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Enhancing member engagement in a Tier 3 personality disorder service during COVID-19: evaluation of a virtual group programme

Published online by Cambridge University Press:  09 September 2022

Emma Smith
Affiliation:
Sussex Partnership NHS Foundation Trust, Trust HQ, Swandean, Arundel Road, Worthing, West Sussex BN13 3EP, UK
Cat Papastavrou Brooks*
Affiliation:
Sussex Partnership NHS Foundation Trust, Trust HQ, Swandean, Arundel Road, Worthing, West Sussex BN13 3EP, UK University of Bristol, Canynge Hall, 58 Whiteladies Road, Clifton, Bristol BS8 2PL, UK
Emma Clifford
Affiliation:
Sussex Partnership NHS Foundation Trust, Trust HQ, Swandean, Arundel Road, Worthing, West Sussex BN13 3EP, UK
Emily Giles
Affiliation:
Sussex Partnership NHS Foundation Trust, Trust HQ, Swandean, Arundel Road, Worthing, West Sussex BN13 3EP, UK
Jessica Dring
Affiliation:
Sussex Partnership NHS Foundation Trust, Trust HQ, Swandean, Arundel Road, Worthing, West Sussex BN13 3EP, UK
Helen Startup
Affiliation:
Sussex Partnership NHS Foundation Trust, Trust HQ, Swandean, Arundel Road, Worthing, West Sussex BN13 3EP, UK University of Sussex, Falmer, Brighton BN1 9RH, UK
*
*Corresponding author. Email: [email protected]
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Abstract

Background:

Drop-out rates from evidence-based interventions for people with a diagnosis of personality disorder (PD) are high. The COVID-19 pandemic has likely exacerbated barriers to engagement with the introduction of virtual working. Virtual therapy has a good evidence-base for Axis I disorders, but limited research for Axis II disorders.

Aims:

To investigate facilitators and barriers to engagement in a Tier 3 PD service virtual group programme.

Method:

A virtual group programme was developed in collaboration with service members, and analysed members’ attendance rates over a 5-month period pre- and post-COVID-19. Thematic analysis of semi-structured telephone interviews with 38 members is reported, describing their experience of the virtual group programme.

Results:

Attendance rates were significantly higher pre-COVID (72%) than post-COVID (50%). Thematic analysis highlighted key barriers to attendance were: practical issues, low motivation, challenges of working in a group online and feeling triggered at home. Main promoters of engagement were: feeling valued, continued sense of connection and maintaining focus on recovery.

Discussion:

The results suggest that the pandemic has exacerbated relational and practical barriers to engagement in a Tier 3 PD service. Ways of enhancing engagement are discussed, as well as preliminary recommendation for services offering virtual therapy to people with a diagnosis of PD.

Type
Main
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the British Association for Behavioural and Cognitive Psychotherapies

Introduction

Borderline personality disorder (BPD) is diagnosed on the basis of ‘a pervasive pattern of instability of interpersonal relationships, self-image, and affects, and marked impulsivity’ (APA, 2013; p. 663). Core clinical features include: frantic efforts to avoid abandonment or rejection, relational instability, identity instability, impulsivity, suicidality and self-harm, mood swings and anger as well as dissociation and paranoia (APA, 2013). The estimated prevalence of BPD in the general population is between 0.7 and 2.7% (Gunderson et al., Reference Gunderson, Weinberg and Choi-Kain2013; Tomko et al., Reference Tomko, Trull, Wood and Sher2014; Trull et al., Reference Trull, Jahng, Tomko, Wood and Sher2010), rising to 12% in out-patient and 22% in in-patient clinical populations (Ellison et al., Reference Ellison, Rosenstein, Morgan and Zimmerman2018). However, it can be as high as 43% in patients admitted for suicidality to in-patient settings (Gregory et al., Reference Gregory, Sperry, Williamson, Kuch-Cecconi and Spink2021). People diagnosed with BPD have a risk of suicide of up to 10% (Paris, Reference Paris2019; Pompili et al., Reference Pompili, Girardi, Ruberto and Tatarelli2005), a high rate of co-morbidities with Axis 1 disorders (Shah and Zanarini, Reference Shah and Zanarini2018) and often substantial impairments in psychosocial and occupational functioning (Javaras et al., Reference Javaras, Zanarini, Hudson, Greenfield and Gunderson2017; Liebke et al., Reference Liebke, Bungert, Thome, Hauschild, Gescher, Schmahl, Bohus and Lis2017).

Despite the clear need for effective and timely treatment for this high-risk group (Evans et al., Reference Evans, Sethi, Dale, Stanton, Sedgwick, Doran, Shoolbred, Goldsack and Haigh2017), services often have difficulty engaging patients with a diagnosis of personality disorder. Systematic reviews of studies evaluating psychological treatments for this population have found drop-out rates ranging from 22.3 to 37% (Barnicot et al., Reference Barnicot, Katsakou, Marougka and Priebe2011; Iliakis et al., Reference Iliakis, Ilagan and Choi-Kain2021; McMurran et al., Reference McMurran, Huband and Overton2010). These rates compare with Axis 1 drop-out rates of 17.5% in psychological therapy for depression (Cooper and Conklin, Reference Cooper and Conklin2015) and 16.9% for generalised anxiety disorder (Gersh et al., Reference Gersh, Hallford, Rice, Kazantzis, Gersh, Gersh and McCarty2017). Unsurprisingly, failure to complete treatments for personality disorder is associated with poorer clinical outcomes (Jacobs et al., Reference Jacobs, Bruce, Sonigra and Blakesley2010; Martin Clarke, Reference Martin Clarke2013). Reviews conducted in this area have not found a significant impact of therapeutic modality or individual factors on treatment completion, with conflicting results reported on the impact of treatment intensity and duration (Barnicot et al., Reference Barnicot, Katsakou, Marougka and Priebe2011; Cristea et al., Reference Cristea, Gentili, Cotet, Palomba, Barbui and Cuijpers2017; Iliakis et al., Reference Iliakis, Ilagan and Choi-Kain2021).

A potential reason why people diagnosed with personality disorder might struggle to engage with treatment is due to an absence of services experienced in meeting the relational needs of this group (Duggan and Kane, Reference Duggan and Kane2010). BPD is thought to develop through a combination of temperamental factors, attachment and exposure to abuse, trauma or neglect in early life (Ball and Links, Reference Ball and Links2009; Levy, Reference Levy2005) constraining how people view themselves, others and the world (Young et al., Reference Young, Klosko and Weishaar2003). By adulthood, people who have survived traumatic early life experiences may have developed maladaptive ways of understanding and engaging with the world, including relationships with others (Jacob and Arntz, Reference Jacob and Arntz2013).

