Article Text
PDF
Abstract
Objectives As part of the ‘Suicidality: Treatment Occurring in Paediatrics (STOP)’ study, we developed and performed psychometric validation of an electronic-clinical-outcome-assessment (eCOA), which included a patient-reported-outcome (ePRO), an observer-rated-outcome (eObsRO) for parents/carers and a clinician-reported-outcome (eClinRO) that allows identification and monitoring of medication-related suicidality (MRS) in adolescents.
Design STOP: Prospective study: A two phase validation study to assess the impact of medication on suicidal ideations.
Setting Six participating countries: Netherlands, UK, Germany, France, Spain and Italy that were part of the Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 261411.
Participants Cohort 1 consisted of 41 adolescent-completions, 50 parent-completions and 56 clinician-completions. Cohort 2 consisted of 244 adolescent-completions, 198 parent-completions and 240 clinician-completions from across the six countries. The scale was administered only to participants who have screened positive for the STOP-Suicidality Assessment Scale (STOP-SAS).
Results A total of 24 items for the development of the STOP-Medication Suicidality Side Effects Scale (STOP-MS3) were identified and three versions (for patients, parents and clinicians) of the STOP-MS3 were developed and validated in two separate study cohorts comprising of adolescents, their parents and clinicians. Cronbach’s α coefficients were above 0.85 for all domains. The inter-rater reliability of the STOP-MS3 was good and significant for the adolescent (ePRO), clinician (eClinRO) (r=0.613), parent (eObsRO) versions of the scale (r=0.394) and parent and clinician (r=0.347). Exploratory factor analysis identified a 3-factor model across 24 items for the adolescent and parent version of the scale: (1) Emotional Dysregulation, (2) Somatic Dysregulation and (3) Behavioural Dysregulation. For the clinician version, a 4-factor model defined the scale structure: (1) Somatic Dysregulation, (2) Emotional Dysregulation, (3) Behavioural Dysregulation and (4) Mood Dysregulation.
Conclusion These findings suggest that the STOP-MS3 scale, a web-based eCOA, allows identification and monitoring of MRS in the adolescent population and shows good reliability and validity.
- child & adolescent psychiatry
- suicide & self-harm
- developmental neurology & neurodisability
- mental health
- information technology
Data availability statement
Data are available upon reasonable request. Data are available upon reasonable request from the corresponding author.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
- child & adolescent psychiatry
- suicide & self-harm
- developmental neurology & neurodisability
- mental health
- information technology
Strengths and limitations of this study
The web-based Suicidality: Treatment Occurring in Paediatrics (STOP)-Medication-Related Suicidality Side Effects Scale is a useful web-based electronic clinical outcome assessment for identifying and monitoring medication-related suicidality in adolescents.
The electronic patient-reported outcome version, the observer-rated outcome version for parents/carers and the clinician-reported outcome version allows different modes for the identification and monitoring of MRS in adolescents.
It is available in multiple languages (English, Spanish, Italian, German, French and Dutch).
Being web-based may appeal more to young people due to the increased accessibility and the anonymity web-based platforms can provide.
Only participants who screened positive on the screening questionnaire of the STOP-Suicidality Assessment Scale were included.
Introduction
Suicide is one of the leading causes of mortality among children and adolescents and is a major public health concern.1 2 The construct of suicidality is multifaceted, ranging from ideations and behaviours to completions and suicide mortality is dependent on several factors3 including age, gender, ethnicity and the presence of psychiatric disorders such as mood disturbances, substance-related and addictive disorders, anxiety, psychotic and personality disorders.4 5 Importantly, there is mounting evidence to suggest that the risk of suicide is high among young people and adolescents (aged 12–26 years), and women were reported to have a high risk of suicide attempt, while men were more likely to complete suicide than their peers.3 While the risk of suicide-related mortality is comparatively low among those younger than 12 years, suicide is the fourth leading cause of mortality in this older age group of people (aged 15–29 years old).6 It is noteworthy indeed that suicidal behaviours become increasingly apparent during the mid-adolescent years, and women have elevated rates of suicidal ideation and behaviours than their counterparts.7 However, there is only limited data available on potential risk factors of suicidality in this group of people, hence suicide risk assessment in adolescents is particularly challenging for clinicians. Therefore, better insights into the risks and mediators of suicidality within this vulnerable age group is pivotal for its prevention and early intervention.
