Developmental Perspectives on Transitions at Age 60 : Individuals Navigating Across the Lifespan (TRAILS) – latest data collection in a longitudinal JYLS study

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/ Developmental Perspectives on Transitions at Age 60 : Individuals Navigating Across the Lifespan (TRAILS) – latest data collection in a longitudinal JYLS study © 2024 the Authors Published version Kokko, Katja; Fadjukoff, Päivi; Reinilä, Emmi; Ahola, Johanna; Kinnunen, MarjaLiisa; Kroger, Jane; Laakkonen, Eija K.; Pitkänen, Tuuli; Pulkkinen, Lea; Rantanen, Taina; Staudinger, Ursula M.; Taipale, Sakari; Törmäkangas, Timo; Kekäläinen, Tiia; Saajanaho, Milla Kokko, K., Fadjukoff, P., Reinilä, E., Ahola, J., Kinnunen, M.-L., Kroger, J., Laakkonen, E. K., Pitkänen, T., Pulkkinen, L., Rantanen, T., Staudinger, U. M., Taipale, S., Törmäkangas, T., Kekäläinen, T., & Saajanaho, M. (2024). Developmental Perspectives on Transitions at Age 60 : Individuals Navigating Across the Lifespan (TRAILS) – latest data collection in a longitudinal JYLS study. Longitudinal and Life Course Studies, 15(2), 251-281. https://doi.org/10.1332/17579597Y2023D000000009 2024 1 Longitudinal and Life Course Studies • vol XX • no XX • 1–31 • © Authors 2024 Online ISSN 1757-9597 • https://doi.org/10.1332/17579597Y2023D000000009 Accepted for publication 14 December 2023 • First published online 24 January 2024 This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license (http://creativecommons.org/licenses/by-nc-nd/4.0/). STUDY PROFILE Developmental Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan (TRAILS) – latest data collection in a longitudinal JYLS study Katja Kokko, katja.r[email protected] Päivi Fadjukoff, paivi.f[email protected] Emmi Reinilä, emmi.e[email protected] Johanna Ahola, [email protected] University of Jyväskylä, Finland Marja-Liisa Kinnunen, [email protected] University of Eastern Finland, Finland Jane Kroger, jane[email protected] UiT: The Arctic University of Norway, Norway Eija K. Laakkonen, [email protected] University of Jyväskylä, Finland Tuuli Pitkänen, [email protected] Finnish Youth Research Society, Finland Lea Pulkkinen, lea.r[email protected] Taina Rantanen, taina.r[email protected] University of Jyväskylä, Finland Ursula M. Staudinger, [email protected] Technische Universität Dresden, Germany Sakari Taipale, sakar[email protected] Timo Törmäkangas, timo.tor[email protected] Tiia Kekäläinen, [email protected] Milla Saajanaho, [email protected] University of Jyväskylä, Finland Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 2 At around age 60, people are approaching late adulthood and are typically going through or anticipating life transitions such as grandparenthood, retirement, or changes in health and functioning. The timing and perception of transitions are individual and based on current circumstances and earlier life history and may link to well-being. The TRAILS (Developmental Psychological Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan) study, which is presented in the current article, examines the diversity and underlying factors of different transitions at around age 60 and how they associate with mental well-being. It also investigates whether these transitions link to personality characteristics, contextual resources, and/or societal challenges. The role of earlier life history in the studied associations requires a prospective multiwave design where the same participants are followed over time. Only a few longitudinal studies have examined the developmental pathways from childhood to the beginning of late adulthood. The TRAILS study continues the Jyväskylä Longitudinal Study of Personality and Social Development (JYLS). The JYLS was initiated in 1968 and includes earlier data collected from ages 8 to 50. At age 61, in 2020–21, 206 of the JYLS participants (of the initial 369 children) took part in TRAILS. The data collection included a Life Situation Questionnaire, a psychological interview, self-report inventories, a health examination and physical activity surveillance covering major areas of adult life. TRAILS extends the JYLS study to over 52 years of follow-up time and provides unique opportunities for studying individual development throughout the lifespan. Keywords late adulthood • lifespan • longitudinal study • well-being • personality Key messages • Around age 60, people approach late adulthood and typically go through or anticipate transitions. • The timing of transitions is based on current circumstances and earlier life history and link to well-being. • Few longitudinal studies have examined development from childhood to late adulthood. • The JYLS is over 52 years’ follow-up and provides unique opportunities for studying development. To cite this article: Kokko, K., Fadjukoff, P., Reinilä, E., Ahola, J., Kinnunen, M.-L., Kroger, J., Laakkonen, E.K., Pitkänen, T., Pulkkinen, L., Rantanen, T., Staudinger, U.M., Taipale, S., Törmäkangas, T., Kekäläinen, T. and Saajanaho, M. (2024) Developmental Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan (TRAILS) – latest data collection in a longitudinal JYLS study, Longitudinal and Life Course Studies, XX(XX): 1–31, DOI: 10.1332/17579597Y2023D000000009 Introduction Traditionally, around age 60 has been considered to mark the end of a developmental period referred to as ‘middle adulthood’ and the beginning of ‘late adulthood’ (Lachman et al, 2015). This is a time when most people begin to anticipate or have already experienced life transitions concerning grandparenthood and changes in work and leisure time, combined with changes in one’s own, a spouse’s or ageing Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 3 parents’ health and functioning. These transitions may require that more resources are directed towards the maintenance of functioning and the regulation of the losses (Baltes, 1997), but they also may lead to successful transition into role patterns that enable individuals to enjoy new roles and experience high levels of mental wellbeing (Wang and Shi, 2014; Infurna et al, 2020). Further, because people currently live healthier for longer than in previous decades, life around age 60 may actually be characterised by fewer or even unparalleled role transitions and, consequently, indicate no major changes in life situation and mental well-being. In any case, the transition or the anticipation thereof may urge the individuals to reflect upon their current situation and to prepare for the future (Kornadt et al, 2015; 2018) to maximise their well-being thereafter (Noone et al, 2009). In the TRAILS (Developmental Psychological Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan1) study, which is presented in the current article, we examine whether the transition into new roles of