Skip to main content
NCBI home page
VA Author Manuscripts logoLink to VA Author Manuscripts
. Author manuscript; available in PMC: 2026 Feb 25.
Published in final edited form as: Aging Ment Health. 2017 Jan 12;22(4):512–518. doi: 10.1080/13607863.2016.1277975

Older Adults Report More Sadness and Less Jealously than Young Adults in Response to Worry Induction

Christine E Gould 1, Lindsay A Gerolimatos 2, Sherry A Beaudreau 3, Nehjla Mashal 4, Barry A Edelstein 5
PMCID: PMC12930713  NIHMSID: NIHMS1757688  PMID: 28112968

Abstract

Objectives:

The present study examined differences between older and younger adults regarding descriptions of their experience of worry and worry content. Obtaining a better understanding of worry has important implications for not only anxiety disorders, but also depressive disorders as there is a growing body of evidence suggesting that worry is a transdiagnostic symptom.

Method:

Twenty-eight older and 25 younger adults participated in an experimental manipulation of worry (i.e., 5-minute worry induction). Participants identified their three main worries and completed an emotion checklist before and after the induction.

Results:

After the induction, younger adults endorsed feeling fearful, impatient, and irritated, whereas older adults endorsed feeling tense or worrying. Older adults were more likely than younger adults to report feeling sad (χ2(53) = 7.52, p = .01), whereas younger adults were marginally more likely to report feeling jealous (χ2(53) = 4.34, p = .05), but these age differences were not significant after applying the Holm-Bonferroni correction. With regards to worry content, older adults worried more about community/world affairs (χ2 = 6.59, p = .01), whereas younger adults worried more about school (χ2 = 17.61, p < .001). Only age differences in worry about school remained significant after applying the Holm-Bonferroni correction.

Conclusion:

Following a worry induction, older and younger adults endorsed a wide variety of negative affect beyond the typical emotions associated with worry. Greater sadness experienced by older compared with younger adults highlights the importance of considering negative affect states, particularly depression, when working with older adult worriers.

Keywords: aging, age differences, anxiety, emotions

The frequency of worry decreases across the lifespan (e.g., Basevitz et al., 2008; Goncalves & Byrne, 2013), and older adults report less trait worry compared with younger age groups (e.g., Brenes, 2006; Gould & Edelstein, 2010). Although worry appears to decrease with age, even mild worry symptoms predict cognitive decline (Pietrzak et al., 2012) and are associated with cardiovascular disease (Tully, Cosh, & Baune, 2013). Research regarding age-related differences in worry has revealed some variations in the phenomenology of worry across the lifespan, which may contribute to the reported decrease in late-life worry. Understanding age differences in the experience of worry and identifying the words that older adults use to describe their symptoms may help improve detection of Generalized Anxiety Disorder (GAD), a common and impairing late-life mental health disorder for which worry is the principal symptom.

With regards to worry content, older adults are more likely than younger adults to worry about health and family, younger adults are more likely to worry about interpersonal issues, work, or minor matters, and findings regarding differences in worry about finances are mixed (Goncalves & Byrne, 2013; Hunt, Wisocki, & Yanko, 2003; Powers, Wisocki, & Whitbourne, 1992; Wuthrich, Johnco, & Wetherell, 2015). These age differences in worry content mirror the differences in the daily lives of older and younger adults. Younger adults likely spend more time working and studying compared with older adults, whereas older adults are more likely to spend time managing chronic health conditions. Wuthrich and colleagues (2015) suggest that older adults worry less frequently about interpersonal issues because older adults may be more likely to have long-term relationships compared with younger adults. Findings of age differences in interpersonal worries also are consistent with Socio-Emotional Selectivity theory, which would suggest that as one ages, one shifts to focus on relationships that optimize emotional well-being (Carstensen, Isaacowitz, & Charles, 1999).

