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Attributional Complexity

Attributional complexity is a psychological theory defined as the extent to which complex and intricate reasons are considered when explaining the causes of an individual’s behaviour (Fast et al., 2008; Fletcher et al., 1986; Follett & Hess, 2002).

Attribution is the process of assigning causes or ‘factors’ to behaviour, to explain why it occurs. Example factors include personality traits, motivation, surrounding influences etc. (Harvey & Weary, 1984). Attributional complexity relates to the degree to which many of these factors are considered when explaining behaviour, ranging from simple to complex (Fletcher et al., 1986).

The attributional complexity scale (ACS) evaluates differences in complexity according to seven primary attributional constructs (Fletcher et al., 1986).

The theory of attributional complexity is based on Heider’s attribution theory, which was further developed by Kelley’s covariation model and research on heuristics (Heider, 1958; Kelley, 1967; Nisbett & Ross, 1980).

The early theories were critiqued for being simplistic since they did not account for the influence of dynamic factors on attributions. Contemporary research addressed these limitations by focusing on exploring the role of culture and other variables, such as age, on attributional complexity (Nisbett et al., 2001; Follett & Hess, 2002).

Attributional complexity has implications in both social and clinical settings. In social contexts, greater attributional complexity is linked to enhanced social judgment and interpersonal skills (Fletcher et al., 1992; Sultan & Kanwal, 2014). In clinical contexts, attributional complexity demonstrates a curvilinear relationship with depression: moderate complexity aligns with optimal well-being, while extremes correlate with depression (Marsh & Weary, 1989). Notwithstanding this, attributional styles rather than complexity, remains a focal point in clinical research (Leighton & Terrell, 2020).

Theoretical Foundations of Attributional Complexity

Examples of factors that can be attributed as a cause of behaviour

Attributional complexity relates to the idea that individuals utilise cognitive frameworks known as ‘attributional schemata’ to understand and explain someone else’s behaviour. Some individuals have frameworks that are more complex than others and involve the ability to account for many factors contributing to another’s behaviour (i.e. personality traits, situational context, cultural norms, etc.). This is polarised by individuals with more simple cognitive frameworks or ‘schemata’ that rely on more one-dimensional explanations (Fletcher et al., 1986). Attributional complexity is related to broader theories such as the need for cognition (NFC), where an individual is motivated to comprehend and articulate the world (Cacioppo & Petty, 1982; Strobel et al., 2017), as well as cognitive complexity, which relates to the capacity to comprehend, differentiate and integrate separate pieces of information (Fletcher et al., 1986; Rosenkrantz & Crockett, 1965).

Fletcher et al. (1986) coined the term ‘attributional complexity’ with their work published in the ‘Journal of Personality and Social Psychology’. The authors proposed the attributional complexity scale (ACS) to assess individual differences in attributional complexity. This measure gathers s-data (self-report data) and includes 28 items in which participants answer on a 6-point Likert scale from strongly agree to strongly disagree. An example of an item from the scale includes: "I don't usually bother to analyse and explain people's behaviour" (Fletcher et al., 1986).

The measure assesses seven key attributional constructs in which individuals fall on a simple-complex spectrum for each one. The measure can distinguish differences in people’s attributional complexity, and the key constructs attempt to explain why some individuals use more simple or complex attributions than others (Fletcher et al., 1986).

The seven attributional constructs are:

1.  Motivation or the extent of interest.

2.  The drive towards more complex explanations as opposed to simple ones.

3.  Utilising metacognitive processes when developing explanations for behaviour.

4.  The knowledge that an individual’s interactions with others influence behaviour

5.  Likelihood to deduce complex internal causes that are abstract

6.  Likelihood to deduce external causes that originate geographically far from the current situation.

7.  Likelihood to deduce external causes that originate from past events (Fletcher et al., 1986).

Historical Background

Heider’s Attribution Theory

Attributional complexity originated from Heider’s work on causal attributions, which laid the framework for his later attribution theory during the mid-20th century. The theory argues that individuals have a tendency to explain the behaviour of others by attributing causes and reasons for their behaviour. These causes can be attributed to internal (dispositional) or external (situational) factors (Banerjee et al., 2020; Heider, 1958). For example, a student performing poorly on a test may attribute causes to internal factors such as their lack of studying. Another student may attribute the causes to external factors, such as the test being unfair (Weiner, 1979).

Kelly’s Covariation Model

Kelly’s model further develops this idea by proposing that individuals choose between internal or external attributions by examining other situations and whether certain factors present together. Consistency, distinctiveness, and consensus are the three key factors that are considered to guide individuals when attributing behaviour to internal or external circumstances (Kelley, 1967; Malle, 2022).

Influence of Heuristics

Nisbett & Ross’s (1980) seminal work on heuristics, mental shortcuts used when making fast-paced judgments and decisions (Gigerenzer & Gaissmaier, 2011), led to further development of attributional complexity. It proposed that while we can use complex attributions in understanding the causes of behaviour in everyday life, we also use simple attributions due to heuristics. This led to the concept of individual differences between simple and complex attributions, leading to attributional complexity as a measure of these individual differences (Nisbett & Ross, 1980).

Advancing Understanding: Early Theories vs. Contemporary Approaches

Heider’s attribution theory revealed an area of novel research in social cognition. However, the model was criticised for being too simplistic. Studies on the fundamental attribution error proposed that individuals overemphasise internal attributions (such as personality) compared to external attributions when explaining the causes of other’s behaviour (Jones & Harris, 1967; Langdridge & Butt, 2004). This highlights a limitation in Heider’s original work, suggesting it was oversimplified and did not acknowledge phenomena such as cognitive biases.