When people with these kinds of adverse formative experiences approach mental health services it is inevitable that they anticipate being let down, humiliated, abused and/or ignored, because these are the interpersonal lenses through which they have come to view the world (Lavender and Startup, Reference Lavender and Startup2018). Unfortunately, these schemas are often reinforced by the responses of services to this patient group. Clinicians frequently report hostility towards and dislike of patients diagnosed with personality disorder (Evans et al., Reference Evans, Sethi, Dale, Stanton, Sedgwick, Doran, Shoolbred, Goldsack and Haigh2017); resulting in attempts to distance themselves from (Aviram et al., Reference Aviram, Brodsky and Stanley2006) or be excessively controlling towards them (Gunderson and Ridolfi, Reference Gunderson and Ridolfi2001), both of which can reinforce existing negative schemas.

Although there is a clear challenge in providing treatment for people with high levels of interpersonal conflict (Holmes, Reference Holmes1999), part of the problem may be a lack of appropriate skills within services. Systematic reviews conducted within non-specialised services find a negative impact of poorly managed interpersonal dynamics on treatment outcomes for patients diagnosed with personality disorder, consistent across crisis services (Warrender et al., Reference Warrender, Bain, Murray and Kennedy2021), primary care (Roininen et al., Reference Roininen, Cheetham, Mueller and Battegay2019) and third-sector organisations (Connell et al., Reference Connell, Furtado, McKay and Singh2017).

Specialist personality services aim to work in a way which meets relational needs of patients in order to more effectively engage them in treatment (Crawford et al., Reference Crawford, Price, Gordon, Josson, Taylor, Bateman, Fonagy, Tyrer and Moran2009). Given that treatment modality has not been found to impact on drop-out rates for this population (Barnicot et al., Reference Barnicot, Katsakou, Marougka and Priebe2011; Cristea et al., Reference Cristea, Gentili, Cotet, Palomba, Barbui and Cuijpers2017; Iliakis et al., Reference Iliakis, Ilagan and Choi-Kain2021), this is less about which treatments are delivered, and more about the context of the relationship of the patient and the service. Improving this relational context can include an increased focus on developing the therapeutic alliance (Jacobs et al., Reference Jacobs, Bruce, Sonigra and Blakesley2010; Martino et al., Reference Martino, Menchetti, Pozzi and Berardi2012), utilising peer support (Price et al., Reference Price, Gillespie, Rutter, Dhillon, Gibson, Faulkner, Weaver and Crawford2009), offering additional crisis support (Nadort et al., Reference Nadort, Arntz, Smit, Giesen-Bloo, Eikelenboom, Spinhoven, van Asselt, Wensing and van Dyck2009), prioritising skilfully facilitated group programmes (Hummelen et al., Reference Hummelen, Wilberg and Karterud2007) and employing staff who are interested and motivated to work with this group (Tetley et al., Reference Tetley, Jinks, Huband, Howells and McMurran2012).

COVID-19 has created an additional barrier to clinicians working therapeutically with this group. As well as the established difficulties services have engaging patients diagnosed with BPD, the COVID-19 outbreak has presented a great deal of uncertainty and enormous emotional burden to the population and it is thought to have impacted service-users with pre-existing mental health conditions particularly badly (Álvaro et al., Reference Álvaro, Navarro, Palma, Farriols, Aliaga, Solves, Hernández, Antón and Riera2020; Yao et al., Reference Yao, Chen and Xu2020). In the UK the outbreak led to a national lockdown in March 2020 and the suspension of most face-to-face clinical work across mental health services. Evidence indicates that lockdowns have had a particularly negative impact on those with diagnoses of personality disorder; worsening feelings of abandonment and isolation, triggering paranoid thoughts, and removing existing coping strategies (Lakeman and Crighton, Reference Lakeman and Crighton2021; Wurman et al., Reference Wurman, Lee, Bateman, Fonagy and Nolte2020).

Services have been required to adapt to meet the needs of vulnerable service-users, with some implementing telephone support (Álvaro et al., Reference Álvaro, Navarro, Palma, Farriols, Aliaga, Solves, Hernández, Antón and Riera2020; Salamin et al., Reference Salamin, Rossier, Joye, Nolde, Pierrehumbert, Gothuey and Guenot2021) as well as virtual group programmes (Weinberg, Reference Weinberg2021). Online therapy has an evidence-base for depression, anxiety disorders, post-traumatic stress disorder and eating disorders (Skinner and Zack, Reference Skinner and Zack2004; Sloan et al., Reference Sloan, Gallagher, Feinstein, Lee and Pruneau2011; Stamm, Reference Stamm1998) and has been suggested as the most helpful way to continue offering a therapy service while restrictions on face-to-face work remain (Situmorang, Reference Situmorang2020). Several population-based studies have indicated that people diagnosed with BPD have received virtual group therapy during COVID-19 (Kvarstein et al., Reference Kvarstein, Zahl, Stänicke, Pettersen, Baltzersen, Johansen, Eikenaes, Arnevik, Hummelen, Wilberg and Pedersen2021; Lakeman and Crighton, Reference Lakeman and Crighton2021), but little is understood about the barriers to or facilitators of the translation of group-therapeutic programmes to a virtual setting for BPD-specific treatments. Evidence from other clinical populations on the difficulties of establishing group-cohesion (Gratz et al., Reference Gratz, Bardeen, Levy, Dixon-Gordon and Tull2015) and managing group dynamics (Weinberg, Reference Weinberg2021) in virtual group therapies suggests that care must be taken in adapting any group programme for patients diagnosed with personality disorder.

It is vital to explore the facilitators and barriers to engagement in virtual groups for this clinical population. This pilot study within one Tier 3 personality disorder community service aimed to assess:

  1. (1) Attendance: do attendance rates change pre- and post-COVID? How much does the move to virtual therapy groups affect attendance?

  2. (2) Member’s perceptions: how do members understand the barriers to engagement in treatment? What do members think are the key reasons that engagement has dropped post-COVID and what do they think is facilitating ongoing engagement?