The question of whether older adults experience or report worry differently from younger adults remains unanswered. Experimental findings indicate that older adults have less anxiety and less subjective, but not less objective, arousal (i.e., heart rate) while worrying when compared with younger adults (Gould, Gerolimatos, & Edelstein, 2015). Furthermore, studies examining older adults’ perceptions of anxiety and worry and the words they use to describe worry could shed some light on this question of the phenomenology of worry in late life. In one study, Wetherell and colleagues (2009) examined age differences in older and younger adults’ classification of anxiety and depressive symptoms compared with the classification of symptoms according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision (DSM-IV-TR, American Psychiatric Association, 2000). The researchers generated a list of symptoms of anxiety disorder and affective disorder criteria and asked older and younger adults to identify the symptom as ‘anxiety’, ‘depression’, ‘both anxiety and depression’, or ‘neither.’ Older adults more often misclassified both anxiety and depression symptoms compared with younger adults. In particular, older adults misclassified emotional symptoms, such as sadness, worthlessness, worry and fear. These findings suggest that older adults’ perception of anxiety symptoms may result in their use of incorrect terms to describe symptoms, which could possibly lead to confusion during assessment and a misunderstanding of the experience and presentation of anxiety among older adults. Alternatively, it is possible that younger adults may be more aware of psychological terms and the correspondence of these terms with mental health symptoms.

In another study, Letamendi et al. (2013) examined the terms that older Latinos use to describe mental health symptoms. The findings suggest older Latinos described their symptoms using terms including sadness, nerves/nervous and desperate/desperation (Letamendi et al., 2013), rather than more common terms such as stress. In a study of older and younger adults seeking anxiety or depression treatment, participants were asked to select words from two lists to describe their symptoms of worry/anxiety and sadness/feeling down (Wuthrich et al., 2015). Older adults were less likely to describe their anxiety or worry as feeling nervous, worried, hesitant, scared, or ‘not yourself’ compared with younger adults. Words most often used by older adults to describe worry or anxiety included stressed, tense, or concerned. These studies provide preliminary evidence that older adults’ characterization of anxiety and worry may differ from younger adults as older adults report less arousal and sometimes include affective symptoms such as sadness alongside anxiety or worry symptoms.

Obtaining a better understanding of worry has important implications for not only anxiety disorders, but also depressive disorders as there is a growing body of evidence that suggests that worry is a transdiagnostic symptom (McEvoy, Watson, Watkins & Nathan, 2013; Ruscio, Seitchik, Gentes, Jones, & Hallion, 2011). The primary aim of the present study was to examine age-related differences in older and younger adults’ descriptions of their experience of worry. It builds on and extends previous research by using an experimental manipulation of worry rather than using older adults’ recall of their past worry or anxiety symptoms. The present study also benefits from using an extensive list of emotion adjectives associated with depression, anxiety and other affective states. A secondary aim of the present study was to examine age-related differences in the content of older and younger adults’ worries. These data were gathered as part of a larger examination of age differences in worry described previously (Gould et al., 2015).

Method

Participants

The 53 participants were 25 younger (aged 18 to 30 years) and 28 older adults (aged 60 years or older) who participated in a worry induction as part of a larger experimental study (see Gould et al., 2015 for detailed description of the study procedure). Young adults were recruited from psychology classes, listserv announcements, flyers, and word-of-mouth. Older adults were recruited via listserv or website announcements, community bulletin postings, visits to senior centers, letters to individuals interested in research opportunities, and word-of-mouth. Participants were excluded from the larger study if they: (1) were current smokers; (2) were using beta-blockers, anxiolytics, psychostimulants, or diet pills; (3) had pacemakers or history of arrhythmias, heart surgery, or heart attacks; or (4) had cognitive impairment as determined by Montreal Cognitive Assessment ≤ 22 (Nasreddine et al., 2005).

Measures

Participants completed self-report measures prior to the worry induction to assess demographic and health characteristics, emotion regulation, and baseline worry, depression, and anxiety. The Penn State Worry Questionnaire (PSWQ; Meyer, Miller, Metzger, & Borkovec, 1990), was used to measure trait worry or one’s tendency to worry. The PSWQ is a 16-item measure with items rated from 1 (not at all typical) to 5 (very typical) with higher scores indicating more severe worry. The Depression Anxiety Stress Scale (DASS-21; Lovibond & Lovibond, 1995) is a 21-item measure of anxiety, stress, and depression symptoms with items rated from 0 (did not apply to me at all) to 3 (applied to me very much, or most of the time). The Emotion Regulation Questionnaire (ERQ; Gross & John, 2003) assesses the use of two emotion regulation strategies (cognitive reappraisal and suppression) using 10-items rated on a scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Participant’s self-reported emotional states were assessed by the state form of the Multiple Affect Adjective Checklist-Revised (MAACL-R; Lubin & Zuckerman, 1999). The MAACL-R is checklist of 132 emotion adjectives displayed on a single page. Participants read through the list and were instructed to place a mark next to the emotions which correspond to how the participant is feeling right now. This measure was completed before and after the worry induction.

