scholarly journals Nothing wrong about change: the adequate choice of the dependent variable and design in prediction of cognitive training success

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
André Mattes ◽  
Mandy Roheger
Keyword(s):  
Regression Model ◽  
Cognitive Training ◽  
Test Score ◽  
Statistical Power ◽  
Individualized Medicine ◽  
Intervention Group ◽  
Change Score ◽  
Control Group ◽  
Absolute Change ◽  
True Model

Abstract Background Even though investigating predictors of intervention success (e.g Cognitive Training, CT) is gaining more and more interest in the light of an individualized medicine, results on specific predictors of intervention success in the overall field are mixed and inconsistent due to different and sometimes inappropriate statistical methods used. Therefore, the present paper gives a guidance on the appropriate use of multiple regression analyses to identify predictors of CT and similar non-pharmacological interventions. Methods We simulated data based on a predefined true model and ran a series of different analyses to evaluate their performance in retrieving the true model coefficients. The true model consisted of a 2 (between: experimental vs. control group) × 2 (within: pre- vs. post-treatment) design with two continuous predictors, one of which predicted the success in the intervention group and the other did not. In analyzing the data, we considered four commonly used dependent variables (post-test score, absolute change score, relative change score, residual score), five regression models, eight sample sizes, and four levels of reliability. Results Our results indicated that a regression model including the investigated predictor, Group (experimental vs. control), pre-test score, and the interaction between the investigated predictor and the Group as predictors, and the absolute change score as the dependent variable seemed most convenient for the given experimental design. Although the pre-test score should be included as a predictor in the regression model for reasons of statistical power, its coefficient should not be interpreted because even if there is no true relationship, a negative and statistically significant regression coefficient commonly emerges. Conclusion Employing simulation methods, theoretical reasoning, and mathematical derivations, we were able to derive recommendations regarding the analysis of data in one of the most prevalent experimental designs in research on CT and external predictors of CT success. These insights can contribute to the application of considered data analyses in future studies and facilitate cumulative knowledge gain.

scholarly journals Nothing wrong about change: The adequate choice of the dependent variable and design in prediction of cognitive training success

2020 ◽  
Author(s):  
André Mattes ◽  
Mandy Roheger
Keyword(s):  
Regression Model ◽  
Cognitive Training ◽  
Test Score ◽  
Statistical Power ◽  
Individualized Medicine ◽  
Intervention Group ◽  
Change Score ◽  
Control Group ◽  
Absolute Change ◽  
True Model

Abstract Background Even though investigating predictors of intervention success (e.g Cognitive Training, CT) is gaining more and more interest in the light of an individualized medicine, results on specific predictors of intervention success in the overall field are mixed and inconsistent due to different and sometimes inappropriate statistical methods used. Therefore, the present paper gives a guidance on the appropriate use of multiple regression analyses to identify predictors of CT and similar non-pharmacological interventions.Methods We simulated data based on a predefined true model and ran a series of different analyses to evaluate their performance in retrieving the true model coefficients. The true model consisted of a 2 (between: experimental vs. control group) x 2 (within: pre- vs. post-treatment) design with two continuous predictors, one of which predicted the success in the intervention group and the other did not. In analyzing the data, we considered four commonly used dependent variables (post-test score, absolute change score, relative change score, residual score), five regression models, eight sample sizes, and four levels of reliability.Results Our results indicated that a regression model including the investigated predictor, Group (experimental vs. control), pre-test score, and the interaction between the investigated predictor and the Group as predictors, and the absolute change score as the dependent variable seemed most convenient for the given experimental design. Although the pre-test score should be included as a predictor in the regression model for reasons of statistical power, its coefficient should not be interpreted because even if there is no true relationship, a negative and statistically significant regression coefficient commonly emerges.Conclusion Employing simulation methods, theoretical reasoning, and mathematical derivations, we were able to derive recommendations regarding the analysis of data in one of the most prevalent experimental designs in research on CT and external predictors of CT success. These insights can contribute to the application of considered data analyses in future studies and facilitate cumulative knowledge gain.

scholarly journals Nothing wrong about change: The adequate choice of the dependent variable and design in prediction of cognitive training success 

2020 ◽  
Author(s):  
André Mattes ◽  
Mandy Roheger
Keyword(s):  
Regression Model ◽  
Cognitive Training ◽  
Test Score ◽  
Statistical Power ◽  
Individualized Medicine ◽  
Intervention Group ◽  
Change Score ◽  
Control Group ◽  
Absolute Change ◽  
True Model