Method

Participants

Participants were recruited from the Tier 3 personality disorder service (the ‘Thinking Well’ service) within Sussex Partnership NHS Foundation Trust. Tier 3 personality disorder services are ‘local, semi-regional specialist and dedicated PD services, incorporating outpatient, day-patient and “partial hospitalisation” interventions’ (Royal College of Psychiatrists, 2020). Criteria for accessing the ‘Thinking Well’ service are: having a diagnosis of personality disorder, being at least 18 years old, being assessed as cluster seven or eight (Self et al., Reference Self, Rigby, Leggett and Paxton2008), and being a ‘high-cost’ service user.

Eligibility criteria for participation in this evaluation were current engagement with the ‘Thinking Well’ service. At the time of recruitment, the service had 60 members. Nine were excluded due to being on a time-out or having recently been referred to the service, and as a result had very low attendance rates (M = 5.55%, SD = 12.57%). Fifty-one eligible members were approached to participate by phone call; if they did not answer they were called twice more. Thirty-eight members accepted and 13 were unavailable or declined to part. Seven out of the 13 members who declined to take part had attendance below the 60% threshold that the service used to quantify whether someone was currently engaging with the service (M = 54.76%, SD = 21.00%), in comparison with the 14 out of the 38 who agreed to participate (M = 63.95%, SD = 23.33%).

All of the participants had a diagnosis of personality disorder as identified by a psychiatrist using DSM-V (APA, 2013), and 30 of these were confirmed by the Millon Clinical Multiaxial Inventory-IV (MCMI-IV; Millon and Grossman, Reference Millon and Grossman2015); see Table 1 for the most prevalent diagnoses. The majority of participants were female (95%) and defined their ethnicity as White-British (97%). Participants ranged in age from 20 to 66 years old (M = 38, SD = 13.11).

Table 1. The number and percentage of participants for whom the following personality patterns were in the top 3 scoring patterns, as assessed by the MCMI-IV

The 38 members who agreed to participate completed all parts of the study, including questions on barriers to engagement, and semi-structured interviews.

Treatment

Prior to COVID-19, the ‘Thinking Well’ service offered its members a comprehensive group-based programme, delivered across three localities, and consisting of two component parts. The community part of the programme included stabilisation work, service-user network groups (Miller et al., Reference Miller, Jones and Warren2011) and psychoeducation groups. Within the clinical part of the programme members were offered a range of evidence-based group therapies (group schema therapy, dialectical behaviour therapy (DBT), STEPPS and mentalisation based therapy), with between nine and 20 members in each clinical group. The aim was over time to move members from the community part of the programme to the clinical programme. No individual therapy sessions were offered pre- or post-COVID.

In March 2020, the service had to close to face-to-face work in response to the national lockdown following the outbreak of COVID-19. In line with co-production guidance (Clark, Reference Clark2015) clinicians met with service members in the monthly ‘service development forum’ to discuss how to adapt the service in response to COVID, and ensure that members’ needs were met in the transition to virtual delivery.

A core guiding principle raised in the service development forum was the importance of creating a sense of community online and maintaining the relational focus of the services’ existing treatment programme. As a result, it was collaboratively decided to modify a DBT skills group to run virtually (with between 19 and 21 members in each DBT group), alongside more informal community groups which could facilitate a sense of connection to both the service and peers. It was decided that it could be too intense to run the other groups comprising the clinical programme online (group schema therapy, STEPPS and mentalisation based therapy).

The DBT skills groups were adapted from the manual to include an ‘ice-breaker’ to increase group-cohesion, reduce attachment anxiety and paranoia and improve members’ ability to engage with the material. Members were concerned about the loss of informal sources of support which occurred after in-person therapy groups and enabled them to manage any distress which might arise. As a result, clinicians created time for a game or activity at the end of each DBT group, in order to facilitate a smooth transition from emotionally difficult therapeutic work to ‘happy child mode’ (Farrell et al., Reference Farrell, Shaw and Shaw2012).

In recognition of the difficulties people with a diagnosis of personality disorder might have in engaging with virtual groups, telephone support structures were also set up to provide members with the emotional containment needed to effectively engage with other aspects of the programme.

Pre-COVID, members could attend the ‘Thinking Well’ service for a day and a half per week, whereas post-COVID members could attend a 90-minute DBT group, plus two 120-minute social groups as well as monthly committee meetings, representing a reduction in the service offered. The DBT group and other virtual groups were offered to all members, regardless of which groups they had previously engaged with.

Measures

Attendance rates

The service keeps registers as part of standard clinical practice and used these to compare attendance rates for the therapeutic groups in the 8 weeks pre-COVID and the 8 weeks post-COVID. Only attendance rate data from members who had consented to take part in the study was utilised.

Barriers to engagement

The researchers reviewed the literature on treatment engagement and met with an experienced member of the service to collaboratively identify potential barriers to engagement post-COVID. Participants were asked closed yes/no questions as to whether or not each barrier was relevant to them. If yes, they rated how problematic these barriers were to their engagement on a scale ranging from 1 (not at all) to 5 (very much). Finally, participants were asked for any other barriers not included in the list.

Perceptions of barriers and promoters of engagement

A semi-structured interview was designed to investigate perceptions of potential barriers to engagement (see Table 2) and there were also optional prompts. The interview was piloted with a member who offered consultation on the topics and questions covered.

Table 2. Interview questions

Procedure

All participants were read information about the study and the consent form over the telephone and gave consent to participate. Interviews were completed over the telephone, audio-recorded and transcribed by the person who had conducted the interview. An intern who was new to the service (E.G.), conducted most of the interviews, as she had not been involved in the delivery of any of the groups, and did not have a therapeutic relationship with any of the members. However, due to capacity constraints and the need to make immediate evidence-based adaptations to the service, two other clinicians (E.C. and J.D.) also conducted a small number of the interviews. The duration of interviews was between 15 minutes and one hour.

Data analysis

Attendance data for the service pre- and post-COVID were analysed descriptively.

