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A characterizing feature of many forms of psychopathology is a loss or absence of goal-directed behavior and/or a sense of direction in life, both of which are key components of sense of purpose. While prior research has identified sense of purpose as a protective factor for mental health more broadly, less is known about the relationship between personality disorders (PDs) and sense of purpose. This study aims to examine the relationships between ten DSM-IV PDs and sense of purpose. We will also examine associations between two other forms of psychopathology (depressive symptoms and alcohol dependence) and sense of purpose.

Disability is common in older adults, with 1 in 4 individuals over the age of 65 reporting a mobility disability and 1 in 10 reporting a cognitive disability (Okoro et al., 2018). Prior research suggests that mobility disability may increase the risk of cognitive decline, in part due to limited physical activity engagement and greater depressive symptoms (Chodosh et al., 2010; Lampinen & Heikkinen, 2003; Rosenberg et al., 2011; Yuenyongchaiwat et al., 2018). In addition, cognitive decline may increase the risk of mobility disability through similar mechanisms (Atkinson et al., 2010; Hartman et al., 2018). Well-being may be a protective factor that disrupts these bi-directional relationships, thereby reducing risk for comorbid mobility disability and cognitive decline in older adulthood. Specifically, research has shown that well-being may help increase engagement in physical activities and decrease depressive symptoms, two theorized mechanisms for documented associations between mobility disability and cognitive decline (Boyle et al., 2010; Kim et al., 2017; Lewis & Hill, 2021). Given the large number of older adults living with mobility and/or cognitive disability, it is crucial to better understand relationships between these two factors as well as the role of well-being in moderating these associations. This study aims to address this using two existing longitudinal datasets: Rush Memory and Aging Project (MAP; Bennett et al., 2018) and the Minority Aging Research Study (MARS; Barnes et al., 2012).

Prior research suggests that individuals who experience higher amounts of discrimination are more likely to report intentions of engaging in racial activism (Wilson et al., in preparation). However, it is unknown whether or how trait-level forgiveness may impact this relationship. Further, prior research has not examined the impact of trait-level forgiveness and discrimination on levels of activist purpose. Therefore, this study aims to examine the relationship between trait-level forgiveness and experiences of discrimination, as well as how both predict engagement with activism.

Prior research suggests that individuals who experience more discrimination may be more likely to engage in racial activism (Wilson et al., in preparation). Further, some evidence suggests that forgivingness may be linked to greater social justice commitment (Jankowski et al., 2013). However, it is unclear whether this would result in activism activity considering other work on the doormat effect, which describes a tendency for those high on forgivingness to avoid addressing transgressors to avoid future conflict. Therefore, this study aims to more formally test the relationships between discrimination, activism, and forgivingness by having participants read and react to a potential racial microaggression (a police stop), and examine their desire for activism following this activity.

Having a broadened perspective on one's future has been associated with better affective well-being, including reduced reports of depressive symptoms. However, research is limited regarding which aspect of future time perspective is associated with depressive symptoms, and whether these findings are consistent across individuals.The current study employed data from a nationally representative sample of Swiss adults (Perceived future time and future opportunities were uniquely predictive of depressive symptoms, even when controlling for chronological age and other covariates, though future opportunities held a stronger association with depressive symptoms. Limited evidence was found for moderation, though opportunities may matter more for predicting depressive symptoms among adults in worse health and those with fewer resources.Future time perspective appears moderately associated with depressive symptoms in adulthood, and researchers need to consider multiple aspects of future time perspective rather than as a unitary construct.

When Covid-19 struck the United States in early March, the typical lives to which people had grown accustomed rapidly changed as people were forced to adapt to their new normal. One of the drastic changes for many people was the novel necessity for the majority of communications, whether for business or pleasure, to be moved online. Video chatting services, such as Zoom and Google Hangout, bring with them a unique situation that provokes important questions regarding appearance satisfaction as users are put in an unusual situation of viewing themselves while they talk to others. With past research indicating that exposure to images of others can negatively influence personal body satisfaction in females (Fitzsimmons-Craft et al., 2014; Thompson, Heinbert, Altabe, & Tantleff-Dunn, 1999; Tiggemann & Slater, 2014), and social comparison is one of the main explanations for the negative association between exposure to media and body dissatisfaction (Fitzsimmons-Craft et al., 2014; Vartanian & Dey, 2013), the question becomes: What influence does video chat usage, and the constant opportunity for comparison, have on women’s appearance satisfaction? Furthermore, body surveillance, or the awareness of how one looks from another’s perspective (McKinley & Hyde, 1996), is consistently accessible as video chat users are able to see how others are viewing them in real time. With past social media research indicating that body surveillance moderates the association between photo investment and bulimia symptomology (Cohen et al., 2018), it is possible that people who experience higher levels of body surveillance while video chatting, may also show lower levels of appearance satisfaction. Finally, with other work indicating that comparing one’s appearance to a peer is more strongly associated with negative appearance satisfaction relative to comparison with celebrities (Fardouly, Pinkus, Vartanian, 2017), the context of the video calls becomes important to take into account. The current study will investigate the influence of video chat usage on appearance satisfaction, whether social comparison and body surveillance moderate the strength of these associations, and whether these associations differ as a function of video chat contexts.

