Affect intensity and negative mood regulation (NMR) expectancies: A preliminary Indian study

Asian Journal of Psychiatry 5 (2012) 137–143

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Affect intensity and negative mood regulation (NMR) expectancies: A preliminary Indian study Seema Mehrotra a,*, Ravikesh Tripathi b a b

Additional Professor, Dept of Clinical Psychology, NIMHANS, Bangalore 29, India Clinical Psychologist, NIMHANS, Bangalore 29, India

A R T I C L E I N F O

A B S T R A C T

Article history: Received 31 May 2011 Received in revised form 10 March 2012 Accepted 2 April 2012

Individuals differ in the intensity with which they typically experience affect as well as in their beliefs regarding their ability to alleviate negative mood states. These variables have been implicated in a range of clinical problems. Most studies utilize a single index of affect intensity. The differential correlates of positive and negative affect intensity, their association with negative mood regulation expectancy and their role as predictors of psychological outcomes have been insufficiently explored. This study aimed at exploring the relationship of affect intensity variables with negative mood regulation (NMR) expectancy, their association with age and gender and examining the role of affect intensity and NMR expectancy as predictors of stress and well being in a community sample of Indian adults. The sample consisted of 206 participants aged between 20 and 60 years. Higher age was associated with higher NMR expectancy but lower positive affect intensity. Positive and negative affect intensity showed differential patterns of association with NMR expectancy. Higher negative affect intensity was associated with lower NMR expectancy whereas higher positive affect intensity was associated with higher NMR expectancy. Affect intensity and NMR expectancy variables jointly predicted 30–39% of variance in perceived stress and well being. Implications for further research are discussed. ß 2012 Elsevier B.V. All rights reserved.

Keywords: Affect intensity Negative mood regulation expectancy Emotional regulation Well being Stress

1. Introduction In theoretical as well as empirical literature, emotional regulation processes are recognized as playing an important role in health and well being (Gross, 2002). Numerous variables conceptually linked with emotional regulation have been examined across studies. The present study focuses on two such variables namely, affect intensity and negative mood regulation expectancies. Affect intensity has been described as ‘‘. . .stable individual differences in the strength with which individuals experience their emotions’’ (Larsen and Diener, 1987). It was originally described as a uni-dimensional construct, cutting across the experience of both positive and negative emotions. It was proposed that some individuals tend to typically experience both positive as well as negative emotions with much more intensity than others and would hence tend to display high affect intensity across a range of emotion-arousing situations. Larsen et al. (1986) provided empirical data in support of this proposition. Although most studies have examined affect intensity as a single index of

* Corresponding author. Tel.: +91 80 2699 5192/80; fax: +91 80 26564830. E-mail addresses: [email protected], [email protected] (S. Mehrotra), [email protected] (R. Tripathi). 1876-2018/$ – see front matter ß 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ajp.2012.04.001

individual difference in line with the original conceptualization mentioned above, a few researchers have brought to light the multi-factorial nature of this construct. Multidimensional models have been found to be superior to a one-dimensional model of affect intensity in confirmatory factor analyses (Bryant et al., 1996; Simonsson-Sarnecki et al., 2000). A three factor model that includes two separate factors related to negative affect (intensity and reactivity) and a single factor called positive affectivity has been found to be one of the best fitting models across these studies. Negative and positive affect intensity reflect general trait-like tendency to typically experience strong negative affect and positive affect respectively. Negative affect reactivity is said to capture situationally driven negative responsiveness to stimuli. Very high correlations between positive affect intensity and positive affect reactivity do not support the differentiation between intensity and reactivity as tenable; unlike the distinction between intensity and reactivity in case of negative affect (Bryant et al., 1996). Affect intensity has been implicated as one of the vulnerability factors for the development of a variety of psychiatric problems. It is positively associated with symptoms of cyclothymia, borderline personality disorder and substance use (Diener et al., 1985a; Flett and Hewitt, 1995; Levine et al., 1997), suicidal behavior (Osman et al., 1999) and fearful reactivity elicited by a panic-relevant biological challenge procedure (Vujanovic et al., 2006). Negative

