scholarly journals Idiom and proverb processing in autism: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Kinga Morsanyi ◽  
Dušan Stamenković
Keyword(s):  
Systematic Review ◽  
Language Processing ◽  
Figurative Language ◽  
Contextual Information ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Medium Effect ◽  
Group Differences ◽  
Medium Effect Size ◽  
Sentential Form

AbstractFigurative language processing impairments in autism have been widely demonstrated, and have been considered a defining feature of autism. Studies in this area often consider different types of figurative language together, and less attention has been paid to identifying the factors that might contribute to difficulties in processing specific types of figurative language. Here we present a preregistered systematic review and meta-analysis of studies assessing the comprehension of idioms and proverbs in autism spectrum disorder (ASD) as compared to typically developing (TD) individuals. Idioms are widely used multi-word figurative expressions, which are understood by using contextual information. Proverbs are a related type of fixed, figurative, formulaic expression in a sentential form, typically linked with wisdom. Idioms and proverbs represent forms of figurative language which are more conventionalized and frequently opaquer than metaphors, pointing to a unique way that they are processed in conversational contexts. Our analysis encompassed a total of 11 studies from 10 papers (involving 235 autistic and 224 TD individuals), which met our inclusion criteria (the ASD and TD groups were matched on both chronological age and intelligence). The analysis of accuracy data revealed a group difference favouring the TD over the ASD group, with a medium effect size, and no indication of a publication bias. Participants’ age was unrelated to the magnitude of group differences, but there was a trend for smaller group differences in the case of participants with higher (verbal) intelligence. We discuss these findings with reference to theories related to the nature of figurative language impairments in autism.

scholarly journals Botulinum Neurotoxin A Intravesical Injections in Interstitial Cystitis/Bladder Painful Syndrome: A Systematic Review with Meta-Analysis

Toxins ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 510 ◽  
Author(s):  
Antonella Giannantoni ◽  
Marilena Gubbiotti ◽  
Vittorio Bini
Keyword(s):  
Systematic Review ◽  
Interstitial Cystitis ◽  
Effect Size ◽  
Botulinum Neurotoxin ◽  
Meta Analysis ◽  
Medium Effect ◽  
Controlled Trials ◽  
Botulinum Neurotoxin A ◽  
Painful Syndrome ◽  
Medium Effect Size

Botulinum neurotoxin A (BoNT/A) appears to be one of the best intravesical treatments for interstitial cystitis/bladder painful syndrome (IC/BPS). We aimed to point out what the evidence is regarding the effects of BoNT/A intravesically injected in patients with IC/BPS. We performed a systematic review of all randomized controlled trials (RCTs) assessing BoNT/A for IC/BPS by using Medline, EMBASE, CINAHL, CENTRAL and MetaRegister of Controlled Trials. Standardized mean differences (SMD) were extracted from the available trials and combined in a meta-analysis applying a random effect model, including heterogeneity of effects. Twelve trials were identified. Significant benefits from BoNT/A injections were detected in: Interstitial Cystitis Symptom Index and Problem Index (ICSI, ICPI) (small to medium effect size: SMD = –0.302; p = 0.007 and –0.430, p = 0.004, respectively); Visual Analog Scale (VAS) for pain and day-time urinary frequency (medium effect size: SMD = –0.576, p < 0.0001 and –0.546, p = 0.013, respectively). A great effect size was detected for post-void residual volume (PVR, SMD = 0.728; p =0.002) although no clinically relevant in most cases. Great heterogeneity was observed in treatments’ methodologies and symptoms assessment. Overall, BoNT/A intravesical injections significantly improve some of the most relevant symptoms affecting IC/BPS patients.

Diagnostic test accuracy for use of machine learning in diagnosis of autism spectrum disorder: A Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Sun Jae Moon ◽  
Jin Seub Hwang ◽  
Rajesh Kana ◽  
John Torous ◽  
Jung Won Kim
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Meta Analysis ◽  
Learning Algorithms ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Machine Learning Algorithms ◽  
Spectrum Disorder ◽  
Test Accuracy

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.

