Does personality moderate the influence of depression on quality of life outcome, once the influence of the symptom severity, demographic, psychosocial and health

variables is accounted for?

Model B explored the prediction of subjective quality of life not only by severity of depressive symptoms, but also by demographics, psychosocial, physical illness together with personality factors. It revealed that 67% of the quality of life variance was explained by the depressive mood only, as observer-rated by the study clinical psychologists on the Hamilton Rating Scale for Depression, and confirmed the predominant impact of current symptom

severity on quality of life measures. Nevertheless, demographic, psychosocial and health variables explained an additional 7%, and personality factors explained yet another 5% of variance. Present results confirm the initial hypothesis. Landau and Litwin (2001) suggested that different factors predict different facets of well-being in later life, and that individual psychosocial features, such as personality, mediate the relationship between health and well-being. According to this conception, the present study hypothesized that personality would influence the impact of depression on quality of life, once prediction by symptom severity and known risk and protective factors, such as physical burden, age and social support, had been accounted for (Chan et al., 2006; Nauman & Byrne, 2004). The integrative approach allowed for highlighting the contribution of individual differences on depressed patients’ subjective perception well-being, besides and above the main influence of their depressive mood state. Statistically, 5% personality-explained variance seems of minor importance in comparison to the 67% depression-explained variance. However, clinical implications are of large amplitude in daily psychiatric treatment routine. Indeed, individual differences related to patients’ personality traits have been repeatedly shown to be relevant to depression treatment response and outcome (Cohen et al., 2004; De Fruyt et al., 2006; Morris et al., 2009; Quilty et al., 2008; Bock et al., 2010) and more precisely related to patients’ utilization of mental health services, their satisfaction with treatment, and their autonomous and responsible implication (Böckerman et al., 2011; Hunt & McKenna, 1992).

From a clinical point of view, this additional influence of individual personality traits may offer one possible empirical explanation why the same depressive disorder is not associated with the same decreased subjective well-being for each patient. Replication of the present result in a larger sample could claim the need for treatment approaches that take into account individual personality differences. Results thus seem to speak in favour of a pathoplastic approach. While only Neuroticism influenced depression, all personality dimensions except Agreeableness influenced patients’ associated subjective quality of life. Rather than showing a causal influence on depressive symptoms, personality rather seems to act as a moderator of the depression-quality of life relationship, and patients’ expression and experience of their symptoms.

Contrary to previous studies in the domain, no significant relationship emerged between quality of life and level of education, marital status, perceived social support or level of dependency. Although adding age, education, marital status, social support, dependency, and physical illness in the regression model increased the amount of explained variance by 5%, only gender emerged as an significant negative predictor of quality of life in addition to depressive mood. In previous studies, higher socioeconomic status had been related to subjective well-being, such as assessed by educational attainment (Ryff & Singer, 2008;

Ryff et al., 2008). Opportunities for self-realization need allocation of resources that allow individuals for making the most out of their talents, capacities and potentials. Level of dependency and autonomy is a complex psychological phenomenon. Mette (2005) showed that in elderly adults, functional dependency and need for home care have been related to lower well-being. Indeed, subjective health perception is strongly and positively correlated with satisfaction with the main activity. Staying home may lead to isolation, and the maintenance of a social activity and social encounters has been shown to be important for well-being and avoiding depression (Mette, 2005). As for depression, these divergences in results may be explained by the fact that the strong correlates between level of education or social relations and well-being described in other studies (Marmot et al., 1998) emerged without the simultaneous inclusion of other psychological background variables. Indeed, Landau and Litwin (2001) claimed that psychosocial resources and perceived health mediate the relationship between these variables and well-being in later life.

Further, physical illness had no impact on quality of life, contrary to depression. Indeed, studies addressing the relationship between objective health impairment and subjective well-being have found a weakening of their correlation in aging. Well-well-being tends to decline slowly, while physical health tends to decline more steeply with age (Jopp & Rott, 2006;

Kunzmann et al., 2000). This paradox is explained in the literature by the observation that older people call into play certain mechanisms which enable them to adapt to declining health, thus helping to preserve their well-being (Brandtstädter & Greve, 1994; Holahan et al., 2001; Idler, 1993; Kunzmann et al., 2000; Rothermund & Brandtstädter, 2003).

In the present study, female gender significantly predicted well-being, once depressive symptoms had been accounted for. Previously, female gender has shown indirect effects on well-being through social support (Lu et al., 1997). According to these authors, women derive happiness from harmonious interpersonal relationships with friends and family members, while men seem to derive greater satisfaction form career success. Interestingly, this variable emerged as a protective influence on the depression-quality of life relationship, rather than emerging as a direct risk factor for depression symptoms.

Interestingly, even though the association between personality and well-being holds in the presence of a depressive state, the individual influences of each of the five factors seem to differ from the general population. Concerning individual predictors in model B, Neuroticism showed a significant negative association with quality of life and emerged as an independent negative predictor of quality of life after adjustment for depressive symptoms. Plus, it interacted precisely with these symptoms to lower their impact on quality of life. Thus,

personality assessment did not merely reflect the individuals’ mood state, and indeed measured state affect as well as trait variances, as has been previously stated (Clark et al., 2003). Lower levels of Neuroticism or emotional stability have been shown to be an even stronger correlate and account for a higher percentage of variance in well-being than Extraversion (Libran, 2006). Libran (2006) suggested that the concept of subjective well-being is more closely related to emotional stability than to the traits of Extraversion.

