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Epidemiologia E Prevenzione 2022to evaluate the impact of school closures, as a measure to contain the transmission of SARS-CoV-2 infection, on the psychological well-being of students of all levels... (Review)
Review
OBJECTIVES
to evaluate the impact of school closures, as a measure to contain the transmission of SARS-CoV-2 infection, on the psychological well-being of students of all levels starting from the 2020-2021 school year.
DESIGN
a systematic literature review was conducted according to the PRISMA 2020 Guidelines. The literature search was conducted on 4 different databases: MedLine, Embase, PsycINFO, and L.OVE Platform. Quantitative observational studies published until 10.01.2022 were included. Studies conducted during the first pandemic wave, i.e., during the 2019-2020 school year and/or during the mandatory lockdown or confinement period, were excluded. The methodological quality of the studies was assessed with validated scales. Study selection, data extraction, and quality assessment were carried out independently by two authors.
SETTING AND PARTICIPANTS
children, adolescents, and young people attending all levels of education (including universities) and, for reasons related to COVID-19, having a suspension of "in presence" school or attending classes remotely.
MAIN OUTCOME MEASURES
a. outcomes directly related to mental health: suicides, emergency department visits, and hospitalizations for psychiatric problems; anxiety and depression, emotional difficulties, feelings of loneliness and isolation; b. well-being outcomes: sleep quality, perceived well-being (by child/adolescent/youth or referred by parents); c. health-related behaviours: tobacco smoking, alcohol, drug use. Outcomes related to school/academic performance, physical health, and those related to parents were not considered.
RESULTS
after having removed duplicate articles, 2,830 records were retrieved with the bibliographic search. Twelve studies (2 uncontrolled before-after studies and 10 cross sectional surveys) were included, involving a total of 27,787 participants. Three studies involved university students, 2 involved high school students, and the remaining involved a mixed population of students attending primary and middle schools. The studies were conducted between September 2020 and April 2021. The methodological quality was rated as high in five studies and intermediate in the remaining studies. Due to the high heterogeneity of outcome measures and statistical analyses performed among the included studies, it was not possible to conduct a meta-analysis of the results of the considered publications. Nevertheless, the present review showed a clear signal of increase in mental health problems in relation to school closure or virtual instruction. In particular, results suggest evidence of association between school closure and risk of suicidal attempts or thoughts, mental health symptoms such as anxiety, depression, emotional disorders, psychological stress. Sleeping problems, drug and alcohol addiction were poorly studied.
CONCLUSIONS
despite the limitations of the included studies and possible residual confounding and contamination due to restrictive measures and social isolation implemented during the pandemic, the available evidence confirms the negative impact on students' mental health associated with school closures and distance learning. Given the availability of vaccination also for young children, a long period of school closure should be avoided also in the case of the emergence of new pandemic waves.
Topics: Child; Adolescent; Humans; Child, Preschool; Mental Health; COVID-19; Cross-Sectional Studies; Suicide; Communicable Disease Control; SARS-CoV-2; Italy; Health Behavior
PubMed: 36384255
DOI: 10.19191/EP22.5-6.A542.089 -
The International Journal of Behavioral... Aug 2017Physical activity is associated with many physical and mental health benefits, however many children do not meet the national physical activity guidelines. While schools... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Physical activity is associated with many physical and mental health benefits, however many children do not meet the national physical activity guidelines. While schools provide an ideal setting to promote children's physical activity, adding physical activity to the school day can be difficult given time constraints often imposed by competing key learning areas. Classroom-based physical activity may provide an opportunity to increase school-based physical activity while concurrently improving academic-related outcomes. The primary aim of this systematic review and meta-analysis was to evaluate the impact of classroom-based physical activity interventions on academic-related outcomes. A secondary aim was to evaluate the impact of these lessons on physical activity levels over the study duration.
METHODS
A systematic search of electronic databases (PubMed, ERIC, SPORTDiscus, PsycINFO) was performed in January 2016 and updated in January 2017. Studies that investigated the association between classroom-based physical activity interventions and academic-related outcomes in primary (elementary) school-aged children were included. Meta-analyses were conducted in Review Manager, with effect sizes calculated separately for each outcome assessed.