Participants also completed a rating of the intensity of their worry with a single item rated on a scale 0 (not at all worried) to 100 (extremely worried). Worry intensity is included to measure of the effectiveness of the worry induction.

Procedure

Participants first completed self-report questionnaires, then sat quietly for a three-minute baseline. At the end of the three minutes, participants completed the MAACL-R checklist of emotion adjectives to assess baseline levels of affect. Next, the researcher used a standard paradigm to induce worry (e.g., McLaughlin, Borkovec, & Sibrava, 2007; McLaughlin, Mennin, et al., 2007). The following definition of worry was read to participants and provided the definition printed on a sheet of paper: ‘intrusive [distracting or bothersome] thoughts or images about potential future events or catastrophes [concerns] that produce negative feelings when they occur’ (McLaughlin, Borkovec, & Sibrava, 2007, p. 27). Then, participants were asked to identify three topics or concerns that they worry about the most. Participants recorded these worries on a piece of paper. Researchers next read the worry induction instructions, which directed participants to worry in a typical fashion, but as intensely as possible until asked to stop (McLaughlin, Mennin, & Farach, 2007). Participants were also instructed that if they ‘normally worry about only one topic [or concern] at a time, please try to do the same during this period’ but if participant’s ‘thoughts change to another worry topic during this period feel free to allow these thoughts to continue’ (McLaughlin, Mennin, et al., 2007, p. 1740). At the end of the 5-minute worry induction, participants completed the MAACL-R again. After the worry induction, participants engaged in a 5-minute focused breathing period and then were debriefed by the researcher. The worry induction was found to be an effective manipulation of worry for both young and older adults as evidenced by a significant increase in worry intensity for young and older adult participants in the worry induction condition compared with those participants in the control condition in which participants recalled recent pleasant/neutral events (Gould et al., 2015).

Data Analysis

Analyses are reported with alpha set at the .05 level. Initial analyses examined age differences in baseline measures and in basic demographic characteristics. We examined whether there were age differences in the effect of the induction on worry intensity using a repeated measures ANOVA. Next, we examined the emotion items endorsed during worry period. To identify the emotions that are unique to the worry period, we calculated a change in emotions endorsed from baseline to the worry period. We focused the analyses on the new emotions endorsed following the worry period. Then, we created rank-ordered lists of the emotions most frequently endorsed during the worry period for younger and older adults. Significant differences in the frequency of most frequently emotions endorsed were tested using Pearson chi-square statistics. We applied the Holm–Bonferroni sequential rejective method (Holm, 1979) to account for multiple tests using the Holm-Bonferroni Excel calculator (Gaetano, 2013). With this correction, the p-values of the tests performed are ordered from the smallest to largest. The p-values next are tested in a step-down procedure by comparing the smallest p-value with a Bonferroni-adjusted alpha. This process continues with next smallest p-value compared with a Bonferroni-adjusted alpha for one fewer test than used with the previous correction.

Worry content was categorized and analyzed using a combination of deductive and inductive strategies. The first author reviewed the list of participant’s worries and created a codebook of inductively-generated categories based on the data. She also compared the codebook with preexisting worry content categories, such as those listed in the Generalized Anxiety Disorder section of the Anxiety and Related Disorders Interview Schedule (Brown, DiNardo, & Barlow, 2007). The codebook was reviewed by the last author and refined during discussions. The resulting codebook was used by the first and last author to code data from 12 younger and 12 older adults. After the first round of coding, Cohen’s kappa coefficients were calculated and the coders adjudicated the codebook. The resulting kappa coefficients surpassed the a priori cut-point > .70 and the first author coded the remaining data. After coding the data, we examined the differences in frequency of worry content categories for younger and older adults using Pearson Chi-Square tests. We also examined whether there were any patterns for worry content domains within individuals.