late adulthood or their anticipation occurs at around age 60 and whether they bring satisfaction or compromise well-being (Figure 1). Mental well-being, including both positive and negative dimensions (Keyes, 2005; Kokko et al, 2013), when approaching late adulthood is assumed to contribute to well-being in later years. We expect much variation in the timing and manner in which individuals navigate through these role transitions. These may be due to individual characteristics such as personality (traits, attitudes and coping mechanisms, for example), availability of support within the individual’s environment (such as relationships and financial resources), or due to the individual’s adjustment to societal challenges (including digitalisation and attitudes towards population ageing). The development of individual differences is a lifelong process rooted in childhood experiences (Moffitt et al, 2017). However, few longitudinal studies are available that actually test this assumption by using information from childhood to the threshold of late adulthood. TRAILS extends the Jyväskylä Longitudinal Study of Personality and Social Development (JYLS), which was initiated in 1968 with 8-year-old participants, to a new data wave in 2020–21 among its currently 60–61-year-old participants (hereafter 61). Thus far, JYLS includes follow-ups ranging from age 8 to age 50. Only a few lines of research on the developmental pathways from age 8 to 50 and in mid-adulthood development are highlighted here. First, personality demonstrates considerable stability during young and middle adulthood (Kokko et al, 2015) and significant but weaker stability from childhood into mid-adulthood (Pulkkinen et al, 2012). Individuals’ identity status develops towards an achieved status from age 27 to 50 (Fadjukoff et al, 2016). Second, personality contributes to functioning in many areas of life. From childhood to adulthood, the links are indirect (Kokko and Pulkkinen, 2000). In mid-adulthood, personality traits as such associate with parenting (Rantanen et al, 2015), self-assessed health (Kinnunen et al, 2012), occupational well-being (Mäkikangas et al, 2015), and leisure-time physical activity (Karvonen et al, 2020). Third, at ages 36 to 50, adults have a high level of mental well-being – composed of emotional, psychological and social well-being, and marked by the absence of depressive symptoms (Kokko et al, 2013; 2015). Continuing JYLS, TRAILS examines the beginning of a new developmental phase and its transitions with respect to work, leisure time, family and health. The present main aim of TRAILS is to study during the transition to late adulthood: Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 4 1. how the experience of mental well-being evolves; 2. how personality characteristics evolve from childhood; 3. how current societal transformations, such as digitalisation and attitudes towards population ageing, evolve and relate to mental well-being; 4. how retirement or its anticipation, grandparenthood, leisure-time activities, and an increased concern over health link to mental well-being; 5. how future orientation links with experienced or anticipated life transitions and whether personality characteristics underlie these associations. With previously collected JYLS data, TRAILS allows for the study of a broader range of research questions. The purpose of the current article is to describe the TRAILS data collection and methods, as well as the representativeness of the study participants in relation to their respective Finnish age-cohort (born in 1959) and to those participants of earlier JYLS data collections who did not participate in TRAILS. Methods Study design and sample TRAILS continues JYLS, a longitudinal study that was initiated in 1968 and led until 2012 by Lea Pulkkinen. Katja Kokko has led JYLS since 2013 and is the principal investigator of TRAILS. Initially 369 participants (173 girls and 196 boys, all native Finns of whom 94% were born in 1959, 4% in 1958, and 3% in 1960) from 12 randomly selected second grade school classes located in Central Finland took part in the study (Pulkkinen, 2017). All children in these classes participated and, therefore, there was no initial attrition. Since then, the major data collections of JYLS have taken place at ages 8 (in 1968), 14 (1974), 27 (1986), 33 (1992), 36 (1995), 42 Figure 1: The study will focus on individuals transitioning into late adulthood from a longitudinal perspective Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 5 (2001) and 50 (2009). Between these major waves, some subsample data collections have been conducted. The participation rate in JYLS has remained high throughout the decades, being 85% for women and 83% for men, calculated from the eligible sample, in the previous data collection in 2009. Throughout the years, those who have participated in the study have been representative of the initial random sample and the respective Finnish age-cohort (Pulkkinen, 2017). For TRAILS, we recruited all eligible participants of the JYLS at the beginning of 2020 (Figure 2). By then, 28 participants had died (8 women and 20 men) and 37 had withdrawn their consent for participation (22 women and 15 men), making the possible sample size 304 participants (143 women and 161 men). The postal information of the possible participants was updated from the Finnish Population Information System, leaving two men and one woman without contact information. Therefore, the eligible study sample was 301 participants (142 women and 159 men). About two thirds of these participants lived in Central Finland and the rest in other parts of Finland and abroad. Ethics The TRAILS data collection was approved on 13 December 2019 by the Ethical Committee of the University of Jyväskylä (JYU), Finland. All data was collected and stored in accordance with the General Data Protection Regulation (GDPR). The participants gave their written informed consent for participation and for storing the data collected about them. They could freely decide in which parts of the study they would participate. Recruitment process and inclusion criteria On 11 February 2020, the eligible participants were sent a letter in which they were informed of the new data collection. The letter included a Life Situation Questionnaire (LSQ) and a written informed consent form, which they were asked to fill in and return via mail. After that, we contacted the participants by phone, and, depending on the participants’ consent, scheduled the psychological interview and/or health examination. A repeat invitation letter was sent to those who had not responded in April 2020 (n = 130) and a second repeat letter in October 2020 (n = 85). There were no exclusion criteria for participation, and all willing