Most unexpectedly, Extraversion showed no significant association with quality of life contrary to non-clinical young and old age samples (De Neve & Cooper, 1998; Steel et al., 2008; Ryff, 2008). This result contrasts with previous evidence in younger and older depressed patients (Masthoff et al., 2007; Duberstein et al., 2003). Indeed, using the same assessment tools as in the present study, Masthoff et al. (2007) had shown a negative relationship between quality of life and Neuroticism as well as a positive relationship with Extraversion and Conscientiousness, in the absence of associations with Openness to experience and Agreeableness. However, their sample did not focus specifically on mood disorders, but included a large variety of psychiatric diseases, such as substance related disorders, anxiety disorders or adjustment disorders. Personality dimensions explained 26%

to 50% of their quality of life variance, however without adjustment for the impact of depressive symptoms. Present data are in line with Cheng and Funham (2003) and Lu and Shih (1997), who described that Extraversion has a strong and direct influence on well-being, while Neuroticism is mediated by depressive symptoms, and shows both a direct negative effect on well-being as well as an indirect impact through its inflating of negative mood. Introversion may be related to lower well-being without being related to depression.

Depression and well-being are mirror and opposite phenomena, however personality is related differently to both outcomes. Explanatory models of well-being described in the general population do not seem to apply in populations including patients with major depression as in the current sample. As described by Masthoff et al. (2007), evidence on the relationship personality and quality of life relationship emerged from research using samples of healthy persons, which makes the interpretation of their data for clinical use in psychiatric patients rather difficult. Moreover, quality of life has been measured mostly in terms of happiness and well-being, and not in a comprehensive and multi-dimensional way such as the WHO quality of life concept. This result clearly warrants further studies in depressed patients to replicate results from the present exploratory study in a larger sample.

In the absence of a positive association with Extraversion, higher levels of Openness and Conscientiousness were related to higher levels of quality of life, after depressive symptoms had been accounted for and in the absence of a significant age effect. Individuals with higher

Openness to experience are more likely to consider changes in their work or family situations and experience actual occurrence of life change in the 12 following months (Whitbourne, 1987). By choosing a life with opportunities for growth and change, they are more likely to achieve personal development, engage in activities that maintain physical and mental health, and thereby maintain higher levels of functioning and subjective well-being. In his article on the psychotherapeutic utility of the Five-Factor Theory of personality, Miller (1991) described how high Openness characterizes patients that are capable of understanding and following psychotherapeutics treatment interventions. Patients with high Neuroticism associated with high Openness “seem to look healthier to most therapists than high Neuroticism, low Openness patients” (p.425). Thus, even though individuals with high Neuroticism tend to experience higher levels of emotional distress, when associated with higher openness to variety, novelty and curiosities, these patients are more willing to try new ways of thinking and relating to others. They may more easily perceive the need for mental health care (Seekles et al., 2012). They may be able to keep a higher level of well-being compared to lower level Openness individuals. These authors suggested a possible positive relationship between high Openness and successful clinical outcome. In a study on old age depressed outpatients in Geneva, this factor was indeed significantly related with successful termination of group psychotherapy, contrary to Neuroticism (Canuto et al., 2008). These patients may be able to invest future treatments and activities after their depressive episode treatment.

With regard to Conscientiousness, this dimension characterizes enduring and pervasive individual differences in organization, persistence, dutifulness and self-discipline (Costa &

McCrae, 1992). Patients with high levels of Conscientiousness are more likely to make an effort, to tolerate discomfort and to delay gratification (Miller, 1991). They might prefer solving their own problems rather than seeking for treatment. However, if they engage in treatment, they might have a higher potential for well-being to start with. Therefore, this factor has also been associated with successful psychotherapy outcome (Miller, 1991).

Miller states that when interacting with Neuroticism respectively Conscientiousness, the impact of depression on quality of life is lowered. “Psychotherapy might be understood as a process of helping unhappy people develop the hope, courage, and determination needed to go on loving and working, even though it often does not feel good to do so” (Miller, 1991, p.424). McCrae and Costa (1991) explained that Conscientiousness promotes well-being through supporting relationships, self-efficiency and sense of discipline. Indeed, besides its direct effect, - as for Neuroticism - Conscientiousness interacted with depression to enhance subjective quality of life. These results clearly illustrate the interest of considering personality dimensions not merely as isolated factors, but as interactions with depression to predict

well-being. While Neuroticism directly reduced, and Openness and Conscientiousness directly enhanced quality of life independently of individuals’ depressive mood state and age, Neuroticism and Conscientiousness additionally acted as moderators on the influence of depression.

In summary, in depressed patients, not only the level of depressive symptoms but also the levels of Neuroticism, Openness, and Conscientiousness predicted their subjective quality of life. These results reflect that those patients who described higher levels of quality of life, reported personality traits characterized by less proneness to psychological distress, more active seeking and appreciation for new experiences, and a stronger degree of organization, persistence, control and goal directed behaviours. Contrary to depression, the prediction of quality of life gained from including four of the five personality factors as well as their interactions with depression, rather than focusing on Neuroticism only. Again, the perspective of the integrative approach revealed to be promising and allowed for showing that personality factors enhance quality of life beyond and above socio-demographic characteristics such as age and education, psychosocial features such as marital status, social support or home care, as well as comorbid somatic illnesses.

Objective III. Do predictors differ between young and old age depression and quality