Results

Basic demographic characteristics and scores on baseline measures are displayed in Table 1. No age differences were found for the DASS total score, or for the two emotion regulation questionnaire subscales of reappraisal or suppression. Nevertheless, we found that younger and older adults differed significantly in PSWQ scores, F(1, 52) = 9.04, p = .004, with older adults having lower scores (less trait worry) compared with younger adults. Despite these baseline age differences in PSWQ scores, we found no significant age differences in the change in worry intensity from baseline to after the worry induction, F(1,51) = 2.00, p = .16. Regardless of age group, worry intensity significantly increased across time, F(1,51) = 65.20, p < .001, suggesting that the manipulation was effective for both age groups. Older and younger adults did not differ in the total number of MAACL-R emotion items following the worry induction, F(1, 52) = 0.65, p = .42. Younger adults endorsed 21.26 (SD = 12.47) emotion items and older adults endorsed 24.36 (SD = 15.03) emotion items following the worry induction. The mean trait worry of younger and older adults fell below age-based clinical cutoffs (Fresco et al., 2003; Wuthrich, Johnco, & Knight, 2014). The DASS-21 total scores also were consistent with scores found in non-clinical samples (Lovibond & Lovibond, 1995).

Table 1.

Participant Characteristics

Younger Adults (n=25) Older Adults (n=28)
M (SD) or n (%) M (SD) or n (%) p
Age 20.92 (2.16) 67.96 (7.71) < .001
Gender .41
 Male 11 (44.0%) 9 (32.1%)
 Female 14 (56.0%) 19 (67.9%)
Race/Ethnicity .33
 White 22 (88.0%) 27 (96.4%)
 Other 3 (8.6%) 1 (3.6%)
PSWQ 47.52 (14.88) 37.29 (9.61) .004
DASS-Total 9.92 (7.37) 7.68 (5.50) .21
ERQ-Suppression 12.84 (4.10) 13.04 (5.82) .89
ERQ-Reappraisal 35.36 (4.52) 35.07 (10.35) .90
Open in a new tab

Note. p corresponds to F-test or χ2 statistic. PSWQ = Penn State Worry Questionnaire; DASS = Depression, Anxiety, and Stress Scale; ERQ = Emotion Regulation Questionnaire

Emotional Experience of Worry

To identify age differences in the words used to describe the emotional experience of worry, we examined the emotion items endorsed during the worry period that were not reported during baseline. The frequencies and percentages of younger and older adults endorsing each item are displayed in Table 2. No specific emotion item was endorsed by more than 44% of younger adult or more than 39% of older adult participants. To compare emotions across the two age groups, we focused on the items endorsed by at least one-third of participants in each age group. Visual inspection revealed that younger adults and older adults endorsed different emotions with the exception of agitation. Younger adults endorsed feeling fearful, impatient, and irritated, whereas older adults endorsed feeling tense or worrying. Despite the differences in patterns, only two emotions, sad and jealous, were endorsed at significantly different rates for younger and older adults. Older adults were more likely than younger adults to report feeling sad, χ2(53) = 7.52, p = .01, whereas younger adults were more likely to report feeling jealous, χ2(53) = 4.34, p = .05. However, after using the Holm-Bonferroni sequential rejective method (Holm, 1979) to account for multiple testing, the findings for sadness and jealousy were no longer significant.

Table 2.

Rank Order of New Emotion Adjectives Endorsed After Worry Induction

Young Adults (N=25) Older Adults (N = 28)
Emotion N (%) Emotion N (%)
Fearful 11 (44%) Agitated 11 (39%)
Agitated 10 (40%) Tense 11 (39%)
Impatient 9 (36%) Worrying 10 (36%)
Irritated 9 (36%) Sad* 9 (32%)
Annoyed 8 (32%) Displeased 8 (29%)
Nervous 8 (32%) Upset 8 (29%)
Critical 7 (28%) Discontented 7 (25%)
Gloomy 7 (28%) Irritated 7 (25%)
Tense 7 (28%) Discouraged 6 (21%)
Afraid 6 (24%) Fearful 6 (21%)
Desperate 6 (24%) Frightened 6 (21%)
Jealous* 6 (24%) Impatient 6 (21%)
Shaky 6 (24%) Shaky 6 (21%)
Worrying 6 (24%) Alone 5 (18%)
Bitter 5 (20%) Cautious 5 (18%)
Cautious 5 (20%) Low 5 (18%)
Discouraged 5 (20%) Nervous 5 (18%)
Displeased 5 (20%) Quiet 5 (18%)
Low 5 (20%) Sullen 5 (18%)
Panicky 5 (20%) Unhappy 5 (18%)
Quiet 5 (20%)
Open in a new tab

Note: *χ2 test indicates that counts differ significantly, p < .05, but after correction for multiple corrections was applied, findings were not significant. Emotion adjectives endorsed by five or more participants are displayed.