Member’s perceptions of barriers to and facilitators of engagement in treatment were analysed using a thematic content analysis methodology (Anderson, Reference Anderson2007).Firstly, interview data were transcribed verbatim and assessed to identify codes related to barriers to and facilitators of engagement. To maintain objectivity, all initial coding was completed by an intern (E.G.), who had not been involved in the development or delivery of the groups. The interviews were read and units of data relevant to engagement were highlighted and inputted into an Excel spreadsheet. All similar units of meaning were grouped into their own tab on the Excel spreadsheet. To ensure the validity and quality of coding, a second data analyst not involved in the interviews, or the delivery of the service (J.D.), reviewed the codes and noted where the categories did not make sense or contained more than one meaning, under the supervision of the other author (E.S.). The research team came together and reviewed the categories to agree the meaning and labels for each category. Categories were grouped into themes and subthemes. These were then shared with the research team who had undertaken the interviews to establish whether this reflected their experience of interviewing participants, as an additional quality check. Discussions were held about codes and emerging findings in the data with the wider research team to minimise the risk that concepts were overlooked and to improve the trustworthiness of the data. Through this, 17 codes were identified, grouped within two wider clusters and four subthemes.

Results

Attendance rates

Table 3 shows the percentage attendance of clinical groups in the 8-week period pre-COVID and the 8-week period of virtual clinical groups post-COVID. Only 24 out of the 38 study participants were engaged in clinical groups for both these times periods. Attendance data for the community part of the programme are not presented as these were not consistently recorded pre- and post-COVID, making comparison difficult.

Table 3. Attendance rates (the mean attendance, standard deviation and percentage of study participants that attended each therapy group, by type of group and timeframe)

The percentage of therapeutic group sessions attended (out of those participants eligible to attend each session) across all therapeutic groups was 60.0% pre-COVID and 49% post-COVID (when only DBT groups were offered.)

Barriers to engagement

The main barrier to engagement was feeling low/unmotivated, which was also reflected in the interview data. There were several barriers particular to the practicalities of accessing virtual therapy from your own home, such as privacy issues, other demands on time, parenting demands, loss of routine. However, practical barriers were not rated highly overall, and rated between 0.8 and 1.6 (see Table 4).

Table 4. The number and percentage of participants (n=38) that endorsed each barrier as problematic and the mean Likert rating and standard deviation for each barrier

* 1, not much; 2, a little bit; 3, more or less; 4, quite a lot; 5, very much.

Qualitative data

Key themes and subthemes relating to members’ engagement and lack of engagement in the Tier 3 personality disorder service are summarised in Table 5 and elaborated below.

Table 5. Themes from semi-structured interviews with 38 members and the number of times each theme was endorsed

Four main themes arose around the barriers to engaging.

A1. Group environment

Members described feelings of anxiety and mistrust working in a group, and a loss of safety in working online, notably struggling with reading body language and cues from other members, which left them feeling more anxious and led to them feeling some insecurity and mistrust. There was an indication that relational security was a barrier prior to COVID-19 and that virtual working amplified these difficulties for some.

I guess it was all about trust, I want to be able to say something clearly and in a way that people understand, but my situation, with my childhood, the barrier for me – opening up and talking is actually very dangerous water for me.

Not picking up everyone’s essence and looking at everyone.

A2. Practicalities (privacy, timings, safety, technology issues, physical health)

Another barrier pertained to more practical issues, notably not having a private space at home where they could access virtual groups, limited data, or WiFi, and that the timings of groups clashed with other obligations:

Internet connection at times this can be sad to see others unable to connect.

I can’t do anything on the call or videocalls because right now my daughter is getting my DVDs and is throwing them all over the floor and she just does not listen and this is why I can’t engage as much recently purely because of her.

A3. Transference/triggering

Members reported the therapeutic work and being in a group can be triggering and they can pick up feelings from other members. It can feel less safe for members to engage with the challenging therapeutic work in their home environment.

The only problem is the anxiety around bringing therapeutic stuff into my own space; I’ve only got one small room to myself so I can’t move to calm down.

I’m worried to do anything that’s going to be too intense because of course if we did it at Thinking Well, I could go out for a cigarette and go for my maccies, I can come home. It just kind of worries me if we are going to do intense […] I don’t know if I would be able to hack that at home on my own. So, I would just end up driving myself crazy, so that’s kind of the only worry is bringing anything too intense into the flat.

A4. Unmotivated to engage

Many members described a lack of motivation to engage, which could be a problem prior to lockdown, but seemed to escalate with the move to virtual working.

I’ve really not been in the mood, and if that was a session at the Thinking Well centre, even if I was in the same frame of mind I would have made myself go to the centre. But because it’s online, I’ve let myself go and thought I’m not going to do it today. So it has had an impact in that way.

I think my concentration levels have decreased because of motivation and concentration, turbulent time with medication and mental health.

Promoters of engagement

Four main themes arose about what helped people to engage.

B1. Sense of community/continued connection

Whereas some members cited a reduced feeling of connection online, others were surprised by how well the sense of community continued.

The groups themselves are useful, I’ve enjoyed having the sessions with the slides then discussion about them. Also, hearing other people’s lived experience is always of value to me. It makes me realise that I’m not alone and how I feel about something is normal. It helps ground me in a way. It’s sad that others have difficulties but it’s also useful for me as it helps me feel less alone.

It has been nice seeing everyone’s faces every week, kind of social. The sense of the community encourages me because it’s something I haven’t had before with other people so that really motivates me as I want to be a part of the community more. I want to be a part and to work with everyone.

Like the linking well [newsletter] and emails as feel connected to the service but not pressured to do the groups.

B2. Recovery

Many members referenced how their focus on and hope for recovery motivated them to attend and they were grateful to be able to continue working towards this through lockdown.

I’m determined to get better. And I want to go on to do peer support training, and I really think that being in Thinking Well helps me. Group works helps me be there for others not just for me getting support.

Since I have been going to TW, I understand my illness so much more that what I ever have done. It really has helped, yeah I can understand triggers that set me off, I can understand now when I need to ask for help and support when before I didn’t.

B3. Valuing staff and feeling valued

A common theme was gratitude for staff and sense of collaboration being a motivator for attendance.

I think that the staff certainly, are doing everything they can to try and teach us the skills and other ways of coping with the diagnosis. I think at the moment I feel frustrated about my progress and not being in schema, there is a good feeling about what we’re doing. It depends, I’m an adult, I have to put as much in to get as much out of it as I can. I think it’s a good partnership.

Because they’re probably the only people in my life that take care of my inner angry child and allow the healthy adult to grow.

The range of activities that the staff try to get us to do, always doing something new, the nature of the staff all very outgoing, talkative, and reassuring.

B4. Increased accessibility online

Some people have found it easier to attend online due to physical health problems, fatigue or trying to fit therapy around other commitments.

Physical health less of a problem to engage in virtual groups.