Of note, the advent of medication-triggered new-onset suicidal ideation and behaviours, especially with selective serotonin reuptake inhibitors, some antipsychotics, atomoxetine, antiepileptics and montelukast in children and adults is of particular concern, and intensely debated especially with its potential association with death by suicide.8 9 Medication-related suicidality (MRS), defined as all suicide-related symptoms that are reported during the period of treatment with the medication, and is a major public health concern. Indeed, a black box label has been mandated by the Food and Drug Administration (FDA) for over 130 medications regarding the risk of increased suicidal ideation or behaviour.10 We have, however, few data regarding the impact of this warning on prescribing to patients and their families. Importantly, the onset of MRS occurs over differing time frames for different medications due to varied pharmacokinetic and pharmacodynamic profiles, mechanisms of action and inter-individual differences in drug metabolism. Our current inability to predict these differences highlights the need for improved approaches to screening and monitoring of the risks of medications regarding suicidal ideation and behaviours in adolescents.
While the assessment of suicidality in post-marketing surveillance of new medications has been highlighted as a critical component in the drug development process,11 the majority of the study instruments currently used to evaluate suicidality were primarily designed for the adult population,12–15 and bear several limitations including false positives, poor predictive validity and inability to capture symptom change across time.16 Therefore, risk assessment of suicidality among children and adolescents, both in research and clinical practice, remains a major clinical challenge and there is an urgent need to develop and evaluate instruments designed for children and adolescents that can comprehensively capture the bio-psycho-social mediators and risk factors for suicidality in this age group. The STOP programme (Suicidality: Treatment Occurring in Paediatrics; grant agreement number: 261411) was developed in response to a specific research call made under the Seventh Framework Programme (FP7), ‘HEALTH.2010.4.2-3: Adverse drug reaction research’ with an overarching aim to develop and validate a web-based protocol for the assessment and monitoring of suicidality and its mediators in children and adolescents.
Patient-reported outcome measures (PROMs) are instruments that collect health outcomes based on self/proxy assessments and have been promoted across primary care for monitoring of common mental health disorders, including suicidal ideation and behaviour.17 As part of the STOP study, we have previously developed PROMs for a Suicidality Assessment Scale (SAS) that specifically assesses suicidality in children and/or adolescents,17 and the STOP-Risk and Resilience Scales.18 We have also developed the Profile Of Neuropsychiatric Symptoms scale that captures symptoms of developmental disorders, disruptive disorders, emerging personality disorders and anxiety/depressive disorders.19
Here we describe the development and psychometric validation of an electronic clinical outcome assessment (eCOA), the STOP-Medication-Related Suicidality Side Effects Scale (MS3), which has a patient-reported outcome (ePRO) version, an observer-rated outcome (eObsRO) version for parents/carers and a clinician-reported outcome (eClinRO) version that allows identification and monitoring of MRS in adolescents. The three versions have been designed to capture different reports of MRS which together facilitate a comprehensive identification and monitoring of MRS in adolescents (12–18 years old).
Methods
As part of the STOP study (www.stop-study.com), we developed a web-based ‘Suite of Suicidality Measures’ that together provide a comprehensive assessment of suicidality in children and adolescents.17 These measures were developed using the HealthTracker platform, a web-based health-monitoring system to host the study instruments (in multiple languages) that has been used in other European Union FP7 funded studies.20 21 The HealthTracker (https://www.healthtracker.co.uk) is a multimodal real-time, web-based monitoring and risk-stratification tool that can gather longitudinal clinical data including psychosocial data, behavioural data, medication side effects, cognitive functions, medication adherence, quality-of-life and post-marketing surveillance of experimental medications.22 The study participants, parents and clinicians completed a comprehensive set of study instruments that assessed suicidality, medication adherence and compliance and quality-of-life. The UK (London) was the lead site for the STOP project.17 Informed consent was provided by all parents and/or legal tutors of the study participants.