Worry Content

Worry content was initially categorized into eleven different domains (Cohen’s Kappa): community/world affairs (Κ = .74), family (Κ = 1.00), finances (Κ = .90), friends (Κ = 1.00), Functioning/being a burden (Κ = .80), health (self) (Κ = .91), minor matters (Κ = .85), other’s health (Κ = 1.00), school (Κ = .95), social/interpersonal matters (Κ = 1.00), and work (Κ = .79). Two additional domains were added after the first round of coding: future and other. Kappas are not reported for those domains because the decisions were made based on the coders’ consensus. Figure 1 displays the frequency of worry content domains for younger and older adults. Older adults most frequently worried about family members, their own health, or minor matters, whereas younger adults most frequently worried about school, finances, and work. Age differences in the frequency of worry content were observed for two of the 13 worry content categories. Older adults were more likely to worry about community/world affairs (χ2 = 6.59, p = .01), whereas younger adults were more likely to worry about school (χ2 = 17.61, p < .001). After the Holm-Bonferroni sequential rejective method was applied, only the finding of younger adults worrying more about school compared with older adults remained significant (adjusted p = .0038). Despite these age differences in worry content domains, many similarities were observed including the finding that older and younger adults’ top five worries included family, one’s own health, and finances.

Figure 1.

Figure 1.

Open in a new tab

Frequency of Worry Content Domains for Younger and Older Adults.

Note. * indicates frequencies differ significantly (p > .05) for younger and older age groups. After correction for multiple testing was applied, only differences in school were significant.

Our findings revealed that the majority of participants worried about several distinct topics, with the exception of three older adults who reported only one worry and two older adults and one younger adult who reported two worries. Only 24.5% of participants had two worries that fell into the same category. Moreover, based on our visual inspection of the categorical data, there did not appear to be a pattern of certain worry domains tending to co-occur.

Discussion

The principal finding of the present study was that, following a worry induction, older and younger adults endorsed a wide variety of emotional descriptors to label negative affect beyond the typical emotions associated with worry such as nervous, worrying, fearful, and frightened. Some emotions endorsed align with the diagnostic criteria for GAD (e.g., feeling irritated or agitated). Other emotions endorsed reflect the transdiagnostic nature of worry. The emotions endorsed extend beyond anxiety disorders in that the emotions endorsed are expected to occur within the context of disorders such as depression (e.g., McEvoy et al., 2013), as in the case of feeling discouraged, displeased, sad, low, or gloomy, or expected to occur in the context of difficulties with anger, as in the case of impatient, irritated, jealous, and agitated. The endorsement of feeling cautious, quiet, and alone may reflect feelings of apprehension that arise along with worry as well as the quiet room that they were in for the experiment.

The top five emotions endorsed by older adults were agitated, tense, worrying, sad and displeased. The endorsement of these emotions fits with previous findings of Wuthrich et al., (2015) indicating that tense, stressed, and concerned were frequently endorsed by older adults with anxiety, and findings from Letamendi et al. (2013) suggesting that older adults report feeling sad and nervous when experiencing mental health problems.

Despite the substantial variability in individual experience of worry, some age differences emerged with regards to the specific negative emotions that older and younger adults experienced. Older adults were more likely to report sadness following worry, whereas younger adults were more likely to report jealousy following the worry induction; however, after corrections for multiple testing, age differences for sadness and jealousy were no longer statistically significant. We explored whether these age differences could be attributed to the topics that older adults selected to focus on during the study. Younger adults selected interpersonal topics more frequently to worry about compared with older adults, but this difference did not reach significance, which could be attributed to the small sample size in the present study. The finding of more frequent endorsement of sadness amongst older adults could be attributed to the high degree of comorbidity of anxiety and depression in late life (Byers, Yaffe, Covinsky, Friedman, & Bruce, 2010), suggesting that worry may be one symptom experienced across both anxiety and depressive disorders. Alternatively, older adults may mislabel worry as sadness (e.g., Wetherell et al., 2009) or may more often experience mixed emotional states compared with younger adults (e.g., Carstensen, Pasupathi, Mayr, & Nesselroade, 2000; Wuthrich et al., 2015).