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intensity in particular is associated with maladaptive emotionregulation strategies, such as thought suppression (Lynch et al., 2007). There is some evidence that thought suppression and ambivalence over emotional expression mediate the links between negative affect intensity and negative outcomes such as depressive symptoms in clinical as well as non-clinical samples (Lynch et al., 2001). Affect intensity and affect liability have been proposed as core dimensions of bipolar disorders during euthymic period (Henry et al., 2008). Gratz et al. (2008) reported that among individuals with substance use disorders, negative affect intensity (in addition to childhood maltreatment) was a unique predictor of borderline personality symptoms. Results from yet another study suggest that negative affect intensity may be a risk factor for Borderline Personality Disorder symptoms in individuals with low distress tolerance (Bornovalova et al., 2011). In a recent Indian study on a community sample of adults, higher negative affect intensity was associated with higher need for emotional disclosure and lower subjective well being (Saxena and Mehrotra, 2010). The generalized expectancies for negative mood regulation (NMR) expectancy refer to the beliefs concerning one’s ability to terminate or alleviate a negative mood state (Catanzaro and Mearns, 1990). High NMR expectancies are associated with adaptive coping strategies (Flett et al., 1996; Kirsch et al., 1990; Mearns, 1991) and lower scores on stress, anxiety and depression (Thorberg and Lyvers, 2006). On the other hand, low NMR expectancies are associated with maladaptive behaviors like excessive drug and alcohol use, clinical and sub-clinical levels of distress, lower use of reappraisal coping and higher use of suppression (Kassel et al., 2000; Simons et al., 2005). Changes in NMR expectancies may also serve as an early prognostic indicator in therapy and act as a mediating variable in psychotherapy for depression (Backenstrass et al., 2006; Cloitre et al., 2004). NMR expectancy and affect intensity have been examined conjointly in very few studies till date. These have shown a small but significant negative correlation between NMR expectancies and overall affect intensity (e.g. Thorberg and Lyvers, 2006).

of affect intensity (Stone and Kozma, 1994; Schimmack and Diener, 1997). Hence it was planned to incorporate a positive and a negative outcome in the present study, viz. well being and stress. Perceived stress was chosen as a variable as it is one of the most generic outcomes, popularly used in studies involving non-clinical samples. A recent review by Thoits (2010) reiterates that stressful experiences have significant impact on physical and mental health. Studies that examine predictors of stress and well being in the general community can be useful in the development of preventive and promotive approaches in mental health. High affect intensity, especially high negative affect intensity, may require higher levels of mood repair efforts and individuals with low NMR expectancy may be highly vulnerable to the impact of high negative affect intensity. However, very few studies have examined negative affect intensity along with NMR expectancy. The present study was undertaken to address some of the above mentioned lacunae through examining the role of positive and negative affect intensity, negative reactivity and NMR expectancy as predictors of perceived stress as well as well being in an Indian sample spanning a broad age range between 20 and 60 years. 1.2. Objectives The specific objectives of the present study were: (1) to examine the association of age and gender with affect intensity variables and NMR expectancies in an Indian adult sample; (2) to examine the relationship of affect intensity variables with NMR expectancies in the above sample; (3) to examine the role of affect intensity variables and NMR expectancies as predictors of perceived stress and well being. Note: The phrase ‘affect intensity variables’ is used to refer to the three indices of affect intensity (positive affect intensity, negative affect intensity and negative reactivity). 2. Method 2.1. Sample

