General motivations, basic psychological needs, and problem gambling: applying the framework of Self-Determination Theory

Abstract

Background

Research into problem gambling has established that the addiction results from a complex array of bio-psycho-social factors. The range of factors, however, has yet to be comprehensively identified. Applications of Self-Determination Theory (SDT) have shown that specific characteristics are associated with problem gambling, including users’ susceptibility to external pressures and a general lack volition in their actions. Additionally, SDT research has found that the frustration of basic psychological needs (i.e. competence, autonomy, and relatedness) is associated with behavioral addictions (e.g. video gaming, exercise dependence). A primary proposal of SDT is that individual characteristics will contribute to maladaptive outcomes through an increased frustration of these needs. This specific proposal has not yet been examined in the context of problem gambling.

Purpose

The present study assesses an SDT-derived model of problem gambling.

Methods

An online sample of gamblers from Amazon’s Mechanical Turk (N = 887; 58.9% female, M = 33.871 years; SD = 9.770) completed a battery of assessments.

Results

Results from a structural equation model largely supported the underlying assumptions of SDT. Specifically, increased susceptibility to external pressures and perceptions of lower control over choice were associated with greater frustration of basic needs, which, in turn, contributed to problem gambling and subsequently to psychological distress. Notably, gamblers were particularly vulnerable to problem gambling if they perceived little to no choice in governing their actions.

Conclusions

The implications for theory and practice as well as future directions for research are discussed.

Keywords:

• Gambling
• problem gambling
• motivation
• Self-Determination Theory
• basic psychological needs
• mental health

Acknowledgments

The present study was not funded by any government agency or private corporation or foundation.

Disclosure statement

The authors do not have any conflicts of interests to report.

Notes

1 The 16-item measure of autonomous motivations includes four subscales that measure highly correlated first-order factors. The creation of the first-, second-, third-, and fourth-item parcels was done by respectively averaging the first, second, third, and fourth items from each of the four subscales.

2 The 8-item measure of controlled motivations includes two subscales that measure highly correlated first-order factors. The creation of the first-, second-, third-, and fourth-item parcels was done by, respectively, averaging the first-, second-, third-, and fourth-items from each of these subscales.

3 Finally, 8 separate item parcels were created using data from the need satisfaction (four item parcels) and need frustration (four item parcels) subscales. The first-, second-, third-, and fourth-item parcels for need satisfaction were created by, respectively, averaging the first-, second-, third-, and fourth-items from the competence, autonomy, and relatedness subscales. An identical process was done to create the item parcels for need frustration.

4 A structural equation model was conducted whereby the problem gambling severity was regressed onto the three motivations simultaneously. Results revealed adequate fit of the data to the model (χ²(234) = 538.475, p < 0.001; RMSEA = 0.038, 90CI [0.034, 0.043]; CFI = 0.972; TLI = 0.967; SRMR = 0.029) with controlled motivations (β = 0.220, p < 0.001) and amotivation (β = 0.378, p < 0.001) being significantly associated with problem gambling severity. The association of autonomous motivation was not significant (β = −0.059, p = 0.160).