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- Hagger, Martin S., et al.
(författare)
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A Multilab Preregistered Replication of the Ego-Depletion Effect
- 2016
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Ingår i: Perspectives on Psychological Science. - : Sage Publications. - 1745-6916 .- 1745-6924. ; 11:4, s. 546-573
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Tidskriftsartikel (refereegranskat)abstract
- Good self-control has been linked to adaptive outcomes such as better health, cohesive personal relationships, success in the workplace and at school, and less susceptibility to crime and addictions. In contrast, self-control failure is linked to maladaptive outcomes. Understanding the mechanisms by which self-control predicts behavior may assist in promoting better regulation and outcomes. A popular approach to understanding self-control is the strength or resource depletion model. Self-control is conceptualized as a limited resource that becomes depleted after a period of exertion resulting in self-control failure. The model has typically been tested using a sequential-task experimental paradigm, in which people completing an initial self-control task have reduced self-control capacity and poorer performance on a subsequent task, a state known as ego depletion. Although a meta-analysis of ego-depletion experiments found a medium-sized effect, subsequent meta-analyses have questioned the size and existence of the effect and identified instances of possible bias. The analyses served as a catalyst for the current Registered Replication Report of the ego-depletion effect. Multiple laboratories (k = 23, total N = 2,141) conducted replications of a standardized ego-depletion protocol based on a sequential-task paradigm by Sripada et al. Meta-analysis of the studies revealed that the size of the ego-depletion effect was small with 95% confidence intervals (CIs) that encompassed zero (d = 0.04, 95% CI [-0.07, 0.15]. We discuss implications of the findings for the ego-depletion effect and the resource depletion model of self-control.
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| 2. |
- Karyotaki, Eirini, et al.
(författare)
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Do guided internet-based interventions result in clinically relevant changes for patients with depression? : An individual participant data meta-analysis
- 2018
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Ingår i: Clinical Psychology Review. - : Elsevier. - 0272-7358 .- 1873-7811. ; 63, s. 80-92
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Forskningsöversikt (refereegranskat)abstract
- Little is known about clinically relevant changes in guided Internet-based interventions for depression. Moreover, methodological and power limitations preclude the identification of patients' groups that may benefit more from these interventions. This study aimed to investigate response rates, remission rates, and their moderators in randomized controlled trials (RCTs) comparing the effect of guided Internet-based interventions for adult depression to control groups using an individual patient data meta-analysis approach. Literature searches in PubMed, Embase, PsycINFO and Cochrane Library resulted in 13,384 abstracts from database inception to January 1, 2016. Twenty-four RCTs (4889 participants) comparing a guided Internet-based intervention with a control group contributed data to the analysis. Missing data were multiply imputed. To examine treatment outcome on response and remission, mixed-effects models with participants nested within studies were used. Response and remission rates were calculated using the Reliable Change Index. The intervention group obtained significantly higher response rates (OR = 2.49, 95% CI 2.17-2.85) and remission rates compared to controls (OR = 2.41, 95% CI 2.07-2.79). The moderator analysis indicated that older participants (OR = 1.01) and native-born participants (1.66) were more likely to respond to treatment compared to younger participants and ethnic minorities respectively. Age (OR = 1.01) and ethnicity (1.73) also moderated the effects of treatment on remission.Moreover, adults with more severe depressive symptoms at baseline were more likely to remit after receiving intemet-based treatment (OR = 1.19). Guided Internet-based interventions lead to substantial positive treatment effects on treatment response and remission at post-treatment. Thus, such interventions may complement existing services for depression and potentially reduce the gap between the need and provision of evidence-based treatments.
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