Adolescent adherence to psychosocial treatment

1 downloads 0 Views 132KB Size Report
Poor adolescent adherence to mental health psychosocial treatment significantly undermines effectiveness. ... Keywords: mental health services research; child psychotherapy; alliance; process ...... Planning for additional research on the.

Psychotherapy Research, May 2012; 22(3): 317326

Adolescent adherence to psychosocial treatment: Mental health clinicians’ perspectives on barriers and promoters


Downloaded by [Columbia University] at 06:50 21 November 2013

(Received 15 February 2011; revised 27 October 2011; accepted 18 December 2011)

Abstract Poor adolescent adherence to mental health psychosocial treatment significantly undermines effectiveness. Approximately one-third of all youth drop out or prematurely terminate from psychosocial treatment. This study examined youth adherence to psychosocial treatment from the perspective of community-based mental health clinicians (n  34) interviewed across three focus groups. A grounded theory analysis was applied to investigate the promoters and barriers influencing adolescent adherence to treatment. Clinicians identified four domains (adolescent, family, clinician, and agency) that serve as promoters and barriers to adherence. Barriers to adherence were located primarily in adolescent and family domains, whereas promoters were attributed within the clinician domain. Understanding of the complex influences on adolescent adherence may facilitate increased awareness and intervention options for clinicians.

Keywords: mental health services research; child psychotherapy; alliance; process research; anxiety; depression; mental health service utilization

Poor adherence of adolescents to mental health interventions is a significant obstacle to treatment effectiveness (Armbruster & Fallon, 1994; Armbruster & Kazdin, 1994; Nock & Kazdin, 2005; Pekarik, 1985). Approximately a third of adolescents drop out or terminate prematurely from mental health psychosocial treatment (Clarkin & Levy, 2004; Garfield, 1994; Kazdin, 2000, 2008; Kazdin & Mazurick, 1994; Olfson et al., 2009; Swift, Callahan, & Levine, 2009; Weersing & Weisz, 2002; Wierzbicki & Pekarik, 1993). Declining adolescent attendance and participation in psychosocial treatment undermines intervention effects (Clarke et al., 1992; Gaynor, Lawrence, & Nelson-Gray, 2006; Lefforge, Donohue, & Strada, 2007; Nock & Kazdin, 2005). Further investigation into the barriers and promoters to adolescent treatment adherence may support improved mental health services within the community. Research has explored adolescent and family factors associated with psychosocial treatment adherence problems. Specific client factors include: client pathology (Killaspy, Banerjee, King, & Lloyd, 2000; King, Hovey, Brand, Wilson, & Ghaziuddin, 1997); symptom severity (Pellerin, Costa, Weems, & Dalton, 2010; Rotheram-Borus et al., 1999); male gender

(Kreyenbuhl, Nossel, & Dixon, 2009), minority ethnicity (Furnham & Wong, 2007; Kreyenbuhl et al., 2009), younger age (Edlund et al., 2002; Furnham & Wong, 2007; Kreyenbuhl et al., 2009), and perceptions and beliefs of the adolescent (Edlund et al., 2002; Poureslami, Roberts, & Tavakoli, 2001); whereas family factors include: financial limitations or lack of insurance coverage (Edlund et al., 2002), problems with access, childcare needs, transportation difficulties, competing time demands (Daley & Zuckoff, 1999; Geffken, Keeley, Kellison, Storch, & Rodrigue, 2006; Stefl & Prosperi, 1985); parental stress or depression (Pellerin et al., 2010), lack of family involvement (Dwight-Johnson et al., 2010; Gearing, 2008), and perceptions and beliefs of parents (Laraque, McLean, Brown-Peterside, Ashton, & Diamond, 1997; Richardson, 2001; Taylor & Stansfield, 1984). Interestingly, research on youth referred to psychosocial mental health treatment found that the number of factors, rather than the presence of any single factor, decreased treatment adherence (MacNaughton & Rodrigue, 2001). Research into the clinicians’ contributions to adherence has focused on the contribution of the therapeutic alliance (Barber et al., 2006; Barber, Khalsa, & Sharpless, 2010; Lazaratou,

Correspondence concerning this article should be addressed to Robin E. Gearing, Columbia University, 1255 Amsterdam Avenue New York, NY 10027, USA. Email: [email protected] ISSN 1050-3307 print/ISSN 1468-4381 online # 2012 Society for Psychotherapy Research

Downloaded by [Columbia University] at 06:50 21 November 2013


R. E. Gearing et al.

Anagnostopoulos, Vlassopoulos, Tzavara, & Zelios, 2006; Murdock, Edwards, & Murdock, 2010; Perron, Zeber, Kilbourne, & Bauer, 2009; Priebe & Mccabe, 2008; Sharf, Primavera, & Diener, 2010). In addition, research has begun to investigate specific adherence strategies employed by clinicians to maintain psychosocial adherence. A recent study found clinicians provided three broad categories of adherence promoters, specifically outreach adherence promoters (i.e., phone calls, letters), concrete adherence promoters (i.e., travel support, childcare), and motivational adherence promoters (i.e., incentives) (Gearing, Schwalbe, Dweck, & Berkowitz, 2011). However, the clinicians’ perspectives on adolescent psychosocial treatment adherence remains underinvestigated (Pekarik & Finney-Owen, 1987; Pulford, Adams, & Sheridan, 2008). Specifically, perceptions of practicing clinicians on the definition of adherence and on the various barriers and promoters they encounter in day to day practice have not been examined. To address this gap in the research, this study has sought to investigate the perspective of clinicians who deliver services and routinely grapple with the fundamental problem of client adherence. Knowledge of the clinicians’ perspective may significantly augment our current understanding of mental health treatment adherence, identify areas for future research, and can inform the intervention development that would bolster client adherence and retention in evidence-based mental health treatment and services. Purpose of the Study The purpose of this grounded theory study was to explore youth adherence to psychosocial treatment from the perspectives of community-based mental health clinicians. Specifically, the study investigated the following two objectives: 1. To define psychosocial treatment adherence from the perspectives of community-based mental health clinicians. 2. Identify barriers and promoters to adolescent psychosocial treatment adherence from the perspectives of community-based mental health clinicians. Method This research was guided by grounded theory approach (Charmaz, 2006; Strauss & Corbin, 1998). Grounded theory is a well established qualitative research method that has been effectively used in focus group investigations (Abrams, Dornig, & Curran, 2009; Wisdom, Clarke, & Green, 2006;