Abstract BackgroundEven though investigating predictors of intervention success (e.g Cognitive Training, CT) is gaining more and more interest in the light of an individualized medicine, results on specific predictors of intervention success in the overall field are mixed and inconsistent due to different and sometimes inappropriate statistical methods used. Therefore, the present paper gives a guidance on the appropriate use of multiple regression analyses to identify predictors of CT and similar non-pharmacological interventions.MethodsWe simulated data based on a predefined true model and ran a series of different analyses to evaluate their performance in retrieving the true model coefficients. The true model consisted of a 2 (between: experimental vs. control group) x 2 (within: pre- vs. post-treatment) design with two continuous predictors, one of which predicted the success in the intervention group and the other did not. In analyzing the data, we considered four commonly used dependent variables (post-test score, absolute change score, relative change score, residual score), five regression models, eight sample sizes, and four levels of reliability.ResultsOur results indicated that a regression model including the investigated predictor, Group (experimental vs. control), pre-test score, and the interaction between the investigated predictor and the Group as predictors, and the absolute change score as the dependent variable seemed most convenient for the given experimental design. Although the pre-test score should be included as a predictor in the regression model for reasons of statistical power, its coefficient should not be interpreted because even if there is no true relationship, a negative and statistically significant regression coefficient commonly emerges.ConclusionEmploying simulation methods, theoretical reasoning, and mathematical derivations, we were able to derive recommendations regarding the analysis of data in one of the most prevalent experimental designs in research on CT and external predictors of CT success. These insights can contribute to the application of considered data analyses in future studies and facilitate cumulative knowledge gain.

scholarly journals Nothing wrong about change: The adequate choice of the dependent variable and design in prediction of cognitive training success

2020 ◽  
Author(s):  
André Mattes ◽  
Mandy Roheger
Keyword(s):  
Regression Model ◽  
Cognitive Training ◽  
Test Score ◽  
Statistical Power ◽  
Individualized Medicine ◽  
Intervention Group ◽  
Change Score ◽  
Control Group ◽  
Absolute Change ◽  
True Model

Abstract Background Even though investigating predictors of intervention success (e.g Cognitive Training, CT) is gaining more and more interest in the light of an individualized medicine, results on specific predictors of intervention success in the overall field are mixed and inconsistent due to different and sometimes inappropriate statistical methods used. Therefore, the present paper gives a guidance on the appropriate use of multiple regression analyses to identify predictors of CT and similar non-pharmacological interventions.Methods We simulated data based on a predefined true model and ran a series of different analyses to evaluate their performance in retrieving the true model coefficients. The true model consisted of a 2 (between: experimental vs. control group) x 2 (within: pre- vs. post-treatment) design with two continuous predictors, one of which predicted the success in the intervention group and the other did not. In analyzing the data, we considered four commonly used dependent variables (post-test score, absolute change score, relative change score, residual score), five regression models, eight sample sizes, and four levels of reliability.Results Our results indicated that a regression model including the investigated predictor, Group (experimental vs. control), pre-test score, and the interaction between the investigated predictor and the Group as predictors, and the absolute change score as the dependent variable seemed most convenient for the given experimental design. Although the pre-test score should be included as a predictor in the regression model for reasons of statistical power, its coefficient should not be interpreted because even if there is no true relationship, a negative and statistically significant regression coefficient commonly emerges.Conclusion Employing simulation methods, theoretical reasoning, and mathematical derivations, we were able to derive recommendations regarding the analysis of data in one of the most prevalent experimental designs in research on CT and external predictors of CT success. These insights can contribute to the application of considered data analyses in future studies and facilitate cumulative knowledge gain.

scholarly journals Nothing Wrong About Change: The Adequate Choice of the Dependent Variable and Design in Prediction of Intervention Success

2020 ◽  
Author(s):  
André Mattes ◽  
Mandy Roheger
Keyword(s):  
Regression Model ◽  
Test Score ◽  
Statistical Power ◽  
Individualized Medicine ◽  
Intervention Group ◽  
Change Score ◽  
Individual Characteristics ◽  
Control Group ◽  
Absolute Change ◽  
True Model