In the present study, we included participants who were screened positive for suicidality on the STOP-SAS.17
We conducted a two-phase programme: Phase 1 focused on the development of the STOP-MS3 scale and phase 2 involved the validation of the psychometric properties of the scale. This STOP-MS3 instrument consists of an adolescent version, parent or carer version and a clinician version that is designed to capture different components of MRS.
Phase 1: development of the STOP-MS3
The general methodology of developing the STOP suite of questionnaires has previously been described.17 18 In brief, the development of the STOP-MS3 scale followed the recommendations of the FDA for PROMs.23 Initial items identified were generated based on an extensive literature search, experts’ opinion, and an examination of items from several medication side effect questionnaires such as the UK Side Effects Rating Scale for the Registration Of Unwanted Effects Of Psychotropics24 and the Paediatric Adverse Event Rating Scale.25 A panel of child psychiatrists with extensive experience in paediatric psychopharmacology used this information to develop a first draft of the STOP-MS3 scale. This draft measure was then further discussed and refined by experts within the STOP consortium and the STOP scientific advisory board.
A systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses26 to identify the core domains. The experts within the STOP consortium and the STOP scientific advisory board then reviewed the identified domains. To gauge participant (parent/carer and young person) understanding of the draft scale, eight focus groups were conducted at the Child and Adolescent Psychiatry Department of the Hospital Clinic of Barcelona. The procedure of these focus groups has already been described in a previous paper.17 In brief, these focus groups consisted of three or four individuals, and participants were representative of the population seen in clinical routinely.17 19 With informed consent from participants, the content of focus group discussions was videotaped, transcribed and analysed using thematic analyses. A detailed summary report was written regarding each transcription. Following this stage, some items were re-worded, and others removed (figure 1). Linguistic experts reviewed the final version of the study tools to ensure comparability and enhance communication with participants.27
Development of the Suicidality: Treatment Occurring in Paediatrics-Medication-Related Suicidality Side Effects Scale.
Discussions between experts from the UK and Spain were held to develop final versions of the scale in English and Spanish. A clinician version was developed based on the questionnaires designed for adolescents and parents. These instruments were reviewed by a professional translator to check whether the meaning of the questions was the same in both languages. The English versions of the scale were then translated into German, French and Italian and then back translated into English. The three versions of the STOP-MS3 were uploaded into the HealthTracker system with all language options.
Phase 2: psychometric evaluation of the STOP-MS3 scale
Subjects and procedures
Psychometric evaluation was conducted in two study cohorts. The STOP-MS3 questionnaire was only completed by adolescents (and the associated parent and clinician) who had suicidal ideation or behaviour as assessed by the STOP Screening Questionnaire (STOP-SQ). This questionnaire cannot be used without the STOP-SQ as the STOP-MS3 specifically evaluates the impact of side effects on suicidality.
Cohort 1: Included 41 adolescent-completions (12–18 years old, mean age 16.27, SD 1.42), 50 parent-completions and 56 clinician-completions of the scale with repeat completion once with a maximum time of 3 weeks between completions (see table 1). Descriptives of individuals with one completion or no completions are presented in online supplemental table 1. Participants were recruited from the various participating centres to explore the ability to capture change of ratings of all versions of the STOP-MS3 across time.
Supplemental material
Baseline characteristics of Cohort 1
For Cohort 1, we assessed completions by triads, dyads and single individuals. There are 13 complete triads (adolescent, parent/carer and clinician completed the scale at both times); 40 dyads (23 dyads of parents/carers and clinicians, 13 dyads of adolescents and clinicians and 4 dyads of adolescents and parents/carers); and 28 individual completions (11 adolescents, 10 parents/carers and 7 clinicians). The remaining subjects from Cohort 1 did not complete scales at two time points and hence were not used for test–retest reliability.