Wong, Sands, & Solomon, 2010) and in eliciting experiential data from clinicians (Braun & Clarke, 2006; Bryman, 2004). Grounded theory allows clinicians to openly describe and examine their experiences and perceptions with adolescent adherence. The capturing of a variety of clinician experiences, beliefs, and constructs facilitates the identification of concepts and themes of interest (Strauss & Corbin, 1998). Focus group interviews were audio-taped and transcribed verbatim. Qualitative analysis methods, appropriate to grounded theory, included open and axial coding (Strauss & Corbin, 1998). Practice Setting The research was conducted at a large outpatient child and family mental health agency consisting of four separate clinics that serve urban, suburban, and rural families in New York State. In addition to outpatient counseling services, agency programs include case management, home-based therapy, foster care, and intensive support program for students with significant emotional difficulties at elementary, middle and high schools. The agency employs psychiatrists, psychologists, social workers and drug and alcohol counselors with expertise in treating children and youth. The clientele of the agency consists of a distribution of diagnoses and conditions including depression, anxiety, alcohol/ substance abuse, teenage pregnancy, physical and sexual abuse, witness/victim of crime and violence, learning disabilities, ADHD, developmental delays, separation and divorce, suicidality, chronic illness or death, postpartum and prenatal mood disorders. Sample Prior to sample recruitment, the Institutional Review Board (IRB) at Columbia University in New York approved this study. Clinicians were purposely recruited from a large outpatient child and family mental health agency where they are employed in various outpatient programs of mental health, substance abuse, home-based services, and intensive school programs. Eligible clinicians were mental health professionals employed by the host agency who provided clinical services to children and adolescents. Thirty-seven clinicians were invited to take part in one of three focus groups scheduled to follow agency-wide monthly meetings in the fall and winter of 20092010; 34 (92%) clinicians agreed to participate. Three focus groups were conducted with mental health clinicians who directly work with youth. Administrators or supervisors who did not provide direct treatment to

Adolescent adherence to psychosocial treatment youth were ineligible to participate. Formal informed consent was obtained from clinicians prior to the beginning of the focus group. Participation in this study was voluntary and no remuneration was provided to clinicians. Clinicians in the focus groups (see Table I: Sample Demographics) consisted of 31 (91%) females and three (9%) males with the average age being 42.5 years (SD 10.8). Twenty-nine were clinical social workers, one was a doctoral-level psychologist and four were clinical social work interns. The average years of experience in the mental health field was 11.4 (SD 9.4).

Downloaded by [Columbia University] at 06:50 21 November 2013

Focus Group Data Collection Data were collected using an in-depth, semi-structured interview guide designed to permit clinicians sufficient latitude to describe their unique experiences and perceptions (Kvale, 1996; Morgan, 1996). Interviews comprised a series of open-ended questions that provided clinicians the latitude to convey their perspectives. Specifically, the interview guide included the following topic areas: (a) definition of adherence to psychosocial treatment; (b) current practices to encourage adherence for adolescents; (c) identifying barriers or obstacles for adolescent adherence; (d) unresolved issues relating to adherence; and (e) recommendations to improve adolescent adherence to mental health psychosocial treatment. Specific example questions included: ‘‘what are your thoughts about adherence to psychosocial treatment?’’; ‘‘is psychosocial adherence a problem for you?’’; ‘‘describe how you in your current practice encourage adherence for adolescents?’’ and ‘‘describe any barriers or obstacles to adherence?’’ The focus group interviews were designed to encourage clinicians to share both positive and negative experiences in a non-judgmental atmosphere. Each focus group had between 10 and 14 clinicians. Focus groups lasted approximately 1.52 hours. Interviews were moderated by one of the authors (RG or CS). Prior to the interview, clinicians completed a brief demographic questionnaire that assessed socio-demographic factors (e.g., gender, age, race), education (e.g., professional designation, training, college degrees), and practice experience (e.g., years of practice, mental health work experience, treatment approaches). Data Analysis Interviews were audio-taped and the data transcribed verbatim. Field notes were also taken during focus group interviews. Recorded interviews and field


notes were transcribed immediately for thematic analysis (Lincoln & Guba, 2000). Transcripts were analyzed using NVivo software 8.0. NVivo is well suited for qualitative research as it allows each discourse to be categorized into individual and group themes. A system of multistage coding was used to assist in data analysis. This approach called for the initial use of open (‘‘in vivo’’) coding (codes that reflected the actual words of respondents) of the raw data to identify key concepts. After open coding, axial coding was conducted to organize the open codes into emergent patterns and themes in the data. As coding categories and themes emerged from the data, they were continually refined and developed until a comprehensive interpretation of the data was achieved. A number of methods were taken to ensure quality, inter-rater consensus, and methodological rigor including: data collection and analysis conducted separately by the authors; inter-rater consensus and agreement on codes reached through regular ongoing peer debriefing with the researchers throughout the analysis; and raw data verification that allowed for comparing analyses with original participant words (Lincoln & Guba, 1985, 2000). In addition, researchers engaged in member checking, a technique for verifying analyzed data, by personally contacting 15% (n 5) participants in order to verify findings.

