Development of therapeutic alliance in mentalization-based treatment

The study "Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder" was performed in order to test the model we proposed in our article named "Battles of the Comfort Zone."

It aimed to investigate the development of the therapeutic alliance in mentalization-based treatment (MBT) therapies for borderline personality disorder (BPD). The sample included 155 patients in an MBT program, and clinical outcomes were based on the Global Assessment of Functioning (GAF) scale. The sample was divided into two subgroups according to GAF levels at the end of treatment (cutoff = 60). The therapeutic alliance was assessed using the Working Alliance Inventory, which measures goals, bonds, and tasks, and was assessed repeatedly over 36 months. The statistical analysis method used was linear mixed models. The results showed that initial levels of goals, bonds, and tasks did not differ by subgroup, but change over time did differ significantly by subgroup. In the good outcome subgroup, ratings of goals, bonds, and especially tasks increased significantly over time. In the poor outcome subgroup, paranoid personality disorder was associated with poorer alliance development over time. These findings suggest that good outcome therapies are characterized by a process where the therapeutic alliance grows over time, and that an explicit focus on tasks in therapy may be particularly helpful for patients with high levels of mistrust. Overall, this study highlights the importance of carefully maintaining the therapeutic alliance in the treatment of poorly functioning patients with BPD, including a longer-term process of attachment and bonding, as well as keeping the goals of therapy understandable, current, and updated, and making the therapeutic work, progress, and challenges relevant and explicit.

Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder


Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder

Despite attachment issues in the target population, there is little research on the relationship between alliance and outcome in the study of PDs. The effects of MBT are well documented, with low dropout rates and substantial improvement in terms of self-destructiveness, and symptom relief. Central relational problems among patients with BPD are associated with hypersensitivity, insecure attachment, and lack of epistemic trust, aspects particularly challenged in the therapy setting. The overriding aim of this quantitative study was to investigate how aspects of therapeutic alliance (goals, tasks, and bonds) developed over time in MBT for patients with BPD. The study primarily aimed to investigate alliance processes in therapies with different clinical outcomes and secondarily to explore variation associated with different patient characteristics.

 

 

The working alliance

As psychotherapy research found no significant differences in terms of efficacy (between bona fide psychotherapies), the search for the effective “ingredients” common to different kinds of treatments was initiated: The “common factors.” (Horvath, 2018, p. 501). As the importance of the relationship between the patient and the healer has been recognized since ancient times, “the helper–client relationship was identified as an obvious candidate” (Horvath, 2018, pp. 501–502). The most researched aspect of the helper–client relationship is the alliance. However, as the concept of the alliance exists as a consensus, it is not constrained within a theoretical framework (Horvath, 2018, p. 500), and an interesting question becomes which relational aspects the alliance includes—for instance whether the real relationship (RR) is part of the alliance or not. Bordin suggested that the RR was captured by the bond aspect of the alliance (Bordin, 1994), while (Gelso & Carter, 1985) theorized that the therapy relationship has three components: Transference, alliance, and the RR. Relational elements such as alliance, empathy, warmth, trust, and genuineness represent different levels of abstractions, and “there is a practical vacuum in the literature addressing questions about the relations among these elements, both from the conceptual and from the empirical perspective: How much do these elements overlap or contribute to each other?” (Horvath, 2018, p. 511).

 

The alliance is considered one of the five elements necessary for therapeutic change (Wampold & Imel, 2015) in the CF approach. However, the proponents of the CFs have no copyright on the importance of the therapeutic relationship. According to Rogers (1951), the three effective components of psychotherapy are empathy, unconditional positive regard, and congruence. The psychoanalyst Greenson (1965) claims that a working alliance is as important as analyzing the patients (e.g., the transference neurosis). Luborsky (1976) applies a counting signs method of assessing alliance and describes two types of alliance, one “based on the patient’s experiencing the therapist as supportive and helpful” and one “based on a sense of working together in a joint struggle” (p. 94). Bordin (1979) redefines the working alliance in terms of a collaboration between therapist and patient while engaging in a series of tasks tailored to lead toward agreed-upon goals. Parallel to that process, a bond develops that supports the patient’s capacity for positive and trustful states. Bordin (1979) claims that across therapies “the effectiveness [is] in part, if not entirely, a function of the strength of the alliance” (p. 253). A variety of definitions of alliance and relationship have shown robust associations with treatment outcome (Norcross et al., 2006). However, Horvath (2006) calls for “a clearer definition of the alliance”, a “consensus about the alliance’s relation to other elements in the therapeutic relationship”, and clarification of “the role and function of the alliance in different phases of treatment” (p. 258). Throughout this thesis, we will elaborate the view that “embedded alliance” is a comforting term when battling with such questions.

 

The definition of the therapeutic alliance proposed by Bordin (1979) was redefined by Horvath and Luborsky (1993) as a “pan-theoretical concept”. Bordin’s formulation highlights the collaborative relationship between patient and therapist in the common quest to overcome the patient’s suffering and (self-) destructive behavior and consists of three essential elements—(1) agreement on the goals of the treatment, (2) agreement on the tasks, and (3) the development of a personal bond made up of reciprocal positive feelings. The variable influence of the alliance in different therapies has led some to propose that this relationship may play differing roles across treatment modalities (Gaston et al., 1998; Safran & Wallner, 1991). In terms of the therapeutic relationship (e.g., the working alliance), correlation studies show that alliance (Bordin, 1979; Bordin, 1983; Bordin, 1994; Gaston, 1990; Luborsky, 1976) at the onset of treatment predicts improvement in symptoms at the termination of treatment (Barber et al., 2000; Cloitre et al., 2004; Horvath & Bedi, 2002; Horvath & Symonds, 1991; Klein et al., 2003; Martin et al., 2000). But as we all know, establishing correlation is but an illusion of explanation (Barber, 2009), and even though meta-analyses from 2011 and 2018 (Fluckiger et al., 2018; Horvath et al., 2011) report an aggregate association between alliance and outcome of .275–.78 (typically in the range of .20–.30), there remains an animated argument about the curative potency of the alliance, predominantly in therapies examined using RCT designs (Horvath et al., 2011; Ulvenes et al., 2012). Notably, “therapists’ individual differences have been found to predict alliance quality and treatment success” (Muran et al., 2010, p. 321). Therefore, Fonagy (2010) and Lemma et al. (2011) conclude “So the ability to form an alliance does mark out our more talented therapists, but what it is that they do more or less of that makes them more or less effective still remains a mystery” (p. 37; p. 17).

 

Despite the assumption that it takes the devoted apprentice decades to learn how to brew these carefully measured psychotherapeutic potions (Fonagy, 2010), we know little about how “talented therapists” obtain their recipes and administering abilities, as the current literature seems to exclude major effects of therapist training (Beutler, 2004; Miller & Binder, 2002; Ogles et al., 1999; Rønnestad & Ladany, 2006): “Overall, these findings tend to cast doubt on the validity of the suggestions that specific training in psychotherapy, even when unconfounded with general experience, may be related to therapeutic success or skill” (Beutler, 2004, p. 239). This is regarded as true for training in manualized short-term psychodynamic treatment (Bein et al., 2000). However, there are some indications for further research; for example, Crits-Christoph et al. (2006a) have reported non-significant but promising results from training five therapists (45 patients) in alliance-fostering techniques.

 

Applying a somewhat seemingly circular logic, Wampold and Imel (2015) simply state that the most important common curative factor is treatment itself, while others call for studies on how psychotherapy actually leads to change (e.g., Elliott, 2011; Greenberg, 2007; Kazdin, 2009). Elliott (2011) emphasizes that even though there are many theories about therapeutic change, we know little of how change actually occurs. Kazdin (2009) concludes that “[a]fter decades of psychotherapy research and thousands of studies, there is no evidence-based explanation of how or why even the most well-studied interventions produce change, that is, the mechanisms through which treatments operate” (p. 426). The foremost enigma today is the last of the four questions Klaus Grawe articulated in 1997: How does psychotherapy work?

 

The working alliance in effective borderline personality disorder treatments

“Clinicians routinely note the challenges involved in psychotherapy with individuals with BPD, yet little research exists on the therapeutic alliance with this population” (Levy et al., 2010, p. 413). Individuals with PDs often undermine the working alliance (Benjamin & Critchfield, 2010, p. 132). Masterson (1978) suggests that “in psychotherapy with the borderline patient the therapeutic alliance is a goal or objective rather than a precondition” (p. 437). Barber et al. (2010) argue that a “strong therapeutic alliance may be an appropriate therapeutic outcome for certain types of patients (e.g., a patient with BPD or a patient with profound levels of trauma who experiences difficulties trusting or working with others)” (p. 38). Bordin perceived alliance as a vehicle that enables and facilitates specific treatment techniques (Horvath & Greenberg, 1989). Thus, the alliance is embedded within the specific treatment method (Bordin, 1979). The goals and tasks specified appear intimately linked to the nature of the relationship between therapist and patient.