With regards to our secondary aim of examining worry content, we found that both older and younger adults selected diverse topics about which to worry during the study. Interestingly, we detected substantial intra-individual variation in topics selected as evidenced by less than a quarter of participants worrying about similar topics (i.e., two health conditions). This finding could be attributed to the instructions to identify three topics that one worries about the most with no explicit instructions that those topics should differ. Although the top three worries differed for older and younger adults, minimal significant age differences emerged. The significant age differences were only with regards to younger adults worrying significantly more about school in the present study after corrections for multiple testing were applied. The difference with respect to school was expected and fits with previously described research findings (e.g., Powers et al., 1992; Wuthrich et al., 2015). The high frequency of worry about health and family concerns among older adults also fits with findings of previous studies (e.g., Hunt et al., 2003), but the finding that older adults endorsed worries about minor matters was unexpected. Nevertheless, we cannot directly compare the present study’s findings to studies that examined the daily frequency of worry content topics because it is possible that individuals in the present study chose topics that they thought would induce worry. In other words, participants in the present study may have selected topics that elicit more intense worry, which may not necessarily be topics that they worry about most frequently. In spite of the differences in design between the present study and other examinations of worry content, the strength of the present study’s design is that participants generated their own topics about which to worry, which may suggest that the topics we analyzed were the most salient worry topics for individuals. On a daily basis it is possible that people naturally worry about less salient topics.

Our findings should be viewed in context of their limitations, which include the small sample size, the mostly white sample, and the lack of matching across age groups with regards to worry severity as measured with assessments such as the PSWQ. The small sample size may hinder the generalizability of the worry content data in that these worries were individually generated and thus closely tied to the experiences of our individual participants. Yet the substantial variability in worry content topics suggests that these findings may generalize to community dwelling samples of older adults and student samples, but possibly not to clinical samples in light of the subclinical levels of trait worry as measured by the PSWQ. While measures such as the PSWQ, DASS, and ERQ were included to characterize the sample, we did not use scores on these measures as covariates in analyses because and because no age differences emerged with the exception of the PSWQ. The age difference on the PSWQ was consistent with previous work (e.g., Gould & Edelstein, 2010) and the younger and older adult mean scores on the PSWQ both fell approximately ten points below the age-based clinical cutoffs (Fresco et al., 2003; Wuthrich et al., 2014), which led us to conclude that there were no substantial differences in the age groups that would influence our findings. Future studies should address whether emotions associated with worry vary based on differences in trait worry as measured with the PSWQ in younger and older adults. Additionally, worry is a covert behavior that is difficult to detect and our study is limited by relying on self-report of emotions rather than measures of physiological arousal such as skin conductance. We also could not identify the amount of time that individuals spent worrying about each topic during the worry induction, which limits our ability to draw conclusions about the extent to which the emotions experienced during the worry period were due to the content of worries compared with the worrying process itself. For instance, if someone were worrying about a family member’s health problems, this may bring about different emotions compared with worries about minor matters. It is also possible that some of these emotions were due to the experimental nature of the study and the experimenter asking participants to engage in an unpleasant thinking task in the context of an unfamiliar situation. Despite the aforementioned limitations, our study has some strengths including an experimental manipulation of worry and ideographic assessment of worry content. Because worry content was generated by individuals and categorized using qualitative analysis rather than using an established measure, we were able to examine worry domains without concerns about measures being content valid for both younger and older adults.

The present study identified both similarities and differences in older and younger adults’ experience of worry and top worry content domains. Future studies might further examine co-occurring anxiety and depressive disorders as well as distinct cases of anxiety and depression. Qualitative methods and the use of open-ended questions in future studies may also help elucidate older adults’ experience of and beliefs about worry and anxiety in general. Taken together, the current findings suggest that when assessing worry at a subthreshold level, one must also consider other negative affect states, particularly depression, when working with older adults. Specifically, these findings imply that providers should ask about sadness in the context of worry and worry in the context of sadness so that psychotherapeutic treatments can be targeted towards both symptoms. Additionally, providers should consider self-report, collateral report, or observation of symptoms of agitation, tension, and irritability, as important symptoms to further assess. These symptoms could be overlooked or could be considered to be unchangeable symptoms due to ageist beliefs about older adults as grumpy, cantankerous, and rigid rather than indicators of underlying anxiety and or depression.

Acknowledgements:

This work was supported by the WVU Department of Psychology Alumni Fund, the WVU Eberly College of Arts and Science, and a Biological Behavioral Science Research Award. Dr. Gould receives support from the United States Department of Veterans Affairs (IK2 RX001478) and from Ellen Schapiro & Gerald Axelbaum through a 2014 NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation. Gratitude is expressed to Melissa Shreve for assistance with data entry. Views expressed in this article are those of the authors and not necessarily those of the Department of Veterans Affairs or the Federal Government.