Findings In the brief demographic questionnaire provided before the focus group interview, all clinicians reported providing direct clinical services to children and adolescents under the age of 21 years, with the majority (85%) working with adolescents 13 years or older. Most clinicians (97%) reported treating clients with mood disorders, anxiety disorders and ADHD, with 91% describing experience working with disruptive behavior disorders. Fewer clinicians reported treating clients with substance abuse (41%), autism (12%), learning disabilities (9%), and psychosis (6%). In describing their practice 94% of clinicians endorsed an eclectic approach. In addition, most clinicians reported infusing techniques from other approaches into their practice, such as 91% incorporated elements of psychoeducation, 85% aspects of cognitive behavioral therapy, and 74% used psychodynamic elements. Clinicians reported that approximately 45% of voluntary clients and 10% of involuntary clients had attendance problems, due to being mandated to treatment. Similarly, 27% of voluntary clients and 6% of involuntary clients were reported to drop out of treatment prematurely.


R. E. Gearing et al.

Table I. Sample demographics

Downloaded by [Columbia University] at 06:50 21 November 2013


n (%)

Gender Male Female Age Years of experience Profession (education) Social workers (MSW) Psychologist (PhD) Interns (graduate student)

29 (85) 1 (3) 4 (12)

Setting Mental health outpatient services School-based services Family-based services Substance abuse outpatient services

11 15 5 3

(32) (44) (15) (9)

Treatment experience with the following mental disorders Mood disorders Anxiety disorders ADHD Disruptive behaviors Substance abuse Autism Learning disability Psychosis

33 33 33 31 14 4 3 2

(97) (97) (97) (91) (41) (12) (9) (6)

Mean (SD)

3 (9) 31 (91)

were identified, in which 361 (91%) were described within the adolescent and family domains.

1. Treatment Adherence: Adolescent Domain 42.5 (10.8) 11.4 (9.4)

Psychosocial Treatment Adherence Clinicians described adherence as a dynamic phenomenon consisting of two essential elements; (a) attendance to treatment, and (b) participation in treatment. In the words of one clinician: ‘‘I think that means two things. I think it means adherence of one actually showing up for the sessions, but [it] also means actually taking part in the treatment.’’ Adolescent psychosocial treatment adherence is further complicated by various promoters and barriers. Clinicians identified the following four domains that serve as barriers and promoters of adherence: the adolescent, their family, the clinician, and the agency where the clinical service is provided. The adolescent domain was defined as the identified patient or client, whereas family was defined as the adolescent’s immediate and extended family. The clinician domain was defined as the mental health professional working with the index adolescent and family. The agency domain reflected the clinical setting where the index adolescent was receiving treatment, such as outpatient, in-home, and school-based services. While each domain had identified barriers and promoters, two dominant themes emerged within these constructs. First, the majority of promoters were attributed within the clinician domain. Of the total 352 promoters of adherence, subjects identified 286 (81%) of all promoters within the clinician domain. Second, the primary barriers were located within adolescent and family domains. A total of 398 barriers

Of the 176 adolescent coded references to treatment adherence, 153 (87%) codes were related to adolescent barriers and 23 (13%) codes were for adolescent promoters. Barriers and promoters identified by clinicians could be clustered into one of three categories: (a) motivation for change, (b) view of treatment, and (c) concrete barriers and promoters. Clinicians frequently described client motivation to change as both an adherence barrier and promoter. For example, ‘‘when you have a student invested, who wants to get better, . . . really seeks you out on a regular basis besides your sessions, wants to report to you and talk to you about this, that, and the other, that is so impactful.’’ According to clinicians, motivation to change was influenced by youth perceptions about the severity of their mental health problems (e.g., ‘‘a lot of times, the kids don’t think there is anything wrong with them’’), confidence (e.g., ‘‘I’m depressed or I’m anxious so nothing can help it, I just have this disorder’’), perceived peer pressure (e.g., ‘‘you have classmates who are sabotaging, you know, saying ‘why are you going to therapy’’’), and experience of success in treatment (e.g., ‘‘realized that yes, okay, the medication does work’’). Client view of treatment was closely associated with motivation in that clients who were motivated and who held positive expectations of treatment were more likely to adhere to treatment. In this regard, adolescent perceptions about the value of treatment stood out. For example, youths who believed that ‘‘there is something in [treatment] for them’’ were more motivated to participate in treatment. However, perceptions of treatment were most often coded as a barrier. Specific barriers described by clinicians included the adolescent perception that ‘‘this is just going to be another person that is just going to reprimand me for the way that I am,’’ and the ‘‘expectation from the beginning that I’m just going to be in trouble. I do stuff wrong and now I have to deal with it here.’’ Other clients simply believe that ‘‘therapy is a joke’’ and that ‘‘I don’t need this medication.’’ Finally, concrete or structural barriers were described by clinicians. Concrete barriers involved life circumstances that interfered with the possibility of attending appointments. The most common concrete barriers described by clinicians were scheduling conflicts. In the words of one clinician, ‘‘if you have a child that happens to have an active or busy social calendar and, you know, having to do with, you

Adolescent adherence to psychosocial treatment know, soccer, karate, boy scouts, this, that and the other thing.’’