Cohort 2: Included 244 adolescent, 198 parent and 240 clinician-completions from across the six countries that were part of the STOP project. Data were collected from the various cohorts (healthy subjects, subjects with respiratory illness, subjects with psychiatric diagnoses without depression and subjects with depression) investigated in the STOP project. Completion rates varied, because an adolescent might have completed the scale but not his/her parent or the related clinician (see table 2 for the descriptive details).
Baseline characteristics of Cohort 2
All study scales were completed using the web-based HealthTracker platform which automatically scored the questionnaires and stored it in the database.
An inclusion criterion for the STOP project was that those participants on treatment should have had it initiated in the month of baseline data collection.
For Cohort 2, there were 59 complete triads (adolescent, parent/carer and clinician completed the scale at both times); 135 dyads (37 dyads of parents/carers and clinicians, 71 dyads of adolescents and clinicians and 27 dyads of adolescents and parents/carers); and 235 individual completions (87 adolescents, 75 parents/carers and 73 clinicians).
Statistical analysis
Descriptive statistics were used to characterise the study cohorts. Reliability was assessed using Cronbach’s alpha, inter-rater reliability through correlations between the three versions of the scales and exploratory factor analyses (EFA) were performed. In the EFA the extraction method used principal axis factoring with Promax rotation. All p values are for two-tailed tests with α=0.05. Data were analysed using SPSS V.23.0, Chicago, Illinois, USA.
Patient and public involvement
In this study, subjects were involved in the development of the STOP-MS3.
Eight focus groups at the Child and Adolescent Psychiatry Department of the Hospital Clinic of Barcelona were done to gather participant (parent/carer and young person) understanding of the draft version of the (STOP-MS3).
Results
Phase 1: Development of the STOP-MS3
The first draft included 46 items, each of which describes a side effect potentially related to suicidality (figure 1). The final STOP-MS3 adolescent version consisted of 24 items for each version of the scale (ie, adolescent, parent/carer and clinician) with a recall period of 3 weeks. Each item included a domain name and a brief description of the side effect. Each domain had two subquestions which were rated on a 5-points Likert scale. One subquestion was about severity of the side effect (scored from 0 (not present) to 4 (extreme)) and the second subquestion specifically explored the impact of the side effect on thoughts or behaviours of hurting oneself (scored from 0 (not at all) to 4 (a great deal)). The score of each item was obtained by the sum of the scores of the two subquestions divided by two. Subjects were not excluded from the analyses if they had missing values. The online HealthTracker platform used to complete the questionnaires, ensures that the data set is always complete, as it does not allow raters to proceed if there are unanswered questions. Therefore, there are no missing responses. However, based on focus group feedback when the questionnaire was developed, we allowed a response of ‘I don’t know’, when study participants were unsure about the relationship between side effects and suicidality. The percentage of the ‘I don’t know’ responses in each version of the scale for Cohort 1 was: adolescents 1.26%, parents/carers 2.47% and clinicians 18.31%. In Cohort 2 the percentages were: adolescents 1.76%, parents/carers 5.65% and clinicians 2.91%. To prepare the data of Cohort 1 and 2 for analyses a composite score for each item was estimated. When the answer to one subquestion was ‘I don’t know’, the answer was coded as an empty data cell, which works like a zero. When the answers to both subquestions regarding a specific side effect were rated as ‘I don’t know’ the data was coded as an empty cell, and that questionnaire completion was excluded from the analysis. A sample screenshot of the questionnaire is shown in online supplemental figure 1.
Phase 2: Psychometric properties of the STOP-MS3
Reliability: Internal consistency (Cohort 2): Cronbach’s alpha was excellent for the adolescent (α=0.941), parent/carer (α=0.925) and clinician versions (α=0.877) of the STOP-MS3.