For example, the kind of bond developed when a therapist presents a patient with a form and asks him to make a daily record of his submissive and assertive acts, and of the circumstances surrounding them, appears quite different from the bond developed when a therapist shares his or her feelings with a patient, in order to provide a model, or to provide feedback on the patient’s impact on others. (Bordin, 1979, p. 254)

In treating poorly functioning patients with PDs, the therapeutic stance—being empathetic, attuned, honest, and curious—may facilitate and help maintain a bond between patient and therapist (Bateman & Fonagy, 2016). However, tasks and goals also seem of superior importance, and “all effective treatments share the characteristics of consistency, coherence and continuity, qualities particularly relevant to borderline personality disorder” (Bateman et al., 2018, p. 44). Research has found that improvements in the alliance lead to a reduction in BPD pathology (Levy et al., 2010; Spinhoven et al., 2007). However, within the field of evidence-based treatments for BPD, we have found no investigations of the three facets of the working alliance. Further, within the larger field of psychotherapy research, few have studied the subparts of alliance (Stiles & Goldsmith, 2010), which motivated the present study (Paper II and «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder»).

 

Methods

This article is a quantitative study of longitudinal data.

Subjects

The studied sample comprised 155 patients treated on a regular basis with MBT on a specialist mental health service level during 2009–2016.

 

Mentalization-based treatment

The MBT program was an intensive, long-term outpatient treatment in accordance with MBT manuals (Karterud, 2011, 2012; Karterud & Bateman, 2010). The first year included weekly individual and group therapy sessions and psychoeducational group session (12 sessions). The frequency of individual therapy was gradually reduced in the second and third years, while group sessions continued throughout treatment. Treatment had an upper time limitation of 36 months.

 

Therapists

The team was multidisciplinary (three psychiatric nurses, three psychiatrists, an art therapist, a physiotherapist, a social worker, and two psychologists). Eight were qualified group analysts, one was qualified in psychoanalysis, and one was qualified in individual psychodynamic psychotherapy; 67% are female, and the mean age (year 2009) was 53 (SD = 9). Other individual therapists involved in the research period were different resident doctors and psychologists in training. All had basic MBT training and attended regular weekly video-based supervision by qualified MBT supervisors.

 

Therapist mentalization-based treatment fidelity

The present study includes measures for treatment fidelity (ratings of MBT adherence and competence) in all three papers. MBT adherence and competence was assessed using videorecorded therapy sessions, the MBT Adherence and Competence Scale (Karterud et al., 2013), and the Adherence and Competence Scale for Mentalization-based Group Therapy (Karterud, 2015). On a 1–7 scale, a score of four or higher indicates adequate MBT adherence/competence. In 2013–2015, five raters evaluated 19 individual sessions (eight therapists) and nine group sessions in the program. For individual therapists, the mean adherence level was 4.7 (SD = 1.2) and the mean MBT competence level was 4.4 (SD = 1.2) (Kvarstein et al., 2015). For group therapists, the mean adherence level was 5.1 (SD = 1.37) and the mean competence level was 4.9 (SD = 1.3) (Kvarstein et al., 2020). This is comparable to a recent RCT study of MBT in groups for adolescents with BPD (Beck et al., 2020). In that study with experienced and motivated therapists, the mean overall adherence score was 5.47 (SD = 0.80) and the mean overall competence was 5.53 (SD = 1.10).

 

Baseline assessment

 

Assessment of diagnoses and personality functioning at the start of treatment (baseline)

Diagnoses were based on the Mini International Neuropsychiatric Interview (MINI) version 4.4 for DSM Axis-I diagnosis (Sheehan et al., 1998) and the Structured Clinical Interview for DSM Disorders (SCID-II) for DSM Axis-II diagnosis (First et al., 1994) (DSM-IV). Experienced (10–20 years of practice) and specifically trained clinical staff performed the MINI and the SCID-II interviews.

 

Aspects of personality functioning were measured using the Severity Indices of Personality Problems (SIPP-118), a 118 item self-report questionnaire aimed at measuring five core domains of personality pathology—self control, identity integration, responsibility, relational functioning, and social concordance (Verheul et al., 2008). High scores indicate better adaptive functioning, whereas lower scores indicate more maladaptive personality functioning. The SIPP subscales have generally yielded adequate to strong internal consistency in PD samples, with α scores ranging from .62–.89 (Feenstra et al., 2011; Verheul et al., 2008). A Norwegian replication of the original Dutch study found good cross-national validity of the SIPP-118 (Arnevik et al., 2009). Further, all facets of SIPP have good discriminative properties with respect to differentiating between a nonclinical sample, a clinical sample without PD, and a clinical PD sample (Pedersen et al., 2017a).

 

Quality of Life (QoL) was measured at the start and end of treatment using the EuroQol (EQ-5D). The EQ-5D is a self-report questionnaire that provides a simple method to measure health problems in five dimensions—mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. EQ-5D is a useful tool to assess QoL in patients with BPD (van Asselt et al., 2009) and is sensitive to change in patients with PDs. The QoL index score as measured with the EQ-5D is expressed as a single index score ranging from 0.33 (worst imaginable health state) to 1.00 (best imaginable health state). According to reports on the QoL index score with BPD patients, the score ranges from .44–.57 (Laurenssen et al., 2016). One Dutch study included 403 BPD patients and found a mean QoL index score of .48, which is comparable to that of patients with severe physical conditions, such as stroke or Parkinson’s disease (Laurenssen et al., 2016). The mean QoL index score of the general population in Western societies ranges from .83–.87 (Saarni et al., 2007).

 

Interpersonal problems were assessed using the Circumplex of Interpersonal Problems (CIP; Pedersen, 2002). CIP is a 48-item version of the Inventory of Interpersonal Problems‐Circumplex version (IIP-C) self-report questionnaire (Alden et al., 1990). Severity is rated on a 0–4 scale (0: not at all; 4: extremely). The mean sum score (CIP) correlates r = .99 with the original IIP-C sum score (Pedersen, 2002). The reliability of CIP is high ((four‐day test–retest coefficient [ICC, 2.1], r = .96, 95% CI; .93–.98; Pedersen et al., 2011). In a non‐clinical Norwegian sample, mean CIP scores were 0.5 (SD = 0.3) (Pedersen, 2002). Including one standard deviation, the clinical/non‐clinical CIP cut‐off score is 0.8. CIP scores of 1.7 and above indicate severe interpersonal distress, scores of 1.3–1.6 indicate significant to moderate interpersonal distress, and scores below 1.2 indicate insignificant to mild interpersonal distress (Pedersen, 2002).

 

Measure for therapeutic alliance: Working Alliance Inventory

The vast majority of empirical studies of the alliance reference Bordin’s writings as a way of defining the concept (Horvath, 2018). There are several ways to assess the concept of working alliance (Bordin, 1979, 1994), such as by rating the alliance using the Working Alliance Inventory–Observer version (Darchuk et al., 2000). In «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder», the Working Alliance Inventory–Short Revised (WAI‐SR; Hatcher & Gillaspy, 2006) was used to measure the patient-rated alliance. Although the alliance is not reducible to the patient’s experience of it, the patient’s experience is important in understanding the relationship between alliance and outcome. In fact, patient-rated alliance has been a consistent predictor of outcome for decades (Fluckiger et al., 2018; Horvath & Symonds, 1991). Proposed by Bordin (1979), the original WAI is a 36-item measure that assesses three aspects of the therapeutic relationship: (a) the bond between patient and therapist, (b) the extent to which the patient and therapist agree on the goals of treatment, and (c) the extent to which the patient and therapist see the tasks of therapy as relevant. All 36 items may be aggregated to create a total score, with high scores reflecting strong alliances. The WAI has been shown to have good internal consistency (  = .93) and adequate convergent and predictive validity (Horvath & Greenberg, 1989). There is an abundance of scales to measure the working alliance (Falkenstrom et al., 2015), but the WAI has the clearest conceptual foundation, as it was developed based on Bordin’s (1979) conceptualization of the alliance as composed of agreement on goals and tasks and supported by bonds. The WAI includes no items referring to specific treatment methods. In short, these measures give a general overall reading of the state of the working alliance at the session level.

Although there is some evidence that these measures tap discernible dimensions of alliance (e.g., Hatcher & Gillaspy, 2006), a compelling argument can be made that these measures are like room thermometers in that they give an overall reading of the quality of the working alliance without being very localized or specific about it.” (Hatcher, 2010, p. 15)

Importantly, Falkenstrom et al. (2015) reported that the intercorrelation between the task and goal factors in their three-factor model was high and concluded that a two-factor structure where the task and goal factors are collapsed into one is psychometrically more defensible than a three-factor structure. This makes two main factors of interest to investigate 1) bonds and 2) tasks and goals. The WAI-SR is a short form of the patient version of the (WAI; Horvath & Greenberg, 1989) and consists of 12 items rated on a seven-point scale ranging from “never” to “always.” Based on Bordin’s (1979) conceptualization of the working alliance, it has three subscales, goals, tasks, and bonds, with four items for each. The short version consists of the items with the highest load on each of the three subscales. Each item is rated on a seven-point scale, with higher scores indicating better alliance. The WAI-SR has been found to have good psychometric properties (Munder et al., 2010).