Abstract Background Investigating predictors of intervention success is a common approach in medical research. In the light of an individualized medicine, it is important not only to investigate the effects of certain pharmacological and nonpharmacological interventions, but also to examine specific individual characteristics of participants who do or do not benefit from these interventions. However, results on specific predictors of intervention success in the overall field are mixed and inconsistent due to different and sometimes inappropriate statistical methods used. Therefore, the present paper gives a guidance on the appropriate use of multiple regression analyses to identify predictors of pharmacological and nonpharmacological interventions.Methods We simulated data based on a predefined true model and ran a series of different analyses to evaluate their performance in retrieving the true model coefficients. The true model consisted of a 2 (between: experimental vs. control group) x 2 (within: pre- vs. post-treatment) design with two continuous predictors, one of which predicted the success in the intervention group and the other did not. In analyzing the data, we considered four commonly used dependent variables (post-test score, absolute change score, relative change score, residual score), five regression models, eight sample sizes, and four levels of reliability.Results Our results indicated that a regression model including the investigated predictor, Group (experimental vs. control), pre-test score, and the interaction between the investigated predictor and the Group as predictors, and the absolute change score as the dependent variable seemed most convenient for the given experimental design. Although the pre-test score should be included as a predictor in the regression model for reasons of statistical power, its coefficient should not be interpreted because even if there is no true relationship, a negative and statistically significant regression coefficient commonly emerges.Conclusion Employing simulation methods, theoretical reasoning, and mathematical derivations, we were able to derive recommendations regarding the analysis of data in one of the most prevalent experimental designs in research on pharmacological and nonpharmacological interventions and external predictors of intervention success. These insights can contribute to the application of considered data analyses in future studies and facilitate cumulative knowledge gain.

scholarly journals 813. The Reduction of the acquisition rate of carbapenem resistant Acinetobacter baumannii after room privatization in the intensive care unit

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S448-S449
Author(s):  
Jongtak Jung ◽  
Pyoeng Gyun Choe ◽  
Chang Kyung Kang ◽  
Kyung Ho Song ◽  
Wan Beom Park ◽  
...  
Keyword(s):  
Regression Model ◽  
Acinetobacter Baumannii ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Intervention Group ◽  
Feeding Tube ◽  
Control Group ◽  
Cox Regression Model ◽  
Carbapenem Resistant ◽  
Hospital Acquired

Abstract Background Acinetobacter baumannii is one of the major pathogens of hospital-acquired infection recently and hospital outbreaks have been reported worldwide. On September 2017, New intensive care unit(ICU) with only single rooms, remodeling from old ICU with multibed bay rooms, was opened in an acute-care tertiary hospital in Seoul, Korea. We investigated the effect of room privatization in the ICU on the acquisition of carbapenem-resistant Acinetobacter baumannii(CRAB). Methods We retrospectively reviewed medical records of patients who admitted to the medical ICU in a tertiary care university-affiliated 1,800-bed hospital from 1 January 2015 to 1 January 2019. Patients admitted to the medical ICU before the remodeling of the ICU were designated as the control group, and those who admitted to the medical ICU after the remodeling were designated as the intervention group. Then we compared the acquisition rate of CRAB between the control and intervention groups. Patients colonized with CRAB or patients with CRAB identified in screening tests were excluded from the study population. The multivariable Cox regression model was performed using variables with p-values of less than 0.1 in the univariate analysis. Results A total of 1,105 cases admitted to the ICU during the study period were analyzed. CRAB was isolated from 110 cases in the control group(n=687), and 16 cases in the intervention group(n=418). In univariate analysis, room privatization, prior exposure to antibiotics (carbapenem, vancomycin, fluoroquinolone), mechanical ventilation, central venous catheter, tracheostomy, the presence of feeding tube(Levin tube or percutaneous gastrostomy) and the length of ICU stay were significant risk factors for the acquisition of CRAB (p< 0.05). In the multivariable Cox regression model, the presence of feeding tube(Hazard ratio(HR) 4.815, 95% Confidence interval(CI) 1.94-11.96, p=0.001) and room privatization(HR 0.024, 95% CI 0.127-0.396, p=0.000) were independent risk factors. Table 1. Univariate analysis of Carbapenem-resistant Acinetobacter baumannii Table 2. Multivariable Cox regression model of the acquisition of Carbapenem-resistant Acinetobacter baumannii Conclusion In the present study, room privatization of the ICU was correlated with the reduction of CRAB acquisition independently. Remodeling of the ICU to the single room would be an efficient strategy for preventing the spreading of multidrug-resistant organisms and hospital-acquired infection. Disclosures All Authors: No reported disclosures

Investigating the Impact of Cognitive Training for Individuals With Bothersome Tinnitus: A Randomized Controlled Trial

2021 ◽  
pp. 019459982199474
Author(s):  
Maggie Xing ◽  
Dorina Kallogjeri ◽  
Jay F. Piccirillo
Keyword(s):  
Randomized Controlled Trial ◽  
Cognitive Training ◽  
Mixed Model ◽  
Controlled Trial ◽  
Intervention Group ◽  
Control Group ◽  
Functional Index ◽  
Open Label ◽  
Randomized Controlled ◽  
The Impact