Kelley’s covariation model addresses this weakness by providing a more comprehensive extension of attribution theory. However, the model was criticised for the assumption that all individuals always thought systematically and included all three factors (consistency, distinctiveness, and consensus) in cognitive processing (Kelley, 1967). Nisbett & Ross’s (1980) work on heuristics evidenced that this is not the case and that individuals also use simplistic attributions. Whilst these early theories were able to advance research understanding in this area, they still lacked acknowledgement of the influence of culture and other factors on attributions (Nisbett et al., 2001; Follett & Hess, 2002).

Later studies have overcome these drawbacks. Studies have found cultural differences in the fundamental attribution error, with individualistic cultures being more prone to error than collectivist cultures (Morris & Peng, 1994; Nisbett et al., 2001). Furthermore, attribution theory has been linked to Theory of Mind (ToM) research, highlighting that attributions depend on an individual’s ToM (Kinderman et al., 1998).

Research has also shown attributional complexity peaks during middle-aged adulthood (Follett & Hess, 2002) and that exposure to literary fiction is also a predictor of high attributional complexity (Castano et al., 2020). Although research has been able to investigate variability in attributional complexity in different cultures and established the impact of factors such as age and ToM, it has yet to investigate the interaction between these factors. Further research is needed to explore how this complexity can evolve and change when interacting with dynamic situations.

Social Implications of Attributional Complexity

Theoretical positive correlation between social judgment and attributional complexity (Fletcher et al., 1992)

Research on social cognition has examined the effects of attributional complexity in social contexts, particularly in social judgment. Fletcher et al. (1992) measured participants' attributional complexity using the attributional complexity scale (ACS), and measured their accuracy when answering causal problems. The findings highlight that more complex participants would provide answers with higher accuracy compared to those with lower complexity. Overall, they concluded that participants with higher attributional complexity have greater social judgment owing to the greater accuracy of answers of causal explanations of others’ behaviour, highlighting evidence of the impact that attributional complexity can have on social contexts (Fletcher et al., 1992). The authors concluded that attributional complexity is related to the cognitive aspects of social intelligence, although they were cautious in interpreting findings in relation to social intelligence due to the many disputed definitions and conceptualisations (Dyussenova et al., 2023; Fletcher et al., 1992).

More contemporary research took this a step further. Rather than measuring the participants accuracy when answering causal problems, the authors videotaped participants social interactions and observed their social skills (Fast et al., 2008). These findings corroborate prior research to demonstrate that individuals with higher attributional complexity have superior social skills (Sultan & Kanwal, 2014), characterised by greater adaptability, openness, expressiveness, and are perceived by peers as having greater social insight, empathy, and consideration for others (Fast et al., 2008). Further research has found a positive impact of attributional complexity on specific social contexts, such as in workplaces. For example, one study found that transformational leaders tend to have a higher complexity (Sun & Anderson, 2012). This type of leadership style benefits the workplace by encouraging and inspiring others to achieve shared goals (David & Amey, 2020).  Research has also shown that attributional complexity can predict job performance when social complexity is salient in the job role, further displaying evidence for its benefits in the workplace (Townsend et al., 2002). More complex individuals are also more likely to notice, for example, subtle racism, showing that it plays a role in helping address systemic issues and creating more diverse and inclusive workplaces (Reid & Foels, 2010).

Nevertheless, research highlighting the relationship between attributional complexity and enhanced social skills and judgment must be interpreted cautiously. These studies deploy correlational research methods in which causal inferences cannot be made, and so one cannot conclude that attributional complexity causes these positive outcomes (Fast et al., 2008; Sun & Anderson, 2012). As an example, although attributional complexity is associated with job performance, this study also found that education level predicts attributional complexity (Townsend et al., 2002). Therefore, the study demonstrates that education level may be responsible for enhanced job performance, with attributional complexity acting as a mediator, rather than being the cause to better performance.

Clinical Implications of Attributional Complexity

Attributional complexity has briefly been studied in a clinical context as it can have an impact on mental health. According to research, mild and moderate depression are associated with high attributional complexity. Paradoxically, low attributional complexity has a relationship with both severe and an absence of depression (Flett & Hewitt, 1990; Marsh & Weary, 1989).  More novel research has found an inverse relationship between attributional complexity and happiness, indicating that higher levels of attributional complexity, in some situations, correspond with lower happiness (Oishi et al., 2024). The research suggests a curvilinear trend in the relationship between attributional complexity and depression, suggesting that moderate complexity results in optimal happiness and psychological wellbeing (Marsh & Weary, 1989). It is thought that low attributional complexity in severe cases of depression is due to a dominant negative bias in thoughts leading to a lack of understanding of the social world (Marsh & Weary, 1989). Furthermore, moderate and mild cases of depression that display high attributional complexity can be explained by the depressed individual’s habit of rumination rather than actively solving problems (Marsh & Weary, 1989). However, there has been a lack of empirical research that has investigated the nature of this relationship.

Research has established greater evidence for the influence of attribution styles on depression rather than attributional complexity. Attribution styles refer to how individuals explain the causes of occurrences in their lives (Leighton & Terrell, 2020). The literature concludes that a negative style, which is characterised by internal, stable and global attributions, is highly linked to depression (Seligman et al., 1979; Sweeney et al., 1986; Valentine et al., 2024). Therapeutic approaches, such as cognitive behavioural therapy (CBT), have been developed that aim to change negative attributional styles to improve well-being (Petersen et al., 2004; Proudfoot et al., 2009).

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