 

In our study, we investigated the three subscales in separate, independent models. Scores above four indicate satisfactory alliance. The WAI-SR scores are presented in Table 2. In the first period of our study, patients received the “old WAI version” (n = 34 patients). From June 2012, all patients received the “new WAI version” (n = 71). Eighty patients in the current investigation have longitudinal data including for both versions of WAI. There are some minor changes between the old and new versions of WAI. However, most variance between the two versions is within and not between the three alliance categories; at a conceptual level, the two WAI versions measure the same in terms of tasks, goals, and bonds.

 

Main measure for clinical outcome: Global assessment of functioning

The first standardized and broadly used instrument for assessing patients’ overall mental health was introduced by Luborsky in 1962 when he developed the Health-Sickness Rating Scale (HSRS; Luborsky & Bachrach, 1974). Some decade later, Endicott et al. (1976) modified the original instrument, which resulted in the Global Assessment Scale (GAS). Both the HSRS and the GAS are single 100-point rating scales reflecting overall functioning from 1 to 100, where 100 would be the hypothetically sickest patient imaginable and 1 the hypothetically healthiest individual. GAF is a widely used measure; it is observer-rated and is a composite variable reflecting both symptoms and functioning, which can be seen as an advantage. GAF includes both symptoms and functioning and reports the lowest value of the two. In «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder», GAF was chosen as parameter for clinical outcomes, as the observer-rated GAF provides a composite score combining social and symptom-related dysfunction (0–100 scale, Axis V, DSM-IV) (Pedersen et al., 2018). Higher GAF scores indicate better overall psychosocial functioning, and a score of 60 represents the cut-off level between mild/no impairment and moderate/severe impairment. Conventional interpretations of severity indicated by GAF scores are as follows: mild (61–70), moderate (51–60), and severe (41–50) (Pedersen et al., 2018). Staff therapists were trained (GAF assessment courses within the Norwegian Network for Personality Disorders) and then performed GAF evaluations. The reliability of the applied method for GAF assessments was tested in 1998 (staff consensus scores) and 2001 (independent scores) (Pedersen et al., 2007). Clinical vignettes were scored by staff consensus in eight different treatment units (including the studied treatment unit) by 58 staff members. Reliability for consensus scores was high (ICC 2.1, single measure, absolute agreement definition: 0.94, 95% CI 0.85–0.98). Adequate reliability and validity of the GAF was reported in a publication by Pedersen et al. (2018). Consistency of GAF scores across units and raters was also high (generalizability coefficients of absolute decision (the score) range .86–.95) (Pedersen et al., 2007). On treatment termination, 59% had scores of 60 or higher (mean GAF end score of 70, SD = 7), and 41% had end scores less than 60 (mean GAF score of 51, SD = 7) in our sample (N = 155). In this study, the sample was divided into two subgroups:

  • Patients with clinical outcomes within a clinical range (GAF below 60) at the end of treatment
  • Patients with clinical outcomes within a non-clinical range (GAF equal or above 60) at the end of treatment

 

Supplementary clinical outcome measures

As our main indicator of clinical outcome was observer-rated, we included two supplementary patient-rated measures to assess functioning and symptom distress, The Brief Symptom Inventory 18 (BSI-18) and the Work and Social Adjustment Scale (WSAS). In «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder», three variables were chosen to reflect clinical outcome—two self-report measures (BSI-18 and WSAS) and the observer-based assessment of GAF. GAF improvement trends in the sample corresponded with improvement trends for the two self-reports. We therefore chose the variable GAF as a main measure to indicate improvement because it had the advantage of combining both symptoms and functioning, and we had more complete GAF data for the final assessment.

 

Work and Social Adjustment Scale

The WSAS is an outcome measure assessing the degree of functional impairment (i.e., work, social, and private leisure activities and home, work, and social relations) (Pedersen et al., 2017b). Each of the items is rated on a nine‐point Likert scale from “not at all” (0) to “severely impaired” (8). The total sum score of all items ranges from 0–40, where higher scores indicate more distress. Scores below 10 indicate a subclinical population, scores from 10–20 indicate significant but not severe functional impairment, and scores above 20 indicate moderately severe to severe impairment (Mundt et al., 2002). Patients also reported current status regarding work functioning, in terms of how many months they participated in more than 50% work or study during the previous year.

 

The Brief Symptom Inventory 18

The BSI-18 is a self-report questionnaire assessing symptom distress (depression, somatization, and anxiety on a 0–4 format scale; 0: “not at all”, 4: “extremely”). BSI-18 includes an overall severity index, the mean sum score (BSI). The BSI-18 is derived from the 53-item BSI, a shortened form of the (SCL-90-R; Derogatis, 2000). The BSI-18 applies the same clinical case rule originally developed for the SCL-90-R. A conservative cut-off for clinical/non-clinical ranges of severity (sum score 0.8) is based on Norwegian sample norms and patient samples (Pedersen & Karterud, 2004). The BSI-18 was administered to all patients in MBT.

 

Data analysis

 

Mixed model analysis

Longitudinal data characteristically imply repeated observations of the same individual. Such repeated observations cannot be regarded as independent observations (Fitzmaurice et al., 2008). The sample in «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» also had unbalanced data with different numbers of assessments per patient. Characteristically, mixed models do not require that all subjects have equal numbers of assessments or that the time intervals between assessments are constant (Norusis, 2008). Unlike somewhat simpler methods, such as repeated measures ANOVA, Linear Mixed Models (LMM; Singer & Willett, 2003) allows for the inclusion of cases with missing values and not only patients with complete datasets. The LMM method was chosen to maximize the use of available patient data. The modelling procedure starts with a model where the time interactions and random effects are not specified. This first unspecified model provides an estimate (fixed effect), corresponding residual variation, and log likelihood estimations of the goodness of model fit (Singer & Willett, 2003). Further specification of a linear model is a stepwise procedure adding a time interaction (fixed effect) and then random effects in accordance with the principle of achieving the best possible goodness of model fit (see «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» for equations and details).

 

The three WAI-S/SR subscales were the dependent variables. The sample was modelled with the GAF ratings in two subgroups according to outcomes (scores at discharge) above or lower than clinical/nonclinical cut-off levels (60) as predictor. The LMM included longitudinal change of WAI-S/SR subscales and variation associated with the dichotomous GAF variable as a predictor, as well as a moderator interaction combining the dichotomous GAF variable and patient factors.

 

All included patients had at least one assessment (even patients with only one assessment can be included in the analyses) (Singer & Willett, 2003), and the mean number of WAI-S/SR assessments was 3.2 (SD = 1.8, range 1–9). The sample had unbalanced data with different numbers of assessments per patient. As LMM incorporates unbalanced data and uses all available data for each individual trajectory, we did not use imputation methods for missing data. A variable counting numbers of assessment points for each individual captured a relevant missing data pattern. To investigate the effect of this missing data pattern on the outcomes, the variable was added as a predictor in all three working alliance subscale models (Hedeker & Gibbons, 1997). Analyses showed poorer initial alliance ratings for patients with fewer assessments (p < 0.05 for all working alliance subscales) but no significant effect of the variable on alliance development over time (p > 0.05 for all WAI subscales).

 

Ethics

All research was performed on anonymous clinical data from an anonymous research database with approved procedures. All patients gave written informed consent to participate in the research. The treatment unit collected clinical data, which was registered in an anonymous database administrated by Oslo University Hospital. Procedures for data collection ensured that participating individuals could not be identified. Data security systems were approved by the Data Protection Official at Oslo University Hospital. Because the data was anonymous, ethical approval was not required from the Regional Committee for Medical Research and Ethics.

 

Results

«Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» demonstrated satisfactory levels of initial working alliance among BPD patients in MBT irrespective of clinical outcomes. MBT therapies with good outcome were characterized by a temporal increase in alliance strength as reported by the patients: In the model with Goals as dependent variable, the predictor indicating subgroups with good and poorer clinical outcomes accounted for 23% of the slope variation for this WAI-S/SR subscale. Corresponding models with bonds and tasks accounted for 25% and 35% slope variation, respectively. Comorbid paranoid PD was more frequent in the subgroup with poor outcomes, and also associated with poorer alliance development in this subgroup. However, there were patients with comorbid PD in the good outcome group as well (i.e., achieving an alliance with these patients is difficult, but not impossible). Differences in alliance development according to outcome were most pronounced for the subscale tasks.

 

Descriptive data in subgroups with different outcomes

 

Patient factors

The patients’ baseline levels indicated severe problems with functioning and distress at treatment onset but no significant differences in severity by outcome subgroup. The sample was characterized by , patients with BPD, reports indicating poor QoL, considerable comorbidity, and personality problems across all domains, especially within the domains of identity and self-control. The good outcome subgroup was characterized by younger age, fewer patients with no months of work/study at all previous year, and fewer with comorbid Paranoid PD and mood disorder. In the preliminary analyses, age and paranoid PD explained 2%–5% of the variation in GAF slope.