RESULTS
Thirty-nine articles met the inclusion criteria for the review, and 16 provided sufficient data and appropriate design for inclusion in the meta-analyses. Studies investigated a range of academic-related outcomes including classroom behaviour (e.g. on-task behaviour), cognitive functions (e.g. executive function), and academic achievement (e.g. standardised test scores). Results of the meta-analyses showed classroom-based physical activity had a positive effect on improving on-task and reducing off-task classroom behaviour (standardised mean difference = 0.60 (95% CI: 0.20,1.00)), and led to improvements in academic achievement when a progress monitoring tool was used (standardised mean difference = 1.03 (95% CI: 0.22,1.84)). However, no effect was found for cognitive functions (standardised mean difference = 0.33 (95% CI: -0.11,0.77)) or physical activity (standardised mean difference = 0.40 (95% CI: -1.15,0.95)).
CONCLUSIONS
Results suggest classroom-based physical activity may have a positive impact on academic-related outcomes. However, it is not possible to draw definitive conclusions due to the level of heterogeneity in intervention components and academic-related outcomes assessed. Future studies should consider the intervention period when selecting academic-related outcome measures, and use an objective measure of physical activity to determine intervention fidelity and effects on overall physical activity levels.
Topics: Academic Success; Child; Cognition; Curriculum; Databases, Factual; Exercise; Health Behavior; Humans; Learning; Physical Education and Training; Schools; Students
PubMed: 28841890
DOI: 10.1186/s12966-017-0569-9 -
JAMA Internal Medicine Oct 2018Physician burnout has taken the form of an epidemic that may affect core domains of health care delivery, including patient safety, quality of care, and patient... (Meta-Analysis)
Meta-Analysis
IMPORTANCE
Physician burnout has taken the form of an epidemic that may affect core domains of health care delivery, including patient safety, quality of care, and patient satisfaction. However, this evidence has not been systematically quantified.
OBJECTIVE
To examine whether physician burnout is associated with an increased risk of patient safety incidents, suboptimal care outcomes due to low professionalism, and lower patient satisfaction.
DATA SOURCES
MEDLINE, EMBASE, PsycInfo, and CINAHL databases were searched until October 22, 2017, using combinations of the key terms physicians, burnout, and patient care. Detailed standardized searches with no language restriction were undertaken. The reference lists of eligible studies and other relevant systematic reviews were hand-searched.
STUDY SELECTION
Quantitative observational studies.
DATA EXTRACTION AND SYNTHESIS
Two independent reviewers were involved. The main meta-analysis was followed by subgroup and sensitivity analyses. All analyses were performed using random-effects models. Formal tests for heterogeneity (I2) and publication bias were performed.
MAIN OUTCOMES AND MEASURES
The core outcomes were the quantitative associations between burnout and patient safety, professionalism, and patient satisfaction reported as odds ratios (ORs) with their 95% CIs.
RESULTS
Of the 5234 records identified, 47 studies on 42 473 physicians (25 059 [59.0%] men; median age, 38 years [range, 27-53 years]) were included in the meta-analysis. Physician burnout was associated with an increased risk of patient safety incidents (OR, 1.96; 95% CI, 1.59-2.40), poorer quality of care due to low professionalism (OR, 2.31; 95% CI, 1.87-2.85), and reduced patient satisfaction (OR, 2.28; 95% CI, 1.42-3.68). The heterogeneity was high and the study quality was low to moderate. The links between burnout and low professionalism were larger in residents and early-career (≤5 years post residency) physicians compared with middle- and late-career physicians (Cohen Q = 7.27; P = .003). The reporting method of patient safety incidents and professionalism (physician-reported vs system-recorded) significantly influenced the main results (Cohen Q = 8.14; P = .007).
CONCLUSIONS AND RELEVANCE
This meta-analysis provides evidence that physician burnout may jeopardize patient care; reversal of this risk has to be viewed as a fundamental health care policy goal across the globe. Health care organizations are encouraged to invest in efforts to improve physician wellness, particularly for early-career physicians. The methods of recording patient care quality and safety outcomes require improvements to concisely capture the outcome of burnout on the performance of health care organizations.