Downloaded by [Columbia University] at 06:50 21 November 2013

2. Treatment Adherence: Family Domain There were a total of 235 family coded references, of which 208 (89%) codes were for family barriers and 27 (11%) codes for family promoters. Barriers and promoters in the family domain fell into four categories: (a) parental agreement with treatment; (b) parent health and strain; (c) concrete barriers; and (d) stigma. The major factor described by clinicians was the degree to which the parents agreed with, and understood, the clinician’s definition of treatment. Parental view of treatment led to adherence problems when parents and clinicians disagreed or had a misunderstanding about the nature or purpose of therapy. In some cases ‘‘they [parents] want the client to attend alone and they don’t want to take part’’ whereas one clinician, speaking for most, noted ‘‘it’s hard to get the parents to realize that it’s not just the kid, it’s a family issue and they need to be involved.’’ Some clinicians observed that ‘‘a lot of time the idea or the concept of therapy is not really understood or maybe they are looking for something more of a quick fix’’ or ‘‘There are certain families . . . who scoff at the whole therapy thing . . . [and think it] doesn’t work.’’ Some clinicians noted the importance of culture and religion as a factor (e.g., ‘‘I also think depending culturally, a lot of time the idea or the concept of therapy is not really understood’’ and ‘‘religious issues can play a part’’). And, parental disagreement with the clinical diagnosis was described as a barrier to involvement and reduced adolescent adherence. Alternatively, parents who agree with the clinician’s views led to higher levels of family involvement and greater adherence to treatment. One clinician commented ‘‘I find that we have the biggest amount of improvement when we have the family’s involvement.’’ This occurred when parents agreed with the clinical diagnosis of their child and when ‘‘parent’s view that their child’s behavior was indicative that that they needed some professional support.’’ Clinicians reported that many parents of children seen in their clinics face personal challenges such as physical health, mental health, substance use, and parenting skills, and that these challenges hinder youth adherence. According to one clinician, youth are aware that their parents ‘‘don’t have the time or the sufficient health to bring the child on a regular basis.’’ Concrete barriers consisted of issues with transportation to treatment, socioeconomic status, the ability of the family to obtain insurance and pay co-payments, issues with child care, and scheduling.


Clinicians reported that ‘‘families are working two jobs; they just don’t have any time.’’ Another added ‘‘and mostly I think it becomes financial or [they lack] transportation and they really feel like they can’t continue.’’ Finally, a concern for stigma also created barriers for family involvement and youth adherence. For example, one clinician stated that ‘‘a lot of it depends on what their thoughts are and in terms of a stigma, or on a stigma of what mental illness means to them, what the participation will be.’’ Another clinician contributed: ‘‘and the parent said, ‘well I really don’t want to do that. I really don’t want that stigma on my child.’’’

3. Treatment Adherence: Clinician Domain The clinician domain had the most codes with a total of 302 coded references. Unlike the adolescent and family domains, which overwhelmingly comprised barrier codes, the barriers within the clinician domain represented only 15 (5%) of coded references, while clinician promoters included 287 (95%) of all codes. The three clinician promoters were classified as techniques or skills: (a) aimed at adolescents; (b) aimed at parents; and (c) used in response to non-adherence. Clinician promoters aimed at adolescents were defined as techniques or skills the therapist used to engage an adolescent in treatment. These promoters included the therapeutic alliance, therapeutic processes, and treatment activities. The therapeutic alliance was defined as the importance of the relationship between the clinician and adolescent and qualities of that relationship. Clinicians noted that ‘‘the relationship that you establish with the client is a prominent feature of whether or not the client is adherent and participating.’’ Another clinician described that ‘‘one of the key ingredients to successful therapy is warmth and empathy.’’ The clinician promoter of therapeutic processes was defined as engaging the adolescent by emphasizing the adolescent’s choice in attending and their key role in the process of therapy to accomplish what they would like to work on and empowering the adolescent to make these changes. For example, a clinician stated that ‘‘you have to make it their choice to be there.’’ A third promoter aimed at the adolescent centered on treatment activities that were defined as the clinician taking an interest in what the adolescent’s interests were and letting the adolescent choose the activity to engage in treatment, and changing the environment and modality when needed. And finally, some clinicians described using cell phones to keep in contact with adolescents. One clinician described ‘‘asking the kid, is it okay if I

Downloaded by [Columbia University] at 06:50 21 November 2013


R. E. Gearing et al.

have your cell phone and then, you know, maybe I could call you in a week and check in?’’ Clinician promoters aimed at parents were defined as techniques or skills the therapist used to engage parents in treatment, including acknowledging past experiences, clarifying what therapy entails and joining with parents. One clinician described that ‘‘if you can join in with the parent(s) and present treatment as a team working help the child, you have a better chance at having them work with you.’’ Another noted that ‘‘psychoeducation is very important in terms of having the parent want to comply with therapy and. . . medication.’’ Finally, a third emphasized the importance of clinician-parent collaboration by saying ‘‘we actually make the family as part of the treatment team.’’ Conversely, a clinicianlevel barrier was recognition that cultural differences with the family may adversely influence adherence. As clinicians noted that ‘‘families feel much more engaged if the parent feels that the therapist speaks their language and is of their culture.’’ The final clinician promoters revolved around techniques in response to non-adherence; these included efforts the clinicians make when a client is not attending sessions, including the use of family sessions, outreach, and interagency collaboration. Clinicians reported ‘‘we try to get the family to come in, the parents and the child to come in, for a session with myself as coordinator and therapist to address what are the reasons that they are not attending.’’ Other clinicians reached out more directly by ‘‘going to the home and reaching out to families at their home. Especially ones that are less committed to coming in.’’ Collaboration was another intervention technique to promote adherence in response to missed appointments. For example, a clinician stated ‘‘I have the advantage of being able to collaborate with other service providers. So if I have a client who is missing appointments with me, I might call someone else and just say is that child in school, has he been meeting with you, is there anything you have noticed?’’