 

Treatment factors

Nearly all patients in the good outcome subgroup completed treatment according to plan (91%), versus 58% in the poor outcome subgroup. Mean treatment duration was 27 months (SD 13), early drop out (< 6-month duration) was minimal (2.5%), and did not differ by subgroup. In the good outcome group, there were no later drop-outs, while 9% were later drop-outs in the poor outcome group.

 

Main analyses: Longitudinal course of working alliance

Initial levels of working alliance (all subscales) were well within an acceptable range, and there was a significant increase of all three working alliance subscales over time. There was significant longitudinal between-subject variation. These change patterns also remained significant in models a) controlling for variation associated with different WAI versions and b) investigating possible bias of different assessment numbers.

 

Variation associated with good and poor outcome subgroups

The good and poor outcome subgroup predictor was investigated in each of the three models. Initial levels of Goals, Bonds, and Tasks did not differ by subgroup, but change over time was significantly different by subgroup. The subscale Goals accounted for 23% of the WAI-S/SR slope variation, Bonds for 25%, and Tasks for 35%. These findings remained significant for the three subscales—Goals, Bonds, and Tasks—in models a) controlling for variation associated with different WAI versions, b) investigating possible bias of different assessment numbers, and c) corresponding differences were also found in models investigating the dichotomous WSAS and BSI outcome variables as predictors. In the good outcome subgroup, ratings of Goals, Bonds, and Tasks increased significantly over time. In the poor outcome subgroup, change over time was not significant for any of the WAI-S/SR subscales.

 

Variation associated with patient factors

Relevant patient factors (age, comorbid mood disorder, and comorbid paranoid PD) were investigated as separate predictors added to the three WAI-S/SR subscale models. Mood disorder was associated with significantly lower initial alliance levels, but not deviating change over time. Age was not associated with significantly deviating initial alliance levels or deviating change over time, but explained some longitudinal variation. Paranoid PD was not associated with baseline deviation of WAI-S/SR ratings in any of the two outcome subgroups. The presence of paranoid PD was associated with poorer development of WAI-S/SR subscales over time in the poor outcome subgroup, but not in the good outcome subgroup. Corresponding results for paranoid PD were also found in models investigating the supplementary dichotomous WSAS and BSI outcome variables. In the good outcome subgroup, ratings for goals, bonds, and tasks increased significantly over time (for all p < 0.05). In the poor outcome subgroup, change over time was not significant for any of the WAI-S/SR subscales (p > 0.1).

 

Discussion

A recent study of 15,000 people receiving a range of psychological treatments across 184 services in England and Wales found that 5.2% of the patients had lasting negative effects from treatment. Patients who were unsure what type of therapy they received reported more negative effects (Crawford et al., 2016). This is perhaps not surprising, but still such findings underscore how important it is that patients “need to accept and engage in the therapeutic process not simply be engaged with the therapist but actively working toward a goal in a coherent way” (Wampold & Imel, 2015, p. 259), that is, focus on tasks and goals in therapy. In congruence with Paper II and indicating the importance of goal-directed work in MBT, «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» highlights the importance of the working alliance (especially tasks and goals) in this therapy. The following four major findings will be discussed in depth:

 

  • Positive temporal development of therapeutic alliance during therapy characterized good outcomes.
  • Tasks and goals are particularly important.
  • Initial alliance ratings were high.
  • Comorbid paranoid PD is difficult but possible.

 

Our first major result was that MBT treatments with good outcome displayed a positive temporal development of therapeutic alliance. The importance of the alliance is particularly pronounced when treating patients with personality pathology (Benjamin et al., 2001; Clarkin & Levy, 2004; De Bolle et al., 2010; Muran et al., 2009; Piper & Joyce, 2001). In fact, as mentioned earlier, the standardized effect of WAI-S on subsequent change was six times greater than in the group without personality problems (Falkenstrom et al., 2013, p. 325). A stronger therapeutic alliance has been shown to predict greater improvement in BPD (Barnicot et al., 2012; Barnicot et al., 2011). For example, Marziali et al. (1999) tested how the therapeutic alliance in an RCT of interpersonal group psychotherapy and individual dynamic psychotherapy for BPD contributed to the outcome. The authors reported that alliance ratings were related to outcome in both individual and group therapy. Linehan (1993) suggested that a good relationship that is high in rapport is essential to treating clients with BPD because these individuals may be unable to fully utilize any other form of reinforcement to change behavior. Within the field of MBT, Fonagy and Bateman (2006) have introduced attachment as a core mechanism of change and state that concepts “such as the therapeutic alliance speak directly to the importance of activating the attachment system” (p. 411). Recently, the importance of alliance in MBT has been described in a qualitative study of MBT patients with comorbid substance abuse. Morken et al. (2019) state that

[According] to our findings, good therapists know when to keep distance and when to come close, they are explicit about the content of own mind, they address the elephant in the room, and they tolerate strong affect. They put focus explicitly on the relationship between themselves and their patients. These findings resonate well with existing knowledge on therapist factors where the ability to form strong alliances and facilitative interpersonal skills is found to be essential. (Morken et al., 2019, pp. 10–11).

 

According to Bordin (1994), as therapy progresses the strength of the working alliance would build and ebb in the normal course of events, and the repair of these stresses in the alliance offers potent therapeutic possibilities and makes a direct contribution to clients’ change. This is in line with the theory that negotiating the alliance and repairing alliance ruptures may be especially important in BPD treatment (e.g., Morken et al., 2019). Linehan has also argued that alliance problems are frequent and that their resolution can lead to the client’s acquiring skills that can be used in interpersonal difficulties outside the sessions. Linehan’s (1993) “techniques of acceptance” involve the therapist’s ability to see reasonableness in the client’s dysfunctional behaviors, accept the client’s hostile affect, and recognize his or her own mistakes. Such an intervention style seems to foster (epistemic) trust, which may be particularly important when working with attachment disturbances. For instance, in working with trauma victims, Hembree et al. (2003) have noted that trust is an absolutely essential element of the therapeutic relationship in prolonged exposure therapy because of the difficult and distressing nature of the process. However, despite attachment pathology being at core of BPD, we have found no quantitative studies investigating the relationship between alliance and outcome in MBT.

 

Could it simply be that “good” patients form good alliances and are destined to get better? Paper II indicated that experienced change would in turn lead to increased epistemic trust and improved working alliance. Therefore, observable symptom change may foster epistemic trust in the treatment and thus the patient’s adherence to therapy (focus on tasks and goals). Several studies have demonstrated that the level of early alliance can be the product of previous symptomatic changes (e.g., Barber et al., 2000; Derubeis & Feeley, 1990). DeRubeis et al. (2005) have presented an “alliance-as-outcome” hypothesis whereby the alliance is partially or even wholly an effect of previous symptom reduction rather than the cause of symptom reduction (e.g., Crits-Christoph et al., 2006b). “Thus, alliance is at least in part a pseudo-outcome, and the alliance–outcome correlation represents the correlation between two outcome measures” (Baldwin et al., 2007, p. 847). As we have seen arguments that a strong therapeutic alliance may be an appropriate therapeutic outcome for BPD patients (Barber et al., 2010), this could be particularly true for these patients. However, if alliance is a consequence of initial symptom change, even partially, then those patients with higher alliances should have better outcomes. In contrast, we observed that within therapists those patients with relatively high alliance ratings did not have better outcomes than those patients with relatively low alliance ratings. (Baldwin et al., 2007, p. 848)

Importantly, Tasca and Lampard (2012) have proposed a reciprocal influence model for the relationship between alliance and symptom change in which alliance and symptoms affect each other throughout treatment, and “our results support this model” (Falkenstrom et al., 2013, p. 326). The transference “is a universal phenomenon of the human mind, it decides the success of all medical influence, and in fact dominates the whole of each person’s relations to his human environment” (Freud, 1961, p. 42). Importantly, without the reference to any unconscious components, Bordin’s (1994) working alliance captures the core curative therapy process conceived in Freud’s classical concept of transference (Horvath, 2018, p. 504). One concept identified as the practical common denominator across alliance measures, is the “clients enthusiastic participation” (Hatcher et al., 1995) in treatment. Hence, the findings in Paper II and III would be aligned with the model by Tasca and Lampard (2012), and it seems reasonable to assume that the patients’ degree of enthusiastic participation would typically be associated with perceived improvement.

 

Let us approach alliance as “a way of looking at the relationship through the lens of effective goal-directed work” (Hatcher, 2010, p. 25). If this is indeed the case, one could argue that to establish agreement about the tasks and goals of therapy, the alliance is dependent on the delivery of a particular treatment (Wampold, 2019). However, in many manualized treatments, “the alliance has typically been treated as a factor that facilitates the use of and adherence to specific techniques not as a change mechanism itself” (Castonguay et al., 2010, p. 154). In addition to an alliance itself being a potential therapeutic outcome with BPD patients (e.g., a focus on alliance and alliance ruptures is in itself curative), we know little about the importance of the three subscales of alliance in psychotherapy in general and particularly in long term-treatments (Stiles & Goldsmith, 2010). There has been little research concerning alliance in (evidence-based) treatment for BPD, and due to “the paucity of research in this area, [Levy et al., 2010] had no reason to predict that different aspects of the alliance bond, agreement on tasks, and agreement on goals would be differentially affected” (p. 415). As Paper II indicated that the bond part of the alliance was an asset the highly rated therapists utilized to focus on tasks and goals, we became curious as to whether tasks and goals would characterize good MBT outcome better than bonds. Interestingly, in this respect Falkenstrom et al. (2015) state that tasks and goals may be one factor (not two), something which is in line with our findings in Papers II and III in that the development of Bonds seems somewhat different than tasks and goals. However, they conclude that because “meaningful differences between these scales are sometimes found in substantive research (...) it may be premature to conclude that the task and goal factors should be combined into one” (p. 591).

