to promote help-seeking behaviors and clinical engagement thereby improving outcomes for young people.

Conclusions

This study demonstrated that involving young people in youth mental health services with peer workers and SDM was feasible and led to participants’ reports of feeling more involved in making decisions about their care. Interventions that target perceived involvement and reduction in conflict about treatment decisions are likely to improve client satisfaction with care.

Dr. Simmons is with Orygen, the National Centre of Excellence in Youth Mental Health, and with the Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia. Ms. Batchelor, Ms. Dimopoulos-Bick, and Ms. Howe are with Children and Young People's Mental Health and with headspace Gosford, Gosford, New South Wales, Australia.
Send correspondence to Dr. Simmons (e-mail: ).

This study was funded by a Service Innovation Project from the Department of Health and Aging through headspace, the National Youth Mental Health Foundation.

The authors report no financial relationships with commercial interests.

The authors acknowledge the following peer workers who codesigned and rolled out this combined intervention: Georgia Coomber, Darcy Cosgrove, Andrew Lawler, Joel Makings, Sarana Schultz, Max Simensen, Eleanor Skinner, and Caitlin Turner. They also acknowledge the staff of headspace Gosford and of Children and Young People’s Mental Health, particularly clinicians, mentors, and others closely involved in the project. They thank Daveena Mawren, B.Psych., M.H.Stats., for statistical advice and Nicholas Fava, B.App.Sci., G.Dip.Psych., for comments on a draft of this article.

References

1 Rickwood DJ, Deane FP, Wilson CJ: When and how do young people seek professional help for mental health problems? Medical Journal of Australia 187(suppl):S35–S39, 2007Crossref, MedlineGoogle Scholar

2 Coates D, Howe D: The importance and benefits of youth participation in mental health settings from the perspective of the headspace Gosford Youth Alliance in Australia. Children and Youth Services Review 46:294–299, 2014CrossrefGoogle Scholar

3 Mental Health: A Report of the Surgeon General. Rockville, MD, US Department of Health and Human Services, US Public Health Service, 1999Google Scholar

4 Hamann J, Langer B, Winkler V, et al.: Shared decision making for in-patients with schizophrenia. Acta Psychiatrica Scandinavica 114:265–273, 2006Crossref, MedlineGoogle Scholar

5 Australian Charter of Healthcare Rights. Canberra, Australian Commission on Safety and Quality in Health Care, 2008Google Scholar

6 Doing It With Us Not for Us. Victoria, Australia, Department of Health, Rural and Regional Health and Aged Care Services Division, 2009Google Scholar

7 National Standards for Mental Health Services, 2010. Canberra, Australian Government Department of Health and Ageing, 2010Google Scholar

8 Institute of Medicine: Improving the Quality of Health Care for Mental and Substance-Use Conditions. Washington, DC, National Academies Press, 2006. http://www.iom.edu/Reports/2005/Improving-the-Quality-of-Health-Care-for-Mental-and-Substance-Use-Conditions-Quality-Chasm-Series.aspxGoogle Scholar

9 Howe D, Batchelor S, Bochynska K: Finding our way: youth participation in the development and promotion of youth mental health services on the NSW Central Coast. Advances in Mental Health 10:20–28, 2011CrossrefGoogle Scholar

10 James AM: Principles of youth participation in mental health services. Medical Journal of Australia 187(suppl):S57–S60, 2007MedlineGoogle Scholar

11 Making Health Services Adolescent Friendly: Developing National Quality Standards for Adolescent-Friendly Health Services. Geneva, World Health Organization, Department of Maternal, Newborn, Child and Adolescent Health, 2012Google Scholar

12 Convention on the Rights of the Child. New York, UNICEF, 2014. http://www.unicef.org/crcGoogle Scholar

13 Crickard EL, O’Brien MS, Rapp CA, et al.: Developing a framework to support shared decision making for youth mental health medication treatment. Community Mental Health Journal 46:474–481, 2010Crossref, MedlineGoogle Scholar

14 Hetrick S, Simmons M, Merry S: SSRIs and depression in children and adolescents: the imperative for shared decision-making. Australasian Psychiatry 16:354–358, 2008Crossref, MedlineGoogle Scholar