4. Treatment Adherence: Agency Domain The domain with the fewest barriers was that at the agency level, in which there were a total of 37 coded references. Agency barriers to adolescent psychosocial treatment adherence consisted of 21 (57%) coded references, with 16 (43%) of the references coded as promoters. The four agency barriers were identified as financial, scheduling, procedural, and technology. Financial barriers were conceptualized as billing issues and funding for non-traditional activities. According to one clinician ‘‘we thought about trying to clump

services together in one day but then insurance won’t pay.’’ Scheduling was conceptualized as the hours of operation. Clinicians noted that traditional hours of operation often impacted treatment. One clinician reported that ‘‘families would say, extend the hours, you know weekends.’’ Procedural agency barriers were conceptualized as policies the agency has that are an obstacle to engagement or adherence. For example, ‘‘they don’t get an appointment to come back to see the person who does the intake.’’ The final barrier, technology, was conceptualized as issues that would make therapy easier, such as ‘‘texting.’’ Agency promoters of adolescent adherence included the requirement of family involvement, accessible locations, goodness of fit, supports, and incentives. The agency requirement of family involvement in treatment with certain clients or presenting problems was described as a distinct promoter, where parents often ‘‘needed to agree that they were going to come in for family sessions.’’ Convenient and accessible agency locations were described as an agency promoter. Also, the agency policy of trying to match clinician and families for goodness of fit was described as improving treatment adherence. One clinician noted that ‘‘we really do try and [maximize] the goodness of fit between the clinician and the client coming in.’’ The agency’s initiative of encouraging support networks was another defined promoter. One clinician reported that in the agency ‘‘we use family support groups and . . . that helps the parents, showing them they are not alone.’’ Finally, incentives such as ‘‘using coupons for food, transportation, child care, etc.’’ were effective agency promoters to encourage clients to come to treatment.

Discussion This study examined the phenomenon of psychosocial treatment adherence from the perspectives of community-based mental health clinicians. According to clinicians, the dual dimensions of adherence include session attendance and participation in treatment. They identified a set of promoters available to foster adherence featuring especially the therapeutic alliance. Moreover, they identified a set of adolescent and family adherence barriers commonly found in practice. Figure 1 presents a conceptual framework that synthesizes the findings of this study. Of note in the framework is the relative promoter-barrier imbalance between clinicians and clients whereby clinicians primarily envisioned themselves as a source of promoters and clients as the source of adherence barriers. In Figure 1, clinicians readily identified their contribution to the adherence of adolescents to

Adolescent adherence to psychosocial treatment Adolescent Domain (n=176)

Family Domain (n=235)

Promoters (n=23)

Promoters (n=27)

Barriers (n=153)

Barriers (n=208)


Session Participation PSYCHOSOCIAL ADHERENCE Clinician Domain (n=302)

Session Attendance

Promoters (n=287)

Agency Domain (n=37)

Promoters (n=16)

Downloaded by [Columbia University] at 06:50 21 November 2013

Barriers (n=21) Barriers (n=15)

Figure 1. Adherence model: The influence of barriers (n 398) and promoters (n 352) on psychosocial treatment.

treatment. Most important, they described their efforts to facilitate the therapeutic alliance and to address potential barriers to the alliance. Specific alliance-building skills mentioned by subjects included empathy, listening, and engaging the client and, when possible, their family. These findings parallel the larger literature that highlights the significance of the therapeutic alliance and the clinician’s role within this relationship (Corning, Malofeeva, & Bucchianeri, 2007; Samstag, Batchelder, Muran, Safran, & Winston, 1998; Sharf et al., 2010). As an estimated 70% of all premature dropout occurs in the first two psychosocial sessions (Olfson et al., 2009), the early development of the therapeutic alliance is essential. Notwithstanding the importance of the therapeutic alliance, clinician evaluations of their salutatory effect on adherence may not match client perspectives. Research has found that clinicians over-attribute premature termination to the client (Murdock et al., 2010), whereas clients report the clinician’s role as having a stronger influence on their decision to terminate prematurely (Hunsley, Aubry, Verstervelt, & Vito, 1999; Westmacott, Hunsley, Best, Rumstein-McKean, & Schindler, 2010). According to Westmacott et al. (2010) and Murdock et al. (2010), this attribution stance may reflect a self-serving bias, where clinicians are less likely to rate themselves too negatively. The present findings may reflect a similar corresponding attribution bias, where clinicians may rate themselves positively as promoters of adherence to psychosocial treatment while simultaneously attributing a majority of adherence barriers to youths and their

families. Practice strategies to improve psychosocial treatment adherence can begin with an increased awareness of their own possible self-serving bias, and concrete efforts to recognize and facilitate adherence promoters in clients and their families. Also shown in the conceptual framework is the emphasis that clinicians’ ascribe to the barriers to adherence within the adolescent and family domains. This weighting can reflect some inverse elements of a self-serving bias, where fewer barriers are identified within the clinician role and more are attributed to adolescent clients and their families. However, these findings also parallel existing research where service providers readily identified client, family or environmental barriers, but were less likely to see their role or relationship as barriers to treatment (Klein, Stone, Hicks, & Pritchard, 2003; Pekarik & Finney-Owen, 1987; Pulford et al., 2008). The Health Beliefs Model may serve as a lens to interpret these described client and family barriers identified by clinicians. Adolescent and parental health beliefs contribute to the adherence of adolescents to psychosocial interventions (Becker & Maiman, 1975; Laraque et al., 1997; Richardson, 2001; Taylor & Stansfield, 1984) where perceived benefits (Bond, Aiken, & Somerville, 1992; Hazavehei, Taghdisi, & Saidi, 2007; Poureslami et al., 2001) and perceived barriers (Poureslami et al., 2001) both exert significant influence on adolescents’ health decisions. In the current study, clinicians reported that youth are more likely to be adherent when they perceive greater ‘‘severity of their mental health problems’’; conversely adherence becomes an issue when ‘‘kids don’t think there is anything wrong with