participants were included in the study. The influence of the COVID-19 pandemic on the data collection and study aims On 16 March 2020, the government of Finland (Finnish Government, 2020) declared the state of emergency due to the outbreak of the COVID-19 pandemic. Because of this, the health examinations were discontinued, and the psychological interviews were continued via video conference program (Zoom Cloud Meetings, CSC/Funet; implemented through NORDUnet in compliance with Finnish law and European data protection regulations) or telephone from 6 April 2020 forward. Fourteen participants had been investigated by the time that data collection was discontinued. Additional questions related to the COVID-19 situation were added to the data collection protocol. The health examinations were continued on 1 June Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 6 2020, and the psychological interviews were conducted both live and via video conference program from July 2020 onwards, depending on the participants’ request of the mode of the interview. The last interview was conducted 1 July 2021 and the last health examination 19 April 2021. Study flow Of the 301 participants to whom the invitation letter was sent, 206 (107 women, 99 men) answered by filling in the informed consent form and the LSQ (Figure2). The participation rates were, for women and men, 75% and 62% of the eligible sample and 62% and 51% of the initial sample. Additionally, seven people advised that they could not participate in the study, and six withdrew their consent of the JYLS study altogether. Of the 206 respondents, 185 (97 women, 88 men) participated in the psychological interview. A total of 171 (89 women, 82 men) participated in the health examination. Moreover, 142 (78 women, 64 men) participants provided valid physical activity data. JYLS 1968 n=369 Non-respondents Not reached n=82 Withdrew consent n=6 Not interested n=1 Not able due to illness or life situation=6 Recruited to TRAILS in 2020 n=301 Excluded Deceased n=28 Withdrew consent n=37 Lacking contact information n=3 Respondents n=206 Life situation questionnaire n=206 Psychological interview n=185 - 47 face-to-face interviews - 125 video conference interviews - 13 telephone interviews Health examination n=171 - 158 health examinations - 13 telephone health interviews Recruited for physical activity monitoring n=179 Declined and non-compliance n=37 - Declined n =30 - Returned the device without use n=2 - Insufficient wear time n =4 - Not returned the device n=1 Valid physical activity data n=142 Figure 2: Study flow of TRAILS Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 7 Representativeness of the study participants The TRAILS participants were compared to the Finnish population born in 1959 (total N = 71,547; data received from the Finnish Population Information System in September 2021) using the newest information that was available for each variable (from years 2018–20) (Table 1) and to the participants of JYLS who did not participate in TRAILS (Tables 2 and 3). In line with the fact that more men (10% of the initial sample) than women (5%) had died, women were overrepresented in TRAILS in comparison to non-participants of the initial study sample of JYLS (52% at TRAILS versus 41% at the initial JYLS sample, p = .029) and, therefore, the analyses were conducted separately for women and men. There was no difference in the mortality rate between the TRAILS participants and the respective Finnish age-cohort. In comparison to the population cohort, the TRAILS women were more likely to have a vocational college education (bachelor’s level) and less often a vocational school education (lower secondary level) (Table 1). The TRAILS men were more likely to be married and have children than the population cohort men. The employment situation of the TRAILS participants was representative of the respective population cohort. We acknowledge that some of the statistically non-significant differences between the TRAILS participants and the Finnish age-cohort group might be due to a lack of statistical power (Table 1). However, it is worth noting that the frequencies shown in Table 1 are quite similar for variables with non-significant pvalues. It is challenging to perceive them as meaningfully different, but additional evidence would be necessary to confirm that the difference is not solely attributable to sampling variation. At age 8, the TRAILS women had better school success than non-participant women, and the TRAILS men had lower behavioural activity than non-participant men (Table 2). Behavioural activity was assessed using a composite score derived from three teacher-rated items on whether the child is actively involved and plays eagerly with others or whether the child exhibits silent, withdrawn and timid behaviour (the latter are reverse scored). There were no differences between the TRAILS participants and non-participants in relation to the parental occupational status, and childhood well-controlled behaviour or negative emotionality. The results remained similar when the deceased participants were excluded from the analyses (Table A1, in the Appendix). When comparing educational level at age 50, both the TRAILS women and men more often had vocational college education in comparison to the non-participants (Table 3). Moreover, the TRAILS women less often had a low level of vocational education than the non-participant women. The differences remained similar when the deceased participants were excluded (Table A2, in the Appendix). Both the TRAILS women and men less often had blue-collar occupational status at age 50 than the non-participants (Table 3). Further, the TRAILS men more often had upper white-collar occupational status than the non-participant men. The differences in occupational status were attenuated and no longer statistically significant when the deceased participants were excluded (Table A2). Smoking at age 27 was less common among the TRAILS men than the non-participant men (Table 3), and the difference remained when the deceased participants were excluded from the analyses (Table A2). Both the TRAILS women and men had lower alcohol consumption (grams per year) at age 27 and less signs of alcohol dependence (CAGE questionnaire) at age 36 than the non-participants in earlier adulthood. Only the difference in CAGE score Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 8 (Continued) Table 1: Representativeness of the TRAILS study participants in relation to the Finnish population cohort born in 1959 (statistically significant p-values in bold) Population women (N = 34,472– 36,339) TRAILS women (n = 107) p-value Population men (N = 33,570– 35,208) TRAILS men (n = 99) p-value % % % % Deceased 4.6 4.6 .990 9.1 10.2 .595 Level of vocational