 

The second major finding in «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» was that an increase in tasks and goals is particularly characteristic for treatments with good outcome in MBT. This is what we would expect to find from such an above-discussed interplay between symptom reduction and alliance, as tasks and goals are the parts of the alliance most connected to actual observable change (for the patient). In line with such an argument, Brotman (2004) suggested that therapists’ “encouraging active involvement in their patients will improve patient adherence” (p. 35): Although encouraging active involvement is a general alliance-enhancing technique, here the focus is quite specific; patients should facilitate therapist adherence to concrete techniques, and therapists should do whatever they can to encourage patients to participate in this way. Consequently, actual perceived/experienced improvement may help patients feel competent (efficacy), increase their trust in both the therapist and the method, and understand and collaborate on the tasks and goals of therapy, thus enhancing the probability of success and building the alliance further. In turn, a strong alliance will increase the likelihood that patients will agree with their therapists on the tasks and goals of therapy, which will affect outcomes (Baldwin et al., 2007; Wampold et al., 2007). Therefore, when change occurs and an alliance is adequate, it makes sense that the alliance effect is especially strong when working with (B)PD patients (e.g., it can offset a synergy effect between increased epistemic trust, actual change, and increased agreement on tasks and goals).

 

The third major finding in «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» was that the average initial alliance levels were above 4, which is considered satisfactory. Obviously, patients’ attachment style and social competencies may affect their ability to foster a strong alliance with their therapist (Fonagy & Bateman, 2006; Mallinckrodt, 2000). Therefore, it was surprising that initial ratings were in the satisfactory range. However, we know that good alliance is created very early in treatment. In fact, it has been reported to be high before some patients even meet their therapists (Iacoviello et al., 2007). Further, given that all patients are required to participate in 12 psychoeducation sessions upon enrolment in the MBT program, one possible explanation for the initial high alliance reported in «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» “is that it may be easier to follow the treatment in the first phase of MBT, in the period providing more structured psychoeducation” (Kvarstein et al., 2020, pp. 8–9). Importantly, the initial working alliance ratings—goals, bonds, and tasks—were not associated with outcome

 

The fourth major result in «Development of therapeutic alliance in mentalization-based treatment—Goals, Bonds, and Tasks in a specialized treatment for borderline personality disorder» was that comorbid paranoid PD was more frequent in the subgroup with poor outcomes and associated with poorer alliance development in this subgroup. However, there were patients with paranoid PD in the good outcome group as well, and here, comorbid paranoid PD was not associated with poorer alliance development in the good outcome subgroup. This is an important clinical finding, as it imprints the therapist to have and display hope and work towards a common therapeutic goal. Somewhat similarly, Baldwin et al. (2007) argued that the “therapist attributions of resistance or maladaptive attachment styles as an explanation of a poor alliance, according to our findings, would be irrelevant with regard to outcomes, although these explanations may be grist for therapeutic work” (p. 851). Interestingly, in terms of attachment styles, or at least mentalizing abilities (measured by Movie for the Assessment of Social Cognition; MASC), one recent study (Kvarstein et al., 2020) indicated that patients who tended to hypermentalize felt increasingly more able to bond with their therapist and find agreement on the aims and tasks of therapy. One may wonder whether a hypermentalizing style resembles an ambivalent (instead of a more dismissive/disorganized) attachment style. If so, that could provide explanatory power to the negative treatment effects often reported for avoidant PD (Kvarstein, 2013). However, one should be careful when associating alliance with personality categories (e.g., applying categorical variables to constructs deemed dimensionally distributed). Pedersen (2008) found that

the number of personality traits defining these disorders were only slightly associated to the perception of the treatment milieu (…) it was the number of PD criteria, not the presence or absence of PD diagnosis that contributed to the variations in the perceived treatment milieu. (p. 72–73)

 

Quiz:

  1. What is the main objective of the study?
    a) To investigate the development of the therapeutic alliance in mentalization-based treatment (MBT) therapies for borderline personality disorder (BPD)
    b) To assess the effectiveness of MBT for treating BPD
    c) To evaluate the impact of comorbid mood disorders on the therapeutic alliance in MBT for BPD
    d) To determine the role of personality disorders in alliance development in MBT for BPD

  2. How was the sample divided in this study?
    a) According to the severity of BPD symptoms
    b) According to the presence of comorbid mood disorders
    c) According to the Global Assessment of Functioning (GAF) scores at the end of treatment
    d) According to the duration of treatment

  3. What was the method used for statistical analysis in this study?
    a) Linear regression
    b) Logistic regression
    c) T-test
    d) Linear mixed models

  4. What was the primary measure of the therapeutic alliance in this study?
    a) The Working Alliance Inventory
    b) The Symptom Checklist-90-Revised
    c) The Beck Depression Inventory
    d) The Personal Assessment of Intimacy in Relationships scale

  5. What were the main findings of this study?
    a) Initial levels of the therapeutic alliance did not differ between the good and poor outcome subgroups
    b) Comorbid mood disorders had a lasting negative impact on the therapeutic alliance in patients with BPD
    c) Good outcome therapies were characterized by a process where the therapeutic alliance grew over time
    d) Poor outcome therapies were characterized by a process where the therapeutic alliance declined over time

  6. What was the most significant difference between the good and poor outcome subgroups in terms of alliance development over time?
    a) The Goals subscale
    b) The Bonds subscale
    c) The Tasks subscale
    d) There was no significant difference between the two subgroups

  7. How was comorbid paranoid personality disorder (PD) associated with alliance development in the poor outcome subgroup?
    a) It was not associated with alliance development in the poor outcome subgroup
    b) It was associated with a positive impact on alliance development in the poor outcome subgroup
    c) It was associated with a negative impact on alliance development in the poor outcome subgroup
    d) It was not mentioned in the study

  8. What is mentalizing?
    a) A form of imaginative mental activity enabling perception and interpretation of the mental states of others
    b) A process of systematic self-reflection
    c) A technique for managing emotions
    d) A method of improving communication skills

  9. What is epistemic trust?
    a) The ability to trust significant social information from others
    b) The ability to accurately understand and interpret the thoughts and feelings of others
    c) The ability to form close relationships with others
    d) The ability to regulate one's own emotions

  10. What is the "last chance saloon"?
    a) A term used to describe the feeling of desperation that may lead patients to seek treatment
    b) A term used to describe the period of time when patients are most receptive to treatment
    c) A term used to describe the final stage of treatment
    d) A term not mentioned in the study

Correct answers:

  1. a) To investigate the development of the therapeutic alliance in mentalization-based treatment (MBT) therapies for borderline personality disorder (BPD)
  2. c) According to the Global Assessment of Functioning (GAF) scores at the end of treatment
  3. d) Linear mixed models
  4. a) The Working Alliance Inventory
  5. c) Good outcome therapies were characterized by a process where the therapeutic alliance grew over time
  6. c) The Tasks subscale
  7. c) It was associated with a negative impact on alliance development in the poor outcome subgroup
  8. a) A form of imaginative mental activity enabling perception and interpretation of the mental states of others
  9. a) The ability to trust significant social information from others
  10. a) A term used to describe the feeling of desperation that may lead patients to seek treatment

 

References

Alden, L. E., Wiggins, J. S., & Pincus, A. L. (1990, Winter). Construction of circumplex scales for the Inventory of Interpersonal Problems. J Pers Assess, 55(3-4), 521-536. https://doi.org/10.1080/00223891.1990.9674088

 

Arnevik, E., Wilberg, T., Monsen, J. T., Andrea, H., & Karterud, S. (2009). A cross‐national validity study of the Severity Indices of Personality Problems (SIPP‐118). Personality and mental health, 3(1), 41-55.

 

Baldwin, S. A., Wampold, B. E., & Imel, Z. E. (2007). Untangling the alliance-outcome correlation: Exploring the relative importance of therapist and patient variability in the alliance. Journal of Consulting and Clinical Psychology, 75(6), 842.

 

Barber, J. P. (2009). Toward a working through of some core conflicts in psychotherapy research. Psychotherapy Research, 19(1), 1-12. https://doi.org/Pii 908627667

10.1080/10503300802609680

 

Barber, J. P., Connolly, M. B., Crits-Christoph, P., Gladis, L., & Siqueland, L. (2000, Dec). Alliance predicts patients' outcome beyond in-treatment change in symptoms. J Consult Clin Psychol, 68(6), 1027-1032. https://doi.org/10.1037//0022-006x.68.6.1027

 

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. 29–43). The Guilford Press.