Being in the comfort of my home and means I can get out of bed and attend the groups.

Discussion

The present study sought to compare attendance rates pre- and post-COVID and to explore members’ perceptions of what impacted their engagement with the service. Results showed that post-COVID virtual groups were significantly less well attended than pre-COVID face-to-face groups. The Likert questionnaire and thematic content analysis highlighted key barriers to and facilitators of engagement that could support the understanding of these differing attendance rates. Questionnaire results suggested that low mood/motivation, a lack of connection to the group, anxiety about online groups, loss of routine and feelings of mistrust were especially challenging for this group. The barriers identified via thematic analysis clustered into four categories: the group environment, practical issues, transference/triggers and low motivation. The promoters of engagement identified were a sense of community/continued connection, recovery, valuing staff/feeling valued and increased accessibility online.

The virtual environment gave rise to reduced feelings of connection and safety in some members. In particular, reading cues in the virtual environment was a key difficulty, and can be understood as presenting a barrier to mentalising, defined as the ability to understanding the mental states underlying behaviours (Bateman and Fonagy, Reference Bateman and Fonagy2016). This is reported as an issue in online groups in general (Lemma and Fonagy, Reference Lemma and Fonagy2013); however, it might be exacerbated in those diagnosed with personality disorder, who find it difficult to read external and internal cues and interpret what is happening in a relational context (Bateman and Fonagy, Reference Bateman and Fonagy2016; Levy et al., Reference Levy, Meehan, Weber, Reynoso and Clarkin2005). Online, the combination of limited visual cues and the tendency for members to turn one’s camera off or drop out of a group without warning may activate greater anxiety in members and a hyper-mentalising response that may lead people to avoid these interactions (Sharp and Vanwoerden, Reference Sharp and Vanwoerden2015).

Many members missed being around each other, reflected in the theme ‘loss of therapeutic community’. They missed the physicality of being in a building together, which helped them to feel contained and enabled them to engage in a way that is difficult to replicate online. Many members spoke about how coming into the centre provided a useful structure to their week that they were finding hard to replicate during the pandemic. They felt less motivated to join a virtual group, or were feeling low, depressed, and struggling to do much at all. This is reflected in the broader literature on engagement in online therapy, where feeling a lack of connection to therapist or therapeutic group made individual motivation a more salient factor in determining retention in treatment (Abbott et al., Reference Abbott, Klein and Ciechomski2008; Wadley et al., Reference Wadley, Lederman, Gleeson and Alvarez-Jimenez2013). However, in the context of this service, there were key practical changes that could have contributed to this. Firstly, some groups were being offered across the three localities, whereas members had been used to only seeing members from their own locality. Secondly, for members who had not joined the virtual groups straight away this increased their anxiety and sense of disconnection from the community.

A few people found that the move to online work increased their agency and prompted them to take more responsibility. Others recognised that they come to ‘Thinking Well’ for the sense of connection to people and not to do active work on their recovery. Virtual service provision increased focus on active work rather than spending time together. This reduced motivation to attend in many members as they did not have the informal peer pressure and praise to engage in group work. Whilst ‘treatment readiness’ in people diagnosed with personality disorder is often seen as a requirement for effective treatment (McMurran, Reference McMurran2012), this gives little guidance on how to support those who might have less intrinsic motivation to engage, potentially due to a range of additional needs or structural disadvantages (Barnicot et al., Reference Barnicot, Katsakou, Marougka and Priebe2011).

Strengths and limitations

This is the first study to explore the barriers and promoters of engagement in a Tier 3 personality disorder service and how virtual service delivery impacts engagement. A strength of this study is the real-world naturalistic nature of the study which took place within a busy community NHS service at a time of unusual national events requiring creative problem solving. However, the data were gathered from a single Tier 3 personality disorder service, which limits the transferability to clinical practice in other settings. Furthermore, we were primarily focused on engagement across time points, but there may well have been other variables not captured within this study that affected outcomes.

Another limitation is that the members have been in the service for differing amounts of time and were exposed to differing amounts of prior support, which likely impacted on their therapeutic relationships with the staff team and their level of engagement. Many members have a range of Axis 1 co-morbidities and substance use problems that may have played a part in non-engagement. Nine members declined to take part in the interviews or did not respond, and it may be that this group of people are even more inclined to disengage from services.

Although service members (through the ‘service development forum’) were core in determining how the service transitioned to remote delivery, no service members, or others with lived experience of personality disorder were involved in the analysis. This presents a significant limitation to this piece of work.

Recommendations

Running evidence-based psychological therapy groups virtually is possible and may be an adaptive way of adhering to NICE-recommended treatments during COVID-19. Given this has become more commonplace, it would be helpful to undertake research into the effectiveness of group-based treatment for personality disorder online to see if outcomes are similar to face-to-face therapy.

Virtual therapy may present practical barriers to some service-users who do not have space or privacy at home, or access to appropriate technology, potentially highlighting economic disadvantages. Looking into funding for technology and providing technology support sessions could help some people engage who might not otherwise.

For many, the barriers to engagement are more psychological and relational, and not dissimilar to barriers that occurred pre-COVID. Low motivation and depression are a significant barrier, so utilising motivational interviewing and pre-commitment strategies from DBT may help to promote engagement (Linehan, Reference Linehan1993). Likewise, using behavioural activation may help to improve low mood and reintroduce structure, which may help to overcome these barriers.

Members felt uncomfortable sharing in the virtual group setting and struggled with being unable to read cues online. An explicit focus on mentalising facial expressions and communication online may help to make this process more explicit and help members to challenges their fears or judgement and rebuild a sense of connection.

Prioritising the development of a therapeutic community and utilising creative ways to foster this bonding and support online may help people to feel safer and more connected. For example, given how frequently the community newsletter was mentioned as a promoter of engagement, it may help to create a collaborative newsletter that members contribute to that can help foster continued connection.

Involving members in the dilemmas faced by the service and seeing this as a shared challenge to understand together and find ways to make the best of things can promote more active engagement and creative problem solving. The service has used this approach throughout and found it helps members feel more trust in the system and empowers them to take ownership of the problem and to feel valued.

Data availability statement

The data that support the findings of this study are not available either publicly or on request, due to their containing information that could compromise the privacy of research participants; it was felt it would be inappropriate to share data given that it was collected within a service evaluation governance structure.

Acknowledgements

None.