Inter-rater reliability (Cohort 2): As shown in table 3, the correlations were all significant: adolescent and parent/carer (r=0.394; p<0.001), adolescent and clinician (r=0.613; p<0.001) and parent/carer and clinician (r=0.347; p<0.001).
Correlations (inter-rater reliability) from the STOP-MS3
Validity
Ability to capture change (Cohort 1)
Analysis was conducted to demonstrate the ability of the scale to capture change of ratings across time. Our findings suggest that the scale has the potential to capture change within a space of 3 weeks. The items in the STOP-MS3 cover medication side effects and associated suicidality. We found a significant difference for the clinician version (p=0.004). This demonstrates the ability of the STOP-MS3 to capture change (see table 4).
Paired differences of the STOP-MS3
Exploratory factor analyses (Cohort 2)
The EFA for the adolescent version (online supplemental table 2) of the STOP-MS3 resulted in a 3-factors model that best fitted the data. Similar results were found for the parent/carer version of the scale (online supplemental table 3). Differently, we found that the clinician version of the scale best fitted with a 4-factors model (online supplemental table 4). The EFAs were performed using Eigen values >1.25 with the minimum loading for EFA threshold of 0.200.18 Based on the pattern of symptom domain loadings in the factors across the adolescent and parent/carer versions of the scales, the factors were named: (1) Emotional Dysregulation, (2) Somatic Dysregulation and (3) Behavioural Dysregulation. For the Clinician version of the scale the factors were named: (1) Somatic Dysregulation, (2) Emotional Dysregulation, (3) Behavioural Dysregulation and (4) Mood Dysregulation.
Discussion
The key finding of this study is that the STOP-MS3 is a reliable instrument for the assessment and monitoring of medication side effects related to suicidality in adolescents. The STOP-MS3 adolescent, parent and clinician versions are web-based measures that consist of 24 items, each of which has a ‘severity’ subquestion and an ‘impact on suicidality’ subquestion that are rated on a 5-point Likert scale. The STOP-MS3 has items that cover symptoms associated with emotional, somatic, behavioural and mood dysregulation, and is concise and easy to use. Of note, the questionnaire cannot be used without the STOP-SQ as the STOP-MS3 specifically evaluates the impact of medication on suicidality.
From a psychometric perspective we observed good internal consistency for all the versions of STOP-MS3, suggesting good reliability and providing preliminary evidence that the symptom domains measure a common underlying construct. We also found significant correlations between the three versions of the STOP-MS3, with a good correlation between the adolescent and clinician versions. This could be interpreted as a robust agreement between their views on the severity and impact of MRS on suicidal thoughts and behaviours. It supports the notion that adolescents can communicate their views on side effects and suicidality with clinicians and highlights the importance of conducting face-to-face interviews with them. A possible factor contributing to this observation may be the use of web-based tools, which may appeal more to adolescents and young people due to their increased accessibility and the anonymity they can provide. We also showed that there is a correlation between parent and adolescent ratings on the questionnaire. This is understandable, as adolescents may be more able to discuss difficult information such as suicidality, with both parents and clinicians.
Our findings suggest that the scale has the potential to capture change within a space of 3 weeks. We observed changes within this period for the adolescent rating of suicidality and side effects suggesting that side effects and associated suicidality fluctuate rapidly and can be reported by the individual experiencing it. This is not surprising because both side effects and suicidality are often subjective experiences, that have previously been shown to be rated better by the adolescent themselves.28 29
The factor structure generated by the EFA for each version of STOP-MS3 was similar across the adolescent and parent/carer versions of the scale. However, the clinician version of the scale is best fitted with a model composed of four factors. These findings suggest that although the adolescent and parent/carer versions of the STOP-MS3 can capture the impact of medication on suicidal ideations and behaviours, the clinician version was better at capturing change. The STOP-MS3 factor structure for all three versions also broadly aligns with the domain framework of the Patient-Reported Outcomes Measurement Information System (PROMIS) (www.nihpromis.org), which proposes factors for Anger, Anxiety and Depression and Pain and Fatigue domains.
