Examining the role of attachment in primary care mental health assessments
GPs and other primary care practitioners regularly make referrals for children to IAPT and other primary care mental health services. But how are these referrals assessed? Every referral regarding children’s mental health is required to assess their attachment status (NICE Guidelines for Children’s attachment, NG26). Yet, to date, no research has examined the use of attachment in assessment and case-formulation in primary care. This is despite calls for such research from the 2015 NICE Guidance, and a recently published consensus statement from 40 experts in children’s mental health (Granqvist, et al., 2017). In particular, concerns have been raised regarding the overextension and misapplication of attachment research and assessments, with significant implications for the pathways of care offered to children and families.
Previous research has studied the assessment of attachment status in practice of social workers (Wilkins, 2016; Lesch, Desit, Booysen & Edwards, 2013; Botes & Ryke, 2011). Funds are sought to conduct a study of the accounts of primary care mental health practitioners of their assessment of attachment and use of attachment concepts. Scoping work has indicated that, among the advantages of use of an online platform, it will be more attractive to busy primary care mental health practitioners than an in-person interview.
Qualitative methods alone have limitations in finding out about the use of concepts in professional practice, as prefabricated professional rhetoric can provide a barrier (Foster, et al. 2017, in prep). Single-dimensional quantitative measures alone have also been unable to capture the complexity of the use of attachment assessments and concepts in practice. Q-methodology will therefore be used in this project to facilitate the assessment of practitioner knowledge in a way that is statistically quantifiable, but which can be interpreted within its context relative to other qualitative data and self-report quantitative data (Watts & Stenner, 2012).
