The diagnostic process from primary care to child and adolescent mental healthcare services: the incremental value of information conveyed through referral letters, screening questionnaires and structured multi-informant assessment

Semiha Aydin; Bart M Siebelink; Matty R Crone; Joost R van Ginkel; Mattijs E Numans; Robert R J M Vermeiren; P Michiel Westenberg

doi:10.1192/bjo.2022.47

The diagnostic process from primary care to child and adolescent mental healthcare services: the incremental value of information conveyed through referral letters, screening questionnaires and structured multi-informant assessment

BJPsych Open. 2022 Apr 7;8(3):e81. doi: 10.1192/bjo.2022.47.

Authors

Semiha Aydin¹, Bart M Siebelink², Matty R Crone³, Joost R van Ginkel⁴, Mattijs E Numans³, Robert R J M Vermeiren⁵, P Michiel Westenberg⁶

Affiliations

¹ Department of Developmental and Educational Psychology, Leiden University, The Netherlands; Department of Child and Adolescent Psychiatry, Leiden University Medical Centre, The Netherlands; and Department of Public Health and Primary Care, Leiden University Medical Centre, The Netherlands.
² Department of Child and Adolescent Psychiatry, Leiden University Medical Centre, The Netherlands.
³ Department of Public Health and Primary Care, Leiden University Medical Centre, The Netherlands.
⁴ Methodology and Statistics Unit, Institute of Psychology, Leiden University, The Netherlands.
⁵ Department of Child and Adolescent Psychiatry, Leiden University Medical Centre, The Netherlands; and Youz, Parnassia Group, The Netherlands.
⁶ Department of Developmental and Educational Psychology, Leiden University, The Netherlands.

Abstract

Background: A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment questionnaires for parents. However, the incremental value of these information sources is still poorly examined.

Aims: To quantify the added and unique predictive value of referral letters, screening, multi-informant assessment and clinicians' remote evaluations in predicting mental health disorders.

Method: Routine medical record data on 1259 referred children and adolescents were retrospectively extracted. Their referral letters, responses to the Strengths and Difficulties Questionnaire (SDQ), results on closed-ended questions from the Development and Well-Being Assessment (DAWBA) and its clinician-rated version were linked to classifications made after face-to-face intake in psychiatry. Following multiple imputations of missing data, logistic regression analyses were performed with the above four nodes of assessment as predictors and the five childhood disorders common in mental healthcare (anxiety, depression, autism spectrum disorders, attention-deficit hyperactivity disorder, behavioural disorders) as outcomes. Likelihood ratio tests and diagnostic odds ratios were computed.

Results: Each assessment tool significantly predicted the classified outcome. Successive addition of the assessment instruments improved the prediction models, with the exception of behavioural disorder prediction by the clinician-rated DAWBA. With the exception of the SDQ for depressive and behavioural disorders, all instruments showed unique predictive value.

Conclusions: Structured acquisition and integrated use of diverse sources of information supports evidence-based diagnosis in clinical practice. The clinical value of structured assessment at the primary-secondary care interface should now be quantified in prospective studies.

Keywords: Evidence-based assessment; diagnostic decision making; primary care; psychological testing; secondary mental healthcare.