The Domain Specific Risk Taking Survey (DOSPERT) is a 30-item self-report scale that measures three aspects of individual differences with regard to risk taking behaviors: risk perceptions (the present measure), risk taking behavior, and expected benefits of taking risks. (For the latter two measures listed above, please see the separate listings in this Measures Repository.) Participants are presented with a series of situations and asked to “indicate how risky you perceive” each one using a 7-point Likert scale: 1 (Not at all Risky), 2 (Slightly Risky), 3 (Somewhat Risky), 4 (Moderately Risky), 5 (Risky), 6 (Very Risky), and 7 (Extremely Risky). Perceived risk levels are assessed in five separate domains (six items corresponding to each domain): Ethical (e.g., “Not returning a wallet you found that contains $200”), Financial (Investment and Gambling) (e.g., “Investing 5% of your annual income in a very speculative stock,” “Betting a day’s income at a high-stakes poker game”), Health and Safety (e.g., “Riding a motorcycle without a helmet”), Recreational (e.g., “Bungee jumping off a tall bridge”), and Social (e.g., “Moving to a city far away from your extended family”). The dependent measures are the risk perceptions scores, which are computed separately for each of the five domains as the sum of all item scores within that domain. An overall risk perceptions score may also be computed across the five domains by summing the relevant score for all 30 items.
The Domain Specific Risk Taking Survey (DOSPERT) measures psychological facets that may promote risk taking behaviors, including the expected benefits of taking risks, the perceived likelihood of taking risks, the perceived riskiness of situations (Blais & Weber, 2006). It measures these facets separately within each of the following domains: ethical, financial, health/safety, recreational, and social. The specific measure of risk perceptions is one potentially relevant construct related to self-regulation that may drive behavior change. For instance, a systematic review suggests that falsely positive perceptions of low risk may be an important factor to test in future research of disordered gambling behavior (Spurrier & Blaszczynski, 2014).
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Text Citation: Blais, A-R. & Weber, E. U. (2006). A Domain-specific Risk-taking (DOSPERT) Scale for
Text Citation: Spurrier, M., & Blaszczynski, A. (2014). Risk perception in gambling: A systematic review. Journal of Gambling Studies, 30(2), 253-276.
This measure has not been measured yet.
This measure has not been influenced yet.
This measure has not been validated yet.
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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 email@example.com.
Has the mechanism been identified as a potential target for behavior change? This section summarizes theoretical support for the mechanism.
Have the psychometric properties of this measure been assessed? This section includes information such as content validity, internal consistency, and test-retest reliability.
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.
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.