Author contributions

Emma Smith: Conceptualization (equal), Data curation (equal), Formal analysis (equal), Investigation (equal), Methodology (equal), Supervision (equal), Writing – original draft (equal), Writing – review & editing (equal); Cat Papastavrou Brooks: Writing – review & editing (equal); Emma Clifford: Conceptualization (equal), Data curation (equal), Investigation (equal), Project administration (equal), Writing – original draft (equal), Writing – review & editing (equal); Emily Giles: Data curation (equal), Formal analysis (equal), Investigation (equal), Writing – original draft (equal); Jessica Dring: Data curation (equal), Formal analysis (equal), Investigation (equal), Methodology (equal), Project administration (equal), Writing – original draft (equal); Helen Startup: Conceptualization (equal), Formal analysis (equal), Methodology (equal), Supervision (equal), Writing – original draft (equal), Writing – review & editing (equal).

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Conflicts of interest

The authors declare none.

Ethical standards

The UK National Health Service National Research Ethics Service guidance established that this study did not require ethical approval as outcomes were collected as part of routine clinical practice. All participants were aware that their data could be used for evaluation purposes and that all data would be fully anonymised assuring no breaches of confidentiality. All authors have abided by the Ethical Principles of Psychologists and Code of Conduct as set out by the BABCP and BPS. The audit was approved by the clinical audit team in Sussex Partnership foundation Trust.