Objective To evaluate the effectiveness of cognitive training in improving tinnitus bother and to identify predictors of patient response. Study Design Prospective open-label randomized controlled trial. Setting Online. Methods Participants were adults with subjective idiopathic nonpulsatile tinnitus causing significant tinnitus-related distress. The intervention group trained by using auditory-intensive exercises for 20 minutes per day, 5 days per week, for 8 weeks. The active control group trained on the same schedule with non–auditory intensive games. Surveys were completed at baseline, 8 weeks, and 12 weeks. Results A total of 64 participants completed the study. The median age was 63 years (range, 25-69) in the intervention group and 61 years (34-68) in the control group. Mixed model analysis revealed that within-subject change in Tinnitus Functional Index in the intervention group was not different than the control group, with marginal mean differences (95% CI): 0.24 (–11.20 to 10.7) and 2.17 (–8.50 to 12.83) at 8 weeks and 2.33 (–8.6 to 13.3) and 3.36 (–7.91 to 14.6) at 12 weeks, respectively. When the 2 study groups were compared, the control group had higher Tinnitus Functional Index scores than the intervention group by 10.5 points at baseline (95% CI, –0.92 to 29.89), 8.1 at 8 weeks (95% CI, –3.27 to 19.42), and 9.4 at 12 weeks (95% CI, –2.45 to 21.34). Conclusion Auditory-intensive cognitive training was not associated with changes in self-reported tinnitus bother. Given the potential for neuroplasticity to affect tinnitus, we believe that future studies on cognitive training for tinnitus remain relevant.

Effects of Cognitive Training on Cognitive Performance of Healthy Older Adults

2017 ◽  
Vol 20 ◽  
Author(s):  
Mariana Teles Santos Golino ◽  
Carmen Flores Mendoza ◽  
Hudson Fernandes Golino
Keyword(s):  
Older Adults ◽  
Cognitive Training ◽  
Repeated Measures ◽  
Digit Span ◽  
Intervention Group ◽  
Control Group ◽  
Digit Symbol ◽  
Transfer Effects ◽  
Healthy Older Adults ◽  
Picture Completion

AbstractThe purpose of this study was to determine the immediate effects of cognitive training on healthy older adults and verify the transfer effects of targeted and non-targeted abilities. The design consisted of a semi-randomized clinical controlled trial. The final sample was composed of 80 volunteers recruited from a Brazilian community (mean age = 69.69; SD = 7.44), which were separated into an intervention group (N = 47; mean age = 69.66, SD = 7.51) and a control group (N = 33; mean age = 69.73, SD = 7.45). Intervention was characterized by adaptive cognitive training with 12 individual training sessions of 60 to 90 minutes (once a week). Eight instruments were used to assess effects of cognitive training. Five were used to assess trained abilities (near effects), including: Memorization Tests (List and History), Picture Completion, Digit Span, Digit Symbol-Coding, and Symbol Search (the last four from WAIS-III). Two instruments assessed untrained abilities (far effects): Arithmetic and Matrix Reasoning (WAIS-III). The non-parametric repeated measures ANOVA test revealed a significant interaction between group by time interaction for Picture Completion [F(74) = 14.88, p = .0002, d = 0.90, CLES = 73.69%], Digit Symbol-Coding [F(74) = 5.66, p = .019, d = 0.55, CLES = 65.21%] and Digit Span [F(74) = 5.38, p = .02, d = 0.54, CLES = 64.85%], suggesting an interventional impact on these performance tasks. The results supported near transfer effects, but did not demonstrate a far transfer effects.

Impact of Multimodal Cognitive Training on Cognitive Traits of Children: A Multicentric Interventional Study

2021 ◽  
Author(s):  
Manjunatha R ◽  
Praveen Pankajakshan ◽  
Alphonsa Joseph ◽  
Gyan Kashyap ◽  
Usha Manjunath ◽  
...  
Keyword(s):  
Cognitive Training ◽  
Statistical Significance ◽  
Intervention Group ◽  
Control Group ◽  
Sleep State ◽  
Eyes Closed ◽  
Before And After ◽  
Slow Sleep ◽  
Mini Mental Status Examination ◽  
External Behavior

