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Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.
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Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung.

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  • 1. 1 Abstract The aim of the present study was to analyze the influence of gender differences, and the number of life events on the levels of trait and state anxiety. The sample comprised 148 male (M= 22.12 years, SD= 2.68 years) and 185 female (M= 22.08 years, SD= 2.64 years) students. Anxiety was determined using the State-Trait Anxiety Inventory (STAI), and Life Events were measured using the 1994 revision of the Social Readjustment Rating Scale (SRRS). Two hypotheses were tested. The first hypothesis was supported that the level of trait and state anxiety increases with the number of life events. The second hypothesis was also supported that women generally rate higher than men in trait anxiety. It was concluded that anxiety cannot be solely determined by the number of experienced major life events, as many social and psychological confounding factors must be considered.
  • 2. 2 Assessing the Influence of Life Events and Gender differences on Anxiety. Janice Fung Anxiety is the pain in reaction to the threat of losing an object (Freud, cited in Finlay-Jones and Brown, 1981). It can be a normal response to an environmental demand for major transition (state anxiety), or it can be a permanent characteristic in the way one‟s personality respond‟s to the world (trait anxiety). Stressful life events may significantly induce anxiety disorders that last longer than transient duration (Blazer, Hughes, and George, 1987). It is necessary to note that the significant associations between major events and psychological symptoms as proposed by previous studies were often weak correlations. For this reason, it has been suggested that major life events may play a minor role to the variance of the prediction of psychological symptoms (Barrett and Heubeck 2000; Johnson and Sarason 1977). In response to this predicament, researchers have considered other variables that may mediate the impact of life change. Several moderating factors that would affect one‟s predisposition to anxiety include personality characteristics (Garnefski, Kraaij, and Spinhoven, 2001); early life experiences (Jackson and Finney, 2002); the availability of social support (Aseltine, Gore, and Gordon, 2000); socioeconomic status (Camasso and Camasso, 1986); physiological and psychological health status (Addolorato, Mirijellow, Angelo, Leggio, Ferrulli, Abenavoli, Vonghia, Cardone, Leso, Cossari, Capristo, and Gasbarrini., 2008); maturity level (Jackson and Finney, 2002) and gender differences (Conger, Lorenz, Elder, Simons, and Ge, 1993).
  • 3. 3 Researchers have suggested that focus should be made on daily life events, rather than major life events (Barrett and Heubeck, 2000). In support of this theory, hassles are more strongly correlated with psychological symptoms, such as anxiety, than are major life events (Wagner, Compas, and Howell, 1988). Hassles are frustrating and distressing experiences that come to characterize the everyday dealings with the environment (Kanner, Coyne, Schaefer, and Lazarus, 1981) (E.g. workplace bullying and financial difficulties). Hassles have been argued to affect trait anxiety (Wagner et al., 1988), as they are a consistent source of stress that requires continued adaptive efforts to cope. Furthermore, studies have found that the frequency of hassles experienced are more influential than major life in events on developing psychological symptoms among older adolescents (Rowlison and Felner 1988; Wagner et al. 1988) and adults (Kanner et al., 1981), with a positive association. These studies have measured psychological symptoms in terms of self-image, mood, and well-being; however, studies on the specific relationship between anxiety and life events have not been extensive (Barrett and Heubeck, 2000). To gain a comprehensive overview of daily experience, uplifts may also be investigated (Barrett and Heubeck, 2000). Uplifts are positive and pleasurable experiences during the daily course. (E.g. building positive relationships, or receiving a compliment (Lazarus, 1984). Previous studies have shown that uplifts increase positive affect (Kanner et al., 1981). People with more mastery and self-efficacy have been found to experience lower levels of anxiety during stressful events (Aseltine et al., 2000). This suggestion is supportive of the proposed stress-buffering effects of uplifts, as the generation of positive affect improves coping ability by promoting behaviors of personal action and problem solving. However, several studies of hassles and uplifts have provided