References

Abbott, J.-A. M., Klein, B., & Ciechomski, L. (2008). Best practices in online therapy. Journal of Technology in Human Services, 26, 360375. https://doi.org/10.1080/15228830802097257 CrossRefGoogle Scholar
Álvaro, F., Navarro, S., Palma, C., Farriols, N., Aliaga, F., Solves, L., Hernández, M., Antón, M., & Riera, A. (2020). Clinical course and predictors in patients with borderline personality disorder during the COVID-19 outbreak: a 2.5-month naturalistic exploratory study in Spain. Psychiatry Research, 292, 113306. https://doi.org/10.1016/j.psychres.2020.113306 CrossRefGoogle ScholarPubMed
Anderson, R. (2007). Thematic content analysis (TCA). Descriptive Presentation of Qualitative Data, pp. 1–4.Google Scholar
APA (2013). Diagnostic and Statistical Manual of Mental Disorders (fifth edition). American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890425596 CrossRefGoogle Scholar
Aviram, R. B., Brodsky, B. S., & Stanley, B. (2006). Borderline personality disorder, stigma, and treatment implications. Harvard Review of Psychiatry, 14, 249256.CrossRefGoogle ScholarPubMed
Ball, J. S., & Links, P. S. (2009). Borderline personality disorder and childhood trauma: evidence for a causal relationship. Current Psychiatry Reports, 11, 6368.CrossRefGoogle ScholarPubMed
Barnicot, K., Katsakou, C., Marougka, S., & Priebe, S. (2011). Treatment completion in psychotherapy for borderline personality disorder – a systematic review and meta-analysis. Acta Psychiatrica Scandinavica, 123, 327338. https://doi.org/10.1111/j.1600-0447.2010.01652.x CrossRefGoogle ScholarPubMed
Bateman, A., & Fonagy, P. (2016). Mentalization-Based Treatment for Personality Disorders: A Practical Guide. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Clark, M. (2015). Co-production in mental health care. Mental Health Review Journal, 20, 213219.CrossRefGoogle Scholar
Connell, C., Furtado, V., McKay, E. A., & Singh, S. P. (2017). How effective are interventions to improve social outcomes among offenders with personality disorder: a systematic review. BMC Psychiatry, 17, 368. https://doi.org/10.1186/s12888-017-1536-3 CrossRefGoogle ScholarPubMed
Cooper, A. A., & Conklin, L. R. (2015). Dropout from individual psychotherapy for major depression: a meta-analysis of randomized clinical trials. Clinical Psychology Review, 40, 5765.CrossRefGoogle ScholarPubMed
Crawford, M. J., Price, K., Gordon, F., Josson, M., Taylor, B., Bateman, A., Fonagy, P., Tyrer, P., & Moran, P. (2009). Engagement and retention in specialist services for people with personality disorder. Acta Psychiatrica Scandinavica, 119, 304311. https://doi.org/10.1111/j.1600-0447.2008.01306.x CrossRefGoogle ScholarPubMed
Cristea, I. A., Gentili, C., Cotet, C. D., Palomba, D., Barbui, C., & Cuijpers, P. (2017). Efficacy of psychotherapies for borderline personality disorder: a systematic review and meta-analysis. JAMA Psychiatry, 74, 319328. https://doi.org/10.1001/jamapsychiatry.2016.4287 CrossRefGoogle ScholarPubMed
Duggan, C., & Kane, E. (2010). Developing a national institute of clinical excellence and health guideline for antisocial personality disorder. Personality and Mental Health, 4, 38.CrossRefGoogle Scholar
Ellison, W. D., Rosenstein, L. K., Morgan, T. A., & Zimmerman, M. (2018). Community and clinical epidemiology of borderline personality disorder. Psychiatric Clinics, 41, 561573. https://doi.org/10.1016/j.psc.2018.07.008 Google ScholarPubMed
Evans, S., Sethi, F., Dale, O., Stanton, C., Sedgwick, R., Doran, M., Shoolbred, L., Goldsack, S., & Haigh, R. (2017). Personality disorder service provision: a review of the recent literature. Mental Health Review Journal, 22, 6582. https://doi.org/10.1108/MHRJ-03-2016-0006 CrossRefGoogle Scholar
Farrell, J. M., Shaw, I., & Shaw, I. A. (2012). Group Schema Therapy for Borderline Personality Disorder: A Step-by-Step Treatment Manual with Patient Workbook. Chichester, UK: John Wiley & Sons.CrossRefGoogle Scholar
Gersh, E., Hallford, D. J., Rice, S. M., Kazantzis, N., Gersh, H., Gersh, B., & McCarty, C. A. (2017). Systematic review and meta-analysis of dropout rates in individual psychotherapy for generalized anxiety disorder. Journal of Anxiety Disorders, 52, 2533.CrossRefGoogle ScholarPubMed
Gratz, K. L., Bardeen, J. R., Levy, R., Dixon-Gordon, K. L., & Tull, M. T. (2015). Mechanisms of change in an emotion regulation group therapy for deliberate self-harm among women with borderline personality disorder. Behaviour Research and Therapy, 65, 2935. https://doi.org/10.1016/j.brat.2014.12.005 CrossRefGoogle Scholar
Gregory, R., Sperry, S. D., Williamson, D., Kuch-Cecconi, R., & Spink, G. L. Jr (2021). High prevalence of borderline personality disorder among psychiatric inpatients admitted for suicidality. Journal of Personality Disorders, 112.Google ScholarPubMed
Gunderson, J. G., & Ridolfi, M. E. (2001). Borderline personality disorder. Annals of the New York Academy of Sciences, 932, 6177.CrossRefGoogle ScholarPubMed
Gunderson, J. G., Weinberg, I., & Choi-Kain, L. (2013). Borderline personality disorder. FOCUS, 11, 129145. https://doi.org/10.1176/appi.focus.11.2.129 CrossRefGoogle Scholar
Holmes, J. (1999). Psychotherapeutic approaches to the management of severe personality disorder in general psychiatric settings. CPD Bulletin Psychiatry, 1, 2968.Google Scholar
Hummelen, B., Wilberg, T., & Karterud, S. (2007). Interviews of female patients with borderline personality disorder who dropped out of group psychotherapy. International Journal of Group Psychotherapy, 57, 6792. https://doi.org/10.1521/ijgp.2007.57.1.67 CrossRefGoogle ScholarPubMed
Iliakis, E. A., Ilagan, G. S., & Choi-Kain, L. W. (2021). Dropout rates from psychotherapy trials for borderline personality disorder: a meta-analysis. Personality Disorders, 12, 193206. https://doi.org/10.1037/per0000453 CrossRefGoogle ScholarPubMed
Jacob, G. A., & Arntz, A. (2013). Schema therapy for personality disorders – a review. International Journal of Cognitive Therapy, 6, 171185.CrossRefGoogle Scholar
Jacobs, B., Bruce, M., Sonigra, K., & Blakesley, J. (2010). Service user experiences of a community forensic personality disorder service: a qualitative survey. The British Journal of Forensic Practice, 12, 4756.CrossRefGoogle Scholar
Javaras, K. N., Zanarini, M. C., Hudson, J. I., Greenfield, S. F., & Gunderson, J. G. (2017). Functional outcomes in community-based adults with borderline personality disorder. Journal of Psychiatric Research, 89, 105114. https://doi.org/10.1016/j.jpsychires.2017.01.010 CrossRefGoogle ScholarPubMed
Kvarstein, E. H., Zahl, K.-E., Stänicke, L. I., Pettersen, M. S., Baltzersen, Å.-L., Johansen, M. S., Eikenaes, I. U.-M., Arnevik, E. A., Hummelen, B., Wilberg, T., & Pedersen, G. (2021). Vulnerability of personality disorder during the Covid-19 crises – a multicenter survey of treatment experiences among patients referred to treatment. Nordic Journal of Psychiatry, 76138149. https://doi-org.bris.idm.oclc.org/10.1080/08039488.2021.1934110 CrossRefGoogle ScholarPubMed
Lakeman, R., & Crighton, J. (2021). The impact of social distancing on people with borderline personality disorder: the views of dialectical behavioural therapists. Issues in Mental Health Nursing, 42, 410416. https://doi.org/10.1080/01612840.2020.1817208 CrossRefGoogle ScholarPubMed
Lavender, A., & Startup, H. (2018). Personality disorders. The Therapeutic Relationship in Cognitive Behavioural Therapy. London, UK: SAGE.Google Scholar
Lemma, A., & Fonagy, P. (2013). Feasibility study of a psychodynamic online group intervention for depression. Psychoanalytic Psychology, 30, 367.CrossRefGoogle Scholar
Levy, K. N. (2005). The implications of attachment theory and research for understanding borderline personality disorder. Development and Psychopathology, 17, 959986.CrossRefGoogle ScholarPubMed
Levy, K. N., Meehan, K. B., Weber, M., Reynoso, J., & Clarkin, J. F. (2005). Attachment and borderline personality disorder: implications for psychotherapy. Psychopathology, 38, 6474. https://doi.org/10.1159/000084813 CrossRefGoogle ScholarPubMed