To the best of our knowledge, this is the first study that used web-based assessments for the identification and monitoring of MRS. Our findings suggest that the STOP-MS3 can comprehensively capture the frequency and severity of MRS in adolescents, and can also be used by their parents/carers and clinicians. The HealthTracker-web-based PROM uses intelligent branching, audio-assistance for those with reading difficulties, adaptions for visual impairment (with large font-size adaptations) and availability in multiple languages (English, Spanish, Italian, German, French and Dutch).21 This allows adolescents, parents and clinicians to complete it effortlessly in a few minutes. In addition, it allows clinicians to monitor MRS in adolescents and assists medication-decision-making, optimise use of clinical time and has the potential to be used in prospective clinical trials to identify medication-related suicidality and its time-course.
Of note, we acknowledge the limitations of this study. We only included subjects who were screened positive on the screening questionnaire of the STOP-SAS.17 We deemed it inappropriate to ask all participants about the impact of the medication side effect on suicidality if there was no suicidality and therefore the STOP-MS3 is only to be used when the STOP-screening is positive. In this study, approximately 80% of the sample was white and 99% cis gender. The study findings would therefore probably not apply for those individuals who do not fall into these socio-demographic categories. Further work would be needed to address representation of the wider clinical population especially from ethnically diverse backgrounds. This element will be crucial to address given that a recent combined systematic review and meta-analysis has highlighted the importance of addressing the differences of suicide risk in groups from ethnic minority backgrounds.30
Conclusion
In summary, our findings suggest that the HealthTracker eCOA of STOP-MS3 adolescent, parent/carer and clinician versions are PROMs and clinician instruments with good psychometric properties that have the potential to identify and monitor MRS in adolescents, using self and proxy measures from parents/carer and clinicians. The STOP-MS3 should be tested in clinical populations in routine clinical care as well as those recruited in clinical trials, to ensure that it can capture the information in non-research settings. Baseline evaluation is essential to ensure that the findings can be attributed to medication initiation. When high scores are detected, it should lead to an in-depth clinical assessment as to the safety of continuing with the medication and to ensure that appropriate risk management strategies are implemented. These patients may require more frequent clinical reviews till they are stabilised.
Data availability statement
Data are available upon reasonable request. Data are available upon reasonable request from the corresponding author.
Ethics statements
Patient consent for publication
Ethics approval
The STOP project and the study was approved by the Kent Research Ethics Committee and Institute of Psychiatry, King’s College London Research and Development Office (REC Reference Number 13/LO/0401). Institutional Review Board approval was obtained in all other participating countries. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
STOP Consortium: All the co-authors of the manuscript and the following: Alastair Sutcliffe. University College London, Institute of Child Health, London, UK. Alberto Rodriguez-Quiroga. Hospital General Universitario Gregorio Marañón, CIBERSAM, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain. Alexander Häge. Paediatric Psychopharmacology, Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. Alexander Schneider. University of Ulm, Ulm, Germany. Alfred C Kolozsvari. HealthTracker Ltd, Gillingham, UK. Amalia La Fuente. University of Barcelona. Ameli Schwalber. Concentris, Germany. Ana Espliego. Hospital General Universitario Gregorio Marañón, CIBERSAM, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain. Ana Ortiz. Fundació Clínic per la Recerca Biomèdica, Barcelona, Spain. Andrea Schwalber. Concentris, Germany. Andrea Wohner. Concentris, Germany. Bruno Falissard. Univ. Paris-Sud, INSERM U669, AP-HP, Paris, France. Claire Baillon. Assistance Publique – Hopitaux de Paris, Robert Debré Hospital, Paris, France. Alexandre Hubert. Assistance Publique – Hopitaux de Paris, Robert Debré Hospital, Paris, France. Cora Drent. University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, The Netherlands. Covadonga Martínez Díaz-Caneja. Hospital General Universitario Gregorio Marañón, CIBERSAM, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain. David Cohen. Assistance Publique – Hopitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière, Paris, France. Elly Bloem. University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, The Netherlands. Ewa Nowotny. