aggression scales Search Results


aggression scales  (Muris Inc)
90
Muris Inc aggression scales
Background and descriptive information on patients' cognitive‐motivational, interpersonal, and behavioral functioning, and treatment and research compliance ( N = 52)
Aggression Scales, supplied by Muris Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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popas (perception of prevalence of aggression scale)  (Beratung GmbH)
90
Beratung GmbH popas (perception of prevalence of aggression scale)
Background and descriptive information on patients' cognitive‐motivational, interpersonal, and behavioral functioning, and treatment and research compliance ( N = 52)
Popas (Perception Of Prevalence Of Aggression Scale), supplied by Beratung GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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hostility-aggression subscale  (Rohner)
90
Rohner hostility-aggression subscale
Background and descriptive information on patients' cognitive‐motivational, interpersonal, and behavioral functioning, and treatment and research compliance ( N = 52)
Hostility Aggression Subscale, supplied by Rohner, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
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aggression scales with the magnitude of the size difference between opponents  (Reichert Inc)
90
Reichert Inc aggression scales with the magnitude of the size difference between opponents
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Aggression Scales With The Magnitude Of The Size Difference Between Opponents, supplied by Reichert Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
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staff observation aggression scale-revised (soas-r)  (Muris Inc)
90
Muris Inc staff observation aggression scale-revised (soas-r)
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Staff Observation Aggression Scale Revised (Soas R), supplied by Muris Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
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perceptions of prevalence of aggression scale  (Radboud University)
90
Radboud University perceptions of prevalence of aggression scale
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Perceptions Of Prevalence Of Aggression Scale, supplied by Radboud University, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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short aggression scale  (SAS institute)
90
SAS institute short aggression scale
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Short Aggression Scale, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
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modified overt aggression scale  (Diagnos Inc)
90
Diagnos Inc modified overt aggression scale
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Modified Overt Aggression Scale, supplied by Diagnos Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/modified overt aggression scale/product/Diagnos Inc
Average 90 stars, based on 1 article reviews
modified overt aggression scale - by Bioz Stars, 2026-03
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staff observation aggression scale – revised  (Instrumente GmbH)
90
Instrumente GmbH staff observation aggression scale – revised
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Staff Observation Aggression Scale – Revised, supplied by Instrumente GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
staff observation aggression scale – revised - by Bioz Stars, 2026-03
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personality scales aggression, excitement-seeking, altruism  (Rundo Cronova)
90
Rundo Cronova personality scales aggression, excitement-seeking, altruism
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Personality Scales Aggression, Excitement Seeking, Altruism, supplied by Rundo Cronova, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
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interpersonal aggression scales  (Meloy Laboratories)
90
Meloy Laboratories interpersonal aggression scales
Evolution of a male signal, body size, and <t>aggression</t> in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)
Interpersonal Aggression Scales, supplied by Meloy Laboratories, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Background and descriptive information on patients' cognitive‐motivational, interpersonal, and behavioral functioning, and treatment and research compliance ( N = 52)

Journal: Journal of Clinical Psychology

Article Title: Cognitive‐motivational, interpersonal, and behavioral functioning in relationship to treatment and research engagement in forensic patients with ADHD

doi: 10.1002/jclp.23016

Figure Lengend Snippet: Background and descriptive information on patients' cognitive‐motivational, interpersonal, and behavioral functioning, and treatment and research compliance ( N = 52)

Article Snippet: The psychometric properties of the aggression scales were sufficient in previous research in (forensic) clinical samples (Hornsveld, Muris, Kraaimaat, & Meesters, ).

Techniques:

Bivariate correlations and descriptive statistics on cognitive‐motivational, interpersonal, and behavioral functioning and no‐shows and treatment time intervals ( N = 52)

Journal: Journal of Clinical Psychology

Article Title: Cognitive‐motivational, interpersonal, and behavioral functioning in relationship to treatment and research engagement in forensic patients with ADHD

doi: 10.1002/jclp.23016

Figure Lengend Snippet: Bivariate correlations and descriptive statistics on cognitive‐motivational, interpersonal, and behavioral functioning and no‐shows and treatment time intervals ( N = 52)

Article Snippet: The psychometric properties of the aggression scales were sufficient in previous research in (forensic) clinical samples (Hornsveld, Muris, Kraaimaat, & Meesters, ).