Topics: Burnout, Psychological; Humans; Patient Safety; Patient Satisfaction; Physicians; Professionalism; Quality of Health Care
PubMed: 30193239
DOI: 10.1001/jamainternmed.2018.3713 -
The Cochrane Database of Systematic... May 2020Over the decades, a variety of psychological interventions for borderline personality disorder (BPD) have been developed. This review updates and replaces an earlier... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Over the decades, a variety of psychological interventions for borderline personality disorder (BPD) have been developed. This review updates and replaces an earlier review (Stoffers-Winterling 2012).
OBJECTIVES
To assess the beneficial and harmful effects of psychological therapies for people with BPD.
SEARCH METHODS
In March 2019, we searched CENTRAL, MEDLINE, Embase, 14 other databases and four trials registers. We contacted researchers working in the field to ask for additional data from published and unpublished trials, and handsearched relevant journals. We did not restrict the search by year of publication, language or type of publication.
SELECTION CRITERIA
Randomised controlled trials comparing different psychotherapeutic interventions with treatment-as-usual (TAU; which included various kinds of psychotherapy), waiting list, no treatment or active treatments in samples of all ages, in any setting, with a formal diagnosis of BPD. The primary outcomes were BPD symptom severity, self-harm, suicide-related outcomes, and psychosocial functioning. There were 11 secondary outcomes, including individual BPD symptoms, as well as attrition and adverse effects.
DATA COLLECTION AND ANALYSIS
At least two review authors independently selected trials, extracted data, assessed risk of bias using Cochrane's 'Risk of bias' tool and assessed the certainty of the evidence using the GRADE approach. We performed data analysis using Review Manager 5 and quantified the statistical reliability of the data using Trial Sequential Analysis.
MAIN RESULTS
We included 75 randomised controlled trials (4507 participants), predominantly involving females with mean ages ranging from 14.8 to 45.7 years. More than 16 different kinds of psychotherapy were included, mostly dialectical behaviour therapy (DBT) and mentalisation-based treatment (MBT). The comparator interventions included treatment-as-usual (TAU), waiting list, and other active treatments. Treatment duration ranged from one to 36 months. Psychotherapy versus TAU Psychotherapy reduced BPD symptom severity, compared to TAU; standardised mean difference (SMD) -0.52, 95% confidence interval (CI) -0.70 to -0.33; 22 trials, 1244 participants; moderate-quality evidence. This corresponds to a mean difference (MD) of -3.6 (95% CI -4.4 to -2.08) on the Zanarini Rating Scale for BPD (range 0 to 36), a clinically relevant reduction in BPD symptom severity (minimal clinical relevant difference (MIREDIF) on this scale is -3.0 points). Psychotherapy may be more effective at reducing self-harm compared to TAU (SMD -0.32, 95% CI -0.49 to -0.14; 13 trials, 616 participants; low-quality evidence), corresponding to a MD of -0.82 (95% CI -1.25 to 0.35) on the Deliberate Self-Harm Inventory Scale (range 0 to 34). The MIREDIF of -1.25 points was not reached. Suicide-related outcomes improved compared to TAU (SMD -0.34, 95% CI -0.57 to -0.11; 13 trials, 666 participants; low-quality evidence), corresponding to a MD of -0.11 (95% CI -0.19 to -0.034) on the Suicidal Attempt Self Injury Interview. The MIREDIF of -0.17 points was not reached. Compared to TAU, psychotherapy may result in an improvement in psychosocial functioning (SMD -0.45, 95% CI -0.68 to -0.22; 22 trials, 1314 participants; low-quality evidence), corresponding to a MD of -2.8 (95% CI -4.25 to -1.38), on the Global Assessment of Functioning Scale (range 0 to 100). The MIREDIF of -4.0 points was not reached. Our additional Trial Sequential Analysis on all primary outcomes reaching significance found that the required information size was reached in all cases. A subgroup analysis comparing the different types of psychotherapy compared to TAU