1.1. Rationale for the present study As mentioned above, several studies have observed the links between affect intensity and multiple negative outcomes. However, despite the evidence for a multidimensional nature of affect intensity, many studies continue to use a global index of affect intensity (e.g. Engelberg and Sjoberg, 2004; Henry et al., 2008; Crust, 2009; Thompson et al., 2011). This approach can obscure the differential correlates of different dimensions of affect intensity. For example, neuroticism has been associated with negative but not positive affect intensity (Lee and Guajardo, 2011). The present study attempted to address this issue by treating affect intensity as a multi dimensional variable. A substantial proportion of studies on affect intensity have been limited to undergraduate college samples restricting inferences that may be drawn across the developmental span. It becomes important to examine these constructs in Indian samples across age and genders because emotional regulation processes are likely to be influenced by sociocultural beliefs, norms and values (Bryant et al., 1996). There is a growing recognition in the mental health literature that positive and negative outcomes or phenomena (e.g. ill being and well being) are not mirror opposites and these may have different external correlates (e.g. Keyes, 2002; Ryff et al., 2006). However, most studies on affect intensity as well as NMR have tended to explore only negative outcomes and very few studies have examined the role of affect intensity and NMR as predictors of well being. The few available studies suggest that affect intensity is unrelated to well being (e.g. Larsen and Diener, 1987). But these have been criticized for their conceptualization and measurement

The authors launched the study after obtaining approval for the same from their Institute’s Ethics Committee. Age range between 20 and 60 years, ability to understand and read English/Kannada and minimum 12 years of formal schooling were used as criteria for sample selection. The participants were recruited from general community through snow balling, with the pre-determined target of obtaining nearly equal representation of individuals in each decade of life (between 20 and 60 years) and both genders. Individuals were not paid for participation in the study. Two hundred and six participants were enrolled after they provided written informed consent. The basic sample characteristics are described in Table 1. 2.2. Measures Affect Intensity Measure (AIM): This is a forty items questionnaire with a six point Likert scale (Larsen and Diener, 1987). It assesses the typical strength/intensity with which an individual experiences emotions. Higher total scores across the forty items reflect higher typical affect intensity. The AIM items elicit typical affect intensity and reactivity using a broad range of affective experiences such as joy, enthusiasm, calmness, anger, and guilt and nervousness. Such coverage is understandable in view of the focus of AIM on capturing general trends in the typical intensity of affect. Factor analyses (Bryant et al., 1996) have indicated the utility of examining three subscales: positive intensity and reactivity labeled as positive affectivity (e.g. ‘‘When I am happy, I feel like I am bursting with joy), negative intensity (e.g. ‘‘When I

S. Mehrotra, R. Tripathi / Asian Journal of Psychiatry 5 (2012) 137–143 Table 1 Sample characteristics (N = 206). Frequency

Percentage

a

Age 20–29 30–39 40–49 50–60 Mean(SD): 39.37 (12.05)

56 47 48 54

27.3 22.9 23.4 26.3

Gender Male Female

108 98

52.4 47.6

Marital statusb Single Married Separated/divorced

60 130 3

31.1 67.4 1.5

Education (years of formal schooling) Up to 12 yeas 12–15 years More than 15 years

19 129 58

9.2 62.6 28.2

a b

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In the pilot phase of the study, standard translation and back translation procedure was used to arrive at the Kannada version of the measures for those participants who were comfortable in responding in this language. 2.3. Analyses Normality of distribution of scores on different variables was examined through Kolmogorov Smirnov test. Non parametric statistics (Spearman’s rho correlation and Mann–Whitney U test) were used for variables involving non-normal distributions. Two tailed test of significance was used for all the analyses. Hierarchical regression analyses are presented after ensuring normality of residuals. 3. Results

Specific age data from one male participant – missing. 13 participants did not provide information on marital status.

