Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health.

The term "digital phenotype" refers to the digital footprint left by patient-environment interactions. It has potential for both research and clinical applications but challenges our conception of health care by opposing 2 distinct approaches to medicine: one centered on illness with the aim of classifying and curing disease, and the other centered on patients, their personal distress, and their lived experiences. In the context of mental health and psychiatry, the potential benefits of digital phenotyping include creating new avenues for treatment and enabling patients to take control of their own well-being. However, this comes at the cost of sacrificing the fundamental human element of psychotherapy, which is crucial to addressing patients' distress. In this viewpoint paper, we discuss the advances rendered possible by digital phenotyping and highlight the risk that this technology may pose by partially excluding health care professionals from the diagnosis and therapeutic process, thereby foregoing an essential dimension of care. We conclude by setting out concrete recommendations on how to improve current digital phenotyping technology so that it can be harnessed to redefine mental health by empowering patients without alienating them.

Maternal immune activation during pregnancy is associated with more difficulties in socio-adaptive behaviors in autism spectrum disorder.

Autism spectrum disorder (ASD) are neurodevelopmental conditions characterised by deficits in social communication and interaction and repetitive behaviours. Maternal immune activation (MIA) during the mid-pregnancy is a known risk factor for ASD. Although reported in 15% of affected individuals, little is known about the specificity of their clinical profiles. Adaptive skills represent a holistic approach to a person's competencies and reflect specifically in ASD, their strengths and difficulties. In this study, we hypothesised that ASD individual with a history of MIA (MIA+) could be more severely socio-adaptively impaired than those without MIA during pregnancy (MIA-). To answer this question, we considered two independent cohorts of individuals with ASD (PARIS study and FACE ASD) screened for pregnancy history, and used supervised and unsupervised machine learning algorithms. We included 295 mother-child dyads with 14% of them with MIA+. We found that ASD-MIA+ individuals displayed more severe maladaptive behaviors, specifically in their socialization abilities. MIA+ directly influenced individual's socio-adaptive skills, independent of other covariates, including ASD severity. Interestingly, MIA+ affect persistently the socio-adaptive behavioral trajectories of individuals with ASD. The current study has a retrospective design with possible recall bias regarding the MIA event and, even if pooled from two cohorts, has a relatively small population. In addition, we were limited by the number of covariables available potentially impacted socio-adaptive behaviors. Larger prospective study with additional dimensions related to ASD is needed to confirm our results. Specific pathophysiological pathways may explain these clinical peculiarities of ASD- MIA+ individuals, and may open the way to new perspectives in deciphering the phenotypic complexity of ASD and for the development of specific immunomodulatory strategies.

Psychotropic drugs consumption during 2020 COVID-19 pandemic and lockdowns: Evidence of a surprising resilience of the drugs delivery system in France.