showed no clear evidence of a difference for BPD severity and psychosocial functioning. Psychotherapy may reduce depressive symptoms compared to TAU but the evidence is very uncertain (SMD -0.39, 95% CI -0.61 to -0.17; 22 trials, 1568 participants; very low-quality evidence), corresponding to a MD of -2.45 points on the Hamilton Depression Scale (range 0 to 50). The MIREDIF of -3.0 points was not reached. BPD-specific psychotherapy did not reduce attrition compared with TAU. Adverse effects were unclear due to too few data. Psychotherapy versus waiting list or no treatment Greater improvements in BPD symptom severity (SMD -0.49, 95% CI -0.93 to -0.05; 3 trials, 161 participants), psychosocial functioning (SMD -0.56, 95% CI -1.01 to -0.11; 5 trials, 219 participants), and depression (SMD -1.28, 95% CI -2.21 to -0.34, 6 trials, 239 participants) were observed in participants receiving psychotherapy versus waiting list or no treatment (all low-quality evidence). No evidence of a difference was found for self-harm and suicide-related outcomes. Individual treatment approaches DBT and MBT have the highest numbers of primary trials, with DBT as subject of one-third of all included trials, followed by MBT with seven RCTs. Compared to TAU, DBT was more effective at reducing BPD severity (SMD -0.60, 95% CI -1.05 to -0.14; 3 trials, 149 participants), self-harm (SMD -0.28, 95% CI -0.48 to -0.07; 7 trials, 376 participants) and improving psychosocial functioning (SMD -0.36, 95% CI -0.69 to -0.03; 6 trials, 225 participants). MBT appears to be more effective than TAU at reducing self-harm (RR 0.62, 95% CI 0.49 to 0.80; 3 trials, 252 participants), suicidality (RR 0.10, 95% CI 0.04, 0.30, 3 trials, 218 participants) and depression (SMD -0.58, 95% CI -1.22 to 0.05, 4 trials, 333 participants). All findings are based on low-quality evidence. For secondary outcomes see review text.
AUTHORS' CONCLUSIONS
Our assessments showed beneficial effects on all primary outcomes in favour of BPD-tailored psychotherapy compared with TAU. However, only the outcome of BPD severity reached the MIREDIF-defined cut-off for a clinically meaningful improvement. Subgroup analyses found no evidence of a difference in effect estimates between the different types of therapies (compared to TAU) . The pooled analysis of psychotherapy versus waiting list or no treatment found significant improvement on BPD severity, psychosocial functioning and depression at end of treatment, but these findings were based on low-quality evidence, and the true magnitude of these effects is uncertain. No clear evidence of difference was found for self-harm and suicide-related outcomes. However, compared to TAU, we observed effects in favour of DBT for BPD severity, self-harm and psychosocial functioning and, for MBT, on self-harm and suicidality at end of treatment, but these were all based on low-quality evidence. Therefore, we are unsure whether these effects would alter with the addition of more data.
Topics: Adolescent; Adult; Borderline Personality Disorder; Depression; Dialectical Behavior Therapy; Female; Humans; Male; Mentalization; Middle Aged; Patient Dropouts; Psychotherapy; Randomized Controlled Trials as Topic; Self-Injurious Behavior; Treatment Outcome; Waiting Lists; Young Adult; Suicide Prevention
PubMed: 32368793
DOI: 10.1002/14651858.CD012955.pub2 -
British Journal of Sports Medicine Jun 2017A systematic review of factors that might be associated with, or influence, clinical recovery from sport-related concussion. Clinical recovery was defined functionally... (Review)
Review
OBJECTIVE
A systematic review of factors that might be associated with, or influence, clinical recovery from sport-related concussion. Clinical recovery was defined functionally as a return to normal activities, including school and sports, following injury.
DESIGN
Systematic review.
DATA SOURCES
PubMed, PsycINFO, MEDLINE, CINAHL, Cochrane Library, EMBASE, SPORTDiscus, Scopus and Web of Science.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES
Studies published by June of 2016 that addressed clinical recovery from concussion.