  • 4. 4 inconsistent results with a combination of proposed positive and negative relationships (Barrett and Heubeck, 2000). It has been strongly suggested that stressful events and social resources are distributed unequally across the different socioeconomic levels. Moreover, individuals of disadvantaged social classes have relatively less access to social support (Thoits, 1982), and higher exposure to hassles (Wagner et al. 1988; Conger et al. 1993) and major adversities (Camasso and Camasso, 1986). Discrete and chronic events of hardship (such as a life-threatening situation, unemployment, marital issues, and financial difficulties) influence the predicament of the onset and intensity of a variety of physical and psychological maladies (Barrett and Heubeck, 2000). Aseltine et al. (2000) suggested that such negative life events are source of high levels of stress that are strongly associated to higher levels of anxiety. Hence, lower socioeconomic status has been found to relate to higher incidences of psychological impairment. This is an enduring finding in community mental health research (Camasso and Camasso, 1986). Having access to social support has been shown to be critical for psychological well-being. Simply having an approachable and understanding relationship with another individual (for example, friendship and family cohesiveness) or feeling belongingness to a group (for example, a church or a club) can lead to reduced levels of anxiety, depression, and physical complains (Camasso and Camasso, 1986). Studies have shown that helpful resources are set in motion to serve individuals of middle and upper socioeconomic classes amidst major life events (Turner, 1981). In contrast, the incidence of stressors in disadvantaged societies brings about extremely high levels of stress and
  • 5. 5 strain, as their already small support networks are overwhelmed. Thus, the risk of anxiety is increased (Turner 1981; Conger et al. 1993). Furthermore, social scientists have consistently found gender differences in experiencing stress (Bird and Fremont, 1991). Researchers have argued that men and women are dissimilar in their reactivity of distress because of gender-oriented patterns of socialization, self-conceptions, and responsibilities (Kessler and McLeod 1984; Gove 1984). For example, women typically bear more household and childcare duties than men, regardless of their employment status (Ross, Mirowsky, and Huber, 1983). These patterns influence the exposure and response to different types of stressful life events. Kessler and McLeod (1984) found that women are more vulnerable than men to experience negative life events in their social network as women tend to be more emotionally involved with the lives of their peers. Women are also more negatively influenced by health difficulties, relationship problems, and uncontrollable life events. In comparison, men have been found to have greater exposure to health and financial difficulties, and are more negatively influenced by income loss and controllable life events (Conger et al., 1993). Women have been found to be at a greater risk to develop symptoms of trait and state anxiety (Pearlin 1989; Finlay-Jones and Brown 1981; Addolorato et al. 2008). Although women tend to indicate a higher frequency of negative life events than men, they may be less likely to report them despite their greater level of distress (Conger et al., 1993). However, there is growing evidence to suggest that men display different symptoms of distress that are channeled into behaviours of overt aggression, substance abuse, or behavioural misconduct (Lennon 1987; Pearlin 1989).
  • 6. 6 Thus this finding is incongruous to the theory that women have a greater vulnerability to develop anxiety. The aim of the present study was to analyze the relationship between trait and state anxiety and the number of life events, and to investigate the differences between men and women in trait anxiety. The first hypothesis stated that the level of trait and state anxiety increases with the number of life events. The second hypothesis stated that women generally rate higher than men in trait anxiety. Method Participants The sample comprised 333 undergraduate psychology students across all Monash University campuses that completed the study as part of a course requirement. There were 148 males (M= 22.12 years, SD= 2.68 years) and 185 females (M= 22.08 years, SD= 2.64 years). Materials Anxiety was determined using the State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) which was comprised of two parts- Form Y-1 (State) and Form Y-2 (Trait). The inventory is a 40-item measure, of which 20 items of Form Y-1 measure transitory forms of anxiety within an individual (State Anxiety). The items of Form Y-1 measure feelings of apprehension, tension, nervousness, and worry about the current situation (A-State). Participants rate the degree to which each item indicates his or her present feelings on a four-point Likert scale, where the scores range from “Not At All
  • 7. 7 (1)” to “Very Much So (4)”. Higher scores indicate higher levels of anxiety. The other 20 items measure of Form Y-2 measure more stable forms of anxiety within an individual (Trait Anxiety). Respondants rate the how they feel in generally, using a four-point Likert scale, ranger from “Almost Never (1)” to “Almost Always (4)”. Life Events were measured using the 1994 revision of the Social Readjustment Rating Scale (SRRS; Holmes & Rahe, 1967). This measure consisted of 53-items that describe different life events. The events were those of which were correlates of outcomes of particular life events, or they were events which would lead one to adapt to the changed circumstances. Each of the 43 items was ranked in order of the impact they make upon one‟s life. The 43 items were divided into two different forms: (1) Controllable, or (2) Uncontrollable life events. Each of the 43 items corresponds to a weighted ranking according to its magnitude of impact. Procedure Class participants across all campuses of the university were to submit a consent form before they completed the STAI and the SRRS. Scores were individually calculated, and all collated data was computerized, and outliers were transformed before conducting further statistical data analyses. Results Positive univariate outliers were detected in the collated data of age (ie. Older students) and the number of life events (NLE). These extreme scores were lowered.