Liebke, L., Bungert, M., Thome, J., Hauschild, S., Gescher, D. M., Schmahl, C., Bohus, M., & Lis, S. (2017). Loneliness, social networks, and social functioning in borderline personality disorder. Personality Disorders: Theory, Research, and Treatment, 8, 349.CrossRefGoogle ScholarPubMed
Linehan, M. (1993). Cognitive Behavioural Therapy for Borderline Personality Disorder. New York, USA: Guilford Press.Google Scholar
Martin Clarke, M. J. (2013). Strategies for engaging people with personality disorder in treatment [Text]. Mental Health Practice. https://doi.org/10.7748/mhp2014.05.17.8.23.e894 CrossRefGoogle Scholar
Martino, F., Menchetti, M., Pozzi, E., & Berardi, D. (2012). Predictors of dropout among personality disorders in a specialist outpatients psychosocial treatment: a preliminary study. Psychiatry and Clinical Neurosciences, 66, 180186. https://doi.org/10.1111/j.1440-1819.2012.02329.x CrossRefGoogle Scholar
McMurran, M. (2012). Readiness to engage in treatments for personality disorder. International Journal of Forensic Mental Health, 11, 289298.CrossRefGoogle Scholar
McMurran, M., Huband, N., & Overton, E. (2010). Non-completion of personality disorder treatments: a systematic review of correlates, consequences, and interventions. Clinical Psychology Review, 30, 277287. https://doi.org/10.1016/j.cpr.2009.12.002 CrossRefGoogle ScholarPubMed
Miller, S., Jones, B., & Warren, F. (2011). The SUN Project: open access community-based support groups for people with personality disorder description of the service model and theoretical foundations. Therapeutic Communities: The International Journal for Therapeutic and Supportive Organizations, 32, 108124.Google Scholar
Millon, T., & Grossman, S. (2015). MCMI-IV: Millon Clinical Multiaxial Inventory Manual. Bloomington, MN: NCS Pearson. Inc.Google Scholar
Nadort, M., Arntz, A., Smit, J. H., Giesen-Bloo, J., Eikelenboom, M., Spinhoven, P., van Asselt, T., Wensing, M., & van Dyck, R. (2009). Implementation of outpatient schema therapy for borderline personality disorder with versus without crisis support by the therapist outside office hours: a randomized trial. Behaviour Research and Therapy, 47, 961973. https://doi.org/10.1016/j.brat.2009.07.013 CrossRefGoogle ScholarPubMed
Paris, J. (2019). Suicidality in borderline personality disorder. Medicina, 55, 223. https://doi.org/10.3390/medicina55060223 CrossRefGoogle ScholarPubMed
Pompili, M., Girardi, P., Ruberto, A., & Tatarelli, R. (2005). Suicide in borderline personality disorder: a meta-analysis. Nordic Journal of Psychiatry, 59, 319324.CrossRefGoogle ScholarPubMed
Price, K., Gillespie, S., Rutter, D., Dhillon, K., Gibson, S., Faulkner, A., Weaver, T., & Crawford, M. J. (2009). Dedicated personality disorder services: a qualitative analysis of service structure and treatment process. Journal of Mental Health, 18, 467475. https://doi.org/10.3109/09638230902968191 CrossRefGoogle Scholar
Roininen, S. M., Cheetham, M., Mueller, B. U., & Battegay, E. (2019). Unmet challenges in treating hypertension in patients with borderline personality disorder. Medicine, 98, e17101. https://doi.org/10.1097/MD.0000000000017101 CrossRefGoogle ScholarPubMed
Royal College of Psychiatrists (2020). Services for People Diagnosable with Personality Disorder.Google Scholar
Salamin, V., Rossier, V., Joye, D., Nolde, C., Pierrehumbert, T., Gothuey, I., & Guenot, F. (2021). Adaptations de la thérapie comportementale dialectique ambulatoire en période de pandémie COVID-19 et conséquences du confinement sur des patients souffrant d’un état-limite. Annales Medico-Psychologiques, 179, 131136. https://doi.org/10.1016/j.amp.2020.08.006 CrossRefGoogle Scholar
Self, R., Rigby, A., Leggett, C., & Paxton, R. (2008). Clinical decision support tool: a rational needs-based approach to making clinical decisions. Journal of Mental Health, 17, 3348.CrossRefGoogle Scholar
Shah, R., & Zanarini, M. C. (2018). Comorbidity of borderline personality disorder: current status and future directions. Psychiatric Clinics, 41, 583593. https://doi.org/10.1016/j.psc.2018.07.009 Google ScholarPubMed
Sharp, C., & Vanwoerden, S. (2015). Hypermentalizing in borderline personality disorder: A model and data. Journal of Infant, Child, and Adolescent Psychotherapy, 14, 3345. https://doi.org/10.1080/15289168.2015.1004890 CrossRefGoogle Scholar
Situmorang, D. D. B. (2020). The issues of transference and countertransference in tele-psychotherapy during COVID-19 outbreak. Asian Journal of Psychiatry, 54, 102427.CrossRefGoogle ScholarPubMed
Skinner, A., & Zack, J. S. (2004). Counseling and the internet. American Behavioral Scientist, 48, 434446.CrossRefGoogle Scholar
Sloan, D. M., Gallagher, M. W., Feinstein, B. A., Lee, D. J., & Pruneau, G. M. (2011). Efficacy of telehealth treatments for posttraumatic stress-related symptoms: a meta-analysis. Cognitive Behaviour Therapy, 40, 111125.CrossRefGoogle ScholarPubMed
Stamm, B. H. (1998). Clinical applications of telehealth in mental health care. Professional Psychology: Research and Practice, 29, 536.CrossRefGoogle Scholar
Tetley, A., Jinks, M., Huband, N., Howells, K., & McMurran, M. (2012). Barriers to and facilitators of treatment engagement for clients with personality disorder: a Delphi survey. Personality and Mental Health, 6, 97110. https://doi.org/10.1002/pmh.1176 CrossRefGoogle Scholar
Tomko, R. L., Trull, T. J., Wood, P. K., & Sher, K. J. (2014). Characteristics of borderline personality disorder in a community sample: comorbidity, treatment utilization, and general functioning. Journal of Personality Disorders, 28, 734750. https://doi.org/10.1521/pedi_2012_26_093 CrossRefGoogle Scholar
Trull, T. J., Jahng, S., Tomko, R. L., Wood, P. K., & Sher, K. J. (2010). Revised NESARC personality disorder diagnoses: gender, prevalence, and comorbidity with substance dependence disorders. Journal of Personality Disorders, 24, 412426.CrossRefGoogle ScholarPubMed
Wadley, G., Lederman, R., Gleeson, J., & Alvarez-Jimenez, M. (2013). Participatory design of an online therapy for youth mental health. Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, 517–526.CrossRefGoogle Scholar
Warrender, D., Bain, H., Murray, I., & Kennedy, C. (2021). Perspectives of crisis intervention for people diagnosed with ‘borderline personality disorder’: an integrative review. Journal of Psychiatric and Mental Health Nursing, 28, 208236. https://doi.org/10.1111/jpm.12637 CrossRefGoogle Scholar
Weinberg, H. (2021). Obstacles, challenges, and benefits of online group psychotherapy. American Journal of Psychotherapy, 74, 8388. https://doi.org/10.1176/appi.psychotherapy.20200034 CrossRefGoogle ScholarPubMed
Wurman, T. V., Lee, T., Bateman, A., Fonagy, P., & Nolte, T. (2020). Clinical management of common presentations of patients diagnosed with BPD during the COVID-19 pandemic: the contribution of the MBT framework. Counselling Psychology Quarterly, 34744770. https://doi.org/10.1080/09515070.2020.1814694 CrossRefGoogle Scholar
Yao, H., Chen, J.-H., & Xu, Y.-F. (2020). Patients with Mental Health Disorders in the COVID-19 Epidemic. CrossRefGoogle Scholar
Young, J., Klosko, J., & Weishaar, M. (2003). Schema Therapy: A Practitioner’s Guide. New York, USA: Guilford Press.Google Scholar
Figure 0

Table 1. The number and percentage of participants for whom the following personality patterns were in the top 3 scoring patterns, as assessed by the MCMI-IV

Figure 1

Table 2. Interview questions

Figure 2

Table 3. Attendance rates (the mean attendance, standard deviation and percentage of study participants that attended each therapy group, by type of group and timeframe)

Figure 3

Table 4. The number and percentage of participants (n=38) that endorsed each barrier as problematic and the mean Likert rating and standard deviation for each barrier

Figure 4

Table 5. Themes from semi-structured interviews with 38 members and the number of times each theme was endorsed

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