Addendum of additional analysis submitted prior to beginning analyses.

Previous research has shown that having a purpose in life, a key component of well-being, is associated with healthier aging and longer survival. However, well-being is characterized by both stability and change across the lifespan. Levels of well-being and longitudinal changes in well-being have been found to have unique associations with physical health. The associations between longitudinal change in purpose in life and health outcomes are not yet known. In the planned research, we will use data from the Midlife in the United States (MIDUS) and Midlife in Japan (MIDJA) studies to examine associations between levels and longitudinal change in purpose in life on the one hand and self-reported general health and chronic health conditions on the other hand.

Examining associations between sense of purpose and financial planning for retirement

The current study investigated the associations between sense of purpose, purposeful retirement expectations, and retirement planning / attitudes.

Preregistration: Personality Beyond the Big Five This preregistration presents a secondary data analysis (Weston et al., 2019) of pooled data sets to test the relationship between autism characteristics as measured by the Autism Quotient Scale (AQ; Baron-Cohen et al., 2001) and measurements of personality beyond the Big Five in a large, age-diverse sample of individuals. Description Since Leo Kanner’s report in 1943, we have learned a great deal about autism. Most recently in the area, DSM-V brought about many changes to the diagnostic criteria and categorization of individuals with autism (American Psychiatric Association, 2013). Autism Spectrum Disorder (ASD) and Social Communication Disorder (SCD) came to replace categories formerly named Autistic Disorder, Asperger’s Syndrome, and Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS). Despite the change in classification, we continue to struggle with the immense heterogeneity of autism and the problems that presents for treatment. Such heterogeneity impedes the progress of clinical trials and evidence-based treatments (Masi et al., 2017). Suggestions have been made to create sub-groups in order to provide the best treatment for these individuals. A study utilized a two factor/three class approach to stratify such a diverse population. Despite being able to create three distinct subgroups, there was still heterogeneity within the subgroups (Georgiades et al., 2013). Another study identified four distinct subgroups of adults with elevated ASD characteristics using Big Five personality traits (Schwartzman et al., 2016). While these findings point towards evidence of multiple autisms with distinct phenotypic profiles (Tordjman et al., 2018), the authors discovered that a great deal of variability remained within the subgroups. Instead of seeing the variability as an impediment to research, it could be argued that variability could be used as leverage when focusing on the individual. In looking at the individual personality trait profiles, there may be patterns and groups that can be identified rather than predefining clusters and groups. This allows for the opportunity to analyze individual differences to create better treatment options for those with autism characteristics. Personality psychology provides the necessary framework to better understand the complex heterogeneity of autism characteristics. A targeted trait therapy could be beneficial for both clinicians and their clients. This focus on unique traits allows for a more personable and individualized treatment as opposed to wholesale, “one-size-fits-all” approaches. Rather than treating a generic diagnosis, clinicians would be able to treat their client for specific behaviors or symptoms to provide optimal, customizable care (Lengel et al., 2016). In the realm of personality psychology, many tend to solely rely on the traits known as the Big Five. Current research shows that ASD characteristics are associated with lower levels of the Big Five personality traits. However, despite seeing lower levels, that does not imply that the trait levels are homogenous in those with ASD. Further, modern personality psychology conceptualizes personality as far more than just the Big Five. Personality beyond the Big Five must be considered to comprehensively articulate the relationship between autism and the complex concept of personality. Such concepts include; attachment, Dark Triad, grit, alexithymia, goals, self-concept clarity, self-esteem, resilience, and purpose (Lodi-Smith et al., 2019). Understanding that personality is more than just the Big Five creates, “an integrative framework for understanding how every person is like all other persons, like some persons, and like no person” (McAdams & Pals, 2006, p. 215). The characteristic adaptations like the aforementioned ones contribute to our uniqueness, further exemplified through our personal narratives and culture (McAdams & Pals, 2006). Hypothesis Due to the lack of research in the area and where research does exist, conflicting findings, we will not create independent hypotheses for each of the personality measures. As the Big Five solely has dominated personality psychology, it is pertinent to explore other measures of personality. In doing so, we hope to help capture the nomological net of personality in the context of autism. Data The planned analyses will be conducted across pooled data (N = 739) from two online samples in which participants completed the AQ. Sample 1 is primarily comprised of undergraduate students and their family members (n = 372, Mage = 23.04, SDage = 23.04, age range = 18 - 63) who completed the AQ for course credit as part of studies by our research team investigating personality in the context of ASD. Sample 2 is primarily older adults (n = 367, Mage = 65.53, SDage = 14.82, age range = 18 - 97) who participated in a study of autism and aging funded by NIH Grant #R21 AG059051-01. Sample 2 participants were primarily recruited through paid advertisements and mailers and entered into a monthly drawing for $100 for their participation. All data was collected with approval of our institution’s IRB and met the APA ethical guidelines for human subjects research. All data is recorded and stored online via REDCap (Research Electronic Data Capture) electronic data capture tools hosted at Canisius College. REDCap is a secure, web-based application designed to support data capture for research studies, providing 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources (Harris et al., 2009). While the primary recruitment effort for the sample is complete, the surveys are not closed to the public at the point of preregistration and the final sample size included in the analyses may vary slightly from this estimate if new individuals participate or an individual skipped a target questionnaire. These data sets are not publically available at the time of preregistration. Data and code for the analyses described below will be posted to the parent OSF for this registration when presenting and submitting findings. Prior Knowledge of the Data & Prior Research Activity The authors have presented findings from this sample in the following manuscripts and at the following professional conferences: -Lodi-Smith, J., Rodgers, J.D., Kozlowski, K.F., Khan, S., Marquez Luna, V., Long, C., Donnelly, J.P., Lopata, C., & Thomeer, M.L. (under review). Autism characteristics and self-reported health in older adulthood. Under review at The Journals of Gerontology, Series B. -Lodi-Smith, J., Rodgers, J.D., Marquez Luna, V., Khan, S., Long, C., Kozlowski, K.F., Donnelly, J.P., Lopata, C., & Thomeer, M.L. (in press). The relationship of age to the Autism-Spectrum Quotient Scale in a large sample of adults. In press at Autism in Adulthood. -Rodgers, J.D., Lodi-Smith, J., Hill, P.H., Spain, S.M., Lopata, C., & Thomeer, M.L. (2018). Personality traits and self-concept clarity mediate the relationship between autism spectrum disorder characteristics and well-being. Journal of Autism and Developmental Disorders, 48, 307 – 315. -Lodi-Smith, J. & Rodgers, J.D. (2018, March). Autism Spectrum Disorder and Functional Personality Maturation across the Lifespan. Talk presented at the Personality Dynamics, Processes, and Functioning Preconference at the Society for Personality and Social Psychology, Atlanta, GA. -Lodi-Smith, J. & Rodgers, J.D. (2020, November). Desired personality trait change and autism spectrum disorder. Poster presented at the 2020 Geneva Centre for Autism Symposium (Virtual