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Ferdinand Keller. University of Ulm, Ulm, Germany. Florence Pupier. CHU Montpellier, Hôpital Saint Eloi, Médecine Psychologique de l’Enfant et de l’Adolescent, Montpellier, France. Franca Ligas. Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy. Francesca Micol Cera. Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy. Helen Furse. HealthTracker Ltd, Gillingham, UK. Hugo Peyre. Assistance Publique – Hopitaux de Paris, Robert Debré Hospital, Paris, France. Ian Craig. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Immaculada Baeza. Fundació Clínic per la Recerca Biomèdica, Barcelona, Spain. Jacqui Paton. University of Dundee, UK. Jatinder Singh. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Jeffrey Glennon. Radboud University Medical Centre., Nijmegen, The Netherlands. Jessica Merchán. CIBERSAM, Madrid, Spain. Jörg Fegert. University of Ulm, Ulm, Germany. Juan José Carballo. Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, CIBERSAM, IiSGM, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain. Juliane Dittrich. Concentris, Germany. Julie Brunelle. Assistance Publique – Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière, Paris, France. Katherine Aitchison. University of Alberta, Edmonton, Canada. Katrin Zimmermann. Concentris, Germany. Keren Yeboah. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Konstantin Mechler. Paediatric Psychopharmacology, Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. Lara Kehrmann. CIBERSAM, Madrid, Spain. Laura Selema. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Loes Vinkenvleugel. Radboud University Medical Centre, Nijmegen, The Netherlands. Macey Murray. University College London, UK. Mahmud Ben Dau. Central Institute of Mental Health, Mannheim, Germany. Manuela Pintor. Child and Adolescent Neuropsychiatry Unit, ‘A. Cao’ Paediatric Hospital, ‘G. Brotzu’ Hospital Trust, Cagliari, Italy. Mark-Peter Steenhuis. University of Groningen, University Medical Center Groningen, Department of Psychiatry. The Netherlands. Matthew Hollocks. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Mireille Bakker. Radboud University Medical Centre, Nijmegen, The Netherlands. Nathalie Franc. CHU Montpellier; Hôpital Saint Eloi, Médecine Psychologique de l’Enfant et de l’Adolescent, France. Nathan Parnell. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Noha Iessa. University College London, UK. Olivier Bonnot. CHU of Nantes, Child and Adolescent Psychiatry, Nantes, France. Paul Plener. University of Ulm, Ulm, Germany. Pierre Raysse. CHU Montpellier, Hôpital Saint Eloi, Médecine Psychologique de l’Enfant et de l’Adolescent, France. Robert Flanagan. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King’s College London, London, UK. Roberta Frongia. Child and Adolescent Neuropsychiatry Unit, ‘A. Cao’ Paediatric Hospital, ‘G. Brotzu’ Hospital Trust, Cagliari, Italy. Ruth Berg. Paediatric Psychopharmacology, Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. Sara Bahadori. Assistance Publique – Hôpitaux de Paris, Robert Debré Hospital, Paris, France. Sarah Curran. King's College London, University of Sussex, Sussex Partnership NHS Foundation Trust, UK. Simon Schlanser. University of Ulm, Ulm, Germany. Soledad Romero. Fundació Clínic per la Recerca Biomèdica, Barcelona, Spain. Sonja Aslan. University of Ulm, Ulm, Germany. Sylke Rauscher. Paediatric Psychopharmacology, Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. Todor Mutafov. HealthTracker Ltd, Gillingham, UK. Véronique Humbertclaude. CHU Montpellier, Hôpital Saint Eloi, Médecine Psychologique de l’Enfant et de l’Adolescent, France.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Deceased In Memoriam of Professor Alessandro Zuddas (1957-2022), Dept. Biomedical Sciences, Sect. Neuroscience & Clinical Pharmacology, University of Cagliari, Italy & Child & Adolescent Neuropsychiatry Unit, “A.Cao” Paediatric Hospital, Cagliari, Italy.