education <.001 .361 Vocational courses or less 12 10 19 24 Vocational schoola 44 24* 49 43 Vocational college or polytechnicb 31 48*21 18 University 13 18 11 14 Employment situation .796 .337 Employed 67.9 70.1 61.3 68.7 Unemployed 10.4 10.3 13.1 11.1 Retired 18.1 17.8 22.0 19.2 Other 3.7 1.9 3.6 1.0 Marital status .928 .046 Married/ in a registered relationship 55.0 53.3 56.2 67.7* Divorced 23.1 25.2 19.3 19.2 Widowed 4.9 5.6 1.4 0.0 Single 17.0 15.9 23.1 13.1* Number of biological children .409 .020 No biological children 16 13 24 13* One child 16 16 15 12 Two children 37 45 33 42* Three or more children 31 26 29 32 Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 15 Measure Reference Age in years Life History Calendar (PI) Caspi et al, 1996 42, 50, 61d Leisure activities Participation in leisure activities (LSQ, PI) 14, 27, 36, 42, 50, 61 Digitalisation Quantity and frequency of the use of modern technology (LSQ) 42, 50, 61 Purposes for the use of modern technology (LSQ) 42, 61 Problems caused by the use of modern technology (LSQ) 42, 61 Physical activity Frequency of leisure-time physical activity (LSQ) Karvonen et al, 2020; Kekäläinen et al, 2020 36, 42, 50, 61 An activity metabolic equivalent index for leisure-time physical activity (PI) Kujala et al, 1998 61 Physical activity at work (PI) 61 Modes of leisure-time physical activity (LSQ, PI) 50, 61 Assessment of current physical activity (PI) Hirvensalo et al, 1998 61 Assessment of physical activity during the COVID-19 pandemic Kekäläinen et al, 2021 61 Physical activity monitoring with tri-axial accelerometer (HE) RM42, UKK Terveyspalvelut, Tampere, Finland 61 Health and health behaviours Self-rated health (LSQ, HE) 27, 36, 42, 50, 61 Perceived stress (PI) Elo et al, 1992 36, 42, 50, 61 Symptom Check List (LSQ) Aro, 1988 36, 42, 50, 61 Physician diagnosed chronic diseases (LSQ, HE) Kinnunen et al, 2005; Rantanen et al, 2012 42, 50, 61 Institutional care (HE) 42, 50, 61 Medication (LSQ, HE) 42, 50, 61 Hearing (HE) 61 Menopause and menopausal symptoms (HE) 50, 61 Blood pressure (HE) 42, 50, 61 Height, weight, Body Mass Index (HE) 8, 14, 27, 36, 42, 50, 61 Waist and hip circumference (HE) 42, 50, 61 Body composition (HE) InBody 720, Biospace, Seoul, South Korea 61 Small blood count, cholesterol (total, LDL, and HDL), triglycerides, sensitiveCRP, fasting blood sugar (HE) 42, 50, 61 Sleeping patterns (HE) 61 Table 4: Continued (Continued) Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 16 international standard for describing the data generated by surveys and other observational methods in the social, behavioural, economic and health sciences. The DDI Codebook and more information about the DDI Alliance can be found on DDI Alliance’s web pages (DDI Alliance, n.d.a, n.d.b). Currently, JYU has its own data deposit system called Converis where the TRAILS metadata have been archived (University of Jyväskylä, 2023). A careful preliminary data analysis is conducted to control for any coding mistakes and outliers in the data, and the reliability and validity of the measures is reported. The JYLS data collected from age 8 to 50 are additionally stored in the FSD repository, and the TRAILS data will also be kept there in the future, by the end of 2025. Due to the sensitivity and privacy of participant data, Finnish law dictates that the data cannot be openly shared. Access to pseudonymised TRAILS data is possible under certain conditions. The data access procedure for those researchers who are not members or collaborators of the TRAILS research team follows the protocol established for previous JYLS data. The latter is described on the FSD website (FSD, n.d.). Measure Reference Age in years Cigarette use (LSQ) 14, 27, 36, 42, 50, 61 Quantity and frequency of drinking (LSQ) Pitkänen et al, 2005 27, 36, 42, 50, 61 CAGE Questionnaire (LSQ) Ewing, 1984; Pitkänen, 2006 36, 42, 50, 61 Reasons for alcohol use 27, 36, 42, 50, 61 Problems caused by alcohol use 27, 36, 42, 50, 61 mm-Michigan Alcoholism Screening Test (HE) Selzer, 1971; Kristenson and Trell, 1982 36, 42, 50, 61 Functioning Maximal isometric handgrip strength (HE) Jamar Plus, Patterson Medical, Cedarburg, WI, USA; Rantanen et al, 2003 50, 61 Physical functioning (HE; self-evaluation at 61) 42, 50, 61 Mobility limitation (HE; self-evaluation at 61) 42, 50, 61 Injuries (HE) 42, 50, 61 Paradise Questionnaire for functional ability (HE) Cieza et al, 2015; Pitkänen et al, 2020 61 CERAD Word List and Word Fluency (HE) Welsh et al, 1994 42, 50, 61 Digit Span memory test (HE) Schaie, 1985 50, 61 Trail Making Test (HE) Reitan, 1958 61 Notes: Abbreviations in parentheses indicate the data collection method at the current data collection: LSQ = Mailed Life Situation Questionnaire, PI = psychological interview, MI = mailed inventory, and HE = health examination. If the measure was used at an earlier data collection phase,a it is indicated by referring to the age of measurement. aFor a complete list of methods used in earlier data collection phases, see Pulkkinen and Kokko, 2017. bAt ages 8 and 14, the assessments were based on teacher-ratings and peer-nominations. cThe Big Five Personality Inventory (Pulver et al, 1995) is an authorised adaptation of the NEO Personality Inventory with 181 items (NEO-PI; (Costa and McCrae, 1985)) of which about one quarter were substitutes for the original American items. dThe age-42 Life History Calendar (LHC) covers years from 15 to 42, the age-LHC years from 42 to 50, and the age-61 from 50 until now. Table 4: Continued Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 17 TRAILS data may be obtained for use in international research articles. The data are actively used by the research team and collaborators. Other qualified researchers need permission through a reasonable request from the principal investigator to use the data. Permission is granted on a case-by-case basis, with the main criteria being whether the research questions align with what participants consented to, as outlined in the research plan, can be answered using the specified data, and do not overlap with work in progress. If permission is granted, the data are generally used in collaboration with the research team members. When it comes to data delivery, pseudonymised data can be shared within the EU/ETA countries. During the delivery process, the GDPR is followed, and the recipient is expected to adhere to GDPR guidelines. Only variables relevant to the research plan are delivered from the complete TRAILS data set. These variables are shared through a secure system approved by the JYU. In terms of data security, each participant has been assigned an identification number. The identification key is held by the TRAILS project’s principal investigator and securely stored. Data