The recovery approach to the care of mentally disordered patients. Does it predict treatment engagement and positive social behaviour beyond quality of life?

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Abstract

The main aim of this study was to investigate whether the ‘recovery approach’ to the care of mentally disordered patients is associated with treatment motivation/engagement and positive social interactions on the ward beyond that of perceived quality of life. The participants were 75 service users in a medium secure unit in south-east England, who completed the Recovery Journey Questionnaire (RJQ), The Manchester Short Assessment of Quality of Life (MANSA), The Beck Hopelessness Scale (BHS), and the Patient Motivation and Perception Questionnaires (PMI and PPQ). The patients’ primary nurse independently completed the Disruptive Behaviour and Social Problem Scale (DBSP) for 33 service users. Multiple regressions showed that after controlling for age, ethnicity and diagnosis (severe mental illness vs personality disorder), the RJQ contributed to the variance in treatment motivation, treatment engagement, and positive social interactions on the ward above quality of life with medium to large effect sizes. The strongest effect size was with regard to treatment engagement where the amount of variance explained increased from 22% to 51% after the RJQ was entered into the regression. The results indicate that the recovery approach explains treatment motivation/engagement and positive social interactions above and beyond quality of life.

Highlights

► The recovery approach to care is being implemented in psychiatric services. ► The study was conduced among forensic inpatients. ► The recovery approach explained positive outcome beyond quality of life. ► The recovery approach is a potential vehicle for improved treatment outcome.

Introduction

Repper and Perkins (2003) introduced a model of mental health practice where the primary focus is on recovery. The model focuses on “enabling people with mental health problems to maintain or rebuild valuable and satisfying lives within and beyond the limits imposed by their difficulties” (p. 219). Within this model “the essence of recovery lies not in the removal of mental health problems but in recovering a meaningful and valued life” (p. 219). This suggests that the central theme in the recovery approach to care is the empowerment of service users to develop optimal self-efficacy and quality of life. This is achieved by facilitating the individual’s sense of hope, opportunity and control (Repper & Perkins, 2003). Developing hope-inspiring relationships and competencies is a key component of the model for mental health practices. Hope is seen as an achievement of goals that have significance for the persons concerned.

Warner (2010) has reviewed the scientific evidence of the ‘recovery model’ in relation to recovery from major mental illness and argues that the concept of empowerment is an important component of the recovery model process. He uses the concept of ‘optimism’ rather than ‘hope’ as a way of facilitating feelings of empowerment, but both concepts are likely to be associated with problem-solving effort (Scheier et al., 1989) and motivation to pursue valued personal goals (Tse, Wu, & Poon, 2011).

Leff and Warner (2006) showed that patients’ participation in efforts to recover ‘best possible’ functioning and to develop meaning in their lives improves quality of life, self-esteem, social contacts, and return to work. Unfortunately, there is a general absence of a consensus on how the concept of ‘recovery’ in mental health should be defined, operationalised, and measured (Slade, 2009). Some authors (e.g. Anthony, 1993) describe it as a ‘uniquely individual process’, which is similar to that described by some authors in relation to the concept ‘quality of life’ (Sprangers & Schwartz, 1999).

One of the most important questions to be answered in relation to the recovery approach to care is whether the key recovery principles (i.e. hope, opportunity, and control) and the associated process (i.e. improved sense of empowerment) predict outcome (e.g. patient motivation and engagement in therapy, improved social inclusion, reduced disruptive/violent behaviour in hospital settings, reduced length of stay in hospital) above and beyond that of quality of life? In other words, does it possess a unique variance beyond a ‘feel good’ factor? Green, Batson, and Gudjonsson (2011) suggest that the recovery process goes beyond feelings of improved quality of life, but this has not been empirically tested. Addressing this important question is the main purpose of the present study.

Green et al. (2011) developed the ‘Recovery Journey Questionnaire’ (RJQ) to measure service users’ experience of recovery over their in-patient journey. The measure was developed from focus groups and in-depth interviews with service users about their understanding of the recovery journey principles and process. The measure had good psychometric properties and the initial validation was promising. In the current study the RJQ is used as a key predictor of treatment motivation/engagement (patient rated) and disruptive behaviour and social problems (rated independently by a key worker) among patients in secure unit facilities in the South of England. The forensic service has a model for therapy programmes, which incorporates the recovery approach to care (Gudjonsson et al., 2010, Gudjonsson and Young, 2007).

There are three hypotheses being tested. The first hypothesis is that the recovery journey, as measured by the RJQ, will be positively correlated with a quality of life measure, and negatively with feelings of hopelessness. The second hypothesis is that the recovery journey and quality of life are significantly related to treatment motivation/engagement, less disruptive behaviour, and fewer social problems on the ward. The third hypothesis is that the RJQ predicts treatment motivation/engagement, less disruptive behaviour, and fewer behavioural problems beyond quality of life.

Section snippets

Participants

At the time of the study there were 152 in-patients in the secure unit services in Lambeth, South London. Twenty-one (14%) patients met exclusion criteria, which were related to unstable mental state, serious language difficulties, and risk of violence to the researcher. This left 131 patients who were approached and 76 (58%) agreed to participate, but one patient withdrew the consent a few days later and his data were deleted from the data base, which left 75 patients in the study, 73 of whom

Mean scores and correlations between the measures

Table 1 gives the mean scores, standard deviations, and Cronbach’s α for the measures used in the study. The Cronbach’s α were satisfactory for all the measures. The table also gives the correlations between the three measures directly relevant to the recovery approach to care: the RJQ, the MANSA and the BHS. As predicted, the RJQ correlated positively with treatment motivation (r = 0.39) and treatment engagement (r = 0.70) and negatively with the Social Problem Scale (r = −0.50). The MANSA did not

Discussion

The three hypotheses were largely supported. As predicted, the RJQ was positively correlated with the quality of life measure (medium effect size), and negatively with the hopelessness scale (medium effect size). The second hypothesis was that the RJQ and the quality of life measure were positively related to treatment motivation/engagement and negatively with disturbed behaviour and social problems on the ward. The RJQ was positively correlated with treatment motivation (medium effect size),

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