The COVID-19 pandemic imposed two lockdowns of eight and six weeks in France. While access to care was reduced during lockdown periods, these stressful situations with the pandemic and lockdown periods may have a negative impact on mental health, especially in vulnerable subgroups. Monitoring of psychotropic drugs consumption in France is a comprehensive and reliable tool for indirectly analyzing the mental health of French people. This historical cohort study (n = 767 147) investigated the short-term and long-term evolution of the weekly trend of psychotropic drugs users in 2020 by performing a Seasonal Trend decomposition time series analysis. Rate of progression of consumers per week increased from 186 in the last week of 2019 to 261 per week in the last week of 2020 (+40.3%). Our results did not show a significant break in psychotropic drugs consumption trends during the year 2020 and its two lockdowns. The increase in trend regarding psychotropic drugs consumptions was greatest in young people (<15 years) and patients not being socially deprived. Despite the increase in consumers with restrictive health measures, the French drugs delivery system has been able to adapt with the support of government and pharmacy network. This point should be kept in mind as the necessary reforms to the health care system are undertaken. The COVID-19 pandemic has a negative impact on mental health and two lockdowns occurred in France with reduced access to care. In this context, monitoring of psychotropic drugs consumption is a comprehensive and reliable tool for analyzing the mental health of French people. We hypothesized that the psychotropic drugs consumption has increased during the 2020 COVID-19 pandemic, testifying to French people mental health deterioration, with psychotropic drugs consumption breaks during lockdowns, especially during the first "grand national lockdown", due to the closure or difficulties for accessing to health care structures. By carrying out a historical cohort study among Pays de la Loire residents (n = 767 147), we investigated evolution of the weekly trend of psychotropic drugs users in 2020 compared to 2019 by performing a Seasonal Trend decomposition time series analysis. Between 2019 to 2020, we found a + 40.3% rate of progression of consumers per week. During the year 2020, changes in trend regarding psychotropic drugs consumptions was observed in various sub-groups, e.g. greater in the youngest (< 15 years), which may indicate a vulnerable group strongly impacted by COVID-19 negative consequences, and patients not being socially deprived, which may indicate a group with probably an easier access to care. Lockdown periods were not associated with a significant change in psychotropic drug use, suggesting a form of resilience in the French health care system to maintain its capacity to deliver psychotropic treatments. We mainly discussed that despite the increase in consumers and the policies of restricting access to care during lockdown periods, the French drugs delivery system has been able to adapt thanks to supportive policy actions (extension of the prescriptions validity without the need for a renewal by a physician during periods of lockdowns), an efficient pharmacy network with a collaborative practice of health actors that need to be developed and/or conserved to face potential future health crises.

Gender differences in psychosocial function and self-reported health status in late-diagnosed autistic adults: results from the FACE-ASD national cohort.

BACKGROUND: While adult outcome in autism spectrum disorder (ASD) is generally measured using socially valued roles, it could also be understood in terms of aspects related to health status - an approach that could inform on potential gender differences. METHODS: We investigated gender differences in two aspects of outcome related to health-status, i.e. general functioning and self-perceived health status, and co-occurring health conditions in a large multi-center sample of autistic adults. Three hundred and eighty-three participants were consecutively recruited from the FondaMental Advanced Centers of Expertise for ASD cohort (a French network of seven expert centers) between 2013 and 2020. Evaluation included a medical interview, standardized scales for autism diagnosis, clinical and functional outcomes, self-perceived health status and verbal ability. Psychosocial function was measured using the Global Assessment of Functioning scale. RESULTS: While autistic women in this study were more likely than men to have socially valued roles, female gender was associated with poorer physical and mental health (e.g. a 7-fold risk for having three or more co-occurring physical health conditions) and a poorer self-perceived health status. Psychosocial function was negatively associated with depression and impairment in social communication. Half of the sample had multiple co-occurring health conditions but more than 70% reported that their visit at the Expert Center was their first contact with mental health services. CONCLUSIONS: To improve objective and subjective aspects of health outcome, gender differences and a wide range of co-occurring health conditions should be taken into account when designing healthcare provision for autistic adults.

Emergence of psychiatric adverse events during antipsychotic treatment in AP-naïve children and adolescents.

BACKGROUND: Over the last decades, antipsychotic prescriptions in children have increased worldwide. However, adverse events are frequently observed, with some such as psychiatric adverse events remaining poorly documented. METHOD: The French ETAPE study is a 12-month naturalistic prospective multisite study that included 190 antipsychotic-naïve pediatric patients (mean age = 12 ± 3 years), treated by antipsychotic for psychotic or non-psychotic symptoms. From the ETAPE database, we performed additional analyses focusing on psychiatric adverse events. RESULTS: Children received mainly second-generation antipsychotic for conditions out of regulatory approval, with risperidone and aripiprazole being the most frequent (respectively 52.5% and 30.83%). Clinicians reported 2447 adverse events, mainly non-psychiatric (n = 2073, 84.72%), including neuromuscular, metabolic, gastroenterological, and (n = 374, 15.28%) psychiatric. 55.88% of psychiatric adverse events were attributable to antipsychotic by the clinician, compared to 89% of non-psychiatric adverse events (p < 0.001). 63.2% (n = 120) of the 190 children and adolescents presented at least one psychiatric adverse event. The most frequent were externalized behaviors such as aggressiveness or agitation (22.7%), mood changes (18.4%) and suicidal ideas or behaviors (11.8%). Half of psychiatric adverse events occurred during the first quarter, 49.46%, compared to 23.79% during the second, 15.77% during the third, and 10.96% during the fourth. CONCLUSION: This additional analysis from the French ETAPE study emphasizes that psychiatric adverse events might be more frequent than expected in the pediatric population. Also, the potential risk of psychiatric adverse events should be part of the benefit-risk evaluation and sub-sequent follow-up.