files are stored on the JYU server and protected by passwords. All users of the TRAILS data must sign a data usage agreement that specifies the intended use, duration of data usage, title of work, research questions and required variables. By signing the agreement, users agree to keep the data for personal use only, maintain data confidentiality, handle the data with care, and return the data to the research team while deleting any copies from personal computers. The agreement is then submitted to the principal investigator for approval. To date, more than 20 researchers have accessed TRAILS data (compared to approximately 160 for the entire JYLS); five international and two national publications have been based on the TRAILS (compared to approximately 190 and 115, respectively, for the entire JYLS); two doctoral theses based on TRAILS are currently in progress (with 17 completed based on the entire JYLS); and 11 masters’ theses based on TRAILS have been completed or are nearing completion (compared 91 completed based on the entire JYLS; University of Jyväskylä, n.d.). Data analyses The main methods of the statistical analyses used to analyse the TRAILS aims 1–5 include path and regression analysis with direct, mediating and modifying effects. We mostly use continuous or Likert-type variables. To capture a transition, such as retirement or grandparenthood, we analyse changes in statuses or scores using the latent change score method. For investigating the evolvement of mental well-being or personality, we apply trajectory (growth curve) models adapted for the measurement scale of the outcome variables. We will utilise Mplus (Muthén and Muthén, 1998-2017) and SPSS software. Our approach is exploratory, and we conducted power analysis for a single coefficient at a time based on a minimal meaningful level of correlation. Some of our research questions are based on a very long-term follow-up, spanning from age 8 to 61. This poses a critical consideration in terms of statistical power. Our preliminary analysis has shown that the correlation between age-8 and age-50 personality characteristics is approximately 0.20. To obtain a rank regression coefficient significant at the 0.05 level of significance and with 80% power, we would require 193 participants. With around 200 TRAILS participants, we are confident that we will have sufficient statistical power to find statistically significant associations even for these analyses Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 18 covering the maximum time span. The analyses including mediating, moderating and confounding variables are even more exploratory in nature, as there are no studies focusing on these effects in similar populations. Consequently, it is difficult to make power calculations for them. Our other strategies to increase the statistical power include the use of continuous (sum) or Likert-type scores as much as possible. This is in contrast to using binary clinical diagnosis variables that characterise extreme types of behaviours or states, which only represent a small proportion of a population and result in small group sizes in analyses. For instance, mental disorders occur in only a small percentage of the participants, which leads to a low number of cases. Therefore, instead of using binary clinical diagnosis of depression, we will use depressive symptoms as a continuous composite score. Regarding missing data, we plan to use suitable models adapted for the relevant missing data mechanisms (Little and Rubin, 2002), such as adjusting for mortality or using not-missing-at random models or weights. Discussion The TRAILS study produces new knowledge on the occurring or anticipated life transitions at the threshold of late adulthood, as well as the longitudinal pathways leading to these transitions and the relation of the transitions to an individual’s well-being. Moreover, new knowledge is presented on how individual characteristics, individual environments or adjustment to societal challenges reflect on these life transitions. The variety of topics covered in the data collection is large and enables research that will lead to more thorough understanding of people’s lives and development at around age 60. Instead of the traditional view of late adulthood being a time of adjusting to the physical, psychological and social changes that typically occur later in life (Hutteman et al, 2014), we are able to examine whether the beginning of late adulthood is a more healthy and psychologically satisfying period of life than previously argued. Moreover, the current data and the previous JYLS data will provide a 52-year basis for continued data collection in the future, providing possibilities to examine the predictors of satisfying and active life throughout late adulthood. A limitation of the study is a relatively small sample size, which prevents us from analysing extreme types of behaviours as binary variables and may limit the statistical power of analyses involving multiple outcome variables within the same model, as well as mediating, moderating and/or confounding factors. However, with some cautionary remarks, it seems that the TRAILS participants closely represent both the initial random sample and the respective Finnish age-cohort. This enhances the observed variability within the sample and improves the generalisability of the results at least to the respective Finnish population. Note 1 It should be noted that there are other studies abbreviated as TRAILS (for example, Tracking Adolescents’ Individual Lines Surveys), but the present study (Developmental Psychological Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan) is independent of them. Funding Developmental Psychological Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan (TRAILS), which covers the most recent data collection of the Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 19 Jyväskylä Longitudinal Study of Personality and Social Development (JYLS), was funded by the Academy of Finland project funding (No. 323541) for 2019–23. Over the years, the Academy of Finland has been the major funder of the JYLS, through its Centre of Excellence on Human Development and Its Risk Factors funding in 1997–2005 and project funding in 1974, 1979 and 1986–2013. Acknowledgements We sincerely thank all the research assistants for their valuable contributions to the data collection of TRAILS and all the participants of the JYLS for participating in the study over the decades. Availability of data and materials The Finnish law dictates that the TRAILS data cannot be openly shared due to the data sensitivity and privacy of participant data. It is possible for those researchers who are not members or collaborators of the TRAILS research team to access the pseudonymised TRAILS