Question
Answered step-by-step
ElderCloverKingfisher32
Abstract This report aims to investigate the relationship between…
Abstract
This report aims to investigate the relationship between intelligence, personality, and life satisfaction. The importance of this study is evident as previous research suggests that intelligence and personality traits are correlated with subjective well-being. The three research questions addressed in this report are: 1) To what extent is fluid intelligence associated with satisfaction with life? 2) To what extent is crystallized intelligence associated with satisfaction with life? and 3) To what extent are the five different factors of the OCEAN personality model associated with satisfaction with life? The study utilized a community sample of 720 Australian residents over the age of 18, recruited via Facebook advertisements, who completed two surveys and two computerized ability tasks. Specifically, we examined the extent to which fluid and crystallized intelligence, and the five-factor model of personality (OCEAN: Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) are associated with life satisfaction in a sample of adults. The data was analysed using JASP 0.17.1.0. Descriptive statistics, reliability analysis, and correlational analyses were used to analyse the data and address the research questions. Results indicated significant associations between fluid intelligence, crystallized intelligence, and certain personality factors with life satisfaction, providing insights into the factors that contribute to life satisfaction. The reliability analysis with Cronbach’s alpha values indicates acceptable internal consistency. In conclusion, the findings point to a significant positive correlation between SWLS, APM and STW, O and C, E and A, and N and E.
“The Correlation Between Intelligence, Personality, and Life Satisfaction: A Comprehensive Analysis.”
Several studies have explored the association between intelligence and life satisfaction, with mixed findings. Some studies have found positive correlations between intelligence and life satisfaction suggesting that higher intelligence may be related to higher life satisfaction (von Stumm, 2018; von Stumm & Ackerman, 2013). For example, von Stumm and Ackerman (2013) found that both fluid intelligence and crystallized intelligence were positively correlated with life satisfaction, even after controlling for demographic variables. However, other studies have reported null or weak associations between intelligence and life satisfaction, indicating that the relationship may be complex and may depend on other factors such as age, gender, or culture (Luchetti et al., 2014; Soto et al., 2011).
Personality, as assessed by the FFM or OCEAN model, has also been implicated in shaping life satisfaction. Extroversion, conscientiousness, and emotional stability (low neuroticism) have consistently been found to be positively correlated with life satisfaction, while agreeableness and openness to experience have shown more mixed findings (Hill & Turiano, 2014; Steel et al., 2018). For example, Hill and Turiano (2014) found that higher extraversion, conscientiousness, and emotional stability were associated with higher life satisfaction, while higher agreeableness and openness were only weakly related to life satisfaction. However, other studies have found different patterns of associations, suggesting that the relationship between personality and life satisfaction may vary depending on the sample or measurement used (Steel et al., 2018; Weiss et al., 2018). Despite the existing literature on intelligence, personality, and life satisfaction, there is a need for a comprehensive analysis that examines the associations between fluid intelligence, crystallized intelligence, different facets of personality as measured by the OCEAN model, and life satisfaction. Moreover, the role of demographic variables such as age and sex in moderating these associations remains unclear. Therefore, the present study aims to address these gaps in the literature by examining the extent to which fluid intelligence, crystallized intelligence, and the five factors of the OCEAN model are associated with life satisfaction in a community sample of Australian residents. The specific research questions addressed in this study are: 1) To what extent is fluid intelligence associated with satisfaction with life? 2) To what extent is crystallized intelligence associated with satisfaction with life? 3) To what extent are the five different factors of the OCEAN personality model associated with satisfaction with life? The study is important because it seeks to contribute to the existing literature by examining the specific relationships between different dimensions of intelligence and personality and life satisfaction. The study’s aims are justified by the inconsistent findings in the literature and the need for further research to clarify these relationships. The study’s findings could have implications for interventions aimed at enhancing life satisfaction, such as those targeting cognitive and personality factors. By addressing these research questions, we hope to contribute to a better understanding of the factors that contribute to life satisfaction.
Method
Participants
720 Australian residents, over the age of 18 (549 female; 171 male). A community sample was recruited via advertisements placed on Facebook. Inclusion criteria: Participants were required to be Australian residents, aged over 18 years.
Procedure
Ethical approval for the study was provided by the University of Adelaide Human Research Ethics Committee. Participants were provided with information about the study before providing informed consent. Participants were not financially reimbursed for their participation; however, they were provided with a copy of their results and a report with information on how to interpret their results. Data collection was conducted via an online portal using the participants’ own computer. Assessments took 40-60 minutes in total. During the data collection process, the participants provided demographic data with age (reported in years) and sex (male/female), as well as completed two surveys and two computerised ability tasks.
Materials
Satisfaction With Life Scale (SWLS)
A 5-item, self-report measure of general life satisfaction (Diener et al., 1985). Participants indicate level of agreement with each item on a 7-point Likert scale (1 = Strongly Disagree, 7 = Strongly Agree). Higher scores indicate higher life satisfaction.