Contributor Information

Christine E. Gould, Department of Psychology, West Virginia University, Morgantown, WV, 26506, USA, Dr. Gould is now located at: Veterans Affairs Palo Alto Health Care System, Geriatric Research Education and Clinical Center, 3801 Miranda Avenue (182B), Palo Alto, CA 94304

Lindsay A. Gerolimatos, Department of Psychology, West Virginia University, Morgantown, WV, 26506, USA, Dr. Gerolimatos is now located at: Behavioral Health Services, MedOptions, 7 Saint Paul Street, Ste 820, Baltimore, MD 21202

Sherry A. Beaudreau, Veterans Affairs Palo Alto Health Care System, Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), 3801 Miranda Ave (161Y), Palo Alto, CA, USA 94304; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA; School of Psychology, University of Queensland, Brisbane, Australia

Nehjla Mashal, Veterans Affairs Palo Alto Health Care System, Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), 3801 Miranda Ave (161Y), Palo Alto, CA, USA 94304; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.

Barry A. Edelstein, West Virginia University, Department of Psychology, P.O. Box 6040, Morgantown, WV, USA 26506-6040

References

  1. American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders, DSM-IV-TR. Washington, DC: American Psychiatric Publishing. [Google Scholar]
  2. Basevitz P, Pushkar D, Chaikelson J, Conway M, & Dalton C (2008). Age-related differences in worry and related processes. International Journal of Aging & Human Development, 66(4), 283–305. [DOI] [PubMed] [Google Scholar]
  3. Brenes GA (2006). Age differences in the presentation of anxiety. Aging & Mental Health, 10(3), 298–302. 10.1080/13607860500409898 [DOI] [PubMed] [Google Scholar]
  4. Byers AL, Yaffe K, Covinsky KE, Friedman MB, & Bruce ML (2010). High occurrence of mood and anxiety disorders among older adults: The National Comorbidity Survey Replication. Archives of General Psychiatry, 67(5), 489–496. 10.1001/archgenpsychiatry.2010.35 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Carstensen LL, Isaacowitz DM, & Charles ST (1999). Taking time seriously. A theory of socioemotional selectivity. The American Psychologist, 54(3), 165–181. [DOI] [PubMed] [Google Scholar]
  6. Carstensen LL, Pasupathi M, Mayr U, & Nesselroade JR (2000). Emotional experience in everyday life across the adult life span. Journal of Personality and Social Psychology, 79(4), 644–655. [PubMed] [Google Scholar]
  7. Fresco DM, Mennin DS, Heimberg RG, & Turk CL (2003). Using the Penn State Worry Questionnaire to identify individuals with generalized anxiety disorder: a receiver operating characteristic analysis. Journal of Behavioral Therapy and Experimental Psychiatry, 34(3-4), 283–291. [DOI] [PubMed] [Google Scholar]
  8. Gaetano J. (2013). Holm-Bonferroni sequential correction: An EXCEL calculator (1.1) [Microsoft Excel workbook]. Retrieved from https://www.researchgate.net/publication/236969037_Holm-Bonferroni_Sequential_Correction_An_EXCEL_Calculator . doi: 10.13140/RG.2.1.4466.9927 [DOI] [Google Scholar]
  9. Goncalves DC, & Byrne GJ (2013). Who worries most? Worry prevalence and patterns across the lifespan. International Journal of Geriatric Psychiatry, 28(1), 41–49. 10.1002/gps.3788 [DOI] [PubMed] [Google Scholar]
  10. Gould CE, & Edelstein BA (2010). Worry, emotion control, and anxiety control in older and young adults. Journal of Anxiety Disorders, 24(7), 759–766. 10.1016/j.janxdis.2010.05.009 [DOI] [PubMed] [Google Scholar]
  11. Gould CE, Gerolimatos LA, & Edelstein BA (2015). Experimental examination of worry among older and young adults. International Psychogeriatrics / IPA, 27(7), 1177–1190. 10.1017/S1041610214000891 [DOI] [PubMed] [Google Scholar]
  12. Gross JJ, & John OP (2003). Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348–362. [DOI] [PubMed] [Google Scholar]
  13. Holm S. (1979). A simple sequential rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65–70. [Google Scholar]