Abstract In this article, we evaluate the hypothesis that a multimodal cognitive training (MCT) program, the Brighter Minds, can enhance certain inherent traits of a child and thus bring changes in the external behavior. For the study, 186 children (randomized to 93 each in intervention and control group) aged 10-15 years were enrolled from three different locations. Psychometric tests, parental/caregiver interviews and EEG (electroencephalography) tests were conducted before and after the program. Intervention group showed strong statistical significance for improvements in Mini Mental Status Examination (MMSE) (P<0.01) but no significance for Raven’s Standard Progrssive Matrices (SPM) or Susan Harter’s test. The parental/caregiver reported satistically significant improvements in focus (P<0.05), empathy (P<0.05), intuition (P<0.05), comprehension (P<0.05) and understanding of abstract concepts (P<0.05) for the intervention group. For the control, Power Spectral Density (PSD) of the baseline eyes-closed (EC) EEG recording, the spectrum below 20Hz exhibited the characteristic “1/f” spectral scaling of the power-law. This signature matches prior reported evidence in literature of those in wakeful state with EC. The intervention group EC PSD, however, exhibited a signature similar to those in a slow sleep state; reflective of the possible transfer effect of the training on other skills like relaxation. We used unsupervised learning methods with dice distance, on the psychometric and interview data, to show the effect of location and the exposure of a few control children to the program.

scholarly journals EFFECTS OF ADAPTIVE COMPUTER-BASED COGNITIVE TRAINING ON COMMUNITY-DWELLING ELDERS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S244-S244
Author(s):  
Guifang Guo ◽  
Huijuan Gongzhi
Keyword(s):  
Cognitive Training ◽  
Digit Span ◽  
Memory Function ◽  
Intervention Group ◽  
Community Dwelling ◽  
Control Group ◽  
Quasi Experimental ◽  
Computer Based ◽  
And Control ◽  
Community Dwelling Older Adults

Abstract This quasi-experimental designed study analyzed the effects of adaptive computer-based cognitive training among community-dwelling older adults. A 6-week (5 times/week) program was implemented with an intervention group (Difficulty Adaptive Training) and control group (Difficulty Fixed Training). General cognitive, memory, executive and attention functions were evaluated before (T1), completion (T2), and one month after intervention (T3). Sixty-one participants completed data collection. (1) General cognitive function: improved in both groups at T2, and T3, intervention group had better effect; (2) Memory function: improved in both groups in immediate, short and long-delayed recalls at T2 and T3, and recognition at T2. (3) Executive function: improved in both groups. Time of simple information processing was shortened at T2 and T3 in intervention group, at T3 in control group; TMT response inhibition was shortened at T2 and T3 in both groups. (4) Attention function: digit span forward was improved at T2 in intervention group.

scholarly journals How does a 4-week motor–cognitive training affect choice reaction, dynamic balance and cognitive performance ability? A randomized controlled trial in well-trained, young, healthy participants

2019 ◽  
Vol 7 ◽  
pp. 205031211987002
Author(s):  
Daniel Niederer ◽  
Ulrike Plaumann ◽  
Tanja Seitz ◽  
Franziska Wallner ◽  
Jan Wilke ◽  
...  
Keyword(s):  
Cognitive Training ◽  
Perceived Exertion ◽  
Intervention Group ◽  
Rating Of Perceived Exertion ◽  
Control Group ◽  
Trail Making Test ◽  
Potential Health ◽  
Time To Stabilization ◽  
Trail Making ◽  
Active Adults

Background: We aimed to investigate the potential effects of a 4-week motor–cognitive dual-task training on cognitive and motor function as well as exercise motivation in young, healthy, and active adults. Methods: A total of 26 participants (age 25 ± 2 years; 10 women) were randomly allocated to either the intervention group or a control group. The intervention group performed a motor–cognitive training (3×/week), while the participants of the control group received no intervention. Before and after the intervention period of 4 weeks, all participants underwent cognitive (d2-test, Trail Making Test) and motor (lower-body choice reaction test and time to stabilization test) assessments. Following each of the 12 workouts, self-reported assessments (rating of perceived exertion, enjoyment and pleasant anticipation of the next training session) were done. Analyses of covariances and 95% confidence intervals plotting for between group and time effects were performed. Results: Data from 24 participants were analysed. No pre- to post-intervention improvement nor a between-group difference regarding motor outcomes (choice-reaction: F = 0.5; time to stabilization test: F = 0.7; p > 0.05) occurred. No significant training-induced changes were found in the cognitive tests (D2: F = 0.02; Trail Making Test A: F = 0.24; Trail Making Test B: F = 0.002; p > 0.05). Both enjoyment and anticipation of the next workout were rated as high. Discussion: The neuro-motor training appears to have no significant effects on motor and cognitive function in healthy, young and physically active adults. This might be explained in part by the participants’ very high motor and cognitive abilities, the comparably low training intensity or the programme duration. The high degree of exercise enjoyment, however, may qualify the training as a facilitator to initiate and maintain regular physical activity. The moderate to vigorous intensity levels further point towards potential health-enhancing cardiorespiratory effects.

Sign in / Sign up

Export Citation Format

Share Document