15 O’Brien MS, Crickard EL, Rapp CA, et al.: Critical issues for psychiatric medication shared decision making with youth and families. Families in Society 92:310–316, 2011CrossrefGoogle Scholar

16 Simmons M, Hetrick S, Jorm A: Shared decision-making: benefits, barriers and current opportunities for application. Australasian Psychiatry 18:394–397, 2010Crossref, MedlineGoogle Scholar

17 Simmons MB, Hetrick SE, Jorm AF: Experiences of treatment decision making for young people diagnosed with depressive disorders: a qualitative study in primary care and specialist mental health settings. BMC Psychiatry 11:194, 2011Crossref, MedlineGoogle Scholar

18 Deegan PE, Drake RE: Shared decision making and medication management in the recovery process. Psychiatric Services 57:1636–1639, 2006LinkGoogle Scholar

19 Hoffmann TC, Del Mar CB: Shared decision making: what do clinicians need to know and why should they bother? Medical Journal of Australia 201:513–514, 2014Crossref, MedlineGoogle Scholar

20 Goossensen A, Zijlstra P, Koopmanschap M: Measuring shared decision making processes in psychiatry: skills versus patient satisfaction. Patient Education and Counseling 67:50–56, 2007Crossref, MedlineGoogle Scholar

21 Goss C, Fontanesi S, Mazzi MA, et al.: Shared decision making: the reliability of the OPTION scale in Italy. Patient Education and Counseling 66:296–302, 2007Crossref, MedlineGoogle Scholar

22 Loh A, Simon D, Hennig K, et al.: The assessment of depressive patients’ involvement in decision making in audio-taped primary care consultations. Patient Education and Counseling 63:314–318, 2006Crossref, MedlineGoogle Scholar

23 Hamann J, Cohen R, Leucht S, et al.: Shared decision making and long-term outcome in schizophrenia treatment. Journal of Clinical Psychiatry 68:992–997, 2007Crossref, MedlineGoogle Scholar

24 Joosten EA, de Jong CA, de Weert-van Oene GH, et al.: Shared decision-making reduces drug use and psychiatric severity in substance-dependent patients. Psychotherapy and Psychosomatics 78:245–253, 2009Crossref, MedlineGoogle Scholar

25 Loh A, Simon D, Wills CE, et al.: The effects of a shared decision-making intervention in primary care of depression: a cluster-randomized controlled trial. Patient Education and Counseling 67:324–332, 2007Crossref, MedlineGoogle Scholar

26 Woltmann EM, Wilkniss SM, Teachout A, et al.: Trial of an electronic decision support system to facilitate shared decision making in community mental health. Psychiatric Services 62:54–60, 2011LinkGoogle Scholar

27 Brinkman WB, Hartl Majcher J, Poling LM, et al.: Shared decision-making to improve attention-deficit hyperactivity disorder care. Patient Education and Counseling 93:95–101, 2013Crossref, MedlineGoogle Scholar

28 Deegan PE: A Web application to support recovery and shared decision making in psychiatric medication clinics. Psychiatric Rehabilitation Journal 34:23–28, 2010Crossref, MedlineGoogle Scholar

29 Deegan PE, Rapp C, Holter M, et al.: A program to support shared decision making in an outpatient psychiatric medication clinic. Psychiatric Services 59:603–605, 2008LinkGoogle Scholar

30 Monson K, Thurley M: Consumer participation in a youth mental health service. Early Intervention in Psychiatry 5:381–388, 2011Crossref, MedlineGoogle Scholar

31 Montague AE, Varcin KJ, Parker AG: Putting Technology Into Practice: Evidence and Opinions on Integrating Technology With Youth Health Services. Melbourne, Young and Well Cooperative Research Centre, 2014Google Scholar

32 Parker AG, Hetrick SE, Purcell R: Psychosocial assessment of young people: refining and evaluating a youth friendly assessment interview. Australian Family Physician 39:585–588, 2010MedlineGoogle Scholar