Symposium), Montreal. -Lodi-Smith, J., Rodgers, J.D., Khan, S., Long, C., Marquez Luna, V., Kozlowski, K., Donnelly, J.P., Lopata, C., & Thomeer, M.L. (2020, November). Autism characteristics and self-reported health in older adulthood. Poster presented at the 2020 Geneva Centre for Autism Symposium (Virtual Symposium), Montreal. -Lodi-Smith, J., Rodgers, J.D., Marquez Luna, V., Khan, S., Long, C., Kozlowski, K., Donnelly, J.P., Lopata, C., & Thomeer, M.L. (2020, November). The relationship of age to the Autism-Spectrum Quotient scale in a large sample of adults. Poster presented at the 2020 Geneva Centre for Autism Symposium (Virtual Symposium), Montreal. -Virginia, H.J., Brennan, S., Lodi-Smith, J., & Rodgers, J.D. (2018, April). The Relationship of Personal Variability to Symptoms and Outcomes in Autism Spectrum Disorder. Poster presented at the Canisius College 2018 Ignatian Scholarship Day, Buffalo, NY. -DiMayo, S., Rosenthal, M., Stoll, M.M., Virginia, H.J., Lodi-Smith, J., Rodgers, J.D., & the Canisius Identity Development Lab (2017, April). Individuals with high autism spectrum disorder characteristics evidence differences in self-defining memories. Poster presented at the Canisius College 2017 Ignatian Scholarship Day, Buffalo, NY. We have worked with data from these samples on the relationship between the AQ and age (https://osf.io/evh6f/); AQ and healthy aging (https://osf.io/nc3m7); and AQ, self-concept clarity, self-esteem, purpose, and Big Five traits in some of the student data (Rodgers et al., 2018). We are aware of the descriptive statistics for and relationship between variables used in these studies but not of the relationship between these variables and other measures of personality beyond the Big Five. Data already included in our prior work (Rodgers et al., 2018) will not be included in the present manuscript. A research assistant blind to study hypotheses and not involved with this preregistration or analyses has developed R scripts to extract data and descriptive statistics from REDCap but these have not been shared with the authors of this preregistration and no analyses beyond descriptive statistics have been conducted. The planned analyses are, therefore, novel. Moment of Preregistration All computations and analyses described below will occur after the submission of this preregistration. Measured Variables Demographic variables. Participant reports of age, gender, and ASD diagnostic status are included in the analysis plan as exploratory moderator variables. The lack of racial and ethnic diversity in the sample prohibits the inclusion of these demographic variables in moderation analyses. Racial and ethnicity data will be reported in the manuscript but will not be included in the final data set uploaded to OSF to protect the identity of the few minority participants in the samples. Autism Quotient Scale. The Autism-Spectrum Quotient scale (AQ; Baron-Cohen et al., 2001) quantified participants’ ASD characteristics. The AQ consists of 50 statements such as “I tend to have very strong interests, which I get upset about if I can’t pursue” and “I find social situations easy”. Participants responded to each statement from “Definitely Agree” (1) to “Definitely Disagree” (4). Following the AQ-Short scoring (Hoekstra et al., 2011), 28 items from the AQ will be used to compute five subscales with four of these subscales (social skills, routines, switching, and imagination) then being used to compute a higher-order index of social interaction and the remaining subscale indicating attention to detail. Alternative scoring may be requested by reviewers and so may eventually be included in analyses or supplementary results. The Experience in Close Relationships-Revised. Participants in the aging sample took the Experiences in Close Relationships-Revised (ECR-R; Fraley et al., 2000) to quantify their individual difference with respect to attachment-related anxiety and attachment-related avoidance. The ECR-R is a 36-item assessment that measures your level of anxiety and avoidance. For each item, the participant answered on a scale from “Strongly Disagree” (1) to “Strongly Agree” (7) to statements such as "I'm afraid that I will lose my partner's love". Dark Triad Scale. Participants in both the aging and student samples took the Short Dark Triad Scale (SD3; Jones & Paulhus, 2014) to quantify their Machiavellianism, Narcissism, and Psychopathy. The SD3 is a 27-item assessment that measures characteristics of the Dark Triad. For each item, the participant answered on a scale from “Strongly Disagree” (1) to “Strongly Agree” (5) to statements such as "It's not wise to tell your secrets". The Grit Scale (Duckworth & Quinn, 2009). Participants in the aging sample took the Grit Scale to quantify the tendency to sustain interest in and effort toward very long-term goals. The Grit is an eight-item assessment that measures your resiliency. For each item, the participant answered on a scale from “Not Like Me at All” (1) to “Very Much Like Me” (5) to statements such as "New ideas and projects sometimes distract me from previous ones." Toronto Alexithymia Scale (TAS-20). Participants in the aging sample took the Toronto Alexithymia Scale (TAS-20; Taylor et al., 1988) to test their Alexithymia levels. Alexithymia refers to people who have trouble identifying and describing emotions and tend to minimize emotional experiences and focus attention externally. The TAS-20 is a twenty-item assessment separated into three subsections that measure alexithymia in areas such as difficulty describing emotions, difficulty identifying emotions, and tendency to focus on their attention externally. For each item, the participant answered on a scale from “Strongly Disagree” (1) to “Strongly Agree” (5) to statements such as "I am often confused about what emotion I am feeling". HERI Life-goal Scale (Hill et al., 2010). Participants in both samples took the HERI life-goal scale to quantify their personal importance of 17 different life-goals ranging from prosocial, financial, creative, and personal recognition goals. The HERI life-goal scale is a seventeen-item assessment that measures how important you find these different goals. For each item, the participant answered on a scale from “Not Important” (1) to “Highly Important” (4) to statements such as "Participating in a community service program". Self-Concept Clarity Scale. Participants in the student and aging samples took the Self-Concept Clarity Scale (SCCS; Campbell et al., 1996) to quantify whether their self-beliefs are defined, consistent, and stable. The SCCS is a 12-item assessment that measures self-belief confidence. For each item, the participant answered on a scale from “Strongly Disagree” (1) to “Strongly Agree” (5) to statements such as "My beliefs about myself often conflict with one another.". Some student self-concept clarity data was included in prior work (Rodgers et al., 2018) and will not be included in the present analyses. Because the self-concept clarity scale is known to have some items that do not function well in all samples (Lodi-Smith & Roberts, 2010), principal components analysis will confirm whether or not all items will be included in the self-concept clarity scale. Rosenberg's Self-Esteem Scale. Participants in the student and aging samples took the Rosenberg's Self-Esteem Scale (Rosenberg, 1965) to quantify their self-esteem. The Rosenberg's Self-Esteem Scale is a 10-item assessment that measures a person's self-esteem. For each item, the participant answered on a scale from “Strongly Disagree” (0) to “Strongly Agree” (3) to statements such as "I feel that I have a number of good qualities". Some student self-esteem data was included in prior work (Rodgers et al., 2018) and will not be included in the present analyses. Resilience. Participants in the aging sample took the Brief Resilience Scale (BRS, Smith et al., 2008). The BRS is a six-item assessment that measures participant’s ability to adapt quickly in the face of stressors. For each item, the participant answered on a scale from “Strongly Disagree” (1) to “Strongly Agree” (5) to statements such as "I tend to bounce back quickly after hard times". Scheier Purpose Measure. Participants in the student and aging samples took the Scheier Purpose Measure (Scheier et al., 2006) to quantify their purpose in life. The Scheier Purpose Measure is a six-item assessment that measures a person's purpose in life based on the person's engagement in activities that are personally valued. For each item, the participant answered on a scale from “Strongly Disagree” (1) to “Strongly