Sex: 50.1/49.9% M/F Percentage with children: 24.5 Percentage ever divorced: 13.0 Percentage with current gambling problem: 1.5 Percentage with at least one traffic ticket in last year: 8.0 Percentage arrested at least once: 21.5 Percentage arrested more than once: 10.3 Percentage with >$10,000 credit card debt: 7.9 30.65 percent subjects with BMI>30 (obese) 7.28 percent subjects with BMI>40 (extreme obesity)

[+]

Identified

The ANT decomposes attentional processing into three separable components: (1) alerting, (2) orienting, and (3) executive control – or resolving conflict among responses. Each of these components, especially executive control, may relate to goal-directed behavior and self-regulation (Fan, McCandliss, Sommer, Raz, & Posner, 2002). Parsing these components may therefore shed light on specific self-regulatory processes underlying health behavior and behavior change.

[+] PMCID, PUBMED ID, or CITATION

Text Citation: Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347.

Measured

The three networks assessed in the ANT are discussed as largely independent, however, interactions between the networks, particularly between the alerting/orienting networks and conflict (i.e. executive control) have been identified (Fan et al., 2002). The ANT has also been used in neuroimaging, which has differentiated these components and related them to three separable anatomical brain networks, and is considered to have good face validity (Fan et al., 2005; Ishigami & Klein, 2010; MacLeod et al., 2010).
The primary measure for the ANT is RT. One study examining the ANT across 10 sessions found practice effects for RT measuring executive function (i.e. RT decreased over time). The measure of RT was robust across all sessions only for executive control (i.e. was significantly different from 0, p < .05), and found that the measure of executive control was reliable regardless of the number of sessions, with split-half reliability increasing up to more than the first five total sessions. The measure of RT for attention was significantly reliable only when more than seven sessions were included, and orienting RT was reliable only when all 10 sessions were included (Ishigami & Klein, 2010). Macleod et al. (2010) found that, across 15 unique studies, reliability RT for executive control (conflict) was generally the most reliable, followed by the orienting, and then the alerting network (weighted split-half reliabilities of .65, .32, and .20 respectively). The distribution of the network scores were also found to be nonnormal, and the networks correlated.

[+] PMCID, PUBMED ID, or CITATION

Text Citation: Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. Neuroimage, 26(2), 471-479.

Text Citation: Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of cognitive neuroscience, 14(3), 340-347.

Text Citation: Ishigami, Y., & Klein, R. M. (2010). Repeated measurement of the components of attention using two versions of the Attention Network Test (ANT): Stability, isolability, robustness, and reliability. Journal of neuroscience methods, 190(1), 117-128.

Text Citation: MacLeod, J. W., Lawrence, M. A., McConnell, M. M., Eskes, G. A., Klein, R. M., & Shore, D. I. (2010). Appraising the ANT: Psychometric and theoretical considerations of the Attention Network Test. Neuropsychology, 24(5), 637.

[+] Demographics

Sex: 50.1/49.9% M/F
Percentage with children: 24.5
Percentage ever divorced: 13.0
Percentage with current gambling problem: 1.5
Percentage with at least one traffic ticket in last year: 8.0
Percentage arrested at least once: 21.5
Percentage arrested more than once: 10.3
Percentage with >$10,000 credit card debt: 7.9
30.65 percent subjects with BMI>30 (obese)
7.28 percent subjects with BMI>40 (extreme obesity)

Influenced

Mindfulness and meditation-based training has been shown to relate to improved conflict scores (executive control) on the ANT, but not to improved alerting or orienting scores (Tang et al., 2007; Ainsworth et al., 2013).

[+] PMCID, PUBMED ID, or CITATION

Text Citation: Ainsworth, B., Eddershaw, R., Meron, D., Baldwin, D. S., & Garner, M. (2013). The effect of focused attention and open monitoring meditation on attention network function in healthy volunteers. Psychiatry research, 210(3), 1226-1231.

Text Citation: Tang, Y. Y., Ma, Y., Wang, J., Fan, Y., Feng, S., Lu, Q., ... & Posner, M. I. (2007). Short-term meditation training improves attention and self-regulation. Proceedings of the National Academy of Sciences, 104(43), 17152-17156.

[+] Demographics

Sex: 50.1/49.9% M/F
Percentage with children: 24.5
Percentage ever divorced: 13.0
Percentage with current gambling problem: 1.5
Percentage with at least one traffic ticket in last year: 8.0
Percentage arrested at least once: 21.5
Percentage arrested more than once: 10.3
Percentage with >$10,000 credit card debt: 7.9
30.65 percent subjects with BMI>30 (obese)
7.28 percent subjects with BMI>40 (extreme obesity)

Validated

This measure has not been validated yet.

Access Measure

SOBC Validation Process

The Science of Behavior Change (SOBC) program seeks to promote basic research on the initiation, personalization and maintenance of behavior change. By integrating work across disciplines, this effort will lead to an improved understanding of the underlying principles of behavior change. The SOBC program aims to implement a mechanisms-focused, experimental medicine approach to behavior change research and to develop the tools required to implement such an approach. The experimental medicine approach involves: identifying an intervention target, developing measures to permit verification of the target, engaging the target through experimentation or intervention, and testing the degree to which target engagement produces the desired behavior change.

Within the SOBC Measures Repository, researchers have access to measures of mechanistic targets that have been (or are in the processing of being) validated by SOBC Research Network Members and other experts in the field. The SOBC Validation Process includes three important stages of evaluation for each proposed measure: Identification, Measurement, and Influence.

The first stage of validation requires a measure to be Identified within the field; there must be theoretical support for the specific measure of the proposed mechanistic target or potential mechanism of behavior change. This evidence may include references for the proposed measure, or theoretical support for the construct that the proposed measure is intended to assess. The second stage of validation requires demonstration that the level and change in level of the chosen mechanistic target can be Measured with the proposed measure (assay). For example, if the proposed measure is a questionnaire, the score on the measure should indicate the activity of the target process, and it must have strong psychometric properties. The third stage of validation requires demonstration that the measure can be Influenced; there must be evidence that the measured target is malleable and responsive to manipulation. Evidence relating to each stage includes at least one peer-reviewed publication or original data presentation (if no peer-reviewed research is available to support the claim) and is evaluated by SOBC Research Network Members and experts in the field.

Once a measure has gone through these three stages, it will then either be Validated or Not validated according to SOBC Research Network standards. If a measure is Validated, then change in the measured target was reliably associated with Behavior Change. If a measure is Not validated, then change in the measured target was not reliably associated with Behavior Change. Why would we share measures that are not validated? The SOBC Research Network values open, rigorous, and transparent research. Our goal is to make meaningful progress and develop replicable and effective interventions in behavior change science. Therefore, the SOBC sees value in providing other researchers in the field with information regarding measures that work and measures that fall short for specific targets. Further, a measure that is not validated for one target in one population may be validated in another target or population.

Want to learn more? For any questions regarding the SOBC Validation Process or Measures Repository, please email info@scienceofbehaviorchange.org.

Identified

Has the mechanism been identified as a potential target for behavior change? This section summarizes theoretical support for the mechanism.

Measured

Have the psychometric properties of this measure been assessed? This section includes information such as content validity, internal consistency, and test-retest reliability.

Influenced

Has a study manipulation led to change in the mechanism? This section addresses evidence that this measure is modifiable by experimental manipulation or clinical intervention.

Not Validated

Has a change in this mechanism been associated with behavior change? This section addresses empirical evidence that causing change in the measure reliably produces subsequent behavior change.