The Independent-Interdependent Problem-Solving Scale

The IIPSS

Problem-Solving

Please indicate how much you agree or disagree with each of the following statements using the following scale:

1 = Strongly Disagree, 2 = Disagree, 3 = Partially Disagree, 4 = Neutral, 5 = Partially Agree, 6 = Agree, 7 = Strongly Agree

1. When faced with a difficult personal problem, it is better to decide yourself rather than to follow the advice of others.

2. I value other people’s help and advice when making important decisions.

3. In general, I do not like to ask other people to help me to solve problems.

4. I prefer to make decisions on my own, rather than with other people.

5. I like to get advice from my friends and family when deciding how to solve my personal problems.

6. I prefer to consult with others before making important decisions.

7. I usually find other people’s advice to be the most helpful source of information for solving my problems.

8. I would rather struggle through a personal problem by myself than discuss it with a friend.

9. I do not like to depend on other people to help me to solve my problems.

10. I usually prefer to ask other people for help rather than to try to solve problems on my own.

Item Characteristics

Five of the items measure the preference for independent problem-solving (items 1, 3, 4, 8, & 9), and five measure the preference for interdependent problem-solving (items 2, 5, 6, 7, 10). Two of the items were taken from Triandis et al.'s (1986) Individualism-Collectivism scale (items 1 & 8), and one was based on Oyserman, Coon, and Kemmelmeier (2002, p. 9; item 6). The remaining items were generated by myself.

Scoring

Researchers should reverse code participants’ responses to either the independent problem-solving items or the interdependent problem-solving items and then compute the average score of all 10 items. The decision about which set of items to reverse code depends on whether you would like to represent independent problem-solving with high scores and interdependent problem-solving with low scores or vice versa. For example, if you reverse-score the responses to the five interdependent items, then higher scores on the scale will mean that participants have a higher independent problem-solving style.

Reliability and Validity

Rubin et al. (2012) reported evidence of the reliability and validity of Version 1 of the IIPSS. In summary, the scale has good reliability, with a single factor structure (eigenvalue = 3.96) and good internal consistency (αs = .77 & .80). The scale also has good convergent validity. It has small-to-medium sized correlations with Cross et al.’s (2000) Relational-Interdependent Self-Construal scale and Goldberg et al.’s (2006) Extraversion scale. Finally, the scale has good predictive validity. Rubin et al. found that the IIPSS predicted participants’ self-reported likelihood that they would (a) search the internet to find a solution to a problem at university (i.e., independent problem-solving) and (b) ask another student to help them with a university problem (i.e., interdependent problem-solving). More recent and extensive evidence of the IIPPS's reliability and validity has been provided by Santakar and Rubin (2023). 

Analysing the IIPSS

There are two approaches to analysing data from the IIPSS: (1) Treat it as a continuous variable ranging from high independence and low interdependence, through a mixture of both types of problem-solving, to low independence and high interdependence. (2) Designate some cut-off point above and below which you categorize individuals as independent problem-solvers and interdependent problem-solvers.

The continuous approach is the more powerful of the two approaches. As an example, you might include the IIPSS and workplace performance in a correlation or regression analysis and find that the higher individuals' IIPSS scores, the better their performance. If the IIPSS is coded with high scores indicating greater independent problem-solving, then you could conclude that independent problem-solvers perform better than interdependent problem-solvers in that workplace situation. Note that, although we are treating the IIPSS as a continuous variable here, it still makes sense to talk about "independent problem-solvers" and "interdependent problem-solvers" in the same way that it makes sense to talk about "shaven" and "bearded" faces, even though there is no sharp discontinuity between the two (Thouless, 1930).

The categorical approach is less powerful, but often necessary. For example, if you are treating independent-interdependent problem-solving as a moderator variable, and you want to demonstrate that an effect occurs for independent problem-solvers but not for interdependent problem-solvers, then you can split your sample of research participants at one standard deviation above and below the IIPSS mean and compare the effect in each of these two groups (e.g., Aiken & West, 1991). Although it is popular, the problem with this +/- 1 standard deviation approach is that you lose a lot of statistical power because you exclude around 68% of your participants from the analysis. So, for example, with a sample of 100 participants, this approach will result in only around 16 participants in the independent problem-solver group and 16 in the interdependent problem-solver group. To minimize sample loss, you can use a more liberal cut-off point. So, for example, you can use the 25th and 75th percentiles as cut-off points in order to ensure larger numbers of participants in each group (e.g., ns = 25 instead of 16; Hayes, 2013).

Recent Research Using the IIPSS

• Vieira (2013) found that the IIPSS is related to consumers' need to touch items prior to purchase.

• Seward and Harris (2016) used the IIPSS in their investigation of suicide-related help-seeking.

• Akinbobola, Uzonwanne, and Udechukwu (2018) found that the IIPSS had good internal reliability, and that it predicted role-based performance among non-academic staff at a Nigerian university. 

• Dorgan (2018) found no significant difference in IIPSS scores between video game players who preferred to play single-player rather than multi-player games. 

• Alexander and Beckling considered the IIPSS in relation to the performance of graduates in the workplace.

• Ainsworth and Oldfield (2019, Table 3) found that, among a sample of UK teachers, independent problem-solving had a significant positive association with perceived conflict between teaching beliefs and practices and significant negative associations with emotional intelligence, life-orientation, and self-care. 

• Sanatkar and Rubin (2020) found that openness to experience moderated the association between the IIPSS and neuroticism: Independent problem-solving was associated with high levels of neuroticism, but only at low levels of openness, possibly because low openness makes independent problem-solvers feel insecure about their problem-solving abilities.

• Sanatkar and Rubin (2023) found that the IIPSS showed adequate test–retest reliability and predicted positive associations with social personality traits. It also showed no significant associations with measures of demand characteristics and social desirability.

Permissions

The IIPSS is free to use for research purposes. No permission is required. However, the scale may not be reproduced for commercial purposes.

Hard Copy

Please click here to download a hard copy of the scale for use in paper-and-pencil surveys.

Referencing the IIPSS

The IIPSS was first reported in a journal article that investigated immigrants’ social integration. To refer to the IIPSS, please use the following references:

Rubin, M., Watt, S. E., & Ramelli, M. (2012). Immigrants’ social integration as a function of approach-avoidance orientation and problem-solving style. International Journal of Intercultural Relations, 36, 498-505. http://dx.doi.org/10.1016/j.ijintrel.2011.12.009 A self-archived version of this journal article is available here.

Sanatkar, S., & Rubin, M. (2023). Reliability and validity of the Independent-Interdependent Problem-Solving Style Scale. International Journal of Psychology, 58(1), 30-41. http://doi.org/10.1002/ijop.12878 

References

Aiken, L. S. & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage.

Cross, S. E., Bacon, P. L., & Morris, M. L. (2000). The relational-interdependent self-construal and relationships. Journal of Personality and Social Psychology, 78, 791-808.

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.

Thouless, E. (1930). Straight and crooked thinking. London: Hodder and Stoughton.