Agree” (5) to statements such as "There is not enough purpose in my life". Some student purpose data was included in prior work (Rodgers et al., 2018) and will not be included in the present analyses. The Personality Inventory for DSM-5 (PID-5). Participants in the aging sample took the Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012) to evaluate personality and related disorders based on the dimensional trait model. The PID-5 is a 25-item assessment separated into five domains that measure a person’s personality and related disorders. For each item, the participant answers on a scale from “Very False or Often False” (0) to “Very True or Often True” (3) to statements such as “I am often confused about what emotion I am feeling”. Data Inclusion/Exclusion Data that has been previously published will not be included in the present analyses. The only inclusion criterion is participation in one of the samples described above and completion of the AQ alongside the target personality measures. Sample Size & Power As we have yet to analyze the data at the writing of this pre-registration, we do not have an anticipated effect size targeted for power analyses. Based on known response rates in the samples, it is anticipated that the number of responses included in our study will be between 100 and 700 participants depending on the target personality measure. Two separate power analyses consisting of a significance of 0.05 and a power of .9, indicate that we can detect relationships of r = .32 and r = .12 respectively. Missing Data Complete data will be used pairwise with missing data excluded for those participants who did not respond to a specific questionnaire. Item-level missing data will be ignored by computing scores as the mean of scales rather than the sum. Analysis Plan All analyses will be conducted in R (R Core Team, 2018). Significance values will be reported for all analyses but no explicit inferences will be based on these values. Instead, judgments of effect will be based on the effect size estimates themselves using guidelines from Funder & Ozer (2019). Our exploratory analysis will first quantify the relationship between autism characteristics and personality measures. Exploratory analyses will test the extent to which age moderates these relationships. All variables will be standardized with AQ, age, and the interaction term of AQ and age entered into a multiple regression predicting each personality measure. We also plan to conduct a series of exploratory analyses to test the extent to which the relationship between autism characteristics and personality measures is moderated by the following demographic variables and sample characteristics: -Individuals who self-identify as having an ASD diagnosis compared to those who do not -Individuals with elevated AQ scores (≥ 26; Booth et al., 2013; Woodbury-Smith et al., 2005) compared to those with lower AQ scores -Gender These analyses will be conducted by computing the correlations within groups and comparing the magnitude of the correlation between groups using Fisher’s r-to-z transformations within psych::paired.r (Revelle, 2018). Sample size permitting, we may also compare the correlation matrix among personality measures between ASD and AQ groups including the correlation of target personality measures with Big Five measures. **N.B. Results from narrative identity analyses from the undergraduate sample were conducted and reported in a poster in 2017 (DiMayo et al., 2017). These analyses were conducted prior to our lab’s adoption of preregistration practices. Results from these analyses may be included in the planned manuscript. References American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Arlington, VA: American Psychiatric. Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The autism-spectrum quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 5-17. Booth, T., Murray, A. L., McKenzie, K., Kuenssberg, R., O’Donnell, M., & Burnett, H. (2013). Brief report: An evaluation of the AQ-10 as a brief screening instrument for ASD in adults. Journal of Autism and Developmental Disorders, 43, 2997-3000. Campbell, J. 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Investigating phenotypic heterogeneity in children with autism spectrum disorder: a factor mixture modeling approach. Journal of Child Psychology and Psychiatry, 54(2), 206-215. Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap): A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42, 377-381. Hill, P. L., Burrow, A. L., Brandenberger, J. W., Lapsley, D. K., & Quaranto, J. C. (2010). Collegiate purpose orientations and well-being in early and middle adulthood. Journal of Applied Developmental Psychology, 31(2), 173-179. Hoekstra, R. A., Vinkhuyzen, A. A., Wheelwright, S., Bartels, M., Boomsma, D. I., Baron-Cohen, S., Posthuma, D., & van der Sluis, S. (2011). The construction and validation of an abridged version of the autism-spectrum quotient (AQ-Short). Journal of Autism and Developmental Disorders, 41, 589-596. Jones, D. N., & Paulhus, D. L. (2014). Introducing the short dark triad (SD3) a brief measure of dark personality traits. Assessment, 21(1), 28-41. Krueger, R. F., Derringer, J., Markon, K. E., Watson, D., & Skodol, A. E. (2012). Initial construction of a maladaptive personality trait model and inventory for DSM-5. Psychological Medicine, 42(9), 1879. Lengel, G. J., Helle, A. C., DeShong, H. L., Meyer, N. A., & Mullins‐Sweatt, S. N. (2016). Translational applications of personality science for the conceptualization and treatment of psychopathology. Clinical Psychology: Science and Practice, 23(3), 288-308. Lodi‐Smith, J., & Roberts, B. W. (2010). Getting to know me: Social role experiences and age differences in self‐concept clarity during adulthood. Journal of Personality, 78(5), 1383-1410. Lodi-Smith, J., Rodgers, J. D., Cunningham, S. A., Lopata, C., & Thomeer, M. L. (2019). Meta-analysis of Big Five personality traits in autism spectrum disorder. Autism, 23(3), 556-565. Masi, A., DeMayo, M. M., Glozier, N., & Guastella, A. J. (2017). An overview of autism spectrum disorder, heterogeneity and treatment options. Neuroscience bulletin, 33(2), 183-193. McAdams, D. P., & Pals, J. L. (2006). A new Big Five: fundamental principles for an integrative science of personality. American psychologist, 61(3), 204. R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Revelle, W. (2018). psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA, https://CRAN.R-project.org/package=psych Version = 1.8.12. Rodgers, J. D., Lodi-Smith, J., Hill, P. H., Spain, S. M., Lopata, C., & Thomeer, M. (2018). Personality traits and self-concept clarity mediate the relationship between autism spectrum disorder characteristics and well-being. Journal of Autism and Developmental Disorders, 48, 307-315. Rosenberg, M. (1965). Rosenberg self-esteem scale (RSE). Acceptance and commitment therapy. Measures package, 61(52), 18. Scheier, M. F., Wrosch, C., Baum, A., Cohen, S., Martire, L. M., Matthews, K. A., ... & Zdaniuk, B. (2006). The life engagement test: Assessing purpose in life. Journal of behavioral medicine, 29(3), 291. Schwartzman, B. C., Wood, J. J., & Kapp, S. K. (2016). Can the five factor model of personality account for the variability of autism symptom expression? Multivariate approaches to behavioral phenotyping in adult autism spectrum disorder. Journal of autism and developmental disorders, 46(1), 253-272. Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Bernard, J. (2008). The brief resilience scale: assessing the ability to bounce back. International journal of behavioral medicine, 15(3), 194-200. Taylor, G. J., Bagby, R. M., Ryan, D. P., Parker, J. D., Doody, K. F., & Keefe, P. (1988). Criterion validity of the Toronto Alexithymia Scale. Psychosomatic medicine, 50(5), 500-509. Tordjman, S., Cohen, D., Coulon, N., Anderson, G. M., Botbol, M., Canitano, R., & Roubertoux, P. L. (2018). Reframing autism as a behavioral syndrome and not a specific mental disorder: Implications of genetic and phenotypic heterogeneity. Neuroscience and Biobehavioral Reviews, 89, 132-150. Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. K. (2019). Recommendations for increasing the transparency of analysis of preexisting data sets. Advances in Methods and Practices in Psychological Science, 2(3), 214-227. Woodbury-Smith, M. R., Robinson, J., Wheelwright, S., & Baron-Cohen, S. (2005). Screening adults for Asperger syndrome using the AQ: A preliminary study of its diagnostic validity in clinical practice. Journal of Autism and Developmental Disorders, 35, 331-335.