Contributors PS led the study, reviewed the manuscript and provided important intellectual content and is the guarantor. RS and MM wrote the manuscript. FF was responsible for the data analyses. JS revised draft versions on the manuscript. Members of the STOP Consortium (CA, JKB, JC-F, DC, RWD, IF, PJH, KL, CL, DP-O, US, AZ, NP) provided intellectual inputs to study design and participant recruitment and critically reviewed the manuscript. In Memoriam of Professor Alessandro Zuddas (1957-2022), Dept. Biomedical Sciences, Sect. Neuroscience & Clinical Pharmacology, University of Cagliari, Italy & Child & Adolescent Neuropsychiatry Unit, ‘A.Cao’ Paediatric Hospital, Cagliari, Italy.
Funding The research leading to this publication has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 261411. CA was supported by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso (Grant No. - N/A), and Fundación Alicia Koplowitz (Grant No. - N/A). JKB has been supported by the EU-AIMS (European Autism Interventions) and AIMS-2-TRIALS programmes which receive support from Innovative Medicines Initiative Joint Undertaking Grant No. 115300 and 777394, the resources of which are composed of financial contributions from the European Union’s FP7 and Horizon2020 Programmes, and from the European Federation of Pharmaceutical Industries and Associations (EFPIA) companies’ in-kind contributions, and AUTISM SPEAKS, Autistica and SFARI).
Competing interests PS is a co-inventor of the HealthTracker platform, a Chief Executive Officer (CEO) of HealthTracker Ltd and a shareholder of HealthTracker Ltd. and has received research funding for conducting clinical trials from Anavex Scientific Corp, GW Pharma, and Newron Pharmaceuticals. FF is a Chief Technology Officer (CTO) and shareholder of HealthTracker Ltd. KL was a Project Manager employed at HealthTracker Ltd. CA has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Minerva, Otsuka, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. JKB has been in the past 3 years a consultant to / member of advisory board of / and/or speaker for Takeda/Shire, Roche, Medice, Angelini, Janssen and Servier. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. He has no other financial or material support, including expert testimony, patents, royalties. RWD has received compensation for serving as consultant or speaker, or he or the institution he works for have received research support or royalties from the organisations or companies indicated: EU (FP7 Programme), US National Institute of Mental Health (NIMH), German Federal Ministry of Health/Regulatory Agency (BMG/BfArM), German Federal Ministry of Education and Research (BMBF), German Research Foundation (DFG), Volkswagen Foundation; Boehringer Ingelheim, Ferring, Janssen-Cilag, Lilly, Lundbeck, Otsuka, Servier, Shire, Sunovion/Takeda and Theravance. He owns Eli Lilly stock. Since 2008, he has fully been affiliated with the Department of CAP, CIMH, Medical Faculty Mannheim, University of Heidelberg, Germany. DP-O reports that in the past 3 years, she had non-financial support from HAC Pharma and Boehringer-Ingelheim, honoraria from Medice outside the submitted work and unpaid scientific coordination for a study sponsored by Mensia. AZ in the past 3 years had been a consultant to / member of advisory board of / and/or speaker or received research grants from: Angelini, Jannsen, Lundbeck and Otsuka, Servier, Shire/Takeda. He is not an employee of any of these companies, and not a stock shareholder of any of these companies, He received royalties from Oxford University Press and Giuntio OS. RS has been an advisor to or has received honoraria from Takeda. US received speaker’s fees from Takeda/Shire. DC has been in the past 3 years a consultant to / member of advisory board of / and/or speaker for Takeda/Shire, Novartis, Medice and Servier. He has received royalties from Oxford University Press and Cambridge University Press. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. Part of this data has been included in an FP7 STOP Report to the European Union.
Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.