About this course
We are currently refining the structure of this training in an online format and so the times and dates may change slightly. Participants will be notified of any changes with sufficient notice.
Interviews such as the Parent Development Interview (PDI, Slade et al, 2004) that tap into parents’ representations of their child, themselves as parents, and the parent-child relationship can provide rich and meaningful information about the quality of the attachment relationship between a child and their caregiver. This training will compliment the Reflective Functioning (RF) on the PDI course.
The PDI RF coding system provides one method of assessing the quality of how parents think and talk about their relationship with their child, i.e. the mentalizing capacity.
However, the PDI can be used to assess other clinically relevant aspects of parental representations which are complex and multifaceted.
The aim of this course will be to provide participants with a broader multidimensional view on some of the other current theoretical and empirical ideas around the assessment of parental representations.
This will enable practitioners to further their understanding of, and capacity to assess:
- A broad range of parental states of mind in relation to their child
- Parental states of mind that predict relational disturbances, many of which are often under-recognised.
- The relationship between parental states of mind and arousal, mentalization and affect regulation
- Parental representations that can serve as starting points for intervention
The training will provide a theoretical overview of the features of parental representations that are associated with risk and resilience in the parent-child relationship.
Trainees will then be introduced to a coding system that can be used to assess these features in PDI transcripts, the “Assessment of Representational Risk” (ARR). The system has been used in coding e.g. clinical, prison, war traumatized, and substance-abusing samples of mothers, and has been found to be very helpful and informative in these (high) risk samples.
- The course will cover
- An introduction to parental representations and attachment
- An overview of the dimensions of parental representations that are related to risk/ resilience
- Introduction to the ARR, a user-friendly coding of parental narratives
- Coding and discussions of interview transcripts
- Preparation for reliability in using the ARR
- Reliability Test
Participants will have the opportunity following the training to complete the reliability test for the ARR coding system. This will entail independently coding a set of interviews and the scores will be compared with the trainer-agreed scores. Passing the reliability test will enable practitioners to use the coding confidently in their own practice.Taking the reliability test will enable participants to use the ARR instrument in research.
- Who is this course suitable for?
Clinical, academic and research professionals working with children and their caregivers who are interested in learning more about the assessment of parent-child relationships.
- Aims of the course?
- To familiarise participants with current research and theory relating to parental representations and attachment
- To introduce the Assessment of Representational Risk (ARR) coding frame
- To give participants some experience of coding interviews with the ARR coding frame
- System requirements for online training
The online platform Zoom will be used to deliver this training. Prior to booking on, please ensure you meet the system requirements so you're able to join this training.
Before the training, please test your equipment is working by going to Zoom.us/test and follow the instructions.
11th May 2022 - 13th May 2022
- Online – live via Zoom (Joining instructions will be sent to the email address you booked on with at least one working day before the event)
- 11th, 12th and 13th May 2022
- Two days spread over three days
- 09:00 - 17:00 (UK time) on 11th May and 09:00 - 12:30 (UK time) on 12th and 13th May
Training fee with reliability
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