A cross-sectional investigation into whether and how having a sense of purpose in life may help promote health behaviour during the pandemic context

Difficulties in self-regulation of cognition and behavior can impede adaptation to ongoing stressors (Vohs & Baumeister et al., 2016). A core mechanism that may explain poor self-regulatory abilities is having a sense of purpose. A sense of purpose is thought to motivate an individual to apply efforts toward personally relevant goals (Kashdan & McKnight, 2009). However, very little is understood about the role of purpose in implementing self-regulation. The aim of this study was to investigate how intra and inter-individual differences in a sense of purpose may influence self-regulation. Past work suggests that having a purpose can impact cognitive and behavioral processes in daily life (Kashdan & McKnight, 2009). Consequently, individual differences in purpose levels may influence self-regulation of cognition and behavior to adapt to daily stressors. The current study examines how weekly variations in purpose and self-regulation are associated. Difficulties in self-regulation were assessed by asking participants to think about their weekly stressors and report how much they were ruminating and avoiding negative experiences (maladaptive self-regulation of thoughts and emotions). They also reported difficulties in initiating and implementing problem solving (maladaptive self-regulation of behavior). Each week, participants were specifically asked to report how purposeful they felt. A trait measure of sense of purpose was also assessed. These data were collected from a sample of 200+ undergraduates who were sampled once a week for 13 weeks in their first semester of college.

