Report on Self-efficacy and Gender
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Added on 2020-04-13
Report on Self-efficacy and Gender
Added on 2020-04-13
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DiscussionSelf-efficacy and gender were used as independent variables in a two-way fixed ANOVA modelin this study using 114 participants. The assumption of the model was tested and the dependentvariable (Mental Wellbeing) met the criteria. Based on the Shapiro test of Normality for MentalWellbeing variable conducted by gender, the p-value for the male participants was 0.044 and thatof females was 0.133. Generally, the test assumes that the data is normally distributed, hencedetermining that female data on Mental Wellbeing is assumed to be normally distributed at 95%confidence interval because the p-value is greater than the significance level (0.05). according tothe frequency distribution of the gender for the participants of the study, 74.6% were female andthe rest (25.4%) were male participants. Based on this distribution we can note that thedistribution of the female in the study can significantly affect that of males, hence normalizingthe whole set of data in the Mental Wellbeing variable. According to the plotted boxplot of thedependent variable, we can observe that it depicts that it was approximately normal. However,there some cases of outliers with some participants having a Mental Wellness score of below 30.These values might have significantly affected the distribution of the data, hence showing normaldistribution. According to Doornbos, (2002) mental health is determined by reality, which is considered asone of most factors influencing well-being on an individual. Therefore, as a person grows, muchis realized, hence affecting the mental state which causes the variation in people based on theirmental wellness. The distribution of the mental wellbeing of the study participants might havebeen highly influenced by the age distribution. The frequency distribution of the participantsshows that 80% were between the ages of 18 – 40 years of age. In addition, we consider the ages
between 18 and 60 years as less vulnerable to stress and mental state changes due to reality.Therefore, the moderate values of mental wellbeing were because the participants were not asvulnerable as those who were below 18 and above 60 years of age. Otherwise, including thevulnerable age groups could have inflated the mental wellbeing score, increasing the variation. Previous studies have established relationships between self-efficacy and mental wellbeing, andthis has been the basis for using the self-efficacy factor in testing whether it can significantlypredict an individual’s mental state. In addition, gender has been referred to as a highly probableconfounder in various studies. This is because in most cases, the distributions between the twogroups are never equal. Also, the groups are termed as independent and any reaction or responsein one group might not necessarily be the same. Therefore, the variable ‘gender’ was included inthe study and be used as an independent variable for the prediction of mental wellbeing score.Having the two categorical variables in a model, a two-way fixed ANOVA was conducted todetermine whether the interaction effect between the two main effects was significant. This testinvolved the 144 participants of the study aiming to provide evidence on the relationshipbetween self-efficacy and mental wellbeing.As indicated in the literature review section, several studies have proved significant relationshipsbetween self-efficacy and mental wellbeing. Also, the self-efficacy levels have also been provedsignificantly different among males and females. However, not many studies that haveresearched on the interaction between gender and self-efficacy on the prediction of mentalwellness. According to the analysis, the interaction between gender and self-efficacy wasstatistically insignificant at 95% confidence level, reporting a p-value of 0.552. Therefore, basedon the evidence provided by the study, we cannot conclude that the interaction between self-efficacy is not significant in predicting mental wellbeing of a person. Since the interaction is not
statistically significant, the model is readjusted and the interaction effect dropped from theanalysis. Based on the two-way ANOVA analysis output, the corrected model is statisticallysignificant (p-value < 0.001) at 95% confidence level. The model involving self-efficacy andgender as the main effects can be used in predicting individuals’ wellbeingThe main aim of a two-way fixed ANOVA analysis is to determine whether the interaction isstatistically significant. According to the analysis of the sample data, the results have shown thatthere is no significant interaction. In other words, the gender and self-efficacy group a person isdoes not determine their level of mental wellbeing. This shows that the main factors are highlyindependent and the distribution of the interaction effect is not predictable. Gender main effect inthe ANOVA output was not significant and this might affect the significance of the interaction.Although according to a study conducted in Kurukshetra University on the impact of emotionalintelligence and self-efficacy on the mental help shown a significant difference between malesand females and their ratios in the study was 1:1. The study showed that the male students werebetter compared to the female counterparts. However, our study had mode female participantsthan males and that might have been the reason for not detecting a significant difference betweenthe two gender categories. Also, according to the average values of the mental wellbeing had shown superiority on males incomparison to the females. In contrast, the frequency of females with a high level of self-efficacywere higher and this might have inflated by the disproportional sample size between gendercategories. Probably, the results would have been more representative of the society if theparticipation ratio would have followed the trend of previous studies. In this study, gender is no asignificant main effect at 95% confidence level. Despite the fact that gender is not a significantmain effect, it will still be included in the model and interpreted accordingly.
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