data under certain conditions. The data access procedure follows the protocol established for previous JYLS data (described on the FSD website; FSD, n.d.). The TRAILS data will be deposited to the FSD by the end of 2025. Statement on human experimentation and informed consent The TRAILS data collection was approved on 13 December 2019 by the Ethical Committee of the University of Jyväskylä, Finland. The participants gave their written informed consent for participation and for storing the data collected about them. The data collection was performed in accordance with the Declaration of Helsinki. Conflict of interest The authors declare that there is no conflict of interest. References Ahola, A., Djerf, K., Heiskanen, M. and Vikki, K. (1995) Elinolotutkimus 1994: Aineistonkeruu [Living Conditions Survey of 1994: Data Collection], Helsinki: Statistics Finland, https://www.doria.fi/handle/10024/185318. Aro, H. (1988) Stress, Development and Psychosomatic Symptoms in Adolescence: A Study of 14 to 16 Year Old School Children, Acta Universitatis Tamperensis, Series A Vol 242, Tampere: University of Tampere. Baltes, P.B. (1997) On the incomplete architecture of human ontogeny: selection, optimization, and compensation as foundation of developmental theory, American Psychologist, 52(4): 366–80. doi: 10.1037//0003-066x.52.4.366 Bengtson, V.L. and Roberts, R.E.L. (1991) Intergenerational solidarity in aging families: an example of formal theory construction, Journal of Marriage and the Family, 53(4): 856–70. doi: 10.2307/352993 Buss, A.H. and Perry, M. (1992) The aggression questionnaire, Journal of Personality and Social Psychology, 63(3): 452–9. doi: 10.1037/0022-3514.63.3.452 Carstensen, L.L. and Lang, F.R. (1996) Future Time Perspective Scale (unpublished manuscript), Stanford, CA: Stanford University, https://lifespan.stanford.edu/ download-the-ftp-scale. Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 20 Caspi, A., Moffitt, T.E., Thornton, A., Freedman, D., Amell, J.W., Harrington, H., Smeijers, J. and Silva, P.A. (1996) The life history calendar: a research and clinical assessment method for collecting retrospective event-history data, International Journal of Methods in Psychiatric Research, 6(2): 101–14. doi: 10.1002/(SICI)1234988X(199607)6:2<101::AID-MPR156>3.3.CO;2-E Cieza, A., Sabariego, C., Anczewska, M., Ballert, C., Bickenbach, J., Cabello, M., Giovannetti, A., Kaskela, T., Mellor, B., Pitkänen, T., Quintas, R., Raggi, A., Świtaj, P., Chatterji, S. and PARADISE Consortium (2015) PARADISE 24: a measure to assess the impact of brain disorders on people’s lives, PLoS ONE, 10(7): art e0132410. doi: 10.1371/journal.pone.0132410 Costa, P.T. Jr and McCrae, R.R. (1985) The NEO Personality Inventory, Odessa, FL: Psychological Assessment Resources. Cutrona, C. and Russell, D. (1987) The provisions of social relationships and adaptation to stress, in W.H. Jones and D. Perlman (eds) Advances in Personal Relationships, Volume 1, Greenwich, CT: JAI Press, pp 37–67. DDI Alliance (The Data Documentation Initiative) (n.d.a) DDI-Codebook, https:// ddialliance.org/Specification/DDI-Codebook/. DDI Alliance (The Data Documentation Initiative) (n.d.b) Welcome to the Data Documentation Initiative, https://ddialliance.org/welcome-to-the-datadocumentation-initiative. Depue, R. (1987) General Behavior Inventory, Ithica, NY: Cornell University, Department of Psychology. Diener, E., Emmons, R.A., Larsen, R.J. and Griffin, S. (1985) The satisfaction with life scale, Journal of Personality Assessment, 49(1): 71–5. doi: 10.1207/s15327752jpa4901_13 Elo, A.L., Leppänen, A., Lindström, K. and Ropponen, T. (1990) TSK: Miten Käytät Työstressikyselyä [OSQ: How to Use the Occupational Stress Questionnaire], Helsinki: Finnish Institute of Occupational Health. Elo, A.L., Leppänen, A. and Lindström, K. (1992) OSQ: Occupational Stress Questionnaire: User’s Instructions, Reviews (Työterveyslaitos), Vol 19, Helsinki: Finnish Institute of Occupational Health. Ewing, J.A. (1984) Detecting alcoholism: the CAGE questionnaire, JAMA: Journal of the American Medical Association, 252(14): 1905–7. doi: 10.1001/jama.252.14.1905 Eysenck, H.J. and Eysenck, S.B.G. (1975) Manual of the Eysenck Personality Questionnaire, London: Hodder and Stoughton. Fadjukoff, P. (2007) Identity Formation in Adulthood, Jyväskylä Studies in Education, Psychology and Social Research, Vol 319, Jyväskylä: University of Jyväskylä. Fadjukoff, P., Pulkkinen, L. and Kokko, K. (2016) Identity formation in adulthood: a longitudinal study from age 27 to 50, Identity, 16(1): 8–23. doi: 10.1080/15283488.2015.1121820 Feldman, L.A. (1995) Valence focus and arousal focus: individual differences in the structure of affective experience, Journal of Personality and Social Psychology, 69(1): 153–66. doi: 10.1037/0022-3514.69.1.153 Finnish Government (2020) Government, in cooperation with the President of the Republic, declares a state of emergency in Finland over coronavirus outbreak, 16 March, https://valtioneuvosto.fi/en/-/10616/hallitus-totesi-suomen-olevanpoikkeusoloissa-koronavirustilanteen-vuoksi. Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 21 Frone, M.R., Russell, M. and Cooper, M.L. (1992) Antecedents and outcomes of work–family conflict: testing a model of the work-family interface, Journal of Applied Psychology, 77(1): 65–78. doi: 10.1037//0021-9010.77.1.65 FSD (Finnish Social Science Data Archive) (n.d.) Jyväskylä Longitudinal Study of Personality and Social Development (JYLS), https://services.fsd.tuni.fi/catalogue/ series/28?lang=en. Haapasalo, J. (1990) Eysenckin Persoonallisuuskyselyn ja Zuckermanin Elämyshakuisuusasteikon Faktorirakenteet ja Pisteitys Suomessa [Scoring and Factor Structure of the Eysenck Personality Questionnaire and Zuckerman Sensation Seeking Scales in Finland], Reports from the Department of Psychology, Vol 311, Jyväskylä: University of Jyväskylä, https://jyx.jyu.fi/handle/123456789/72297. Hietalahti, M., Tolvanen, A. and Kokko, K. (2015) Values and personal life investment in middle-age: Measures and relations, Journal of Adult Development, 22(4): 206–20. doi: 10.1007/s10804-015-9212-7 Hirvensalo, M., Lampinen, P. and Rantanen, T. (1998) Physical exercise in old age: an eight-year follow-up study on involvement, motives, and obstacles among persons age 65–84, Journal of Aging and Physical Activity, 6(2): 157–68. doi: 10.1123/ japa.6.2.157 Hutteman, R., Hennecke, M., Orth, U., Reitz, A.K. and Specht, J. (2014) Developmental tasks as a framework to study personality development in adulthood and old age, European Journal of Personality, 28(3): 267–78. doi: 10.1002/per.1959 Infurna, F.J., Gerstorf, D. and Lachman, M.E. (2020) Midlife in the 2020s: opportunities and challenges, American Psychologist, 75(4): 470–85. doi: 