Openness Conscientiousness Extraversion Agreeableness Neuroticism Index Condensed (OCEANIC)
Contains 45 items and assesses the Five Factor Model personality constructs (Schulze & Roberts, 2006). This measure asks participants to rate the frequency with which they engage in each of the 45-item behaviours on a 6-point Likert scale, with a response of (1) indicating that they never engage in the specified behaviours and (6) indicating that they always engage in the specified behaviours.
Raven’s Advanced Progressive Matrices Short Form (APM-SF)
This was a computerized 12-item version of the original test (Raven et al., 1998). The 12 items used were the subset validated by Bors and Stokes (1998) for use as a brief form. The task measures abstract reasoning and involves presenting participants with a series of visual geometric designs with a missing piece. The participant is required to select the missing piece from six to eight options. It is a measure of fluid intelligence (Gf).
Spot-the-Word (STW)
This task involves presenting participants with pairs of items comprising one word and one non-word, and requiring them to identify the word (Baddeley et al., 1993). It is a measure of crystallised intelligence (Gc).
Results
The data was analysed using JASP 0.17.1. Descriptive statistics were used to calculate continuous variables and categorical variables. Reliability Analysis (Cronbach’s Alpha) has been used to check the internal consistency of the scales used in this study and Correlational analyses were conducted using Pearson’s correlation coefficients to examine the association between fluid intelligence, crystallised intelligence, each of the five personality factors, and life satisfaction.
Table 1
Descriptive statistics for Satisfaction with Life Scale (SWLS), Advanced Progressive Matrices (APM), Spot-the-Word (STW), and OCEANIC
Measure Mean (SD) Minimum Maximum Reliability
SWLS 24.47 (6.14) 5.00 35.00 .86
APM 7.61 (2.67) .00 12.00 .74
STW 24.67 (3.30) 11.00 30.00 .71
O 32.96 (7.01) 9.00 53.00 .82
C 37.96 (7.30) 9.00 54.00 .87
E 33.47 (7.20) 9.00 52.00 .86
A 43.14 (5.69) 9.00 54.00 .87
N 27.79 (7.21) 9.00 50.00 .88
Note. The reliability scores are Cronbach’s a. A = Agreeableness; APM = Advanced Progressive Matrices; C = Conscientiousness; E = Extraversion; N = Neuroticism; O = Openness to Experience; STW = Spot-the-Word; SWLS = Satisfaction With Life Scale.
Table 2
Pearson correlations for Satisfaction with Life Scale (SWLS), Advanced Progressive Matrices (APM), Spot-the-Word (STW), and OCEANIC.
Measure 1 2 3 4 5 6 7 8
1. SWLS
2. APM -.008
3. STW .034 .197***
4. O .107** .100** .129***
5. C .269*** -.063 -.004 .259***
6. E .340*** .211*** -.072 .103** .201***
7. A .297*** -.060 -.088* .258*** .419*** .314***
8. N .388*** -.007 -.106** -.013 -.076 .358*** .143***
Note. A = Agreeableness; APM = Advanced Progressive Matrices; C = Conscientiousness; E = Extraversion; N = Neuroticism; O = Openness to Experience; STW = Spot-the-Word; SWLS = Satisfaction With Life Scale.
*p < .05, **p < .01, ***p < .001.
According to the correlation analysis conducted in JASP 0.17.1.0, SWLS was positively correlated with O (r = .107, p < .01), C (r = .269, p < .001), E (r = .340, p < .001), A (r = .297, p < .001), and N (r = .388, p < .001). APM was not significantly correlated with any of the other measures (all ps > .05). STW was positively correlated with A (r = .314, p < .001) and negatively correlated with N (r = -.106, p < .01). O was positively correlated with C (r = .259, p < .001) and E (r = .103, p < .01), while it was not significantly correlated with A or N (both ps > .05). C was not significantly correlated with any of the other measures, except for O (r = .259, p < .001). E was positively correlated with C (r = .201, p < .001) and A (r = .314, p < .001), while it was negatively correlated with STW (r = -.072, p < .05). Finally, A was positively correlated with C (r = .419, p < .001) and negatively correlated with STW (r = -.088, p < .05). In conclusion, the findings point to a significant positive correlation between SWLS, APM and STW, O and C, E and A, and N and E.
With the above report, Summarise and discuss
what you have found, and how the findings relate to your research questions,
and to the previously published research outlined in the Introduction (take care
not to simply restate all your findingsyou need to go beyond this in the
discussion).
Interpret how your results add to previous research. For example, does the
results contradict or support previous research? Are there any possible
theoretical or applied implications?
Identify the limitations and strengths of your study. Can you make suggestions
for the improvement of future studies?
Consider future directions for new research on this topic (e.g., what might be
some next logical step that could be explored in future research)? use recent peer reviewed journal articles for references.
