| 1. |
- Eliaz, D., et al.
(författare)
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Micro and nano-scale compartments guide the structural transition of silk protein monomers into silk fibers
- 2022
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Silk is a unique, remarkably strong biomaterial made of simple protein building blocks. To date, no synthetic method has come close to reproducing the properties of natural silk, due to the complexity and insufficient understanding of the mechanism of the silk fiber formation. Here, we use a combination of bulk analytical techniques and nanoscale analytical methods, including nano-infrared spectroscopy coupled with atomic force microscopy, to probe the structural characteristics directly, transitions, and evolution of the associated mechanical properties of silk protein species corresponding to the supramolecular phase states inside the silkworm's silk gland. We found that the key step in silk-fiber production is the formation of nanoscale compartments that guide the structural transition of proteins from their native fold into crystalline beta-sheets. Remarkably, this process is reversible. Such reversibility enables the remodeling of the final mechanical characteristics of silk materials. These results open a new route for tailoring silk processing for a wide range of new material formats by controlling the structural transitions and self-assembly of the silk protein's supramolecular phases.
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| 3. |
- Falkenström, Fredrik, et al.
(författare)
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Do therapist effects really impact estimates of within-patient mechanisms of change? A Monte Carlo simulation study
- 2020
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Ingår i: Psychotherapy Research. - : ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD. - 1050-3307 .- 1468-4381. ; 30:7, s. 885-899
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Tidskriftsartikel (refereegranskat)abstract
- Objective:Existing evidence highlights the importance of modeling differential therapist effectiveness when studying psychotherapy outcome. However, no study to date examined whether this assertion applies to the study of within-patient effects in mechanisms of change. The study investigated whether therapist effects should be modeled when studying mechanisms of change on a within-patient level. Methods:We conducted a Monte Carlo simulation study, varying patient- and therapist level sample sizes, degree of therapist-level nesting (intra-class correlation), balanced vs. unbalanced assignment of patients to therapists, and fixed vs random within-patient coefficients. We estimated all models using longitudinal multilevel and structural equation models that ignored (2-level model) or modeled therapist effects (3-level model). Results:Across all conditions, 2-level models performed equally or were superior to 3-level models. Within-patient coefficients were unbiased in both 2- and 3-level models. In 3-level models, standard errors were biased when number of therapists was small, and this bias increased in unbalanced designs. Ignoring random slopes led to biased standard errors when slope variance was large; but 2-level models still outperformed 3-level models. Conclusions:In contrast to treatment outcome research, when studying mechanisms of change on a within-patient level, modeling therapist effects may even reduce model performance and increase bias.
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| 4. |
- Falkenström, Fredrik, 1972-, et al.
(författare)
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How to Model and Interpret Cross-Lagged Effects in Psychotherapy Mechanisms of Change Research : A Comparison of Multilevel and Structural Equation Models
- 2022
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Ingår i: Journal of Consulting and Clinical Psychology. - : American Psychological Association (APA). - 0022-006X .- 1939-2117. ; 90:5, s. 446-458
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Modeling cross-lagged effects in psychotherapy mechanisms of change studies is complex and requires careful attention to model selection and interpretation. However, there is a lack of field-specific guidelines. We aimed to (a) describe the estimation and interpretation of cross lagged effects using multilevel models (MLM) and random-intercept cross lagged panel model (RI-CLPM); (b) compare these models' performance and risk of bias using simulations and an applied research example to formulate recommendations for practice. Method: Part 1 is a tutorial focused on introducing/describing dynamic effects in the form of autoregression and bidirectionality. In Part 2, we compare the estimation of cross-lagged effects in RI-CLPM, which takes dynamic effects into account, with three commonly used MLMs that cannot accommodate dynamics. In Part 3, we describe a Monte Carlo simulation study testing model performance of RI-CLPM and MLM under realistic conditions for psychotherapy mechanisms of change studies. Results: Our findings suggested that all three MLMs resulted in severely biased estimates of cross-lagged effects when dynamic effects were present in the data, with some experimental conditions generating statistically significant estimates in the wrong direction. MLMs performed comparably well only in conditions which are conceptually unrealistic for psychotherapy mechanisms of change research (i.e., no inertia in variables and no bidirectional effects). Discussion: Based on conceptual fit and our simulation results, we strongly recommend using fully dynamic structural equation modeling models, such as the RI-CLPM, rather than static, unidirectional regression models (e.g., MLM) to study cross-lagged effects in mechanisms of change research. What is the public health significance of this article? We describe the differences between multilevel and structural equation modeling in the study of mechanisms of change in psychotherapy research. We argue that the common application of multilevel modeling assumes that there is no within-patient inertia in predictor or outcome variable, and the outcome variable does not impact the predictor, both of which seem highly unrealistic in psychotherapy research. Moreover, we demonstrate that violations of these assumptions may lead to severe bias in estimated coefficients, resulting in inaccurate recommendations for clinical practice. Thus, we recommend researchers to use structural equation modeling to estimate the effects of proposed change mechanisms over time.
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| 5. |
- Wienicke, Frederik J., et al.
(författare)
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Efficacy and moderators of short-term psychodynamic psychotherapy for depression : A systematic review and meta-analysis of individual participant data
- 2023
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Ingår i: Clinical Psychology Review. - : Elsevier. - 0272-7358 .- 1873-7811. ; 101
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Forskningsöversikt (refereegranskat)abstract
- Background: Short-term psychodynamic psychotherapy (STPP) is frequently used to treat depression, but it is unclear which patients might benefit specifically. Individual participant data (IPD) meta-analyses can provide more precise effect estimates than conventional meta-analyses and identify patient-level moderators. This IPD meta-analysis examined the efficacy and moderators of STPP for depression compared to control conditions.Methods: PubMed, PsycInfo, Embase, and Cochrane Library were searched September 1st, 2022, to identify randomized trials comparing STPP to control conditions for adults with depression. IPD were requested and analyzed using mixed-effects models.Results: IPD were obtained from 11 of the 13 (84.6%) studies identified (n = 771/837, 92.1%; mean age = 40.8, SD = 13.3; 79.3% female). STPP resulted in significantly lower depressive symptom levels than control conditions at post-treatment (d = −0.62, 95%CI [−0.76, −0.47], p < .001). At post-treatment, STPP was more efficacious for participants with longer rather than shorter current depressive episode durations.Conclusions: These results support the evidence base of STPP for depression and indicate episode duration as an effect modifier. This moderator finding, however, is observational and requires prospective validation in future large-scale trials.
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