10.1037/amp0000591 Jokisaari, M. (2007) Attainment and Reflection: The Role of Social Capital and Regrets in Developmental Regulation, Jyväskylä Studies in Education, Psychology and Social Research, Vol 321, Jyväskylä: University of Jyväskylä. Kahn, H. and Wiener, A.J. (1967) The Year 2000: A Framework for Speculation on the Next Thirty-Three Years, New York: Macmillan. Karasek, R.A. (1979) Job demands, job decision latitude, and mental strain: implications for job redesign, Administrative Science Quarterly, 24(2): 285–308. doi: 10.2307/2392498 Karasek, R.A. (1985) Job Content Questionnaire and User’s Guide, Lowell: University of Massachusetts Lowell. Karvonen, J., Törmäkangas, T., Pulkkinen, L. and Kokko, K. (2020) Associations of temperament and personality traits with frequency of physical activity in adulthood, Journal of Research in Personality, 84: art 103887. doi: 10.1016/j.jrp.2019.103887 Kekäläinen, T., Freund, A.M., Sipilä, S. and Kokko, K. (2020) Cross-sectional and longitudinal associations between leisure time physical activity, mental well-being and subjective health in middle adulthood, Applied Research in Quality of Life, 15(4): 1099–116. doi: 10.1007/s11482-019-09721-4 Kekäläinen, T., Sipilä, S., Saajanaho, M. and Kokko, K. (2021) The role of personality traits in leisure time physical activity during COVID-19 pandemic, Personality and Individual Differences, 182: art 111080. doi: 10.1016/j.paid.2021.111080 Keyes, C.L.M. (1998) Social well-being, Social Psychology Quarterly, 61(2): 121–40. doi: 10.2307/2787065 Keyes, C.L.M. (2005) Mental illness and/or mental health? Investigating axioms of the complete state model of health, Journal of Consulting and Clinical Psychology, 73(3): 539–48. doi: 10.1037/0022-006X.73.3.539 Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 22 King, L.A. and Emmons, R.A. (1990) Conflict over emotional expression: psychological and physical correlates, Journal of Personality and Social Psychology, 58(5): 864–77. doi: 10.1037/0022-3514.58.5.864 Kinnunen, M.-L., Kokkonen, M., Kaprio, J. and Pulkkinen, L. (2005) The associations of emotion regulation and dysregulation with the metabolic syndrome factor, Journal of Psychosomatic Research, 58(6): 513–21. doi: 10.1016/j.jpsychores.2005.02.004 Kinnunen, M.-L., Metsäpelto, R.L., Feldt, T., Kokko, K., Tolvanen, A., Kinnunen, U., Leppänen, E. and Pulkkinen, L. (2012) Personality profiles and health: longitudinal evidence among Finnish adults, Scandinavian Journal of Psychology, 53(6): 512–22. doi: 10.1111/j.1467-9450.2012.00969.x Kinnunen, U., Feldt, T., Siltaloppi, M. and Sonnentag, S. (2011) Job demands– resources model in the context of recovery: testing recovery experiences as mediators, European Journal of Work and Organizational Psychology, 20(6): 805–32. doi: 10.1080/1359432X.2010.524411 Klaus, D., Engstler, H., Mahne, K., Wolff, J.K., Simonson, J., Wurm, S. and Tesch-Römer, C. (2017) Cohort profile: The German Ageing Survey (DEAS), International Journal of Epidemiology, 46(4): 1105–1105g. doi: 10.1093/ije/dyw326 Kokko, K. and Pulkkinen, L. (2000) Aggression in childhood and long-term unemployment in adulthood: a cycle of maladaptation and some protective factors, Developmental Psychology, 36(4): 463–72. doi: 10.1037/0012-1649.36.4.463 Kokko, K. and Pulkkinen, L. (2005) Stability of aggressive behavior from childhood to middle age in women and men, Aggressive Behavior, 31(5): 485–97. doi: 10.1002/ ab.20063 Kokko, K., Korkalainen, A., Lyyra, A. and Feldt, T. (2013) Structure and continuity of well-being in mid-adulthood: a longitudinal study, Journal of Happiness Studies, 14(1): 99–114. doi: 10.1007/s10902-011-9318-y Kokko, K., Rantanen, J. and Pulkkinen, L. (2015) Associations between mental wellbeing and personality from a life span perspective, in M. Blatný (ed) Personality and Well-Being Across the Life-Span, Basingstoke: Palgrave Macmillan, pp 134–59. doi: 10.1057/9781137439963_8 Kornadt, A.E. and Rothermund, K. (2014) Preparation for old age in different life domains: dimensions and age differences, International Journal of Behavioral Development, 38(3): 228–38. doi: 10.1177/0165025413512065 Kornadt, A.E., Voss, P. and Rothermund, K. (2015) Hope for the best, prepare for the worst? Future self-views and preparation for age-related changes, Psychology and Aging, 30(4): 967–76. doi: 10.1037/pag0000048 Kornadt, A.E., Hess, T.M. and Rothermund, K. (2020) Domain-specific views on aging and preparation for age-related changes: development and validation of three brief scales, Journals of Gerontology: Series B, 75(2): 303–7. doi: 10.1093/geronb/gby055 Kornadt, A.E., Voss, P. and Rothermund, K. (2018) Subjective remaining lifetime and concreteness of the future as differential predictors of preparation for age-related changes, European Journal of Ageing, 15(1): 67–76. doi: 10.1007/s10433-017-0426-3 Kristenson, H. and Trell, E. (1982) Indicators of alcohol consumption: comparisons between a questionnaire (Mm-MAST), interviews and serum γ-glutamyl transferase (GGT) in a health survey of middle-aged males, British Journal of Addiction, 77(3): 297–304. doi: 10.1111/j.1360-0443.1982.tb02459.x Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 23 Kujala, U.M., Kaprio, J., Sarna, S. and Koskenvuo, M. (1998) Relationship of leisuretime physical activity and mortality: the Finnish twin cohort, Journal of the American Medical Association, 279(6): 440–4. doi: 10.1001/jama.279.6.440 Lachman, M.E., Teshale, S. and Agrigoroaei, S. (2015) Midlife as a pivotal period in the life course: balancing growth and decline at the crossroads of youth and old age, International Journal of Behavioral Development, 39(1): 20–31. doi: 10.1177/0165025414533223 Lang, F.R. and Carstensen, L.L. (2002) Time counts: future time perspective, goals, and social relationships, Psychology and Aging, 17(1): 125–39. doi: 10.1037/08827974.17.1.125 Levy, B.R., Slade, M.D., Kunkel, S.R. and Kasl, S.V. (2002) Longevity increased by positive self-perceptions of aging, Journal of Personality and Social Psychology, 83(2): 261–70. doi: 10.1037//0022-3514.83.2.261 Liang, J. and Bollen, K.A. (1983) The structure of the Philadelphia Geriatric Center Morale scale: a reinterpretation, Journal of Gerontology, 38(2): 181–9. doi: 10.1093/ geronj/38.2.181 Little, B.R. (1983) Personal projects: a rationale and method for investigation, Environment and Behavior, 15(3): 273–309. doi: 10.1177/0013916583153002 Little, R.J.A. and Rubin, D.B. (2002) Statistical Analysis with Missing Data, New York, NY: John Wiley & Sons. Lyyra, T.M. and Heikkinen, R.L. (2006) Perceived social support and mortality in older people, Journals of Gerontology: Series B, 61(3): S147–152. doi: 10.1093/ geronb/61.3.s147 Mäkikangas, A., Rantanen, J., Bakker, A.B., Kinnunen, M.L., Pulkkinen, L. and