Digital phenotype of mood disorders: A conceptual and critical review.

Background: Mood disorders are commonly diagnosed and staged using clinical features that rely merely on subjective data. The concept of digital phenotyping is based on the idea that collecting real-time markers of human behavior allows us to determine the digital signature of a pathology. This strategy assumes that behaviors are quantifiable from data extracted and analyzed through digital sensors, wearable devices, or smartphones. That concept could bring a shift in the diagnosis of mood disorders, introducing for the first time additional examinations on psychiatric routine care. Objective: The main objective of this review was to propose a conceptual and critical review of the literature regarding the theoretical and technical principles of the digital phenotypes applied to mood disorders. Methods: We conducted a review of the literature by updating a previous article and querying the PubMed database between February 2017 and November 2021 on titles with relevant keywords regarding digital phenotyping, mood disorders and artificial intelligence. Results: Out of 884 articles included for evaluation, 45 articles were taken into account and classified by data source (multimodal, actigraphy, ECG, smartphone use, voice analysis, or body temperature). For depressive episodes, the main finding is a decrease in terms of functional and biological parameters [decrease in activities and walking, decrease in the number of calls and SMS messages, decrease in temperature and heart rate variability (HRV)], while the manic phase produces the reverse phenomenon (increase in activities, number of calls and HRV). Conclusion: The various studies presented support the potential interest in digital phenotyping to computerize the clinical characteristics of mood disorders.

Efficacy and Safety of Transcranial Electric Stimulation during the Perinatal Period: A Systematic Literature Review and Three Case Reports.

Introduction: The perinatal period is an at-risk period for the emergence or decompensation of psychiatric disorders. Transcranial electrical stimulation (tES) is an effective and safe treatment for many psychiatric disorders. Given the reluctance to use pharmacological treatments during pregnancy or breastfeeding, tES may be an interesting treatment to consider. Our study aims to evaluate the efficacy and safety of tES in the perinatal period through a systematic literature review followed by three original case reports. Method: Following PRISMA guidelines, a systematic review of MEDLINE and ScienceDirect was undertaken to identify studies on tES on women during the perinatal period. The initial research was conducted until 31 December 2021 and search terms included: tDCS, transcranial direct current stimulation, tACS, transcranial alternating current stimulation, tRNS, transcranial random noise stimulation, pregnancy, perinatal, postnatal, and postpartum. Results: Seven studies reporting on 33 women during the perinatal period met the eligibility criteria. No serious adverse effects for the mother or child were reported. Data were limited to the use of tES during pregnancy in patients with schizophrenia or unipolar depression. In addition, we reported three original case reports illustrating the efficacy and safety of tDCS: in a pregnant woman with bipolar depression, in a pregnant woman with post-traumatic stress disorder (sham tDCS), and in a breastfeeding woman with postpartum depression. Conclusions: The results are encouraging, making tES a potentially safe and effective treatment in the perinatal period. Larger studies are needed to confirm these initial results, and any adverse effects on the mother or child should be reported. In addition, research perspectives on the medico-economic benefits of tES, and its realization at home, are to be investigated in the future.

Efficacy, Tolerability, and Acceptance of Long-Lasting Antipsychotics in Children and Adolescents: A Systematic Review.