Downloaded by [Columbia University] at 06:50 21 November 2013


R. E. Gearing et al.

them.’’ Families are more likely to support treatment when they ‘‘view that their child’s behavior was indicative that they needed some professional support.’’ In the view of participating clinicians, these health beliefs, among others, contributed substantially to the adherence of their clients. Understanding adherence from the perspective of practicing clinicians offers service providers and researchers implications to engage and retain youth in treatment and to maximize their participation. For example, in viewing adherence to psychosocial treatment through a Health Beliefs Model lens, clinicians can inform and structure practice strategies to address specific beliefs held by adolescents and their families. Specifically, clients will have perceived barriers that will negatively influence their ability to adhere to treatment. To address these potential barriers, clinicians may want to take non-judgmental positions that expect the existence of barriers and work openly with the client to make these perceptions transparent and possible to ameliorate. Also, youth and family promoters should be quickly identified, explicated, and supported by the clinician. Early in the therapeutic process, clinicians may want to assess the perceived severity of the mental health problem or symptoms, and the youth’s self-efficacy. Clients and families that minimized mental health concerns may benefit from psychoeducation and open dialogue about their perceptions. Adherence may be strengthened by working with the child or adolescent to enhance their self-efficacy, including emphasizing their efforts to improve their condition by attending and participating in treatment. Findings from the study should be interpreted with some caution because of its limitations in its sampling design. First, the study included clinicians from a single, albeit multi-centered, agency. By restricting participation to clinicians from a single agency, agency effects on clinician perspectives (e.g., client attendance policies, agency training) on adherence cannot be compared with clinician experiences from other agencies. Future studies may crossvalidate these findings with new samples derived from alternative agencies. Second, the study is limited by its sole emphasis on the clinician perspective and does not include the perspectives of parents, family members, or youth receiving services. Clearly the perspectives of adolescents and their parents are key to developing a more comprehensive view of adherence. Planning for additional research on the client and family perspectives is currently under way. Third, the sample is not representative as it consists of predominantly female (91%) social workers (85%). Currently in the USA, social workers represent over 65% of mental health professionals in direct practice and the profession is predominantly

female (81%) (Center for Health Workforce Studies, 2006; Gibelman, 1995; Gibelman & Schervesh, 1993). Future research investigating variation across professions and gender is recommended. The perspectives of community-based mental health clinicians augment our knowledge of psychosocial adherence and inform practice and intervention research. Results suggest clinicians consider their role in adherence problems. When clinicianbased barriers are more fully articulated, training and supervision strategies can be developed to strengthen adherence-promoting efforts. Also, by examining client and family-related barriers and promoters through the lens of health beliefs, specific interventions targeting health belief barriers can be implemented. Needed next are studies that examine adherence promoters and barriers from the perspectives of clients and their families and that translate these findings into specific intervention strategies for adherence promotion. References Abrams, L.S., Dornig, K., & Curran, L. (2009). Barriers to service use for postpartum depression symptoms among lowincome ethnic minority mothers in the United States. Qualitative Health Research, 19(4), 535551. Armbruster, P., & Fallon, T. (1994). Clinical, sociodemographic, and systems risk factors for attrition in a children’s mental health clinic. American Journal of Orthopsychiatry, 64(4), 577585. Armbruster, P., & Kazdin, A.E. (1994). Attrition in child psychotherapy. Advances in Clinical Child Psychology, 16, 81109. Armbruster, P., & Kazdin, A.E. (1994). Attrition in child psychotherapy. In: T.H. Ollendick & R.J. Prinz (Eds.), Advances in clinical child psychology (Vol. 16, pp. 81109). New York: Plenum Press. Barber, J. (2009). Toward a working through of some core conflicts in psychotherapy research. Psychotherapy Research, 19(1), 112. Barber, J.P., Gallop, R., Crits-Christoph, P., Frank, A., Thase, M.E., Weiss, R.D., et al. (2006). The role of therapist adherence, therapist competence, and alliance in predicting outcome of individual drug counseling: Results from the National Institute Drug Abuse Collaborative Cocaine Treatment Study. Psychotherapy Research, 16(2), 229240. Barber, J.P., Khalsa, S.R., & Sharpless, B.A. (2010). The validity of the alliance as a predictor of psychotherapy outcome. In J.C. Muran & J.P. Barber (Eds.), The therapeutic alliance: An evidence-based guide to practice (pp. 2943). New York: Guilford Press. Becker, M., & Maiman, L. (1975). Sociobehavioral determinants of compliance with health and medical care recommendations. Medical Care, 13, 1024. Bond, G.G., Aiken, L.S., & Somerville, S.C. (1992). The health belief model and adolescents with insulin-dependent diabetes mellitus. Health Psychology, 11(3), 190198. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77101. Bryman, A. (2004). Social research methods (2nd ed.). Oxford: Oxford University Press.