The current project is evaluating how the Big Five personality traits are associated with video chat usage, the main form of communication for most following the spread of Covid-19, both in the amount of time spent and the behaviors enacted.

In this study, we will be exploring the associations between depressive symptoms, a sense of purpose in life, and reactions to the COVID-19 campus shutdowns.

The connection between sense of purpose and health is a robust one, with higher sense of purpose levels predicting better cognitive, physical, and mental health outcomes (Pfund & Lewis, 2020). Those who report feeling that they have a greater sense of direction in life (i.e., a higher sense of purpose; Ryff, 1989) are at lower risk for cardiovascular events (Cohen et al., 2016; Kim et al., 2013a), stroke (Kim et al., 2013b), and even death (Boyle et al., 2009; Hill & Turiano, 2014). However, while the findings surrounding purpose and health are salient, the mechanisms for the associations are not fully known. Some cross-sectional research has found that people with a higher sense of purpose are more likely to engage in health behaviors like eating vegetables, flossing, and exercising (Hill et al., 2019; Hooker & Masters, 2016). Moreover, longitudinal work using three waves of data has found that sense of purpose predicts physical activity over time, though physical activity does not predict later purpose (Zhang & Chen, 2021). Though this prior study was valuable in establishing these relationships over time, the measurement occasions were four years a part, preventing the nuanced understanding of the connection of these constructs that would come from shorter time periods between waves. Furthermore, these participants were from the Health and Retirement Study, which is mainly an older adult sample. In fact, research on health behaviors to this point have focused either exclusively on older adults (Hill et al., 2019; Kim et al., 2020; Zhang & Chen, 2021) or college students (Hookers & Masters, 2016). Thus, the current study will be addressing the gaps in the literature in three primary ways. First, participants filled out reports on their sense of purpose and reports on physical activity (average daily minutes of both moderate and vigorous) at the monthly level, allowing for a shorter-term, and likely more accurate perspective in answering this question. Second, the current study will utilize a more sophisticated analytic approach by conducting a random intercept cross-lagged panel model, which assures the disaggregation of within-person processes from between-person differences (Hamaker et al., 2015). Third, this sample has a wide age range of participants, allowing us to test whether age moderates the associations between sense of purpose and physical activity.