Autism spectrum disorder and air pollution: a systematic review and meta-analysis

2021 ◽  
pp. 116856
Author(s):  
Frédéric Dutheil ◽  
Aurélie Comptour ◽  
Roxane Morlon ◽  
Martial Mermillod ◽  
Bruno Pereira ◽  
...  
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Air Pollution ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Spectrum Disorder

The effectiveness of hope-fostering interventions in palliative care: A systematic review and meta-analysis

2021 ◽  
pp. 026921632199472
Author(s):  
Natalia Salamanca-Balen ◽  
Thomas V Merluzzi ◽  
Man Chen
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Palliative Care ◽  
Meta Analysis ◽  
Symptom Burden ◽  
Well Being ◽  
Medium Effect ◽  
Spiritual Well Being ◽  
Quasi Experimental

Background: The concept of hope is an important theme in chronic illness and palliative care and has been associated with increased psycho-spiritual well-being and quality of life. Psycho-spiritual interventions have been described in this population, but no systematic review of hope-enhancing interventions or hopelessness-reducing interventions has been conducted for persons with palliative care diseases. Aim: To describe and assess the effectiveness of interventions in palliative care that measure hope and/or hopelessness as an outcome. Design: This systematic review and meta-analysis was pre-registered (Prospero ID: CRD42019119956). Data sources: Electronic databases, journals, and references were searched. We used the Cochrane criteria to assess the risk of bias within studies. Results: Thirty-five studies (24 randomized controlled trials, 5 quasi-experimental, 6 pre-post studies) involving a total of 3296 palliative care patients were included. Compared with usual/standard cancer care alone, interventions significantly increased hope levels at a medium effect size ( g = 0.61, 95% confidence interval (CI) = 0.28–0.93) but did not significantly reduce hopelessness ( g = −0.08, 95% CI = −0.18 to 0.02). It was found that interventions significantly increase spirituality ( g = 0.70, 95% CI = 0.02–1.37) and decrease depression ( g = −0.29, 95% CI = −0.51 to −0.07), but had no significant effect over anxiety, quality of life, and symptom burden. Overall, quality of evidence across the included studies was rated as low. Conclusions: Evidence suggests that interventions can be effective in increasing hope in palliative care patients.

scholarly journals A Systematic Review and Meta-Analysis of Immunoglobulin G Abnormalities and the Therapeutic Use of Intravenous Immunoglobulins (IVIG) in Autism Spectrum Disorder

2021 ◽  
Vol 11 (6) ◽  
pp. 488
Author(s):  
Daniel A Rossignol ◽  
Richard E Frye
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Immunoglobulin G ◽  
Meta Analysis ◽  
Intravenous Immunoglobulins ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Effect Sizes ◽  
Aberrant Behavior ◽  
Children With Asd