Downloaded by [Columbia University] at 06:50 21 November 2013

Adolescent adherence to psychosocial treatment Center for Health Workforce Studies. (2006). Licenced social workers in the united states, 2004. Washington DC: School of Public Health, University at Albany. Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. Thousand Oaks, CA: Sage. Clarke, G.N., Hops, H., Lewinsohn, P.M., Andrews, J., Seeley, J.R., & Williams, J. (1992). Cognitive-behavioral group treatment of adolescent depression: Prediction of outcome. Behavior Therapy, 23, 341354. Clarkin, J.F., & Levy, K.N. (2004). Influence of client variables on psychotherapy. In M.J. Lambert (Ed.), Handbook of psychotherapy and behavior change (5th ed., pp. 194226). New York: Wiley. Corning, A.F., Malofeeva, E.V., & Bucchianeri, M.M. (2007). Predicting termination type from client-therapist agreement on the severity of the presenting problem. Psychotherapy: Theory, Research, Practice, Training, 44(2), 193204. Daley, D.C., & Zuckoff, A. (1999). Improving treatment compliance: Counseling and systems strategies for substance abuse and dual disorders. Center City, MN: Hazelden. Dwight-Johnson, M., Lagomasino, I.T., Hay, J., Zhang, L., Tang, L., Green, J.M., et al. (2010). Effectiveness of collaborative care in addressing depression treatment preferences among low-income Latinos. Psychiatric Services, 61(11), 11121118. Edlund, M.J., Wang, P.S., Berglund, P.A., Katz, S.J., Lin, E., & Kessler, R. (2002). Dropping out of mental health treatment: Patterns and predictors among epidemiological survey respondents in the United States and Ontario. American Journal of Psychiatry, 159(5), 845851. Furnham, A., & Wong, L. (2007). A cross-cultural comparison of British and Chinese beliefs about the causes, behaviour manifestations and treatment of schizophrenia. Psychiatry Research, 151(12), 123138. Garfield, S.L. (1994). Research on client variables. In S.L. Garfield & A.E. Bergin (Eds.), Handbook on psychotherapy and behavior change (4th ed., pp. 190228). New York: Wiley. Gaynor, S.T., Lawrence, P.S., & Nelson-Gray, R.O. (2006). Measuring homework compliance in cognitive-behavioral therapy for adolescent depression: Review, preliminary findings, and implications for theory and practice. Behavior Modification, 30(5), 647672. Gearing, R.E. (2008). Evidence-based family psychoeducational interventions for children and adolescents with psychotic disorders. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 17(1), 211. Gearing, R.E., Schwalbe, C.S., Dweck, P., & Berkowitz, J. (2011). Investigating adherence promoters in evidence-based mental health interventions with children and adolescents. Community Mental Health Journal. doi: 10.1007/s10597-0119394-9 Geffken, G.R., Keeley, M.L., Kellison, I., Storch, E.A., & Rodrigue, J.R. (2006). Parental adherence to child psychologies’ recommendations from psychological testing. Professional Psychology: Research and Practice, 37, 499505. Gibelman, M. (1995). What social workers do. Washington DC: NASW Press. Gibelman, M., & Schervesh, P.H. (1993). Who we are: The social work labor force as reflected in the NASW membership. Washington DC: NASW Press. Hazavehei, S.M., Taghdisi, M.H., & Saidi, M. (2007). Application of the Health Belief Model for osteoporosis prevention among middle school girl students. Education for Health: Change in Learning & Practice, 20(1), 111. Hunsley, J., Aubry, T., Verstervelt, C.M., & Vito, D. (1999). Comparing therapist and client perspectives on reasons for psychotherapy termination. Psychotherapy: Theory, Research, Practice and Training, 36(4), 380388.