RESULTS
A total of 7617 articles were identified using the search strategy, and 101 articles were included. There are major methodological differences across the studies. Many different clinical outcomes were measured, such as symptoms, cognition, balance, return to school and return to sports, although symptom outcomes were the most frequently measured. The most consistent predictor of slower recovery from concussion is the severity of a person's acute and subacute symptoms. The development of subacute problems with headaches or depression is likely a risk factor for persistent symptoms lasting greater than a month. Those with a preinjury history of mental health problems appear to be at greater risk for having persistent symptoms. Those with attention deficit hyperactivity disorder (ADHD) or learning disabilities do not appear to be at substantially greater risk. There is some evidence that the teenage years, particularly high school, might be the most vulnerable time period for having persistent symptoms-with greater risk for girls than boys.
CONCLUSION
The literature on clinical recovery from sport-related concussion has grown dramatically, is mostly mixed, but some factors have emerged as being related to outcome.
Topics: Athletic Injuries; Attention Deficit Disorder with Hyperactivity; Brain Concussion; Cognition; Depression; Headache; Humans; Learning Disabilities; Neuropsychological Tests; Postural Balance; Return to Sport; Risk Factors; Sports
PubMed: 28566342
DOI: 10.1136/bjsports-2017-097729 -
BMJ (Clinical Research Ed.) Mar 2020To systematically examine the design, reporting standards, risk of bias, and claims of studies comparing the performance of diagnostic deep learning algorithms for...
OBJECTIVE
To systematically examine the design, reporting standards, risk of bias, and claims of studies comparing the performance of diagnostic deep learning algorithms for medical imaging with that of expert clinicians.
DESIGN
Systematic review.
DATA SOURCES
Medline, Embase, Cochrane Central Register of Controlled Trials, and the World Health Organization trial registry from 2010 to June 2019.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES
Randomised trial registrations and non-randomised studies comparing the performance of a deep learning algorithm in medical imaging with a contemporary group of one or more expert clinicians. Medical imaging has seen a growing interest in deep learning research. The main distinguishing feature of convolutional neural networks (CNNs) in deep learning is that when CNNs are fed with raw data, they develop their own representations needed for pattern recognition. The algorithm learns for itself the features of an image that are important for classification rather than being told by humans which features to use. The selected studies aimed to use medical imaging for predicting absolute risk of existing disease or classification into diagnostic groups (eg, disease or non-disease). For example, raw chest radiographs tagged with a label such as pneumothorax or no pneumothorax and the CNN learning which pixel patterns suggest pneumothorax.
REVIEW METHODS
Adherence to reporting standards was assessed by using CONSORT (consolidated standards of reporting trials) for randomised studies and TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) for non-randomised studies. Risk of bias was assessed by using the Cochrane risk of bias tool for randomised studies and PROBAST (prediction model risk of bias assessment tool) for non-randomised studies.
RESULTS
Only 10 records were found for deep learning randomised clinical trials, two of which have been published (with low risk of bias, except for lack of blinding, and high adherence to reporting standards) and eight are ongoing. Of 81 non-randomised clinical trials identified, only nine were prospective and just six were tested in a real world clinical setting. The median number of experts in the comparator group was only four (interquartile range 2-9). Full access to all datasets and code was severely limited (unavailable in 95% and 93% of studies, respectively). The overall risk of bias was high in 58 of 81 studies and adherence to reporting standards was suboptimal (<50% adherence for 12 of 29 TRIPOD items). 61 of 81 studies stated in their abstract that performance of artificial intelligence was at least comparable to (or better than) that of clinicians. Only 31 of 81 studies (38%) stated that further prospective studies or trials were required.
CONCLUSIONS
Few prospective deep learning studies and randomised trials exist in medical imaging. Most non-randomised trials are not prospective, are at high risk of bias, and deviate from existing reporting standards. Data and code availability are lacking in most studies, and human comparator groups are often small. Future studies should diminish risk of bias, enhance real world clinical relevance, improve reporting and transparency, and appropriately temper conclusions.