  14. Hunt S, Wisocki P, & Yanko J (2003). Worry and use of coping strategies among older and younger adults. Journal of Anxiety Disorders, 17(5), 547–560. [DOI] [PubMed] [Google Scholar]
  15. Letamendi AM, Ayers CR, Ruberg JL, Singley DB, Wilson J, Chavira D, … Wetherell JL (2013). Illness conceptualizations among older rural Mexican-Americans with anxiety and depression. Journal of Cross-Cultural Gerontology, 28(4), 421–433. 10.1007/s10823-013-9211-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Lovibond PF, & Lovibond SH (1995). The structure of negative emotional states: comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behaviour Research and Therapy, 33(3), 335–343. [DOI] [PubMed] [Google Scholar]
  17. Lubin B, & Zuckerman M (1999). The Multiple Affect Adjective Check List-Revised (3rd ed.). San Diego, CA: Educational and Industrial Testing Service. [Google Scholar]
  18. McEvoy PM, Watson H, Watkins ER, & Nathan P (2013). The relationship between worry, rumination, and comorbidity: Evidence for repetitive negative thinking as a transdiagnostic construct. Journal of Affective Disorders, 151(1), 313–320. [DOI] [PubMed] [Google Scholar]
  19. McLaughlin KA, Borkovec TD, & Sibrava NJ (2007). The effects of worry and rumination on affect states and cognitive activity. Behavior Therapy, 38(1), 23–38. 10.1016/j.beth.2006.03.003 [DOI] [PubMed] [Google Scholar]
  20. McLaughlin KA, Mennin DS, & Farach FJ (2007). The contributory role of worry in emotion generation and dysregulation in generalized anxiety disorder. Behaviour Research and Therapy, 45(8), 1735–1752. 10.1016/j.brat.2006.12.004 [DOI] [PubMed] [Google Scholar]
  21. Meyer TJ, Miller ML, Metzger RL, & Borkovec TD (1990). Development and validation of the Penn State Worry Questionnaire. Behaviour Research and Therapy, 28(6), 487–495. [DOI] [PubMed] [Google Scholar]
  22. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, … Chertkow H (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. 10.1111/j.1532-5415.2005.53221.x [DOI] [PubMed] [Google Scholar]
  23. Pietrzak RH, Maruff P, Woodward M, Fredrickson J, Fredrickson A, Krystal JH, … Darby D (2012). Mild worry symptoms predict decline in learning and memory in healthy older adults: a 2-year prospective cohort study. The American Journal of Geriatric Psychiatry : Official Journal of the American Association for Geriatric Psychiatry, 20(3), 266–275. 10.1097/JGP.0b013e3182107e24 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Powers CB, Wisocki PA, & Whitbourne SK (1992). Age differences and correlates of worrying in young and elderly adults. Gerontologist, 32(1), 82–88. [DOI] [PubMed] [Google Scholar]
  25. Ruscio AM, Seitchik AE, Gentes EL, Jones JD, & Hallion LS (2011). Perseverative thought: A robust predictor of response to emotional challenge in generalized anxiety disorder and major depressive disorder. Behaviour Research and Therapy, 49(12), 867–874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Tully PJ, Cosh SM, & Baune BT (2013). A review of the affects of worry and generalized anxiety disorder upon cardiovascular health and coronary heart disease. Psychology, Health & Medicine, 18(6), 627–644. 10.1080/13548506.2012.749355 [DOI] [PubMed] [Google Scholar]
  27. Wetherell JL, Petkus AJ, McChesney K, Stein MB, Judd PH, Rockwell E, … Patterson TL (2009). Older adults are less accurate than younger adults at identifying symptoms of anxiety and depression. The Journal of Nervous and Mental Disease, 197(8), 623–626. 10.1097/NMD.0b013e3181b0c081 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Wuthrich VM, Johnco CJ, & Knight A (2014). Comparison of the Penn State Worry Questionnaire (PSWQ) and abbreviated version (PSWQ-A) in a clinical and non-clinical population of older adults. Journal of Anxiety Disorders, 28(7), 657–663. [DOI] [PubMed] [Google Scholar]
  29. Wuthrich VM, Johnco CJ, & Wetherell JL (2015). Differences in anxiety and depression symptoms: comparison between older and younger clinical samples. International Psychogeriatrics / IPA, 27(9), 1523–1532. 10.1017/S1041610215000526 [DOI] [PubMed] [Google Scholar]

RESOURCES