Worldwide efforts to promote healthy aging have increased in recent years, given the longer life expectancies. The current volume was organized in order to discuss how personality science may be employed in these efforts. In this introduction, we discuss the previous efforts to link personality constructs to the promotion of healthy aging. In so doing, we set the stage for the remaining chapters that target specific topics along this front.

Research has made great progress in recent years to better understand how individual differences predict consequential healthy aging outcomes and why and when individual differences may matter in everday life. This final chapter integrates and discusses the contributions in this volume around three broad sections. The first section relates to “new” constructs beyond the Big Five personality traits. The second section discusses “new” assessment and analytical methods. Finally, the third section refers to “new” questions in the field of personality and healthy aging.

The current study will investigate the associations between vocational interests and purpose in life among German emerging adults. Data for this work comes from the long-running TRAIN study run by the University of Tübingen (https://uni-tuebingen.de/en/faculties/faculty-of-economics-and-social-sciences/subjects/department-of-social-sciences/education-sciences-and-psychology/research/aktuelle-studien/train/).

Personality traits are increasingly being considered as useful tools in applied settings, including education, health, industrial psychology, and economics. The initial use of personality traits in applied settings has been predicated on their ability to predict valued outcomes. Most of these initial efforts have focused on using traits under the assumption that traits are functionally unchanging. The assumption that traits are unchanging is both untrue and a limiting factor on using personality traits more widely in applied settings where the emphasis is on both selection and development. To address the misconceptions concerning personality trait change, we address seven related questions surrounding the stability and change of personality traits and their relevance to interventions. In so doing, we present a case that traits can serve both as predictors of success in applied settings, as well as potential intervention targets across different domains. Though trait change will likely prove a more difficult target outcome than typical targets in applied interventions, it also may be a more fruitful one given the variety of life domains affected by personality traits.

Income inequality gained increasing attention in public discourse. Promoting upward mobility is a potential solution to income inequality. The current study tested whether upward mobility predicts greater well-being, whether upward mobility attenuates the negative effects of income inequality, and whether gender differences in upward mobility differentially predict well-being for men and women. Upward mobility was operationalized as changes in income rank across generations for families in the lowest income quartile. In a pre-registered study on 917,331 US workers, results supported neither the main effect of upward mobility nor the moderating role of upward mobility on the association between income inequality and life satisfaction. Gender differences in upward mobility did not consistently predict well-being of men or women. The null results were robust across measures of well-being, measures of upward mobility, and different analytical strategies. The results consistently indicated that regional upward mobility may have little to no association with well-being.

The inclusion of psychosocial variables into electronic health records provides a unique opportunity for the translation of findings from social, psychological, and behavioral domains into patient care. This commentary is a response to the recommendations of a committee convened by the Institute of Medicine to address this opportunity (Matthews, Adler, Forrest, & Stead, 2016). We concur with the committee that the inclusion of psychosocial variables in electronic health records will broadly benefit researchers, practitioners, and patients and that there is clear need for a recommended panel of psychosocial measures that is ready for implementation in clinical settings. In fact, it seems likely that these recommendations will have lasting consequences. Given this, our response highlights several concerns about the recommendations and criteria. We suggest further clarification of the audience for these recommendations, reconsideration of the overly restrictive inclusion criteria, and more extensive engagement of psychosocial researchers to achieve broader consensus. (PsycINFO Database Record

Cognitive complaints and engagement in cognitive activities are two consistent predictors of cognitive aging outcomes, including risk for nonnormative decline. Though research has considered predictors of complaints and engagement in general, little work has attended to the fact that these fluctuate at the daily level. The current study examined individual difference predictors of means and variability for engagement and complaints across 10 days in a sample of older adults (n = 136; Mage = 70.45 years). When comparing personality traits to indicators of cognitive performance, personality differences appeared better unique predictors for these measures of daily cognitive life. Specifically, even when accounting for demographics, measures of cognitive performance, and the other personality traits investigated, older adults higher on openness to experience reported fewer daily cognitive complaints and more engagement on average, as well as greater daily variability in engagement. In addition, higher neuroticism predicted greater variability in reports of cognitive complaints across days. Implications are discussed with respect to how these findings advance our understanding of cognitive complaints and engagement in daily life. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Being securely attached and willing to forgive your partner tends to promote greater relationship success. Though attachment and partner forgiveness are associated cross-sectionally, research has yet to investigate whether and how these positive relationship factors tend to codevelop over time. The current study examined cross-lagged effects and correlated changes in partner forgivingness and attachment across a 2-year period with two measurement occasions ( n = 514 individuals). Additionally, dyadic analyses were conducted with a subsample of dyads in the study ( n = 149 dyads). Individual level analyses evidenced negative cross-sectional and longitudinal associations between attachment-anxiety and forgivingness. Attachment-avoidance and forgivingness showed significant correlated changes over time. Dyadic level analyses showed that attachment-avoidance predicted partner forgivingness 2 years later but not vice versa. Findings suggest that longitudinal associations between attachment and forgivingness may take different forms at the individual and dyadic level.