Objectives: While long-lasting antipsychotics (LLA) were specifically developed to address the problem of adherence in patients with chronic psychiatric disorders, their role in pediatric populations is not clear. Methods: To document the efficacy, tolerance, and acceptance of LLAs in children and adolescents, a literature search was conducted using several databases for published studies (PubMed, PsycINFO) from January 1965 to December 2020. Twenty-two studies were identified (16 case reports/series, 3 open label studies, 2 controlled studies, and 1 retrospective analysis of national database). Results: Demographic features were widely heterogeneous across studies (total N = 480, 58% male, mean age = 15.0 ± 1.8). Case reports/series presented positive therapeutic outcomes in noncompliant youths with severe mental illness. Three open-label one-arm studies supported the clinical efficacy of risperidone long-acting injection in patients previously stabilized with oral risperidone. One study showed lower clinical symptoms and higher functioning at 12 months in youths treated for an acute psychotic episode with paliperidone palmitate compared to oral risperidone. The types and rates of side effects of LLA were comparable to those observed for oral antipsychotics. Two studies suggested better metabolic and neurological tolerance of LLA compared to an oral form. Preliminary evidence supported a satisfactory level of treatment satisfaction in patients treated with LLA and their families, while concerns were raised regarding practical administration in outpatient services. However, the average quality of the evidence based on the RoB2 tool was low. Conclusions: The level of evidence was low for the efficacy of LLA in pediatric populations and very low for the tolerance and acceptance. It concerned mostly the effect of risperidone long-acting injection in adolescents with psychotic disorders. Randomized maintenance clinical trials using noninferiority analysis would be more appropriate for further research.

Early Detection of Neurodevelopmental Disorders of Toddlers and Postnatal Depression by Mobile Health App: Observational Cross-sectional Study.

BACKGROUND: Delays in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) in mothers are major public health issues. In both cases, early intervention is crucial. OBJECTIVE: We aimed to assess if a mobile app named Malo can reduce delay in the recognition of NDD and PND. METHODS: We performed an observational, cross-sectional, data-based study in a population of young parents with a minimum of 1 child under 3 years of age at the time of inclusion and using Malo on a regular basis. We included the first 4000 users matching the criteria and agreeing to participate between November 11, 2021, and January 14, 2022. Parents received monthly questionnaires via the app, assessing skills on sociability, hearing, vision, motricity, language of their infants, and possible autism spectrum disorder. Mothers were also requested to answer regular questionnaires regarding PND, from 4-28 weeks after childbirth. When any patient-reported outcomes matched predefined criteria, an in-app notification was sent to the user, recommending the booking of an appointment with their family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the median time of PND notifications after childbirth. One secondary outcome was the relevance of the NDD notification for a consultation as assessed by the physicians. RESULTS: Among 4242 children assessed by 5309 questionnaires, 613 (14.5%) had at least 1 disorder requiring a consultation. The median age of notification for possible autism spectrum, vision, audition, socialization, language, or motor disorders was 11, 9, 17, 12, 22, and 4 months, respectively. The sensitivity of the alert notifications of suspected NDDs as assessed by the physicians was 100%, and the specificity was 73.5%. Among 907 mothers who completed a PND questionnaire, highly probable PND was detected in 151 (16.6%) mothers, and the median time of detection was 8-12 weeks. CONCLUSIONS: The algorithm-based alert suggesting NDD was highly sensitive with good specificity as assessed by real-life practitioners. The app was also efficient in the early detection of PND. Our results suggest that the regular use of this multidomain familial smartphone app would permit the early detection of NDD and PND. TRIAL REGISTRATION: ClinicalTrials.gov NCT04958174; https://clinicaltrials.gov/ct2/show/NCT04958174.

Development of a suspicion index for secondary schizophrenia using the Delphi method.