 

Barnicot, K., Katsakou, C., Bhatti, N., Savill, M., Fearns, N., & Priebe, S. (2012, Jul). Factors predicting the outcome of psychotherapy for borderline personality disorder: a systematic review. Clin Psychol Rev, 32(5), 400-412. https://doi.org/10.1016/j.cpr.2012.04.004

 

Barnicot, K., Katsakou, C., Marougka, S., & Priebe, S. (2011, May). Treatment completion in psychotherapy for borderline personality disorder: a systematic review and meta-analysis. Acta Psychiatr Scand, 123(5), 327-338. https://doi.org/10.1111/j.1600-0447.2010.01652.x

 

Bateman, A., Campbell, C., Luyten, P., & Fonagy, P. (2018). A mentalization-based approach to common factors in the treatment of borderline personality disorder. Current Opinion in Psychology, 21, 44-49. https://doi.org/10.1016/j.copsyc.2017.09.005

 

Bateman, A., & Fonagy, P. (2016). Mentalization-based treatment for personality disorders: A practical guide. Oxford University Press.

 

Beck, E., Bo, S., Jorgensen, M. S., Gondan, M., Poulsen, S., Storebo, O. J., Fjellerad Andersen, C., Folmo, E., Sharp, C., Pedersen, J., & Simonsen, E. (2020, May). Mentalization-based treatment in groups for adolescents with borderline personality disorder: a randomized controlled trial. J Child Psychol Psychiatry, 61(5), 594-604. https://doi.org/10.1111/jcpp.13152

 

Bein, E., Anderson, T., Strupp, H., Henry, W., Schacht, T., Binder, J., & Butler, S. (2000, Feb 1). The effects of training in time-limited dynamic psychotherapy: changes in therapeutic outcome. Psychother Res, 10(2), 119-132. https://doi.org/10.1080/713663669

 

Benjamin, J., Ebstein, R. P., & Belmaker, R. H. (2001). Genes for human personality traits: "endophenotypes" of psychiatric disorders? World J Biol Psychiatry, 2(2), 54-57. https://doi.org/10.3109/15622970109027494

 

Benjamin, L. S., & Critchfield, K. L. (2010). An interpersonal perspective on therapy alliances and techniques. In J. C. Muran & J. P. Barber (Eds.), The therapeutic alliance: An evidence-based guide to practice (pp. 123-149). Guilford Press.

 

Beutler, L. E., Malik, M., Alimohamed, S., Harwood, T. M., Talebi, H., Noble, S., et al. (2004). Therapist variables. In M. J. Lambert (Ed.), Bergin and Garfield’s handbook of psychotherapy and behavior change (pp. 227−306). Wiley.

 

Bordin, E. S. (1979). The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy: Theory, research & practice, 16(3), 252.

 

Bordin, E. S. (1983). A Working Alliance Based Model of Supervision. Counseling Psychologist, 11(1), 35-42. https://doi.org/Doi 10.1177/0011000083111007

 

Bordin, E. S. (1994). Theory and research on the therapeutic working alliance: New directions. In A. O. Horvath & L. S. Greenberg (Eds.), The working alliance: Theory, research, and practice (pp. 13–37). Wiley.

 

Brotman, M. A. (2004). Therapeutic alliance and adherence in cognitive therapy for depression [Doctoral thesis, University of Pennsylvania]. Dissertation Abstracts International, 65(3146), 6B. (UMI No. 3169565).

 

Castonguay, L., Constantino, M., McAleavey, A., & Goldfried, M. (2010). The therapeutic alliance in cognitive-behavioral therapy. In J. Muran & J. Barber (Eds.), The therapeutic alliance: An evidence-based guide to practice (pp. 150–171). New York: Guilford Press.

 

Clarkin, J. F., & Levy, K. N. (2004). The influence of client variables on psychotherapy. In M. J. Lambert (Ed.), Bergin and Garfield’s handbook of psychotherapy and behavior change (5 ed., pp. 194–226). Wiley.

 

Cloitre, M., Stovall-McClough, K. C., Miranda, R., & Chemtob, C. M. (2004, Jun). Therapeutic alliance, negative mood regulation, and treatment outcome in child abuse-related posttraumatic stress disorder. J Consult Clin Psychol, 72(3), 411-416. https://doi.org/10.1037/0022-006X.72.3.411

 

Crawford, M. J., Thana, L., Farquharson, L., Palmer, L., Hancock, E., Bassett, P., Clarke, J., & Parry, G. D. (2016, Mar). Patient experience of negative effects of psychological treatment: results of a national survey. British Journal of Psychiatry, 208(3), 260-265. https://doi.org/10.1192/bjp.bp.114.162628

 

Crits-Christoph, P., Gibbons, M. B. C., Crits-Christoph, K., Narducci, J., Schamberger, M., & Gallop, R. (2006a). Can therapists be trained to improve their alliances? A preliminary study of alliance-fostering psychotherapy. Psychotherapy Research, 16(03), 268-281.

 

Crits-Christoph, P., Gibbons, M. B. C., & Hearon, B. (2006b). Does the alliance cause good outcome? Recommendations for future research on the alliance. Psychotherapy: Theory, Research, Practice, Training, 43(3), 280–285.

 

Darchuk, A., Wang, V., Weibel, D., Fende, J., Anderson, T., & Horvath, A. (2000). Manual for the Working Alliance Inventory—Observer form, 4th revision. Unpublished manuscript.

 

De Bolle, M., Johnson, J. G., & De Fruyt, F. (2010). Patient and clinician perceptions of therapeutic alliance as predictors of improvement in depression. Psychotherapy and Psychosomatics, 79(6), 378-385.

 

Derogatis, L. (2000). The Brief Symptom Inventory-18 (BSI-18): Administration. Scoring, and Procedures Manual (3rd ed.), Minneapolis: National Computer Systems.

 

DeRubeis, R. J., Brotman, M. A., & Gibbons, C. J. (2005, Sum). A conceptual and methodological analysis of the nonspecifics argument. Clinical Psychology-Science and Practice, 12(2), 174-183. https://doi.org/10.1093/clipsy/bpi022

 

Derubeis, R. J., & Feeley, M. (1990, Oct). Determinants of Change in Cognitive Therapy for Depression. Cognitive therapy and research, 14(5), 469-482. https://doi.org/Doi 10.1007/Bf01172968

 

Elliott, R. (2011). Qualitative methods for studying psychotherapy change processes. In Qualitative research methods in mental health & psychotherapy: A Guide for Students and Practitioners (pp. 69-81). Wiley-Blackwell.

 

Endicott, J., Spitzer, R. L., Fleiss, J. L., & Cohen, J. (1976). The Global Assessment Scale: A procedure for measuring overall severity of psychiatric disturbance. Archives of general psychiatry, 33(6), 766-771.

 

Falkenstrom, F., Granstrom, F., & Holmqvist, R. (2013, Jul). Therapeutic alliance predicts symptomatic improvement session by session. J Couns Psychol, 60(3), 317-328. https://doi.org/10.1037/a0032258

 

Falkenstrom, F., Hatcher, R. L., & Holmqvist, R. (2015, Oct). Confirmatory Factor Analysis of the Patient Version of the Working Alliance Inventory--Short Form Revised. Assessment, 22(5), 581-593. https://doi.org/10.1177/1073191114552472

 

Feenstra, D. J., Hutsebaut, J., Verheul, R., & Busschbach, J. J. (2011, Sep). Severity Indices of Personality Problems (SIPP-118) in adolescents: reliability and validity. Psychol Assess, 23(3), 646-655. https://doi.org/10.1037/a0022995

 

First, M. B., Spitzer, R. L., Gibbon, M., & Williams, J. B. (1994). Structured clinical interview for Axis I DSM-IV disorders. New York: Biometrics Research.

 

Fitzmaurice, G., Davidian, M., Verbeke, G., & Molenberghs, G. (2008). Longitudinal data analysis. CRC press.

 

Fluckiger, C., Del Re, A. C., Wampold, B. E., & Horvath, A. O. (2018, Dec). The alliance in adult psychotherapy: A meta-analytic synthesis. Psychotherapy (Chic), 55(4), 316-340. https://doi.org/10.1037/pst0000172

 

Fonagy, P. (2010). The changing shape of clinical practice: Driven by science or by pragmatics? Psychoanalytic Psychotherapy, 24(1), 22-43.

 

Fonagy, P., & Bateman, A. W. (2006, Apr). Mechanisms of change in mentalization-based treatment of BPD. J Clin Psychol, 62(4), 411-430. https://doi.org/10.1002/jclp.20241

 

Freud, S. (1961). The future of an illusion, civilization and its discontents, and other works. In J. Strachey (Ed.), The standard edition of the complete psychological works of Sigmund Freud (Vol. 21, pp. 5–58). Hogarth Press.