All the measures had high internal consistency reliability and the obtained scores were normally distributed for most of the measures (Table 2). 3.1. Age and gender

do feel anxiety, it is normally very strong) and negative reactivity (e.g. ‘‘Seeing a picture of some violent car accident in a newspaper make me feel sick to my stomach’’). In calculation of the three subscale scores, 27 of the 40 items are taken in account (Bryant et al., 1996). Generalized expectancy for (NMR) expectancy measure: It is a 30 items measure to assess the extent to which one believes that one can change one’s negative mood (Catanzaro and Mearns, 1990). The items begin with a common stem ‘‘When I’m upset, I believe that’’. Items are rated on a 5-point scale ranging from ‘strongly disagree’ to ‘strongly agree’. Higher scores indicate higher generalized expectancy for negative mood regulation. Perceived Stress scale: This is a 14 items measure of the degree to which situations in one’s life in general are appraised as stressful (Cohen et al., 1983). It has a five point response format (ranging from ‘never’ to ‘very often’). The scale was designed for use in community samples. Higher scores indicate higher perceived stress in the ‘last one month’ period. Psychological well being scale: Bhogle and Jaiprakash (1995) operationalized psychological well being in terms of the degree of happiness, satisfaction or gratification that is subjectively experienced by an individual. Their scale of psychological well being consists of 28 items with a dichotomous response format. This measure utilizes a broad-based conceptualization of well being that includes aspects pertaining to both hedonic and eudaimonic aspects of well being. It is a brief and easy to administer measure of well being that was developed for use in Indian samples. Higher scores indicate higher levels of well being.

Age had a weak positive correlation with NMR expectancy (r = 0.13, p = 0.10) but was negatively correlated with positive affect intensity (r = 0.15, p < 0.05) and overall affect intensity (r = 0.26, p < 0.001). It was uncorrelated with typical intensity of negative affect (r = 0.09, NS) or negative reactivity (r = 0.02, NS). In the overall sample, men and women did not differ from each other on affect intensity variables or on negative mood regulation expectancy. An examination of gender differences within age groups revealed no significant differences on various dimensions of affect intensity except for a trend toward significant difference on negative affect reactivity. Women in the youngest age group (20–29 years) tended to have higher scores on negative affect reactivity (Mean = 4.29, SD = 0.68) as compared to their men counterparts (Mean = 3.92, SD = 0.82), with t-value being 1.83, p < 0.10. 3.2. Associations between affect intensity variables All the affect intensity variables were positively correlated with each other. Negative affect intensity showed a moderately strong correlation with both negative reactivity as well as positive affect intensity, sharing roughly 19–20% of variance with each (Table 3). 3.3. Affect intensity variables and NMR expectancy Among the affect intensity variables, negative affect intensity was most strongly associated with NMR expectancy. Higher levels of overall affect intensity, negative affect intensity and negative reactivity scores went hand in hand with lower NMR expectancy.

Table 2 Descriptive statistics on the study measures. Variables

Min–max possible

Min–max obtained

Mean

Median

SD

KS-Za

Cronbach’s alpha

Affect intensity Total affect intensity Positive affect intensity Negative affect intensity Negative affect reactivity Negative mood regulation expectancy Perceived stress Psychological well being

1–6 1–6 1–6 1–6 30–150 14–70 0–28

2–5 2–6 2–6 2–6 76–150 20–52 2–27

3.71 4.16 3.34 4.06 109.28 38.03 21.72

3.70 4.13 3.33 4.00 109.00 38.0 23.0

0.47 0.81 0.76 0.83 15.64 6.67 4.45

0.62 0.75 1.46* 1.01 0.74 0.80 1.73**

0.87 0.89 0.64 0.64 0.87 0.72 0.82

a * **

Kolmogorov–Smirnov Test for checking normality of score distributions. Significant at 0.05 level. Significant at 0.01 level.

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Table 3 Affect intensity and negative mood regulation expectancy zero order correlations. Negative affect intensity Positive affect intensity Negative affect intensity Negative reactivity a * **

0.44

Negative reactivity

a,**

Negative mood regulation expectancy

**

0.14* 0.29a,** 0.15*

0.34 0.45a,**

Spearman correlations coefficients (all other values depict Pearson product moment correlations). Significant at 0.05 level. Significant at 0.01 level.