Kazdin, A.E. (2000). Psychotherapy for children and adolescents: Directions for research and practice. New York: Oxford University Press. Kazdin, A.E. (2008). Evidence-based treatments and delivery of psychological services: Shifting our emphases to increase impact. Psychological Services, 5(3), 201215. Kazdin, A.E., & Mazurick, J.L. (1994). Dropping out of child psychotherapy: Distinguishing early and late dropouts over the course of treatment. Journal of Consulting and Clinical Psychology, 6(5), 10691074. Killaspy, H., Banerjee, S., King, M., & Lloyd, M. (2000). Prospective controlled study of psychiatric out-patient nonattendance: Characteristcis and outcome. British Journal of Psychiatry, 176, 160165. King, C.A., Hovey, J.D., Brand, E., Wilson, R., & Ghaziuddin, N. (1997). Suicidal adolescents after hospitalization: Parent and family impacts on treatment follow-through. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 8593. Klein, E.B., Stone, W.N., Hicks, M.W., & Pritchard, I.L. (2003). Understanding dropouts. Journal of Mental Health Counseling, 25(2), 89100. Kreyenbuhl, J., Nossel, I.R., & Dixon, L.B. (2009). Disengagement from mental health treatment among individuals with schizophrenia and strategies for facilitating connections to care: A review of the literature. Schizophrenia Bulletin, 35(4), 696703. Kvale, S. (1996). Interviews: An introduction to qualitative research interviewing. Thousand Oaks, CA: Sage. Laraque, D., McLean, D.E., Brown-Peterside, P., Ashton, D., & Diamond, B. (1997). Predictors of reported condom use in central Harlem youth as conceptualized by the health belief model. Journal of Adolescent Health, 21(5), 318327. Lazaratou, H., Anagnostopoulos, D.C., Vlassopoulos, M., Tzavara, C., & Zelios, G. (2006). Treatment compliance and early termination of therapy: A comparative study. Psychotherapy and Psychosomatics, 75(2), 113121. Lefforge, N.L., Donohue, B., & Strada, M.J. (2007). Improving session attendance in mental health and substance abuse settings: A review of controlled studies. Behavior Therapy, 38(1), 122. Lincoln, Y.S., & Guba, E. (1985). Naturalistic inquiry. Thousand Oaks, CA: Sage. Lincoln, Y.S., & Guba, E. (2000). Paradimatic controversies, contradictions, and emerging confluences. In N.K. Denzin & Y.S. Lincoln (Eds.), Handbook of qualitative research (2nd ed.). Thousand Oaks, CA: Sage. MacNaughton, K.L., & Rodrigue, J.R. (2001). Predicting adherence to recommendations by parents of clinic-referred children. Journal of Consulting and Clinical Psychology, 69, 262270. Morgan, D.L. (1996). Focus groups. Annual Review of Sociology, 22, 129152. Murdock, N.L., Edwards, C.E., & Murdock, T.B. (2010). Therapists’ attributions for client premature termination: Are they self-serving? Psychotherapy: Theory/Research/Practice/ Training, 47(2), 221234. Nock, M.K., & Kazdin, A.E. (2005). Randomized controlled trial of a brief intervention for increasing participation in parent management training. Journal of Consulting and Clinical Psychology, 73(5), 872879. Olfson, M., Mojtabai, R., Sampson, N.A., Hwang, I., Druss, B., Wang, P.S., et al. (2009). Dropout from outpatient mental health care in the United States. Psychiatric Services, 60(7), 898907. Pekarik, G. (1985). Coping with dropouts. Professional Psychology: Research and Practice, 16, 114123.

Downloaded by [Columbia University] at 06:50 21 November 2013


R. E. Gearing et al.

Pekarik, G., & Finney-Owen, K. (1987). Outpatient clinic therapist attitudes and beliefs relevant to client dropout. Community Mental Health Journal, 23(2), 120130. Pellerin, K.A., Costa, M., Weems, F., & Dalton, F. (2010). An examination of treatment completers and non-completers at a child and adolescent community mental health clinic. Community Mental Health Journal, 46, 273281. Perron, B.E., Zeber, J.E., Kilbourne, A.M., & Bauer, M.S. (2009). A brief measure of perceived clinician support by patients with bipolar spectrum disorders. Journal of Nervous and Mental Disease, 197(8), 574579. Poureslami, M., Roberts, S., & Tavakoli, R. (2001). College students’ knowledge, beliefs and attitudes towards AIDS in predicting their safe sex behaviour. Eastern Mediterranean Health Journal, 7(6), 880894. Priebe, S., & Mccabe, R. (2008). Therapeutic relationships in psychiatry: The basis of therapy or therapy in itself? International Review of Psychiatry, 20(6), 521526. Pulford, J., Adams, P., & Sheridan, J. (2008). Therapist attitudes and beliefs relevant to client dropout revisited. Community Mental Health Journal, 44, 181186. Richardson, L.A. (2001). Seeking and obtaining mental health services: What do parents expect? Archives of Psychiatric Nursing, 15, 223231. Rotheram-Borus, M.J., Piacentini, J., Van Rossem, R., Graae, F., Cantwell, C., Castro-Blanco, D., et al. (1999). Treatment adherence among Latina female adolescent suicide attempters. Suicide & Life-Threatening Behavior, 29, 319331. Samstag, L.W., Batchelder, S.T., Muran, J.C., Safran, J.D., & Winston, A. (1998). Early identification of treatment failures in short-term psychotherapy: An assessment of therapeutic alliance and interpersonal behavior. Journal of Psychotherapy Practice & Research, 7, 126143. Sharf, J., Primavera, L.H., & Diener, M.J. (2010). Dropout and therapeutic alliance: A meta-analysis of adult individual

psychotherapy. Psychotherapy Theory, Research, Practice, and Training, 47(4), 637645. Stefl, M.E., & Prosperi, D.C. (1985). Barriers to mental health service utilization. Community Mental Health Journal, 21, 167178. Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park; CA: Sage. Swift, J.K., Callahan, J.L., & Levine, J.C. (2009). Using clinically significant change to identify premature termination. Psychotherapy: Theory, Research, Practice, and Policy, 46, 328335. Taylor, E., & Stansfield, S. (1984). Children who poison themselves: A clinical comparison with psychiatric controls. British Journal of Psychiatry, 145, 127132. Weersing, V., & Weisz, J.R. (2002). Community clinic treatment of depressed youth: Benchmarking usual care against CBT clinical trials. Journal of Consulting and Clinical Psychology, 70(2), 299310. Westmacott, R., Hunsley, J., Best, M., Rumstein-McKean, O., & Schindler, D. (2010). Client and therapist views of contextual factors related to termination from psychotherapy: A comparison between unilateral and mutual terminators. Psychotherapy Research, 20(4), 423435. Wierzbicki, M., & Pekarik, G. (1993). A meta-analysis of psychotherapy dropout. Professional Psychology: Research and Practice, 24, 190195. Wisdom, J.P., Clarke, G.N., & Green, C.A. (2006). What teens want: Barriers to seeking care for depression. Administration and Policy in Mental Health and Mental Health Services Research, 33(2), 133145. Wong, Y.I., Sands, R.G., & Solomon, P.L. (2010). Conceptualizing community: The experience of mental health consumers. Qualitative Health Research, 20(5), 654667.

Suggest Documents