 

Gaston, L. (1990, Sum). The Concept of the Alliance and Its Role in Psychotherapy - Theoretical and Empirical Considerations. Psychotherapy, 27(2), 143-153. https://doi.org/Doi 10.1037/0033-3204.27.2.143

 

Gaston, L., Thompson, L., Gallagher, D., Cournoyer, L. G., & Gagnon, R. (1998, Sum). Alliance, technique, and their interactions in predicting outcome of behavioral, cognitive, and brief dynamic therapy. Psychotherapy Research, 8(2), 190-209. https://doi.org/DOI 10.1093/ptr/8.2.190

 

Gelso, C. J., & Carter, J. A. (1985). The Relationship in Counseling and Psychotherapy - Components, Consequences, and Theoretical Antecedents. Counseling Psychologist, 13(2), 155-243. https://doi.org/Doi 10.1177/0011000085132001

 

Grawe, K. (1997, Spr). Research-informed psychotherapy. Psychotherapy Research, 7(1), 1-19. https://doi.org/Doi 10.1080/10503309712331331843

 

Greenberg, L. S. (2007, Jan). A guide to conducting a task analysis of psychotherapeutic change. Psychotherapy Research, 17(1), 15-30. https://doi.org/10.1080/10503300600720390

 

Greenson, R. R. (1965, Apr). The Working Alliance and the Transference Neurosis. Psychoanal Q, 34, 155-181. https://www.ncbi.nlm.nih.gov/pubmed/14302976

 

Hatcher, R. L. (2010). Alliance theory and measurement. Guilford Press.

 

Hatcher, R. L., Barends, A., Hansell, J., & Gutfreund, M. J. (1995, Aug). Patients and Therapists Shared and Unique Views of the Therapeutic Alliance - an Investigation Using Confirmatory Factor-Analysis in a Nested Design. Journal of Consulting and Clinical Psychology, 63(4), 636-643. https://doi.org/Doi 10.1037/0022-006x.63.4.636

 

Hatcher, R. L., & Gillaspy, J. A. (2006, Jan). Development and validation of a revised short version of the Working Alliance Inventory. Psychotherapy Research, 16(1), 12-25. https://doi.org/10.1080/10503300500352500

 

Hedeker, D., & Gibbons, R. D. (1997, Mar). Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychological Methods, 2(1), 64-78. https://doi.org/Doi 10.1037/1082-989x.2.1.64

 

Hembree, E. A., Rauch, S. A. M., & Foa, E. B. (2003, Win). Beyond the manual: The insider's guide to prolonged exposure therapy for PTSD. Cognitive and Behavioral Practice, 10(1), 22-30. https://doi.org/Doi 10.1016/S1077-7229(03)80005-6

 

Horvath, A., & Bedi, R. (2002). The alliance. In J. C. Norcross (Ed.), Psychotherapy relationships that work (pp. 37–69). Oxford University Press.

 

Horvath, A. O. (2006, Fall). The alliance in context: Accomplishments, challenges, and future directions. Psychotherapy (Chic), 43(3), 258-263. https://doi.org/10.1037/0033-3204.43.3.258

 

Horvath, A. O. (2018, Jul). Research on the alliance: Knowledge in search of a theory. Psychother Res, 28(4), 499-516. https://doi.org/10.1080/10503307.2017.1373204

 

Horvath, A. O., Del Re, A. C., Fluckiger, C., & Symonds, D. (2011, Mar). Alliance in individual psychotherapy. Psychotherapy (Chic), 48(1), 9-16. https://doi.org/10.1037/a0022186

 

Horvath, A. O., & Greenberg, L. S. (1989, Apr). Development and Validation of the Working Alliance Inventory. Journal of counseling psychology, 36(2), 223-233. https://doi.org/Doi 10.1037/0022-0167.36.2.223

 

Horvath, A. O., & Luborsky, L. (1993, Aug). The role of the therapeutic alliance in psychotherapy. J Consult Clin Psychol, 61(4), 561-573. https://doi.org/10.1037//0022-006x.61.4.561

 

Horvath, A. O., & Symonds, B. D. (1991). Relation between working alliance and outcome in psychotherapy: A meta-analysis. Journal of counseling psychology, 38(2), 139.

 

Iacoviello, B. M., McCarthy, K. S., Barrett, M. S., Rynn, M., Gallop, R., & Barber, J. P. (2007, Feb). Treatment preferences affect the therapeutic alliance: implications for randomized controlled trials. J Consult Clin Psychol, 75(1), 194-198. https://doi.org/10.1037/0022-006X.75.1.194

 

Karterud, S. (2011). Manual for mentaliseringsbasert psykoedukativ gruppeterapi (MBT-I). Gyldendal akademisk.

 

Karterud, S. (2012). Manual for mentaliseringsbasert gruppeterapi (MBT-G). Gyldendal akademisk Oslo.

 

Karterud, S. (2015). Mentalization-Based Group Therapy (MBT-G): A theoretical, clinical, and research manual. OUP Oxford.

 

Karterud, S., & Bateman, A. (2010). Manual for mentaliseringsbasert terapi (MBT) og MBT vurderingsskala. Versjon individualterapi. Oslo: Gyldendal akademisk.

 

Karterud, S., Pedersen, G., Engen, M., Johansen, M. S., Johansson, P. N., Schluter, C., Urnes, O., Wilberg, T., & Bateman, A. W. (2013). The MBT Adherence and Competence Scale (MBT-ACS): development, structure and reliability. Psychother Res, 23(6), 705-717. https://doi.org/10.1080/10503307.2012.708795

 

Kazdin, A. E. (2009). Understanding how and why psychotherapy leads to change. Psychotherapy Research, 19(4-5), 418-428. https://doi.org/10.1080/10503300802448899

 

Klein, D. N., Schwartz, J. E., Santiago, N. J., Vivian, D., Vocisano, C., Castonguay, L. G., Arnow, B., Blalock, J. A., Manber, R., Markowitz, J. C., Riso, L. P., Rothbaum, B., McCullough, J. P., Thase, M. E., Borian, F. E., Miller, I. W., & Keller, M. B. (2003, Dec). Therapeutic alliance in depression treatment: controlling for prior change and patient characteristics. J Consult Clin Psychol, 71(6), 997-1006. https://doi.org/10.1037/0022-006X.71.6.997

 

Kvarstein, E. (2013). Psychotherapy of personality disorder: Large variations in the severity and longitudinal course of global functioning, symptom distress, and costs of health services [Doctoral dissertation, University of Oslo].

 

Kvarstein, E. H., Folmo, E., Antonsen, B. T., Normann-Eide, E., Pedersen, G., & Wilberg, T. (2020, Jul 22). Social Cognition Capacities as Predictors of Outcome in Mentalization-Based Treatment (MBT). Frontiers in psychiatry, 11, 691. https://doi.org/ARTN 691

10.3389/fpsyt.2020.00691

 

Kvarstein, E. H., Pedersen, G., Urnes, Ø., Hummelen, B., Wilberg, T., & Karterud, S. (2015). Changing from a traditional psychodynamic treatment programme to mentalization‐based treatment for patients with borderline personality disorder–Does it make a difference? Psychology and Psychotherapy: Theory, Research and Practice, 88(1), 71-86. https://doi.org/10.1111/papt.12036

 

Laurenssen, E. M., Eeren, H. V., Kikkert, M. J., Peen, J., Westra, D., Dekker, J. J., & Busschbach, J. J. (2016, Oct 12). The burden of disease in patients eligible for mentalization-based treatment (MBT): quality of life and costs. Health Qual Life Outcomes, 14(1), 145. https://doi.org/10.1186/s12955-016-0538-z

 

Lemma, A., Target, M., & Fonagy, P. (2011). Brief dynamic interpersonal therapy: A clinician's guide. Oxford University Press.

 

Levy, K. N., Beeney, J. E., Wasserman, R. H., & Clarkin, J. F. (2010, Jul). Conflict begets conflict: executive control, mental state vacillations, and the therapeutic alliance in treatment of borderline personality disorder. Psychother Res, 20(4), 413-422. https://doi.org/10.1080/10503301003636696

 

Linehan, M. (1993). Cognitive-behavioral Treatment of Borderline Personality Disorder. Guilford Press.

 

Luborsky, L. (1976). Helping alliances in psychotherapy: The groundwork for a study of their relationship to its outcome. In J. L. Cleghhorn (Ed.), Successful psychotherapy (pp. 92–116). Brunner/Mazel.