Table 4A Hierarchical regression: predictors of perceived stress. Block

Predictors

R

R Square

Adjusted R square

R Square change

F Change

Sig. F change

Block 1 Block 2

Gender and age Positive affect intensity, negative affect intensity and negative reactivity Negative mood regulation expectancy

0.153 0.453

0.024 0.205

0.014 0.186

0.024 0.182

2.437 15.188

0.090 0.000

0.635

0.404

0.386

0.198

65.772

0.000

Block 3

Table 4B Summary of the final model (predictors of perceived stress). Variables

Un-standardized coefficient (B)

Std. error

(Constant) Age Gender Positive affect intensity Negative affect intensity Negative reactivity Negative mood regulation expectancy

37.730 0.436 0.749 1.040 1.009 1.018 3.263

0.500 0.371 0.724 0.446 0.478 0.422 0.402

* **

Standardized coefficients Beta)

t-Value 75.403** 1.175 1.034 2.333* 2.111* 2.412* 8.110**

0.066 0.057 0.158 0.152 0.155 0.495

Significant at 0.05 level. Significant at 0.01 level.

But, positive affect intensity had a small positive correlation with NMR expectancy (Table 3). 3.4. Predictors of perceived stress and psychological well being The mean well being of the overall sample fell toward the higher end of the possible range of scores. This is in keeping with reports of high average well being levels generally noted in various general community-based studies including a recent large scale study from urban India (Biswas-Diener et al., 2005; Agrawal et al., 2011). Hierarchical regression analysis was carried out for examining the predictors of perceived stress. All the continuous predictor variables were standardized for entry. Gender (dummy coded) and age were entered in the first block. Affect intensity variables were entered in the second block to examine their effects over and above age and gender. In the last block, NMR expectancy was entered to examine whether it predicted additional variance over and above affect intensity. In the final model, lower NMR expectancy, higher negative affect reactivity, higher negative affect intensity as well as lower positive affect intensity predicted higher levels of perceived stress, jointly explaining 39% of variance. Similarly, in the final model for prediction of psychological well being, higher NMR expectancy, lower negative affect intensity as well as higher positive affect intensity predicted higher levels of psychological

well being, jointly explaining 30% of variance in the same. Unlike in case of perceived stress, negative reactivity did not emerge as a significant predictor of psychological well being (Tables 4A, 4B, 5A and 5B). 4. Discussion 4.1. Age and gender The study results suggest a minimal role of gender and age on affect intensity and NMR expectancy. There were no gender differences on NMR expectancy in the present study and this is similar to the observations made by the authors of the NMR expectancy measure (Catanzaro and Mearns, 1990). Older participants were somewhat higher on NMR expectancy. This is in keeping with the available literature (Phillips et al., 2008). It has been argued that older adults make more effective use of reappraisal strategies to regulate emotions but are less likely to use emotion suppression (John and Gross, 2004). Older adults are also likely to regulate the experience of emotions earlier in the emotion-generation process than do their younger counterparts, who instead may rely more on the suppression of expression (Magai et al., 2006). In our study, increasing age was linked with experiencing lower intensity of affect in general and lower positive affect intensity in particular. Diener et al. (1985b) have reported

Table 5A Hierarchical regression: predictors of psychological well being. Block

Predictors

R

R Square

Adjusted R square

R Square change

Block 1 Block 2

Gender and age Positive affect intensity, negative affect intensity and negative reactivity Negative mood regulation expectancy

0.177 0.412

0.031 0.170

0.018 0.141

0.031 0.138

2.417 8.113

0.093 0.000

0.575

0.331

0.303

0.161

34.864

0.000

Block 3

F Change

Sig. F Change

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Table 5B Summary of the final model (predictors of psychological well being). Variables

Un-standardized coefficient (B)