  • 8. 8 Furthermore, two positive univariate outliers were found in the LEcontrolled data and were winsorised. No ouliers were detected in the LE-Uncontrolled data. The relationship between anxiety (as measured by the STAI) and life events (as measured by the SRRS) was investigated using Pearson product-moment correlation. Preliminary analyses were conducted to ensure there was no violation of the assumptions of normality, linearity, and homoscedasticity. There was a weak, positive correlation between trait anxiety and the number of life events [r=.14, n=333, p<.01]; and a weak, positive correlation between state anxiety and the number of life events [r=.15, n=333, p<.01], with increasing number of life events associated with increases in trait/state anxiety. Table 1: Correlation between Anxiety (State and Trait) and the Number of Life Events. Correlation with life events (r) N Significance State anxiety 0.15 333 0.005 Trait anxiety 0.14 333 0.009 Notes: Correlation is significant at the 0.01 level (2-tailed). An independent-samples t-test was conducted to compare the trait anxiety levels for males and females. There was a significant difference in scores for males (M= 38.53 ,
  • 9. 9 SD= 9.36) and females [M= 41.42 , SD= 9.72 ; t(331)= -2.74, p= 0.007]. The magnitude of the differences in the means was very small (eta squared= 0.02). Table 2: Means and Standard Deviations of Trait Anxiety in Males and Females. Mean Standard Deviation Males 38.53 9.36 Females 41.42 9.72 Notes: The unit of measurement is the „life events units‟ scores from the SRRS. Discussion In this study, some causal linkages have been addressed by the analysis of life events and gender relating to trait and state anxiety levels. The results of the current study parallel most of the previous research by supporting the hypotheses that (1) the level of trait and state anxiety increases with the number of life events, and (2) that women generally rate higher than men in trait anxiety. The findings of the current study indicate that approximately 1.96% (r= 0.14) of the respondents‟ scores of trait anxiety and 2.25% (r= 0.15) of state anxiety are explained by the experienced number of life events. This is consistent with results obtained by previous researchers, that major life events are significantly but weakly associated to anxiety (Barrett and Heubeck 2000; Johnson and Sarason 1977). Therefore, as suggested by Johnson and Sarason (1977), further analyses need to be made on the validity of the
  • 10. 10 life stress measures, and also on other factors that may affect the relationship between life events and anxiety. Thoits (1982) offers some insight into the factors of social status on anxiety, proposing that disadvantaged individuals have greater exposure to hassles, and less access to social support, thus increasing anxiety levels. Turner (1981) proposes that disadvantaged societies have smaller support networks. Hence it can be reasoned that this would lead to an increased impact of daily hassles (Barrett and Heubeck, 2000). With increased experiences of hassles, experiences of negative affect may be increased. Positive affect has been found to improve coping ability by encouraging characteristics of mastery and self-efficacy (Aseltine et al. 2000; Barrett and Heubeck 2000), therefore it can be predicted that increased negative affect may consequently decrease stress coping abilities, thus increasing trait anxiety levels. The results of the current study suggest that women significantly rate higher than men in trait anxiety levels, where 2% (eta squared= 0.02) of the scores of trait anxiety are explained by gender differences. This finding is congruous with the theory that women are more susceptible than men to higher levels of trait anxiety (Pearlin 1989; Finlay-Jones and Brown 1981; Addolorato et al. 2008). However, the scale disregards several confounding variables of gender differences which may have affected the validity of the results. It needs to be considered that men and women are different in their exposure and response to different types of life events (Ross et al., 1983). The items of the SRRS do not consider this gender difference in its weighting of distress for each item. Furthermore, previous research has suggested that men and women display distress with different symptoms (Lennon 1987; Pearlin 1989); and that women tend to be reluctant in reporting anxiety symptoms, despite experiencing high levels of distress (Conger et al., 1993). It is
