Functional Behavioral Assessment-based interventions on adults’ delusions, hallucinations and disorganized speech: A single case meta-analysis

Froján-Parga, María Xesús; Prado-Gordillo, Miguel Núñez de; Álvarez-Iglesias, Alejandra; Alonso-Vega, Jesús

doi:10.1016/j.brat.2019.103444

Cited by 9 publications

(8 citation statements)

References 54 publications

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“…Acceptance and commitment therapy (ACT) and meta‐cognitive therapy both have shown moderate beneficial effects for positive symptoms, although no significant effects for negative symptoms 284 . Functional behavioral assessment‐based interventions appear to be effective for disorganization symptoms across disorders 285 .…”

Section: Validity Evidencementioning

confidence: 99%

“…Social skills training is efficacious for both detachment symptoms and traits, and emerging evidence suggests that antipsychotics may be efficacious for trait psychoticism as well as frank psychosis. Much less is known about treatment for lower‐order dimensions, although social skills training may be particularly efficacious for avolition 293 , and functional behavioral assessment‐based interventions for disorganization 285 .…”

Section: Validity Evidencementioning

confidence: 99%

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Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

et al. 2020

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The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co‐occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis‐related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

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Section: Validity Evidencementioning

confidence: 99%

Section: Validity Evidencementioning

confidence: 99%

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

et al. 2020

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“…The standardized mean difference is one of the most widely used effect size indices in meta-analysis of between-groups studies, and methods for estimating it are available for a range of experimental designs (Borenstein, 2009). Arguing by analogy to its use in between-groups designs, Gingerich (1984) proposed a version of the metric for quantifying effect size in SCEDs, but defined in terms of within-case variability in the outcome (see also Busk & Serlin, 1992). This within-case standardized mean difference (WC-SMD) effect size is…”

Section: Within-case Standardized Mean Differencementioning

confidence: 99%

“…The two-stage approach to synthesis requires choosing an effect size metric that quantifies the direction and magnitude of an intervention effect for each case within an SCED. Among the available effect size measures, the log response ratio (LRR, Pustejovsky, 2018), within-case standardized mean difference (WC-SMD, Busk & Serlin, 1992;Gingerich, 1984), nonoverlap of all pairs (NAP, Parker & Vannest, 2009), and Tau index are suitable for meta-analysis because they have known sampling variances. However, available formulas for the sampling variances of these indices are all based on the assumption that outcome measurements are independent within each measurement phase.…”

mentioning

confidence: 99%

Multilevel meta-analysis of single-case experimental designs using robust variance estimation.

Chen¹,

Pustejovsky²

2024

Psychological Methods

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Single-case experimental designs (SCEDs) are used to study the effects of interventions on the behavior of individual cases, by making comparisons between repeated measurements of an outcome under different conditions. In research areas where SCEDs are prevalent, there is a need for methods to synthesize results across multiple studies. One approach to synthesis uses a multilevel meta-analysis (MLMA) model to describe the distribution of effect sizes across studies and across cases within studies. However, MLMA relies on having accurate sampling variances of effect size estimates for each case, which may not be possible due to auto-correlation in the raw data series. One possible solution is to combine MLMA with robust variance estimation (RVE), which provides valid assessments of uncertainty even if the sampling variances of effect size estimates are inaccurate. Another possible solution is to forgo MLMA and use simpler, ordinary least squares (OLS) methods with RVE. This study evaluates the performance of effect size estimators and methods of synthesizing SCEDs in the presence of auto-correlation, for several different effect size metrics, via a Monte Carlo simulation designed to emulate the features of real data series. Results demonstrate that the MLMA model with RVE performs properly in terms of bias, accuracy, and confidence interval coverage for estimating overall average log response ratios. The OLS estimator corrected with RVE performs the best in estimating overall average Tau effect sizes. None of the available methods perform adequately for meta-analysis of within-case standardized mean differences.

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“…Pustejovsky (2018) illustrated the approach in an empirical application. The approach has also been applied in several recent syntheses of SCEDs (e.g., Collins et al, 2020;Froján-Parga, Prado-Gordillo, Álvarez-Iglesias, & Alonso-Vega, 2019;Ledford & Pustejovsky, 2020;Wahman, Pustejovsky, Ostrosky, & Santos, 2019;Zimmerman et al, 2018).…”

mentioning

confidence: 99%

Multi-level meta-analysis of single-case experimental designs using robust variance estimation

Chen¹,

Pustejovsky²

2021

Preprint

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Single-case experimental designs (SCEDs) are used to study the effects of interventions on the behavior of individual cases, by making comparisons between repeated measurements of an outcome under different conditions. In research areas where SCEDs are prevalent, there is a need for methods to synthesize results across multiple studies. One approach to synthesis uses a multi-level meta-analysis (MLMA) model to describe the distribution of effect sizes across studies and across cases within studies. However, MLMA relies on having accurate sampling variances of effect size estimates for each case, which may not be possible due to auto-correlation in the raw data series. One possible solution is to combine MLMA with robust variance estimation (RVE), which provides valid assessments of uncertainty even if the sampling variances of effect size estimates are inaccurate. Another possible solution is to forgo MLMA and use simpler, ordinary least squares (OLS) methods, with RVE. This study evaluates the performance of effect size estimators and methods of synthesizing SCEDs in the presence of auto-correlation, for several different effect size metrics, via a Monte Carlo simulation designed to emulate the features of real data series. Results demonstrate that the MLMA model with RVE performs properly in terms of bias, accuracy, and confidence interval coverage for estimating overall average log response ratios. The OLS estimator corrected with RVE performs the best in estimating overall average Tau effect sizes. None of the available methods perform adequately for meta-analysis of within-case standardized mean differences.

show abstract

Functional Behavioral Assessment-based interventions on adults’ delusions, hallucinations and disorganized speech: A single case meta-analysis

Cited by 9 publications

References 54 publications

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

Multilevel meta-analysis of single-case experimental designs using robust variance estimation.

Multi-level meta-analysis of single-case experimental designs using robust variance estimation

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