STUDY REGISTRATION
PROSPERO CRD42019123605.
Topics: Algorithms; Bias; Deep Learning; Diagnostic Imaging; Humans; Image Processing, Computer-Assisted; Physicians; Randomized Controlled Trials as Topic; Research Design
PubMed: 32213531
DOI: 10.1136/bmj.m689 -
Frontiers in Psychology 2022Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will...
BACKGROUND
Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored.
OBJECTIVES
The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare?
MATERIALS AND METHODS
A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice.
RESULTS
Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, = 1 to 2021, = 47 and from Jan-Aug 2022 = 35 articles). Overarching themes related to the review questions were: (1) (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships.
CONCLUSION
There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships.
IMPLICATIONS
In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.
PubMed: 36733854
DOI: 10.3389/fpsyg.2022.971044 -
The Cochrane Database of Systematic... Nov 2022Among people with a diagnosis of borderline personality disorder (BPD) who are engaged in clinical care, prescription rates of psychotropic medications are high, despite... (Review)
Review
BACKGROUND
Among people with a diagnosis of borderline personality disorder (BPD) who are engaged in clinical care, prescription rates of psychotropic medications are high, despite the fact that medication use is off-label as a treatment for BPD. Nevertheless, people with BPD often receive several psychotropic drugs at a time for sustained periods.
OBJECTIVES
To assess the effects of pharmacological treatment for people with BPD.
SEARCH METHODS
For this update, we searched CENTRAL, MEDLINE, Embase, 14 other databases and four trials registers up to February 2022. We contacted researchers working in the field to ask for additional data from published and unpublished trials, and handsearched relevant journals. We did not restrict the search by year of publication, language or type of publication.
SELECTION CRITERIA
Randomised controlled trials comparing pharmacological treatment to placebo, other pharmacologic treatments or a combination of pharmacologic treatments in people of all ages with a formal diagnosis of BPD. The primary outcomes were BPD symptom severity, self-harm, suicide-related outcomes, and psychosocial functioning. Secondary outcomes were individual BPD symptoms, depression, attrition and adverse events.
DATA COLLECTION AND ANALYSIS
At least two review authors independently selected trials, extracted data, assessed risk of bias using Cochrane's risk of bias tool and assessed the certainty of the evidence using the GRADE approach. We performed data analysis using Review Manager 5 and quantified the statistical reliability of the data using Trial Sequential Analysis.
MAIN RESULTS
We included 46 randomised controlled trials (2769 participants) in this review, 45 of which were eligible for quantitative analysis and comprised 2752 participants with BPD in total. This is 18 more trials than the 2010 review on this topic. Participants were predominantly female except for one trial that included men only. The mean age ranged from 16.2 to 39.7 years across the included trials. Twenty-nine different types of medications compared to placebo or other medications were included in the analyses. Seventeen trials were funded or partially funded by the pharmaceutical industry, 10 were funded by universities or research foundations, eight received no funding, and 11 had unclear funding. For all reported effect sizes, negative effect estimates indicate beneficial effects by active medication. Compared with placebo, no difference in effects were observed on any of the primary outcomes at the end of treatment for any medication. Compared with placebo, medication may have little to no effect on BPD symptom severity, although the evidence is of