AIM: The aim of this study was to develop a suspicion index that aids diagnosis of secondary schizophrenia spectrum disorders in regular clinical practice. METHOD: We used the Delphi method to rate and refine questionnaire items in consecutive rounds. Differences in mean expert responses for schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders populations allowed to define low/middle/high predictive items, which received different weights. Algorithm performance was tested in 198 disease profiles by means of sensitivity and specificity. RESULTS: Twelve experts completed the Delphi process, and consensus was reached in 19/24 (79.2%) items for schizophrenia spectrum disorders and 17/24 (70.8%) for secondary schizophrenia spectrum disorders. We assigned rounded values to each item category according to their predictive potential. A differential distribution of scores was observed between schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders when applying the suspicion index for validation to 198 disease profiles. Sensitivity and specificity analyses allowed to set a >8/10/16 risk prediction score as a threshold to consider medium/high/very high suspicion of secondary schizophrenia spectrum disorders. CONCLUSION: Our final outcome was the Secondary Schizophrenia Suspicion Index, the first paper-based and reliable algorithm to discriminate secondary schizophrenia spectrum disorders from schizophrenia spectrum disorders with the potential to help improve the detection of secondary schizophrenia spectrum disorder cases in clinical practice.

In Search of Digital Dopamine: How Apps Can Motivate Depressed Patients, a Review and Conceptual Analysis.

INTRODUCTION: Depression is highly prevalent and causes considerable suffering and disease burden despite the existence of wide-ranging treatment options. Momentary assessment is a promising tool in the management of psychiatric disorders, and particularly depression. It allows for a real-time evaluation of symptoms and an earlier detection of relapse or treatment efficacy. Treating the motivational and hedonic aspects of depression is a key target reported in the literature, but it is time-consuming in terms of human resources. Digital Applications offer a major opportunity to indirectly regulate impaired motivational circuits through dopaminergic pathways. OBJECTIVE: The main objective of this review was twofold: (1) propose a conceptual and critical review of the literature regarding the theoretical and technical principles of digital applications focused on motivation in depression, activating dopamine, and (2) suggest recommendations on the relevance of using these tools and their potential place in the treatment of depression. MATERIAL AND METHODS: A search for words related to "dopamine", "depression", "smartphone apps", "digital phenotype" has been conducted on PubMed. RESULTS: Ecological momentary interventions (EMIs) differ from traditional treatments by providing relevant, useful intervention strategies in the context of people's daily lives. EMIs triggered by ecological momentary assessment (EMA) are called "Smart-EMI". Smart-EMIs can mimic the "dopamine reward system" if the intervention is tailored for motivation or hedonic enhancement, and it has been shown that a simple reward (such as a digital badge) can increase motivation. DISCUSSION: The various studies presented support the potential interest of digital health in effectively motivating depressed patients to adopt therapeutic activation behaviors. Finding effective ways to integrate EMIs with human-provided therapeutic support may ultimately yield the most efficient and effective intervention method. This approach could be a helpful tool to increase adherence and motivation. CONCLUSION: Smartphone apps can motivate depressed patients by enhancing dopamine, offering the opportunity to enhance motivation and behavioral changes, although longer term studies are still needed.

Prevention of Suicidal Relapses in Adolescents With a Smartphone Application: Bayesian Network Analysis of a Preclinical Trial Using In Silico Patient Simulations.