  • 11. 11 suggested that the STAI be revised to account for these gender differences, perhaps by developing segregate inventories for men and women. The results of this study also fail to reflect the influences of daily hassles, socioeconomic status, personality characteristics, gender characteristics, and the availability of social support and sources of uplifts; hence the external validity of the results is low. Several limitations have been found regarding the adequacy of the two measures (STAI and SRRS) to account for many confounding factors. First of all, the STAI scale consists of measures that can be indicative of several psychological disorders, such as depression. Therefore, it is suggested for future research that the items of the scale be revised to be more discriminatory towards anxiety among other diagnostic groups. Secondly, the SRRS measure is biased in the weighting of stress levels of each event. It does not consider the confounding individual differences, such as social status, cultural values, personality, gender, or personal history. For example, the life event of „major purchase (>$10,000)‟ may vary in its weighting of distress, depending on the individual‟s financial circumstances. Finally, the SRRS does not consider the differential sampling of participants with each application of the scale, thus undermining the generalisability of the scale in its developmental research. By exploring the many variables that influence the development of anxiety, this study has implications in helping the wider community gain awareness of the various social factors that accumulate to the development of anxiety. Thus communal attention can be augmented towards the more vulnerable groups. In addition, this study may increase awareness in the gender differences of the development of anxiety, thus increasing responsiveness from psychological first-aid. In conclusion, this study has
  • 12. 12 revealed that trait and state anxiety levels cannot be solely determined by the number of experienced major life events. In research, many confounding factors must be considered with the methods of measurement as they affect one‟s predisposition to anxiety when coping with stress.
  • 13. 13 References Addolorato, G. et al. (2008). State and trait anxiety and depression in patience affected by gastrointestinal disease: Psychometric evaluation of 1641 patience referred to an inernal medicine outpatient setting. Journal of Clinical Practice, 62(7), 1063- 1069. Aseltine, R. H. et al. (2000). Life stress, anger and anxiety, and delinquency: An empirical test of general strain theory. Journal of Health and Social Behavior, 41(3), 256-275. Barrett, S. and Heubeck, B. G. (2000). Relationships between school hassles and uplifts and anxiety and conduct problems in grades 3 and 4. Journal of Applied Developmental Psychology, 21(5), 537-554. Bieling, P. J. et al. (1998). The state-trait anxiety inventory, trait version: Structure and content re-examined. Behaviour Research and Therapy, 36, 777-788. Bird, C. E. and Fremont, A. M. (1991). Gender, time use, and health. Journal of Health and Social Behavior, 32(2), 114-129. Blazer, D. et al. (1987). Stressful life events and the onset of a generalized anxiety syndrome. American Journal of Psychiatry, 144(9), 1178-1183. Camasso, M. J. and Camasso, A. E. (1986). Social supports, undesirable life events, and psychological distress in a disadvantaged population. The Social Service Review, 60(3), 378-394.
  • 14. 14 Conger, R. D. et al. (1993). Husband and wife differences in response to undesirable life events. Journal of Health and Social Behavior, 34(1), 71-88. Finlay-Jones, R. and Brown, G. W. (1981). Types of stressful life event and the onset of anxiety and depressive disorders. Psychological Medicine, 11,803-815. Garnefski, N. et al. (2001). Negative life events, cognitive emotion regulation and emotional problems. Personality and Individual Differences, 30, 1311-1327. Gove, W. (1984). Gender differences in mental and physical illness: The effects of fixed roles and nurturant roles. Social Science and Medicine, 19, 77-91. Jackson, P. B. and Finney, M. (2002). Negative life events and psychological distress among young adults. Social Psychology Quarterly, 65(2), 186-201. Kanner, A. D. et al. (1981). Comparison of two modes of stress measurement: Daily hassles and uplifts verses major life events. Journal of Behaviour Medicine, 4, 1- 39. Kessler, R. C. and McLeod, J. D. (1984). Sex differences in vulnerability to undesirable life events. American Sociological Review, 49, 620-631. Lazarus, R. S. (1984). Puzzles in the study of daily hassles. Journal of Behavioural Medicine, 7, 375-389. Lennon, M. C. (1987). Sex differences in distress: The impact of gender and work roles, Journal of Health and Social Behavior, 28, 290-305.