Both mobility and personality are key determinants of healthy aging. However, these two constructs have barely been explored in combination, although mobility and personality effects on healthy aging are expected to not be independent from another. This chapter aims at combining both perspectives and setting a foundation to foster future research, jointly investigating personality and mobility effects on healthy aging. Therefore, the chapter suggests to decompose mobility in the two components motility (i.e., the movement potential) and movement (i.e., the actual manifested mobility). This decomposition allows to draw parallels to the commonly used distinction between personality traits and states. While motility and personality traits refer to the temporally stable underlying dispositions of an individual, movement and personality states conceptualize the day-by-day manifestation of the respective construct. Drawing upon the parallels regarding the distinct levels of analysis in both domains, a conceptual model is proposed that links the individual components with healthy aging. The individual links are discussed using relevant empirical research and theories and hypothesizing potential causal pathways between mobility, personality and healthy aging.

As proposed by the healthy aging model of the World Health Organization (2015), participation in social and cognitive activities is important for healthy aging and for understanding individual differences in personality and health trajectories. This chapter introduces a naturalistic observation method for assessing social and cognitive activities in everyday life: Electronically Activated Recorder (EAR) – a portable audio recorder that periodically and unobtrusively records ambient sounds and speech in everyday life. Using this method, researchers have reliably and objectively measured social activities (e.g., conversing, engaging in small talk or substantive conversations) and cognitive activities (e.g., reminiscing, planning the future, grammatical complexity) in everyday life. We reviewed studies that examined interindividual and intraindividual differences in these activities. Furthermore, we discussed how this behavioural evidence could help to understand personality and health in old age. In sum, the EAR method offers useful real-life, personality-related data for the healthy aging literature.

Though dispositional forgiveness has been associated with affective well-being, it remains unclear whether these associations are consistent throughout adulthood. The current study investigated whether forgivingness interacted with chronological age or future time perspective to predict affect at the trait and daily level. Participants (n = 332, mean age: 45.5 years) completed baseline measures of forgivingness, positive and negative affect, and future time perspective, along with daily assessments of positive and negative affect for up to ten days. Results suggest that the associations between forgivingness and affective well-being differ somewhat based on age and future time perspective, and level of analysis.

The current study focused on three aspects of identity development relevant to the adolescent years: being an authentic person, perceiving control over and consistency in one's environment, and having consistent expectations from close others. In a two-wave study of adolescents (n = 750), we examined how these aspects change over the course of a year, as well as whether these aspects correspond to the Big Five personality traits. Results indicated three important findings. First, all three aspects evidenced the capacity for change over a year, and appeared more malleable than personality traits. Second, youth higher on all aspects reported a more adaptive personality profile. Third, changes on these aspects coincide with those on personality traits over the year. Findings are discussed with respect to future directions for studying the interplay of identity and personality development.

The current study examined whether dispositional gratitude predicts physical health among adults, and if so, whether this relationship occurs because grateful individuals lead healthier lives, either psychologically or physically. Specifically, we examined whether psychological health, healthy activities, and willingness to seek help for health concerns mediated the link between gratitude and self-reported physical health, as well as if these mediational pathways are moderated by age, in a broad sample of Swiss adults (N = 962, M(age) = 52 years, age range: 19 to 84). Dispositional gratitude correlated positively with self-reported physical health, and this link was mediated by psychological health, healthy activities, and willingness to seek help for health concerns. However, the indirect effects for psychological health and healthy activities were stronger for older than younger adults. In other words, the mechanisms explaining why gratitude predicts health appear to differ across adulthood.

The current studies tested possible explanations for the link between conscientiousness and forgivingness. Using two Swiss adult samples, we examined three reasons why conscientious people tend to be more dispositionally forgiving. Findings suggest that self-regulation ability served as the best explanation for this relationship. Conscientious individuals tend to be better at self-regulation, which in turn enables them to be more forgiving of others. Moreover, this explanation only holds when discussing the link between forgivingness and conscientiousness, and not with respect to why agreeable and emotionally stable participants are more forgiving. Findings are discussed with respect to the role of regulatory processes in explaining the linkages between broad personality dimensions and forgivingness.

The field of positive psychology has sparked significant interest for researchers, in part given the apparent potential for individuals higher on “positive” dispositions to experience better health and well‐being. However, as the field has grown, so too have the number of conceptually similar dispositions identified by researchers as important to study. As such, there is an increasing need for researchers to understand whether and how conceptually similar “positive” dispositions are actually unique, an issue that may not be unique to positive psychology but has worsened with the field's prominence. The current manuscript provides a roadmap for one approach to differentiating conceptually close constructs in psychology, with examples couched within positive psychology. We will discuss the importance of combining quantitative and qualitative inquiries, as well as the adoption of techniques from multiple psychology disciplines, in order to better distinguish characteristics frequently studied in positive psychology.