very low certainty (antipsychotics: SMD -0.18, 95% confidence interval (CI) -0.45 to 0.08; 8 trials, 951 participants; antidepressants: SMD -0.27, 95% CI -0.65 to 1.18; 2 trials, 87 participants; mood stabilisers: SMD -0.07, 95% CI -0.43 to 0.57; 4 trials, 265 participants). The evidence is very uncertain about the effect of medication compared with placebo on self-harm, indicating little to no effect (antipsychotics: RR 0.66, 95% CI 0.15 to 2.84; 2 trials, 76 participants; antidepressants: MD 0.45 points on the Overt Aggression Scale-Modified-Self-Injury item (0-5 points), 95% CI -10.55 to 11.45; 1 trial, 20 participants; mood stabilisers: RR 1.08, 95% CI 0.79 to 1.48; 1 trial, 276 participants). The evidence is also very uncertain about the effect of medication compared with placebo on suicide-related outcomes, with little to no effect (antipsychotics: SMD 0.05, 95 % CI -0.18 to 0.29; 7 trials, 854 participants; antidepressants: SMD -0.26, 95% CI -1.62 to 1.09; 2 trials, 45 participants; mood stabilisers: SMD -0.36, 95% CI -1.96 to 1.25; 2 trials, 44 participants). Very low-certainty evidence shows little to no difference between medication and placebo on psychosocial functioning (antipsychotics: SMD -0.16, 95% CI -0.33 to 0.00; 7 trials, 904 participants; antidepressants: SMD -0.25, 95% CI -0.57 to 0.06; 4 trials, 161 participants; mood stabilisers: SMD -0.01, 95% CI -0.28 to 0.26; 2 trials, 214 participants). Low-certainty evidence suggests that antipsychotics may slightly reduce interpersonal problems (SMD -0.21, 95% CI -0.34 to -0.08; 8 trials, 907 participants), and that mood stabilisers may result in a reduction in this outcome (SMD -0.58, 95% CI -1.14 to -0.02; 4 trials, 300 participants). Antidepressants may have little to no effect on interpersonal problems, but the corresponding evidence is very uncertain (SMD -0.07, 95% CI -0.69 to 0.55; 2 trials, 119 participants). The evidence is very uncertain about dropout rates compared with placebo by antipsychotics (RR 1.11, 95% CI 0.89 to 1.38; 13 trials, 1216 participants). Low-certainty evidence suggests there may be no difference in dropout rates between antidepressants (RR 1.07, 95% CI 0.65 to 1.76; 6 trials, 289 participants) and mood stabilisers (RR 0.89, 95% CI 0.69 to 1.15; 9 trials, 530 participants), compared to placebo. Reporting on adverse events was poor and mostly non-standardised. The available evidence on non-serious adverse events was of very low certainty for antipsychotics (RR 1.07, 95% CI 0.90 to 1.29; 5 trials, 814 participants) and mood stabilisers (RR 0.84, 95% CI 0.70 to 1.01; 1 trial, 276 participants). For antidepressants, no data on adverse events were identified.
AUTHORS' CONCLUSIONS
This review included 18 more trials than the 2010 version, so larger meta-analyses with more statistical power were feasible. We found mostly very low-certainty evidence that medication may result in no difference in any primary outcome. The rest of the secondary outcomes were inconclusive. Very limited data were available for serious adverse events. The review supports the continued understanding that no pharmacological therapy seems effective in specifically treating BPD pathology. More research is needed to understand the underlying pathophysiologic mechanisms of BPD better. Also, more trials including comorbidities such as trauma-related disorders, major depression, substance use disorders, or eating disorders are needed. Additionally, more focus should be put on male and adolescent samples.
Topics: Humans; Adolescent; Male; Female; Young Adult; Adult; Borderline Personality Disorder; Reproducibility of Results; Antidepressive Agents; Depressive Disorder, Major; Antipsychotic Agents
PubMed: 36375174
DOI: 10.1002/14651858.CD012956.pub2 -
World Psychiatry : Official Journal of... Feb 2023Neurodevelopmental disorders - including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disability,...