  • 15. 15 Pearlin, L. I. (1989). The sociological study of stress. Journal of Health and Social Behavior, 30, 241-256. Ross, C., Mirowsky, J., and Huber, J. (1983). Dividing work, sharing work, and in- between: Marriage patterns and depression. Journal of Health and Social Behavior, 25, 189-197. Rowlinson, R. T. and Felner, R. D. (1988). Major life events, hassles, and adaptation in adolescence: Confounding in the conceptualization and measurement of life stress and adjustment revisited. Journal of Personality and Social Psychology, 55, 432- 444. Thoits, P. A. (1982). Life stress, social support and psychological vulnerability: Epidemiological considerations. Journal of Community Psychology, 10, 341-362. Turner, R. J. (1981). Social support as a contingency in psychological well-being. Journal of Health and Social Behavior, 22, 357-367. Wagner, B. M. et al. (1988). Daily and major life events: A test of an integrative model of psychosocial stress. American Journal of Community Psychology, 16, 189-205.
  • 16. 16 Appendices Appendix 1: Check for assumption of normal distribution. Descriptive Statistics N Minimum Maximum Mean Std. Deviation Skewness Statistic Statistic Statistic Statistic Statistic Statistic Std. Error age 333 19 44 22.09 2.649 2.676 .134 nr LE 333 0 20 5.77 3.280 .621 .134 state anxiety 333 20 67 37.66 9.480 .495 .134 trait anxiety 333 20 70 40.14 9.651 .319 .134 Valid N (listwise) 333 Descriptive Statistics Kurtosis Statistic Std. Error age 14.515 .266 nr LE .458 .266 state anxiety -.018 .266 trait anxiety -.172 .266 Gender Case Processing Summary gender Cases Valid Missing Total N Percent N Percent N Percent trait anxiety male 148 100.0% 0 .0% 148 100.0% female 185 100.0% 0 .0% 185 100.0%
  • 17. 17 Descriptives gender Statistic Std. Error trait anxiety male Mean 38.53 .769 95% Confidence Interval for Mean Lower Bound 37.01 Upper Bound 40.05 5% Trimmed Mean 38.31 Median 38.00 Variance 87.516 Std. Deviation 9.355 Minimum 20 Maximum 66 Range 46 Interquartile Range 14 Skewness .377 .199 Kurtosis .040 .396 female Mean 41.42 .714 95% Confidence Interval for Mean Lower Bound 40.01 Upper Bound 42.83 5% Trimmed Mean 41.20 Median 41.00 Variance 94.429 Std. Deviation 9.717 Minimum 20 Maximum 70 Range 50 Interquartile Range 14 Skewness .269 .179 Kurtosis -.274 .355
  • 18. 18 Extreme Values gender Case Number Value trait anxiety male Highest 1 250 66 2 68 62 3 86 61 4 45 59 5 210 59 Lowest 1 70 20 2 42 20 3 41 20 4 40 20 5 292 21 female Highest 1 324 70 2 314 65 3 112 63 4 311 63 5 134 62 a Lowest 1 295 20 2 145 23 3 104 23 4 139 24 5 137 24 a. Only a partial list of cases with the value 62 are shown in the table of upper extremes.
  • 19. 19 Trait anxiety:
  • 20. 20
  • 21. 21 Appendix 2: The correlation between trait anxiety (TA), state anxiety (SA), and the number of life events (NLE).
  • 22. 22 Correlations nr LE trait anxiety state anxiety nr LE Pearson Correlation 1 .143 ** .153 ** Sig. (2-tailed) .009 .005 N 333 333 333 trait anxiety Pearson Correlation .143 ** 1 .710 ** Sig. (2-tailed) .009 .000 N 333 333 333 state anxiety Pearson Correlation .153 ** .710 ** 1 Sig. (2-tailed) .005 .000 N 333 333 333 **. Correlation is significant at the 0.01 level (2-tailed). Appendix 3: The comparison of males and females in trait anxiety (TA) levels. Group Statistics gender N Mean Std. Deviation Std. Error Mean trait anxiety male 148 38.53 9.355 .769 female 185 41.42 9.717 .714 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df trait anxiety Equal variances assumed .313 .576 -2.735 331 Equal variances not assumed -2.746 319.888
  • 23. 23 Independent Samples Test t-test for Equality of Means Sig. (2-tailed) Mean Difference Std. Error Difference trait anxiety Equal variances assumed .007 -2.882 1.054 Equal variances not assumed .006 -2.882 1.050 Independent Samples Test t-test for Equality of Means 95% Confidence Interval of the Difference Lower Upper trait anxiety Equal variances assumed -4.956 -.809 Equal variances not assumed -4.948 -.817

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