Techniques:

Evolution of a male signal, body size, and aggression in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)

Journal: Ecology Letters

Article Title: Runaway evolution from male‐male competition

doi: 10.1111/ele.13921

Figure Lengend Snippet: Evolution of a male signal, body size, and aggression in response to male‐male competition. Panels (a) and (b) show evolutionary trajectories for each trait over 200 generations, and panels (c) and (d) show predicted lines of equilibria (heavy line) and their stability (gray arrows). In all panels, all three traits have the same genetic variance ( G = 1 ), benefit ( b A = 0.2 ) and cost of aggression ( c A = 0.05 ), fitness cost deriving from the threat of a male's opponent ( c B = 0.2 ), cost of signal size ( c s = 0.05 ; with naturally selected optimum θ S = 0 ), and a responsiveness of aggression to body size ( δ AS = 0.4 ). The line of equilibria is calculated from Equation using these values. In panels (a) and (c), signal size is weakly correlated with body size ( G SB = 0.4 ), while in panels (b) and (d), the two traits are more strongly correlated ( G SB = 0.8 ). When the genetic correlation between signal size and body size is weak, all three traits reach equilibria (a), with equilibrium aggression predicted solely by costs and benefits. Signal size and body size reach a point on the predicted line of equilibrium (c) that differs depending on their starting values. When the genetic correlation is strong, aggression still reaches an equilibrium, but signal size and body size run away together (b), overshooting the predicted line of equilibria (d). As in Fisherian selection from female mate choice (Lande, ), male‐male competition can drive traits to runaway elaboration or extinction when the line of equilibria is unstable (d)

Article Snippet: This effect is captured in our model as a term in which aggression scales with the magnitude of the size difference between opponents, which is supported by optimality models and empirical studies (Emlen, , ; Huxley, ; Maynard Smith & Harper, ; Parker, ; Riechert, ; Sneddon et al., ).

Techniques: Selection

Stronger dependence of male aggressive behavior leads to more elaborate traits at equilibrium. Panel (a) illustrates a relatively weak influence of opponent signal on male aggression ( δ AS = 0.4 ), while panel (b) illustrates a stronger influence ( δ AS = 0.8 ). In each panel, we use starting values for traits relevant to the highly sexually dimorphic earwig Labidura riparia , which uses its forceps as a signaling trait and is shown to the right of each panel (drawing modified from Lucas, ). Other parameters are the same as Figure . When the influence of opponent signal is weak (a), both body size and signal show a moderate evolutionary increase. When the influence is stronger (b), both body size and signal increase more, but the final signal size is much larger relative to body size. The highly elaborate elongate forceps in panel (b) may be found in other earwig species like Forcipula gariazzi

Journal: Ecology Letters

Article Title: Runaway evolution from male‐male competition

doi: 10.1111/ele.13921

Figure Lengend Snippet: Stronger dependence of male aggressive behavior leads to more elaborate traits at equilibrium. Panel (a) illustrates a relatively weak influence of opponent signal on male aggression ( δ AS = 0.4 ), while panel (b) illustrates a stronger influence ( δ AS = 0.8 ). In each panel, we use starting values for traits relevant to the highly sexually dimorphic earwig Labidura riparia , which uses its forceps as a signaling trait and is shown to the right of each panel (drawing modified from Lucas, ). Other parameters are the same as Figure . When the influence of opponent signal is weak (a), both body size and signal show a moderate evolutionary increase. When the influence is stronger (b), both body size and signal increase more, but the final signal size is much larger relative to body size. The highly elaborate elongate forceps in panel (b) may be found in other earwig species like Forcipula gariazzi

Article Snippet: This effect is captured in our model as a term in which aggression scales with the magnitude of the size difference between opponents, which is supported by optimality models and empirical studies (Emlen, , ; Huxley, ; Maynard Smith & Harper, ; Parker, ; Riechert, ; Sneddon et al., ).

Techniques: Modification