BACKGROUND: Recently, artificial intelligence technologies and machine learning methods have offered attractive prospects to design and manage crisis response processes, especially in suicide crisis management. In other domains, most algorithms are based on big data to help diagnose and suggest rational treatment options in medicine. But data in psychiatry are related to behavior and clinical evaluation. They are more heterogeneous, less objective, and incomplete compared to other fields of medicine. Consequently, the use of psychiatric clinical data may lead to less accurate and sometimes impossible-to-build algorithms and provide inefficient digital tools. In this case, the Bayesian network (BN) might be helpful and accurate when constructed from expert knowledge. Medical Companion is a government-funded smartphone application based on repeated questions posed to the subject and algorithm-matched advice to prevent relapse of suicide attempts within several months. OBJECTIVE: Our paper aims to present our development of a BN algorithm as a medical device in accordance with the American Psychiatric Association digital healthcare guidelines and to provide results from a preclinical phase. METHODS: The experts are psychiatrists working in university hospitals who are experienced and trained in managing suicidal crises. As recommended when building a BN, we divided the process into 2 tasks. Task 1 is structure determination, representing the qualitative part of the BN. The factors were chosen for their known and demonstrated link with suicidal risk in the literature (clinical, behavioral, and psychometrics) and therapeutic accuracy (advice). Task 2 is parameter elicitation, with the conditional probabilities corresponding to the quantitative part. The 4-step simulation (use case) process allowed us to ensure that the advice was adapted to the clinical states of patients and the context. RESULTS: For task 1, in this formative part, we defined clinical questions related to the mental state of the patients, and we proposed specific factors related to the questions. Subsequently, we suggested specific advice related to the patient's state. We obtained a structure for the BN with a graphical representation of causal relations between variables. For task 2, several runs of simulations confirmed the a priori model of experts regarding mental state, refining the precision of our model. Moreover, we noticed that the advice had the same distribution as the previous state and was clinically relevant. After 2 rounds of simulation, the experts found the exact match. CONCLUSIONS: BN is an efficient methodology to build an algorithm for a digital assistant dedicated to suicidal crisis management. Digital psychiatry is an emerging field, but it needs validation and testing before being used with patients. Similar to psychotropics, any medical device requires a phase II (preclinical) trial. With this method, we propose another step to respond to the American Psychiatric Association guidelines. TRIAL REGISTRATION: ClinicalTrials.gov NCT03975881; https://clinicaltrials.gov/ct2/show/NCT03975881.

Mobile App for Parental Empowerment for Caregivers of Children With Autism Spectrum Disorders: Prospective Open Trial.

BACKGROUND: Conflicting data emerge from literature regarding the actual use of smartphone apps in medicine; some considered the introduction of smartphone apps in medicine to be a breakthrough, while others suggested that, in real-life, the use of smartphone apps in medicine is disappointingly low. Yet, digital tools become more present in medicine daily. To empower parents of a child with autism spectrum disorder, we developed the Smartautism smartphone app, which asks questions and provides feedback, using a screen with simple curves. OBJECTIVE: The purpose of this study was to evaluate usage of the app by caregivers of individuals with autism spectrum disorders. METHODS: We conducted a prospective longitudinal exploratory open study with families that have a child with autism spectrum disorder. Data were recorded over a period of 6 months, and the outcome criteria were (1) overall response rates for a feedback screen and qualitative questionnaires, and (2) response rates by degree of completion and by user interest, based on attrition. RESULTS: Participants (n=65) had a very high intent to use the app during the 6-month period (3698/3900 instances, 94.8%); however, secondary analysis showed that only 46% of participants (30/65) had constant response rates over 50%. Interestingly, these users were characterized by higher use and satisfaction with the feedback screen when compared to low (P<.001) and moderate (P=.007) users. CONCLUSIONS: We found that real or perceived utility is an important incentive for parents who use empowerment smartphone apps. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2016-012135.

Improving clinical decision-making in psychiatry: implementation of digital phenotyping could mitigate the influence of patient's and practitioner's individual cognitive biases.

High stake clinical choices in psychiatry can be impacted by external irrelevant factors. A strong understanding of the cognitive and behavioural mechanisms involved in clinical reasoning and decision-making is fundamental in improving healthcare quality. Indeed, the decision in clinical practice can be influenced by errors or approximations which can affect the diagnosis and, by extension, the prognosis: human factors are responsible for a significant proportion of medical errors, often of cognitive origin. Both patient's and clinician's cognitive biases can affect decision-making procedures at different time points. From the patient's point of view, the quality of explicit symptoms and data reported to the psychiatrist might be affected by cognitive biases affecting attention, perception or memory. From the clinician's point of view, a variety of reasoning and decision-making pitfalls might affect the interpretation of information provided by the patient. As personal technology becomes increasingly embedded in human lives, a new concept called digital phenotyping is based on the idea of collecting real-time markers of human behaviour in order to determine the 'digital signature of a pathology'. Indeed, this strategy relies on the assumption that behaviours are 'quantifiable' from data extracted and analysed through connected tools (smartphone, digital sensors and wearable devices) to deduce an 'e-semiology'. In this article, we postulate that implementing digital phenotyping could improve clinical reasoning and decision-making outcomes by mitigating the influence of patient's and practitioner's individual cognitive biases.