33 O’Connor AM, Tugwell P, Wells GA, et al.: A decision aid for women considering hormone therapy after menopause: decision support framework and evaluation. Patient Education and Counseling 33:267–279, 1998Crossref, MedlineGoogle Scholar

34 Elwyn G, O’Connor A, Stacey D, et al.: Developing a quality criteria framework for patient decision aids: online international Delphi consensus process. BMJ 333:417, 2006Crossref, MedlineGoogle Scholar

35 Shepherd HL, Barratt A, Trevena LJ, et al.: Three questions that patients can ask to improve the quality of information physicians give about treatment options: a cross-over trial. Patient Education and Counseling 84:379–385, 2011Crossref, MedlineGoogle Scholar

36 O’Connor AM: Validation of a decisional conflict scale. Medical Decision Making 15:25–30, 1995Crossref, MedlineGoogle Scholar

37 Kriston L, Scholl I, Hölzel L, et al.: The 9-item Shared Decision Making Questionnaire (SDM-Q-9). Development and psychometric properties in a primary care sample. Patient Education and Counseling 80:94–99, 2010Crossref, MedlineGoogle Scholar

38 Rickwood D, Nicholas A, Mazzer K, et al.: Satisfaction with youth mental health services: further scale development and findings from headspace—Australia's National Youth Mental Health Foundation. Early Intervention in Psychiatry (Epub ahead of print May 21, 2015)CrossrefGoogle Scholar

39 IBM SPSS Statistics for Macintosh, 22.0 ed. Armonk, NY, IBM Corp, 2013Google Scholar

40 Patel V, Flisher AJ, Hetrick S, et al.: Mental health of young people: a global public-health challenge. Lancet 369:1302–1313, 2007Crossref, MedlineGoogle Scholar

41 Simmons MB, Parker AG, Hetrick SE, et al.: Development of a satisfaction scale for young people attending youth mental health services. Early Intervention in Psychiatry 8:382–386, 2014Crossref, MedlineGoogle Scholar

42 Le Blanc A, Herrin J, Williams MD, et al.: Shared decision making for antidepressants in primary care: a cluster randomized trial. JAMA Internal Medicine 11:E1–E10, 2015Google Scholar

43 Loh A, Simon D, Wills CE, et al.: The effects of a shared decision-making intervention in primary care of depression: a cluster-randomized controlled trial. Patient Education and Counseling 67:324–332, 2007Crossref, MedlineGoogle Scholar

44 Hamann J, Cohen R, Leucht S, et al.: Shared decision making and long-term outcome in schizophrenia treatment. Journal of Clinical Psychiatry 68:991–997, 2007Google Scholar

45 Simon D, Kriston L, von Wolff A, et al.: Effectiveness of a Web-based, individually tailored decision aid for depression or acute low back pain: a randomized controlled trial. Patient Education and Counseling 87:360–368, 2012Crossref, MedlineGoogle Scholar

46 Westermann GMA, Verheij F, Winkens B, et al.: Structured shared decision-making using dialogue and visualization: a randomized controlled trial. Patient Education and Counseling 90:74–81, 2013Crossref, MedlineGoogle Scholar

47 Aljumah K, Hassali MA: Impact of pharmacist intervention on adherence and measurable patient outcomes among depressed patients: a randomised controlled study. BMC Psychiatry 15:219, 2015Crossref, MedlineGoogle Scholar

48 Montague AE, Varcin KJ, Simmons MB, et al.: Putting technology into youth mental health practice: young people’s perspectives. SAGE Open 5:1–10, 2015CrossrefGoogle Scholar

49 Blanchard M, Herrman H, Frere M, et al.: Attitudes informing the use of technologies by the youth health workforce to improve young people’s well-being: understanding the nature of the “digital disconnect.” Youth Studies Australia 31(s1):s14–s24, 2012Google Scholar

50 Burns J, Birrell E: Enhancing early engagement with mental health services by young people. Psychology Research and Behavior Management 7:303–312, 2014Crossref, MedlineGoogle Scholar

51 Elwyn G, Hutchings H, Edwards A, et al.: The OPTION scale: measuring the extent that clinicians involve patients in decision-making tasks. Health Expectations 8:34–42, 2005Crossref, MedlineGoogle Scholar