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting approximately 2% of children in the United States. Growing evidence suggests that immune dysregulation is associated with ASD. One immunomodulatory treatment that has been studied in ASD is intravenous immunoglobulins (IVIG). This systematic review and meta-analysis examined the studies which assessed immunoglobulin G (IgG) concentrations and the therapeutic use of IVIG for individuals with ASD. Twelve studies that examined IgG levels suggested abnormalities in total IgG and IgG 4 subclass concentrations, with concentrations in these IgGs related to aberrant behavior and social impairments, respectively. Meta-analysis supported possible subsets of children with ASD with low total IgG and elevated IgG 4 subclass but also found significant variability among studies. A total of 27 publications reported treating individuals with ASD using IVIG, including four prospective, controlled studies (one was a double-blind, placebo-controlled study); six prospective, uncontrolled studies; 2 retrospective, controlled studies; and 15 retrospective, uncontrolled studies. In some studies, clinical improvements were observed in communication, irritability, hyperactivity, cognition, attention, social interaction, eye contact, echolalia, speech, response to commands, drowsiness, decreased activity and in some cases, the complete resolution of ASD symptoms. Several studies reported some loss of these improvements when IVIG was stopped. Meta-analysis combining the aberrant behavior checklist outcome from two studies demonstrated that IVIG treatment was significantly associated with improvements in total aberrant behavior and irritability (with large effect sizes), and hyperactivity and social withdrawal (with medium effect sizes). Several studies reported improvements in pro-inflammatory cytokines (including TNF-alpha). Six studies reported improvements in seizures with IVIG (including patients with refractory seizures), with one study reporting a worsening of seizures when IVIG was stopped. Other studies demonstrated improvements in recurrent infections, appetite, weight gain, neuropathy, dysautonomia, and gastrointestinal symptoms. Adverse events were generally limited but included headaches, vomiting, worsening behaviors, anxiety, fever, nausea, fatigue, and rash. Many studies were limited by the lack of standardized objective outcome measures. IVIG is a promising and potentially effective treatment for symptoms in individuals with ASD; further research is needed to provide solid evidence of efficacy and determine the subset of children with ASD who may best respond to this treatment as well as to investigate biomarkers which might help identify responsive candidates.

scholarly journals A systematic review and meta-analysis of studies on metaphor comprehension in individuals with autism spectrum disorder: Do task properties matter?

2019 ◽  
Vol 40 (6) ◽  
pp. 1421-1454 ◽  
Author(s):  
Tamar Kalandadze ◽  
Valentina Bambini ◽  
Kari-Anne B. Næss
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Syntactic Structure ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Response Format ◽  
Metaphor Comprehension ◽  
The Relationship

AbstractIndividuals with autism spectrum disorder (ASD) often experience difficulty in comprehending metaphors compared to individuals with typical development (TD). However, there is a large variation in the results across studies, possibly related to the properties of the metaphor tasks. This preregistered systematic review and meta-analysis (a) explored the properties of the metaphor tasks used in ASD research, and (b) investigated the group difference between individuals with ASD and TD on metaphor comprehension, as well as the relationship between the task properties and any between-study variation. A systematic search was undertaken in seven relevant databases. Fourteen studies fulfilled our predetermined inclusion criteria. Across tasks, we detected four types of response format and a great variety of metaphors in terms of familiarity, syntactic structure, and linguistic context. Individuals with TD outperformed individuals with ASD on metaphor comprehension (Hedges’ g = −0.63). Verbal explanation response format was utilized in the study showing the largest effect size in the group comparison. However, due to the sparse experimental manipulations, the role of task properties could not be established. Future studies should consider and report task properties to determine their role in metaphor comprehension, and to inform experimental paradigms as well as educational assessment.

scholarly journals Autism Spectrum Disorder and Clinical High Risk for Psychosis: A Systematic Review and Meta-analysis

2021 ◽  
Author(s):  
Julio Vaquerizo-Serrano ◽  
Gonzalo Salazar de Pablo ◽  
Jatinder Singh ◽  
Paramala Santosh
Keyword(s):  
Systematic Review ◽  
High Risk ◽  
Literature Search ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Clinical High Risk ◽  
Psychotic Experiences ◽  
Attenuated Psychosis Syndrome ◽  
The Mean ◽  
Spectrum Disorders

AbstractPsychotic experiences can occur in autism spectrum disorders (ASD). Some of the ASD individuals with these experiences may fulfil Clinical High-Risk for Psychosis (CHR-P) criteria. A systematic literature search was performed to review the information on ASD and CHR-P. A meta-analysis of the proportion of CHR-P in ASD was conducted. The systematic review included 13 studies. The mean age of ASD individuals across the included studies was 11.09 years. The Attenuated Psychosis Syndrome subgroup was the most frequently reported. Four studies were meta-analysed, showing that 11.6% of CHR-P individuals have an ASD diagnosis. Symptoms of prodromal psychosis may be present in individuals with ASD. The transition from CHR-P to psychosis is not affected by ASD.

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