Advocacy for better metabolic monitoring after antipsychotic initiation: based on data from a French health insurance database.

Background: Nearly 3% of the population is treated by antipsychotic. The aim of this study was to assess the conformity of monitoring with guidelines to prevent Metabolic Syndrome. Research design and method: The analysis was conducted using SNIIRAM data (2013 to 2017) on a cohort of patients who received at least eight antipsychotic dispensings in the first year. Glucose and lipid testings were recorded according to refunds at initiation [between -3 and 0.5 months], 3 months [between 2 and 4 months], and 12 months [between 11 and 13 months] after, and assuming optimal testing during hospitalization (exclusive of psychiatric unit). Descriptive and comparative analysis, «chi-squared test or Student's t-test¼, were performed as well as multivariate analysis with logistic regression. Results: 18 760 patients were selected, 14 421 were still alive and monitored at the end of the follow up. In the recommended period, only 2.89% of patients had three complete testings and 50.6% one or two complete testings Non-optimal testing was more likely to occur in children and adults (vs elderly), in patients with less than 3 prescribers, and with universal medical coverage. Conclusion: Monitoring remains dramatically insufficient. New actions involving patients, practitioners, and authorities are warranted.

A randomized controlled trial of 25 sessions comparing music therapy and music listening for children with autism spectrum disorder.

BACKGROUND: Music therapy is based on the use of musical elements by a trained and qualified therapist. Clinical researches have suggested that children with Autism Spectrum Disorders (ASD) may benefit from MT. In this regard, this study examines if MT is more effective than simply listening to music for children with ASD. METHOD: A 8-month RCT has been carried out comparing music therapy (MT) to music listening (ML) for children with ASD aged from 4 to 7 years old. Thirty-seven participants were randomly assigned to one of the two groups (MT vs. ML). The outcome measures were the Clinical Global Impression (CGI), the Childhood Autism Rating Scale (CARS) and the Aberrant Behavior Checklist (ABC) in each condition (MT and ML). RESULTS: CGI scores decreased more for participants in the MT than in the ML condition. This clinical improvement was associated with an improvement of autistic symptoms on lethargy and stereotypy ABC subscales. CONCLUSION: Our findings suggest that music therapy is more efficient than music listening for children with ASD. The present study thus supports the consideration of MT as a rightful add-on to ASD healthcare programs.

Psychiatric Advance Directives and Artificial Intelligence: A Conceptual Framework for Theoretical and Ethical Principles.

The patient's decision-making abilities are often altered in psychiatric disorders. The legal framework of psychiatric advance directives (PADs) has been made to provide care to patients in these situations while respecting their free and informed consent. The implementation of artificial intelligence (AI) within Clinical Decision Support Systems (CDSS) may result in improvements for complex decisions that are often made in situations covered by PADs. Still, it raises theoretical and ethical issues this paper aims to address. First, it goes through every level of possible intervention of AI in the PAD drafting process, beginning with what data sources it could access and if its data processing competencies should be limited, then treating of the opportune moments it should be used and its place in the contractual relationship between each party (patient, caregivers, and trusted person). Second, it focuses on ethical principles and how these principles, whether they are medical principles (autonomy, beneficence, non-maleficence, justice) applied to AI or AI principles (loyalty and vigilance) applied to medicine, should be taken into account in the future of the PAD drafting process. Some general guidelines are proposed in conclusion: AI must remain a decision support system as a partner of each party of the PAD contract; patients should be able to choose a personalized type of AI intervention or no AI intervention at all; they should stay informed, i.e., understand the functioning and relevance of AI thanks to educational programs; finally, a committee should be created for ensuring the principle of vigilance by auditing these new tools in terms of successes, failures, security, and relevance.