Std. error

(Constant) Age Gender Positive affect Intensity Negative affect Intensity Negative Reactivity Negative mood regulation expectancy

21.481 0.515 9.720E 02 0.854 0.792 0.184 1.967

0.455 0.343 0.608 0.386 0.388 0.354 0.333

* **

Standardized coefficient (Beta) 0.105 0.011 0.186 0.178 0.042 0.446

t-Value 47.227** 1.499 0.160 2.213* 2.041* 0.519 5.905**

Significant at 0.05 level. Significant at 0.01 level.

decrease in overall affect intensity with advancing age in a sample spanning adults within the 16 and 68 age range. Backs et al. (2005) observed in a quasi-experimental study that younger adults found pleasant stimuli to be more pleasant and arousing than did older adults. This difference was explained in terms of greater affect intensity and surgency in the younger group and greater leveling of positive affect in the older group. Another study observed that older and younger adults were not different on negative affect intensity and reactivity (Cheavens et al., 2008). In our study, no significant gender differences were noted except that the women in the youngest group tended to report higher negative affect reactivity than men in the same age group. This finding is somewhat dissimilar to the pattern of findings across other studies on affect intensity in general (Diener et al., 1985b; Fujita et al., 1991; Williams, 1989). Variations in methods of arriving at affect intensity scores may account for this difference. The present study used three affect intensity indices as advocated by Bryant et al. (1996). An elevation on the negative reactivity dimension, particularly among young females, was observed in Bryant and colleagues’ study (1996) and this mirrors the observation in the present study. 4.2. Affect intensity variables and NMR expectancy The findings highlight the importance of separately examining negative affect intensity, positive affect intensity and negative reactivity. Differential patterns of correlates for negative intensity and reactivity on one hand and positive affect intensity on the other hand been reported earlier in community samples of adults (Simonsson-Sarnecki et al., 2000). In the present study, the correlations between these variables were not so high as to indicate redundancy. Positive and negative affect intensity shared only 19% proportion of variance. Similarly, negative affect intensity shared only 20% of variance with negative reactivity. Interestingly, these affect variables also differed in terms of the pattern of their correlations with other variables. Individuals who reported strong positive affect intensity were higher on NMR expectancy whereas those reporting high negative affect intensity or high negative reactivity had lower NMR expectancy. 4.3. Prediction of perceived stress and well being and implications The hierarchical regression analyses suggest that NMR expectancy and positive and negative affect intensity play an important role in predicting not just perceived stress but also psychological well being. Strong negative reactivity was an additional predictor of perceived stress. It has been observed that subjects with high NMR expectancies have more mood incongruent memories after negative mood induction than subjects with low NMR expectancies and this reflects a quicker repair response to negative mood in the former (Rusting and DeHart, 2000; Smith and Petty, 1995). Hemenover (2003) had observed that individuals high on NMR expectancies showed characteristics of positive affect augmenters