 

Luborsky, L., & Bachrach, H. (1974, Sep). Factors influencing clinician's judgments of mental health. Eighteen experiences with the Health-Sickness Rating Scale. Arch Gen Psychiatry, 31(3), 292-299. https://doi.org/10.1001/archpsyc.1974.01760150014002

 

Mallinckrodt, B. (2000, Fal). Attachment, social competencies, social support, and interpersonal process in psychotherapy. Psychotherapy Research, 10(3), 239-266. https://doi.org/DOI 10.1093/ptr/10.3.239

 

Martin, D. J., Garske, J. P., & Davis, M. K. (2000, Jun). Relation of the therapeutic alliance with outcome and other variables: a meta-analytic review. J Consult Clin Psychol, 68(3), 438-450. https://www.ncbi.nlm.nih.gov/pubmed/10883561

 

Marziali, E., Munroe-Blum, H., & McCleary, L. (1999, Win). The effects of the therapeutic alliance on the outcomes of individual and group psychotherapy with borderline personality disorder. Psychotherapy Research, 9(4), 424-436. https://doi.org/DOI 10.1093/ptr/9.4.424

 

Masterson, J. F. (1978, Apr). The borderline adult: therapeutic alliance and transference. Am J Psychiatry, 135(4), 437-441. https://doi.org/10.1176/ajp.135.4.437

 

Miller, S. J., & Binder, J. L. (2002, Sum). The effects of manual-based training on treatment fidelity and outcome: A review of the literature on adult individual psychotherapy. Psychotherapy, 39(2), 184-198. https://doi.org/10.1037/0033-3204.39.2.184

 

Morken, K. T. E., Binder, P.-E., Arefjord, N. M., & Karterud, S. W. (2019). Mentalization-Based Treatment From the Patients’ Perspective–What Ingredients Do They Emphasize? Frontiers in psychology, 10(1327). https://doi.org/10.3389/fpsyg.2019.01327

 

Munder, T., Wilmers, F., Leonhart, R., Linster, H. W., & Barth, J. (2010, May-Jun). Working Alliance Inventory-Short Revised (WAI-SR): psychometric properties in outpatients and inpatients. Clin Psychol Psychother, 17(3), 231-239. https://doi.org/10.1002/cpp.658

 

Mundt, J. C., Marks, I. M., Shear, M. K., & Greist, J. H. (2002, May). The Work and Social Adjustment Scale: a simple measure of impairment in functioning. Br J Psychiatry, 180(5), 461-464. https://doi.org/10.1192/bjp.180.5.461

 

Muran, J. C., Safran, J. D., & Eubanks-Carter, C. (2010). Developing therapist abilities to negotiate alliance ruptures. In J. C. Muran & J. P. Barber (Eds.), The therapeutic alliance: An evidence-based guide to practice (pp. 320–340). Guilford Press.

 

Muran, J. C., Safran, J. D., Gorman, B. S., Samstag, L. W., Eubanks-Carter, C., & Winston, A. (2009, Jun). The Relationship of Early Alliance Ruptures and Their Resolution to Process and Outcome in Three Time-Limited Psychotherapies for Personality Disorders. Psychotherapy, 46(2), 233-248. https://doi.org/10.1037/a0016085

 

Norcross, J. C., Beutler, L. E., & Levant, R. F. (2006). Evidence-based practices in mental health: Debate and dialogue on the fundamental questions. American Psychological Association.

 

Norusis, M. (2008). SPSS 16.0 advanced statistical procedures companion. Prentice Hall Press.

 

Ogles, B. M., Anderson, T., & Lunnen, K. M. (1999). The contribution of models and techniques to therapeutic efficacy: Contradictions between professional trends and clinical research. In M. A. Hubble, B. L. Duncan, & S. D. Miller (Eds.), The heart and soul of change: What works in therapy (pp. 201–225). American Psychological Association.

 

Pedersen, G. (2008). Psychological assessment in clinical settings. Evaluation and clinical utility of psychometric measures for the treatment of patients with personality disorders. [Doctoral dissertation, University of Oslo. Norway].

 

Pedersen, G., Arnevik, E. A., Hummelen, B., Walderhaug, E., & Wilberg, T. (2017a). Psychometric properties of the severity indices of personality problems (SIPP) in two samples. European Journal of Psychological Assessment, 35(5), 698–711.

 

Pedersen, G., Hagtvet, K. A., & Karterud, S. (2007, Jan-Feb). Generalizability studies of the Global Assessment of Functioning-Split version. Compr Psychiatry, 48(1), 88-94. https://doi.org/10.1016/j.comppsych.2006.03.008

 

Pedersen, G., Hagtvet, K. A., & Karterud, S. (2011, Mar). Interpersonal problems: self-therapist agreement and therapist consensus. J Clin Psychol, 67(3), 308-317. https://doi.org/10.1002/jclp.20762

 

Pedersen, G., & Karterud, S. (2004). Is SCL‐90R helpful for the clinician in assessing DSM‐IV symptom disorders? Acta Psychiatrica Scandinavica, 110(3), 215-224.

 

Pedersen, G., Kvarstein, E. H., & Wilberg, T. (2017b, Nov). The Work and Social Adjustment Scale: Psychometric properties and validity among males and females, and outpatients with and without personality disorders. Personality and mental health, 11(4), 215-228. https://doi.org/10.1002/pmh.1382

 

Pedersen, G., Urnes, O., Hummelen, B., Wilberg, T., & Kvarstein, E. H. (2018, Jun). Revised manual for the Global Assessment of Functioning scale. Eur Psychiatry, 51, 16-19. https://doi.org/10.1016/j.eurpsy.2017.12.028

 

Pedersen, G. A. (2002). Norsk revidert versjon av Inventory of Interpersonal Problems—Circumplex (IIP-C). Tidsskrift for Norsk Psykologforening, 39(1), 25–34.

 

Piper, W. E., & Joyce, A. S. (2001). Psychosocial treatment outcome. In W. J. Livesley (Ed.), Handbook of personality disorders: Theory, research, and treatment (pp. 323–343). Guilford Press.

 

Rønnestad, M. H., & Ladany, N. (2006). The impact of psychotherapy training: Introduction to the special section. Psychotherapy Research, 16(03), 261-267.

 

Safran, J. D., & Wallner, L. K. (1991). The relative predictive validity of two therapeutic alliance measures in cognitive therapy. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 3(2), 188.

 

Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., Hergueta, T., Baker, R., & Dunbar, G. C. (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry, 59 Suppl 20(Suppl 20), 22-33;quiz 34-57. https://www.ncbi.nlm.nih.gov/pubmed/9881538

 

Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. Oxford university press.

 

Spinhoven, P., Giesen-Bloo, J., van Dyck, R., Kooiman, K., & Arntz, A. (2007). The therapeutic alliance in schema-focused therapy and transference-focused psychotherapy for borderline personality disorder. J Consult Clin Psychol, 75(1), 104-115. https://doi.org/10.1037/0022-006X.75.1.104

 

Stiles, W. B., & Goldsmith, J. Z. (2010). The alliance over time. In J. C. Muran & J. P. Barber (Eds.), The therapeutic alliance: An evidence-based guide to practice (pp. 44–62). The Guilford Press.

 

Saarni, S. I., Suvisaari, J., Sintonen, H., Koskinen, S., Harkanen, T., & Lonnqvist, J. (2007, Dec). The health-related quality-of-life impact of chronic conditions varied with age in general population. J Clin Epidemiol, 60(12), 1288-1297. https://doi.org/10.1016/j.jclinepi.2007.03.004

 

Tasca, G. A., & Lampard, A. M. (2012, Oct). Reciprocal influence of alliance to the group and outcome in day treatment for eating disorders. J Couns Psychol, 59(4), 507-517. https://doi.org/10.1037/a0029947

 

Ulvenes, P. G., Berggraf, L., Hoffart, A., Stiles, T. C., Svartberg, M., McCullough, L., & Wampold, B. E. (2012, Sep). Different processes for different therapies: therapist actions, therapeutic bond, and outcome. Psychotherapy (Chic), 49(3), 291-302. https://doi.org/10.1037/a0027895

 

van Asselt, A. D., Dirksen, C. D., Arntz, A., Giesen-Bloo, J. H., & Severens, J. L. (2009, Mar). The EQ-5D: A useful quality of life measure in borderline personality disorder? Eur Psychiatry, 24(2), 79-85. https://doi.org/10.1016/j.eurpsy.2008.11.001

 

Verheul, R., Andrea, H., Berghout, C. C., Dolan, C., Busschbach, J. J., van der Kroft, P. J., Bateman, A. W., & Fonagy, P. (2008, Mar). Severity Indices of Personality Problems (SIPP-118): development, factor structure, reliability, and validity. Psychol Assess, 20(1), 23-34. https://doi.org/10.1037/1040-3590.20.1.23

 

Wampold, B. E. (2019). The basics of psychotherapy: An introduction to theory and practice. American Psychological Association.

 

Wampold, B. E., & Imel, Z. E. (2015). The great psychotherapy debate: The evidence for what makes psychotherapy work. Routledge.

 

Wampold, B. E., Imel, Z. E., Bhati, K. S., & Johnson-Jennings, M. D. (2007). Insight as a Common Factor. In L. G. Castonguay & C. Hill (Eds.), Insight in psychotherapy (pp. 119–139)). American Psychological Association.

What is Blockchain?

Bitcoin and Blockchain – A New Backbone for Human Trust

MBT – Gyldendal

MBT Mentaliseringsbasert terapi av Sigmund Karterud, Espen Folmo og Mickey Kongerslev, Gyldendal

Mentalizing and MBT

A movie about Mentalization-based treatment (MBT) featuring Anthony Bateman and Espen Folmo

LOOK UP

LOOK UP — The science of cultural evolution