The Pictorial Representation of Illness and Self Measure (PRISM) assesses suffering. In this article, the authors explored the feasibility and psychometric qualities of 2 revised versions of the PRISM-PRISM-R1 and PRISM-R2-that they used in 3 studies of participants with different medical problems. The results showed significant differences between the patient groups in suffering as measured with the revised PRISMs. In addition, the revised PRISMs appeared to be sensitive to change in the predicted direction after an intervention. Last, the 2 measures of the revised PRISM seemed to indicate different aspects of suffering. These findings yield preliminary support for the feasibility and validity of the PRISM-R2.
Several interventions have been developed to support families living with parental mental illness (PMI). Recent evidence suggests that programmes with whole-family components may have greater positive effects for families, thereby also reducing costs to health and social care systems. This review aimed to identify whole-family interventions, their common characteristics, effectiveness and acceptability. A systematic review was conducted according to PRISMA 2020 guidelines. A literature search was conducted in ASSIA, CINAHL, Embase, Medline, and PsycINFO in January 2021 and updated in August 2022. We double screened 3914 abstracts and 212 papers according to pre-set inclusion and exclusion criteria. The Mixed Methods Appraisal Tool was used for quality assessment. Quantitative and qualitative data were extracted and synthesised. Randomised-control trial data on child and parent mental health outcomes were analysed separately in random-effects meta-analyses. The protocol, extracted data, and meta-data are accessible via the Open Science Framework (https://osf.io/9uxgp/). Data from 66 reports—based on 41 independent studies and referring to 30 different interventions—were included. Findings indicated small intervention effects for all outcomes including children’s and parents’ mental health (dc = −0.017, −027; dp = −0.14, −0.16) and family outcomes. Qualitative evidence suggested that most families experienced whole-family interventions as positive, highlighting specific components as helpful, including whole-family components, speaking about mental illness, and the benefits of group settings. Our findings highlight the lack of high-quality studies. The present review fills an important gap in the literature by summarising the evidence for whole-family interventions. There is a lack of robust evidence coupled with a great need in families affected by PMI which could be addressed by whole-family interventions. We recommend the involvement of families in the further development of these interventions and their evaluation.
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BackgroundE-mental health holds promise for people with severe mental illness, but has a limited evidence base. This study explored the effect of e-health added to face-to-face delivery of the Illness Management and Recovery Programme (e-IMR).MethodIn this multi-centre exploratory cluster randomized controlled trial, seven clusters (n = 60; 41 in intervention group and 19 in control group) were randomly assigned to e-IMR + IMR or IMR only. Outcomes of illness management, self-management, recovery, symptoms, quality of life, and general health were measured at baseline (T0), halfway (T1), and at twelve months (T2). The data were analysed using mixed model for repeated measurements in four models: in 1) we included fixed main effects for time trend and group, in 2) we controlled for confounding effects, in 3) we controlled for interaction effects, and in 4) we performed sub-group analyses within the intervention group.ResultsNotwithstanding low activity on e-IMR, significant effects were present in model 1 analyses for self-management (p = .01) and recovery (p = .02) at T1, and for general health perception (p = .02) at T2, all in favour of the intervention group. In model 2, the confounding covariate gender explained the effects at T1 and T2, except for self-management. In model 3, the interacting covariate non-completer explained the effects for self-management (p = .03) at T1. In model 4, the sub-group analyses of e-IMR-users versus non-users showed no differences in effect.ConclusionBecause of confounding and interaction modifications, effectiveness of e-IMR cannot be concluded. Low use of e-health precludes definite conclusions on its potential efficacy. Low use of e-IMR calls for a thorough process evaluation of the intervention.
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