experiencing lower rates of positive affect decay and rapid rates of negative affect decay. These may be some of the mechanisms that link NMR expectancy and well being as observed in the present study. Frequent experience of positive emotions can play an important role in broadening the repertoire of thoughts and behaviors as well as building various resources (Fredrickson, 2001). Intensity of affect and frequency of affect have been postulated as two separate dimensions of affective structure (Diener et al., 1985b) and the latter has been implicated to be more relevant than the former for well being (e.g. Larsen and Diener, 1987). The present study examined typical intensity rather than frequency of positive affect and we observed that individuals who report typically experiencing strong intensity of positive affect were likely to exhibit better efficacy for NMR, lower perceived stress and higher well being. Differences in ways of conceptualizing affect intensity (global vs. multidimensional) as well as the nature of measures used for assessment of affect intensity and well being may account for differences in results obtained across studies (Stone and Kozma, 1994; Schimmack and Diener, 1997). On the whole, the findings on positive affect intensity are broadly in keeping with the existing theoretical framework as well as the growing body of empirical literature that positive emotions can buffer stress and enhance resources for coping. Savoring beliefs refer to people’s perceptions of their ability to derive pleasure through anticipating positive events and savoring beliefs are positively correlated with affect intensity (Bryant, 2003). Whether savoring beliefs mediate the relationship of positive affect intensity with NMR expectancy and well being is a fertile area for further exploration. Only a handful of studies (Flett et al., 1996; Thorberg and Lyvers, 2006) have examined affect intensity and NMR expectancy together. In the present study, affect intensity variables jointly with NMR expectancy predicted a significant proportion of variance in psychological outcomes. The findings highlight that individuals who tend to quickly react with negative affect to minor negative events, are likely to experience higher stress. Negative affect reactivity was a unique predictor of perceived stress. Although a tendency for high negative reactivity is likely to enhance an individual’s overall perception of stress, it may not play a significant role in global reports of psychological well being. This reiterates the importance of examining differential correlates of positive and negative outcomes in psychological research, as discussed in an earlier section. Smyth and Arigo (2009) reviewed available evidence to conclude that interventions that promote emotional regulation are likely to have beneficial health outcomes for at risk as well as clinical populations. The present study suggests that individuals with strong negative affect intensity along with low NMR expectancy may form an especially vulnerable subgroup that deserves attention of researchers interested in preventive approaches in the field of mental health. Although enhancement

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of NMR efficacy through mood regulations skills training may be useful for this subgroup; intensive/prolonged intervention may be needed in view of their strong intensity of negative affect. Affect intensity is conceptualized as a stable trait-like intrapersonal variable and the extent to which high negative affect intensity may be modifiable through certain forms of interventions needs to be examined in further research (Yen et al., 2002). A likely candidate for such an examination could be mindfulness based intervention approaches that emphasize non-judgmental awareness and acceptance of emotions and thoughts (Schroevers and Brandsma, 2010; Williams, 2010). 4.4. Limitations and directions for further research The study attempted to obtain a sample representative of various age groups and both genders within 20–60 years range. However, a stratified random sampling method could not be used due to logistical constraints. Replication of results would be important for drawing firm conclusions regarding generalizability of the findings. The relationship of perceived stress with negative affect intensity may possibly stem from the potential conceptual overlap between these variables. However, this does not seem very likely. The construct of perceived stress focuses on the general appraisal of one’s life demands as stressful and the responses on this measure indicate ‘how often’ one felt stressed in the last one month period. On the other hand, the affect intensity measure captures an individual’s emotional experience in terms of typical intensity or reactivity. Assessment of all the variables involved self report measures and some possible role of shared method variance cannot be ruled out. Moderators and mediators of the relationships of affect intensity variables (especially positive affect intensity) with negative mood regulation expectancy as well as with a variety of psychological outcomes need to be examined in future studies. 4.5. Conclusion The study results highlight the differential correlates of different dimensions of affect intensity. High positive affect intensity was observed to go hand in hand with higher NMR expectancy while a reverse relationship was seen between negative affect intensity or reactivity and NMR expectancy. Various dimensions of affect intensity and NMR expectancy emerged as significant predictors of perceived stress as well as well being in community-dwelling adults. Negative reactivity was a specific predictor of perceived stress. Co-occurrence of high negative affect intensity with low negative mood regulation expectancy is likely to pose challenges for emotion regulation and has implications for psychological interventions. Funding source The paper is based on part of a research project funded by the National Institute of Mental Health & Neuro Sciences (NIMHANS) Bangalore, India. The funding body had no other role in the study design, data collection, analysis, interpretation, report writing and the decision to submit this paper. Contributors The first author developed the study design, was responsible for supervising data collection, conducted data analysis, interpreted the findings and wrote the manuscript. The second author contributed to literature searches, data entry, assisted in data analysis and co-wrote the paper with the first author.

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