Kokko, K. (2015) The circumplex model of occupational well-being: its relation with personality, Journal for Person-Oriented Research, 1(3): 115–29. doi: 10.17505/ jpor.2015.13 Marcia, J.E. (1966) Development and validation of ego-identity status, Journal of Personality and Social Psychology, 3(5): 551–8. doi: 10.1037/h0023281 Maslach, C. and Jackson, S. (1986) MBI: Maslach Burnout Inventory Manual, 2nd edn, Palo Alto, CA: Consulting Psychologists Press. Mayer, J.D. and Gaschke, Y.N. (1988) The experience and meta-experience of mood, Journal of Personality and Social Psychology, 55(1): 102–11. doi: 10.1037/00223514.55.1.102 Moffitt, T.E., Belsky, D.W., Danese, A., Poulton, R. and Caspi, A. (2017) The longitudinal study of aging in human young adults: knowledge gaps and research agenda, Journals of Gerontology: Series A, 72(2): 210–15. doi: 10.1093/gerona/glw191 Muthén, L.K. and Muthén, B.O. (1998–2017) Mplus User’s Guide, 8th edn, Los Angeles, CA: Muthén & Muthén. Netemeyer, R.G., Boles, J.S. and McMurrian, R. (1996) Development and validation of work–family and family–work conflict scales, Journal of Applied Psychology, 81(4): 400–10. doi: 10.1037/0021-9010.81.4.400 Noone, J.H., Stephens, C. and Alpass, F.M. (2009) Preretirement planning and well-being in later life: a prospective study, Research on Aging, 31(3): 295–317. doi: 10.1177/0164027508330718 Perho, H. and Korhonen, M. (1993) Elämänvaiheiden onnellisuus ja sisältö keski-iän kynnyksellä [Happiness and content of different life phases in the frontier of midadulthood], Gerontologia, 7: 271–85. Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Katja Kokko et al 24 Pitkänen, L. (1969) A Descriptive Model of Aggression and Non-Aggression with Applications to Children’s Behaviour, Jyväskylä Studies in Education, Psychology and Social Research, Vol 19, Jyväskylä: University of Jyväskylä, https://jyx.jyu.fi/ handle/123456789/71191. Pitkänen, T. (2006) Alcohol Drinking Behavior and its Developmental Antecedents, Jyväskylä Studies in Education, Psychology and Social Research, Vol 293, Jyväskylä: University of Jyväskylä, https://jyx.jyu.fi/handle/123456789/13365. Pitkänen, T., Lyyra, A.L. and Pulkkinen, L. (2005) Age of onset of drinking and the use of alcohol in adulthood: a follow-up study from age 8–42 for females and males, Addiction, 100(5): 652–61. doi: 10.1111/j.1360-0443.2005.01053.x Pitkänen, T., Levola, J.M., de la Fuente, J. and Cabello, M. (2020) Identifying psychosocial difficulties of inpatients with substance use disorders: evaluation of the usefulness of the PARADISE24 for clinical practise, Disability and Rehabilitation, 42(1): 130–6. doi: 10.1080/09638288.2018.1493543 Pulkkinen, L. (1987) Offensive and defensive aggression in humans: a longitudinal perspective, Aggressive Behavior, 13(4): 197–212. doi: 10.1002/1098-2337(1987)13:4<197::AID-AB2480130404>3.0.CO;2-E Pulkkinen, L. (2006) The Jyväskylä Longitudinal Study of Personality and Social Development (JYLS), in L. Pulkkinen, J. Kaprio and R.J. Rose (eds) Socioemotional Development and Health from Adolescence to Adulthood, Cambridge Studies on Child and Adolescent Health, Cambridge: Cambridge University Press, pp 29–55. doi: 10.1017/CBO9780511499784.004 Pulkkinen, L. (2017) Human Development from Middle Childhood to Middle Adulthood: Growing Up to Be Middle-Aged, Abingdon: Routledge. Open access: doi: 10.4324/9781315732947 Pulkkinen, L. and Kokko, K. (2017) The Jyväskylä Longitudinal Study of Personality and Social Development: measures used for the study of major topics in different data waves, 1 February, https://web.archive.org/web/20210921061153/https://services. fsd.tuni.fi/catalogue/FSD2059/PIP/LAKU_JYLS_MethodsTable_2017.pdf. Pulkkinen, L. and Rönkä, A. (1994) Personal control over development, identity formation, and future orientation as components of life orientation: a developmental approach, Developmental Psychology, 30(2): 260–71. doi: 10.1037/0012-1649.30.2.260 Pulkkinen, L., Kokko, K. and Rantanen, J. (2012) Paths from socioemotional behavior in middle childhood to personality in middle adulthood, Developmental Psychology, 48(5): 1283–91. doi: 10.1037/a0027463 Pulver, A., Allik, J., Pulkkinen, L. and Hämäläinen, M. (1995) A Big Five personality inventory in two non-Indo-European languages, European Journal of Personality, 9(2): 109–24. doi: 10.1002/per.2410090205 Puohiniemi, M. (1995) Values, Consumer Attitudes and Behaviour: An Application of Schwartz’s Value Theory to the Analysis of Consumer Behaviour and Attitudes in Two National Samples, Research Reports, Department of Social Psychology, Vol 3-1995, Helsinki: University of Helsinki. Rantanen, T., Portegijs, E., Viljanen, A., Eronen, J., Saajanaho, M., Tsai, L.T., Kauppinen, M., Palonen, E.M., Sipilä, S., Iwarsson, S. and Rantakokko, M. (2012) Individual and environmental factors underlying life space of older people – study protocol and design of a cohort study on life-space mobility in old age (LISPE), BMC Public Health, 12(1): art 1018. doi: 10.1186/1471-2458-12-1018 Brought to you by University of Jyväskylä | Unauthenticated | Downloaded 02/05/24 02:23 PM UTC Developmental Perspectives on Transitions at Age 60 31 Table A2: Representativeness of the TRAILS study participants (n = 206) in relation to surviving non-participants from the initial JYLS sample in adulthood (statistically significant p-values in bold) Non-participants women (n = 33–51) Participants women (n = 100–107) p-value Non-participants men (n = 45–71) Participants men (n = 93–99) p-value % (n) % (n) % (n) % (n) Level of vocational education at 50 .007 .035 Vocational courses or less 27.5 (14)*10.3 (11)*28.8 (21) 24.2 (24) Vocational schoola33.3 (17) 24.3 (26) 53.4 (39) 44.4 (44) Vocational college or polytechnicb 25.5 (13)*47.7 (51)*4.1 (3)*19.2 (19)* University 13.7 (7) 17.8 (19) 13.7 (10) 12.1 (12) Occupational status at 50 .070 .114 Blue-collar 22.0 (9) 8.4 (9) 61.9 (39) 47.5 (47) Lower white-collar 58.5 (24) 64.5 (69) 19.0 (12) 19.2 (19) Upper white-collar 19.5 (8) 27.1 (29) 19.0 (12) 33.3 (33) Self-rated health at 36 .185 .511 Good 30.3 (10) 43.0 (43) 42.2 (19) 52.8 (47) Fairly good 48.5 (16) 31.0 (31) 33.3 (15) 27.0 (24) Average or poor 21.2 (7) 26.0 (26) 24.4 (11) 20.2 (18) Smoking at 27 .183 .012 Never 28.3 (13) 46.1 (47) 15.0 (9)*33.3 (31)* Quitted 23.9 (11) 21.6 (22) 16.7 (10) 16.1 (15) Occasionally 13.0 (6) 10.8 (11) 8.3 (5) 15.1 (14) Daily 34.8 (16) 21.6 (22) 60.0 (36)*35.5 (33)* Alcohol consumption M (SD) M (SD) M (SD) M (SD) Grams per year (at 27) 1,182 (1,358) 814 (1,034) .074 3,247 (3,508) 2,421 (2,617) .121 CAGE mean score (at 36) 1.45 (1.61) 0.71 (1.09) .012 2.15 (2.16) 1.67 (1.72) .145 *Adjusted residual > ±1.96. aLower secondary level. bBachelor’s level. 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