The primary focus of much of my research has
distinguished between two types of goals. Extrinsic, materialistic
goals (e.g., financial success, image, popularity) are those focused on
attaining rewards and praise, and are usually means to some other end.
Intrinsic goals (e.g., personal growth, affiliation, community feeling)
are, in contrast, more focused on pursuits that are supportive of
intrinsic need satisfaction.
The Aspiration Index is my preferred way of assessing the constructs I typically study, as it is quite flexible, allows assessment of various goals on various dimensions, and, most importantly, allows for the assessment of the relative centrality of particular goals within an individual's personal goal system. Briefly, the AI presents individuals with a variety of possible goals they may have for the future and asks them to rate them on different kinds of dimensions. Versions of the AI have proliferated, as it is a fairly flexible instrument that has undergone substantial revision over the years.
The original version of the AI (Kasser & Ryan, 1993) examined four domains of aspirations (self-acceptance, affiliation, community feeling, and financial success) and assessed ratings of how important and likely to occur subjects perceived these goals as being. Kasser & Ryan (1996) added three more aspirational domains (image, popularity, and physical health) and Kasser (1996) added another of spirituality. The most recent published version of the AI (Grouzet, Kasser, et al., 2005) also assesses conformity, safety/security and hedonism, for a total of 11 domains. This 47-item version of the AI was validated in a sample of over 1800 college students from 15 nations. Factor analyses supported an 11-factor solution, MACS analyses demonstrated the cross-cultural comparability of the instrument, and multi-dimensional scaling analyses and circular stochastic modeling showed that the AI is organized across cultures in a circumplex fashion as shown below:
Goals next to each other in this circumplex are psychologically consistent with each other; that is, people who care about personal growth also often care about affiliation, and people who care about image are often oriented towards popularity. Goals on the opposite side of the circumplex are in conflict with each other; for example, spirituality and hedonism oppose each other, as do financial success and community feeling.
There are a variety of types of validity data supporting the use of the AI. For example, over the years, my collaborators and I have replicated results that come from the AI when we have used other measures such as guiding principles (Kasser & Ryan, 1993, 1996) and personal strivings (Sheldon & Kasser, 1995, 1998, 2001). Other researchers have also used reaction time methods (Schmuck, 2001; Solberg, Diener, & Robinson, 2004) as well as self-reports of Materialistic values (Richins & Dawson, 1992) to yield some similar results. I'd also note that Kasser & Ahuvia (2002) found substantial positive correlations between other measures of materialism and the extrinsic values of financial success, image, and popularity.
Using the Aspiration Index
You are welcome to use the AI in your research without charge. Here is some advice about using the AI.
- If you are only interested in assessing intrinsic and extrinsic goals, you probably could just use the Kasser & Ryan (1996) version published in PSPB.
- You do not have to use all of the 11 domains, and can mix and match if you desire; I have certainly done that in my work. I do recommend, however, that you use the whole AI if possible, for it gives the fullest description of a person's goal system. If this is not possible, I would recommend using goals that come from the different areas of the circumplex shown above.
- We almost always ask individuals to rate the importance of these goals. Some studies have looked at ratings of the likelihood of attaining these goals. One other has looked at ratings of current attainment of the goals. Another, unpublished study, examined motivation for the goals. Theoretically, many other rating dimensions could also be applied to these goal domains. Again, I consider the AI as a flexible measure that can be adapted for many purposes.
- I must emphasize that, from our perspective, it is crucial when using the AI to compute relative centrality measures (see Kasser & Ryan, 1993, 1996) in order to test the hypotheses we are interested in; you may of course have other uses for it. That is, it is necessary to control for the overall importance (likelihood, etc.) ratings before looking at the associations of the AI with other measures. We have done this in a variety of ways; the simplest is to subtract the subject's grand mean (i.e., ratings averaged across all domains) from the subject's particular aspiration score (e.g., financial success, extrinsic, etc.).
The Kasser & Ryan (1996) version of the Aspiration index, with scoring instructions, is available.
The English version of the newest version of the AI (Grouzet, Kasser, et al. 2005) with scoring instructions, is available.
We also have French, Spanish, Korean, and Chinese versions available upon request.