Neurodevelopmental disorders - including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disability, motor disorders, specific learning disorders, and tic disorders - manifest themselves early in development. Valid, reliable and broadly usable biomarkers supporting a timely diagnosis of these disorders would be highly relevant from a clinical and public health standpoint. We conducted the first systematic review of studies on candidate diagnostic biomarkers for these disorders in children and adolescents. We searched Medline and Embase + Embase Classic with terms relating to biomarkers until April 6, 2022, and conducted additional targeted searches for genome-wide association studies (GWAS) and neuroimaging or neurophysiological studies carried out by international consortia. We considered a candidate biomarker as promising if it was reported in at least two independent studies providing evidence of sensitivity and specificity of at least 80%. After screening 10,625 references, we retained 780 studies (374 biochemical, 203 neuroimaging, 133 neurophysiological and 65 neuropsychological studies, and five GWAS), including a total of approximately 120,000 cases and 176,000 controls. While the majority of the studies focused simply on associations, we could not find any biomarker for which there was evidence - from two or more studies from independent research groups, with results going into the same direction - of specificity and sensitivity of at least 80%. Other important metrics to assess the validity of a candidate biomarker, such as positive predictive value and negative predictive value, were infrequently reported. Limitations of the currently available studies include mostly small sample size, heterogeneous approaches and candidate biomarker targets, undue focus on single instead of joint biomarker signatures, and incomplete accounting for potential confounding factors. Future multivariable and multi-level approaches may be best suited to find valid candidate biomarkers, which will then need to be validated in external, independent samples and then, importantly, tested in terms of feasibility and cost-effectiveness, before they can be implemented in daily clinical practice.
PubMed: 36640395
DOI: 10.1002/wps.21037 -
JAMA Dermatology Jun 2020Most clinical trials assessing systemic immunomodulatory treatments for patients with atopic dermatitis are placebo-controlled.
IMPORTANCE
Most clinical trials assessing systemic immunomodulatory treatments for patients with atopic dermatitis are placebo-controlled.
OBJECTIVE
To compare the effectiveness and safety of systemic immunomodulatory treatments for patients with atopic dermatitis in a systematic review and network meta-analysis.
DATA SOURCES
The Cochrane Central Register of Controlled Trials, MEDLINE, Embase, Latin American and Caribbean Health Science Information database, Global Resource of Eczema Trials database, and clinical trial registries were searched from inception to October 28, 2019.
STUDY SELECTION
English-language randomized clinical trials of 8 weeks or more of treatment with systemic immunomodulatory medications for moderate to severe atopic dermatitis were included. Titles, abstracts, and articles were screened in duplicate. Of 10 324 citations, 39 trials were included.
DATA EXTRACTION AND SYNTHESIS
Data were extracted in duplicate, and the review adhered to Preferred Reporting Items for Systematic Reviews and Meta-analyses for Network Meta-Analyses guidelines. Random-effects bayesian network meta-analyses were performed and certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation criteria.
MAIN OUTCOMES AND MEASURES
Prespecified outcomes were change in signs of disease, symptoms, quality of life, itch, withdrawals, and serious adverse events.
RESULTS
A total of 39 trials with 6360 patients examining 20 medications and placebo were included. Most trials were conducted for adults receiving up to 16 weeks of therapy. Dupilumab, 300 mg every 2 weeks, was associated with improvement in the Eczema Area and Severity Index score vs placebo (mean difference, 11.3-point reduction; 95% credible interval [CrI], 9.7-13.1 [high certainty]). Cyclosporine (standardized mean difference, -1.1; 95% CrI, -1.7 to -0.5 [low certainty]) and dupilumab (standardized mean difference, -0.9; 95% CrI, -1.0 to -0.8 [high certainty]) were similarly effective vs placebo in clearing clinical signs of atopic dermatitis and may be superior to methotrexate (standardized mean difference, -0.6; 95% CrI, -1.1 to 0.0 [low certainty]) and azathioprine (standardized mean difference, -0.4; 95% CrI, -0.8 to -0.1 [low certainty]). Several investigational medications for atopic dermatitis are promising, but data to date are limited to small early-phase trials. Safety analyses were limited by low event rates.
CONCLUSIONS AND RELEVANCE
Dupilumab and cyclosporine may be more effective for up to 16 weeks of treatment than methotrexate and azathioprine for treating adult patients with atopic dermatitis. More studies directly comparing established and novel treatments beyond 16 weeks are needed and will be incorporated into future updates of this review.
Topics: Adult; Antibodies, Monoclonal, Humanized; Azathioprine; Cyclosporine; Dermatitis, Atopic; Dermatologic Agents; Humans; Immunologic Factors; Methotrexate; Network Meta-Analysis; Pruritus; Quality of Life; Severity of Illness Index; Treatment Outcome
PubMed: 32320001
DOI: 10.1001/jamadermatol.2020.0796