Reply to letter to the editor by Peters: knowledge transfer is the key

Siemens, Waldemar; Schwarzer, Guido; Rohe, Miriam S.; Buroh, Sabine; Meerpohl, Jörg J.; Becker, Gerhild

doi:10.1016/j.jclinepi.2021.05.017

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…The results provide clear evidence in support of this hypothesis: greater hypnotic suggestibility among patients relative to controls was observed in the aggregate set of studies and in each patient subgroup independently. These results were partially corroborated in the computation of prediction intervals, but only in DD patients (Riley et al, 2011;Siemens et al, 2021). Elevated hypnotic suggestibility was most pronounced among DD patients, which aligns with previous predictions to this effect (Dell, 2017;Mertens & Vermetten, 2018) and suggests that hypnotic suggestibility varies according to the severity of dissociative symptomatology or specific constellations of dissociative phenomena (Brown, 2006;Holmes et al, 2005).…”

Section: Discussionsupporting

confidence: 84%

“…Further analyses attest to the relative robustness of this central result. Prediction intervals (Riley et al, 2011;Siemens et al, 2021) did not overlap with 0 in the DD and DID samples; this suggests that future studies will reliably observe elevated suggestibility in the DD population with at least moderate effect sizes. Jackknife sensitivity analyses further demonstrated that these effects were not driven by any individual studies.…”

Section: Discussionmentioning

confidence: 79%

“…For analyses with k>=5, we supplemented SMDs and 95% CIs with 95% prediction intervals (PIs) following Riley and colleagues (Riley et al, 2011) (see also Higgins et al, 2009;IntHout et al, 2016). PIs provide information regarding the distribution of the respective effect, can be used to estimate the likely effect in a future individual study with similar characteristics, and can be especially valuable in aiding interpretation of clinical heterogeneity (Riley et al, 2011;Siemens et al, 2021). We assessed publication bias by examining funnel plots of effect sizes against standard errors for asymmetry and used the Egger's bias test (Egger et al, 1997) for which p<.05 is indicative of asymmetry.…”

Section: Meta-analysis and Meta-regressionmentioning

confidence: 99%

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Hypnotic suggestibility in dissociative and related disorders: A meta-analysis

Wieder¹,

Brown

Thompson³

et al. 2022

Preprint

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Elevated responsiveness to verbal suggestions following a hypnotic induction is hypothesized to represent a predisposing factor for dissociative disorders (DDs) and germane conditions. However, the magnitude of this effect has not been estimated in these populations nor has the potential moderating influence of methodological limitations on effect size variability across studies. This study quantitatively assessed whether patients with DDs, trauma- and stressor-related disorders (TSDs), and functional neurological disorder (FND) display elevated hypnotic suggestibility. A systematic literature search identified 20 datasets. A random-effects meta-analysis revealed that patients displayed greater hypnotic suggestibility than controls, Hedges’s g=0.92 [0.66, 1.18]. Elevated hypnotic suggestibility was observed in all subgroups but was most pronounced in the DDs. Although there was some evidence for publication bias, a bias- corrected estimate of the group effect remained significant. Moderation analyses did not yield evidence for any link between effect sizes and methodological limitations. These results demonstrate that DDs and germane conditions are characterized by heightened hypnotic suggestibility and have implications for the mechanisms, risk factors, and treatment of dissociative psychopathology.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 79%

Section: Meta-analysis and Meta-regressionmentioning

confidence: 99%

See 1 more Smart Citation

Hypnotic suggestibility in dissociative and related disorders: A meta-analysis

Wieder¹,

Brown

Thompson³

et al. 2022

Preprint

View full text Add to dashboard Cite

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Research on the knowledge transfer mechanism of digital platform in the digital innovation ecosystem: an improved model of SIR embedded in symbiosis theory

Liu,

Ning,

Gao

2023

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PurposeIn the digital economy era, digital platforms are vital infrastructure for innovation subjects to perform digital innovation activities. Achieving efficient and smooth knowledge transfer between innovation subjects through digital platforms has become a novel research subject. This study aims to examine the knowledge transfer mechanism of digital platforms in the digital innovation ecosystem through modeling and simulation to offer a theoretical basis for digital innovation subjects to acquire digital value through knowledge-sharing and thus augment their competitive advantage.Design/methodology/approachThis study explores the optimal symbiotic interaction rate between different users based on the classic susceptible-infected-removed (SIR) model. Additionally, it constructs a knowledge transfer mechanism model for digital platforms in the digital innovation ecosystem by combining the theories of communication dynamics and symbiosis. Finally, Matrix Laboratory (MATLAB) software is used for the model and numerical simulation.FindingsThe results demonstrate that (1) the evolutionary path of the symbiotic model is key to digital platforms' knowledge transfer in the digital innovation ecosystem. In the symbiotic model, the knowledge transfer path of digital platforms is “independent symbiosis—biased symbiosis (user benefit)—reciprocal symbiosis,” aligning with the overall interests of the digital innovation ecosystem. (2) Digital platforms' knowledge transfer effects within the digital innovation ecosystem show significant differences. The most effective knowledge transfer model for digital platforms is reciprocal symbiosis, whereas the least effective is parochial symbiosis (platform benefit). (3) The symbiotic rate has a significant positive impact on the evolutionary dynamics of knowledge transfer on digital platforms, especially in the reciprocal symbiosis model.Originality/valueThis study's results aid digital innovators in achieving efficient knowledge transfer through digital platforms and identify how symbiotic relationships affect the knowledge transfer process across the ecosystem. Accordingly, the authors propose targeted recommendations to promote the efficiency of knowledge transfer on digital platforms.

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Reply to letter to the editor by Peters: knowledge transfer is the key

Cited by 2 publications

References 5 publications

Hypnotic suggestibility in dissociative and related disorders: A meta-analysis

Hypnotic suggestibility in dissociative and related disorders: A meta-analysis

Research on the knowledge transfer mechanism of digital platform in the digital innovation ecosystem: an improved model of SIR embedded in symbiosis theory

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