Skip to main content Accessibility help
×
Home
Hostname: page-component-6f6fcd54b-sdp72 Total loading time: 0.305 Render date: 2021-05-11T13:37:48.970Z Has data issue: true Feature Flags: {}

Wisconsin Twin Project Overview: Temperament and Affective Neuroscience

Published online by Cambridge University Press:  10 December 2019

Nicole L. Schmidt
Affiliation:
Waisman Center, University of Wisconsin–Madison, Madison, WI, USA
Kathryn Lemery-Chalfant
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ, USA
H. Hill Goldsmith
Affiliation:
Waisman Center, University of Wisconsin–Madison, Madison, WI, USA Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
Corresponding
E-mail address:

Abstract

The Wisconsin Twin Project encompasses nearly 30 years of longitudinal research that spans infancy to early adulthood. The twin sample was recruited from statewide birth records for birth cohorts 1989–2004. We summarize early recruitment, assessment, retention and recently completed twin neuroimaging studies. In addition to the focal twins, longitudinal data were also collected from two parents and nontwin siblings. Our adolescent and young adult neuroimaging sample (N = 600) completed several previous behavioral and environmental assessments, beginning shortly after birth. The extensive phenotyping is meant to support a range of empirical investigations with potentially differing theoretical perspectives.

Type
Articles
Copyright
© The Author(s) 2019 

The Wisconsin Twin Project began in the early 1990s in the state of Wisconsin, which is north-centrally located in the United States. The design of the Wisconsin Twin Project accommodates a range of research on emotional and cognitive development, with a strong emphasis on clinical outcomes. Assessments for some participants began in the prenatal period, and the oldest age of follow-up was approximately 24 years.

The broad themes of our results span psychophysiology, temperament development, gene–environment interplay and other aspects of mental and physical health. Many studies incorporate observational behavior and laboratory temperament assessments that were partially developed in our lab (Buss & Goldsmith, Reference Buss and Goldsmith2000; Gagne et al., Reference Gagne, Van Hulle, Aksan, Essex and Goldsmith2011; Goldsmith et al., Reference Goldsmith, Lemery-Chalfant, Schmidt, Schmidt, Chow and Justen2010; Planalp et al., Reference Planalp, Van Hulle, Gagne and Goldsmith2017). Several of our neuroimaging studies incorporate the monozygotic (MZ) difference design (Adluru et al., Reference Adluru, Luo, Van Hulle, Schoen, Davidson, Alexander and Goldsmith2017; Alisch et al., Reference Alisch, Van Hulle, Chopra, Bhattacharyya, Zhang, Davidson and Goldsmith2017; Burghy et al., Reference Burghy, Fox, Cornejo, Stodola, Sommerfeldt, Westbrook and Birn2016; Carroll et al., Reference Carroll, Planalp, Van Hulle and Goldsmith2019). Recent empirical results from more than 30 papers are summarized in Schmidt et al. (Reference Schmidt, Brooker, Carroll, Gagne, Luo, Planalp and Goldsmith2019).

Sample, Recruitment, and Retention

The Wisconsin Twin Project sample is based on birth-record-based cohorts of twins born in the state of Wisconsin during the years 1989–2004 (Goldsmith et al., Reference Goldsmith, Lemery-Chalfant, Schmidt, Arneson and Schmidt2007; Lemery-Chalfant et al., Reference Lemery-Chalfant, Goldsmith, Schmidt, Arneson and Van Hulle2006; Schmidt et al., Reference Schmidt, Van Hulle, Brooker, Meyer, Lemery-Chalfant and Goldsmith2013; Van Hulle et al., Reference Van Hulle, Lemery-Chalfant and Goldsmith2002). According to US Census Bureau and other data, of the 50 states, Wisconsin ranks 20th in total population, 25th in physical size, 23rd in median household income, 20th in gross domestic product, 11th in percentage of people who are high school graduates, 26th in percentage of people who are college graduates and 37th in percentage of people who identify as racial or ethnic minorities. Although differences in state ranks in these categories often reflect small differences, Wisconsin is clearly about average in many characteristics among US states. As a result, data from Wisconsin are likely to represent the US population reasonably well.

After nearly 30 years, the research program encompasses a series of longitudinal studies that span infancy to early adulthood (see Figure 1), with another currently planned longitudinal follow-up in early adulthood. Families entered the Wisconsin Twin Project through two primary mechanisms: (1) multimethod recruiting (e.g., advertising, recruiting from twin groups); and (2) state birth records, both depicted at the top of Figure 1. No new recruiting occurred after the infant–toddler years except for subsets of participants for Studies 3 and 5. The arrows in Figure 1 depict sequences of subsequent testing occasions across development. The boxes in Figure 1 represent studies that each comprise one or more testing occasions. A given study typically yields several published papers, some of which span studies. Each study includes a target age (e.g., birth, age 12–18 years). The arrows also depict what earlier and later data exist. For instance, the sample in Study 2c was tested previously in either Study 1 or Study 2a. A portion of the Study 2c sample was also tested in Study 4. Study 2c encapsulated three separate testing occasions at ages 7, 12 and 15 years. Detailed descriptions of early assessment were reported in Schmidt et al. (Reference Schmidt, Van Hulle, Brooker, Meyer, Lemery-Chalfant and Goldsmith2013).

Note: Parent and sibling data were also collected in Studies 1–4, 6 and 7.

Figure 1. Wisconsin twin research project overview.

As an illustration, consider a twin pair recruited from state birth records (top center of Figure 1). Generally, the twins would have still been infants when we accessed the birth records. The parents were sent an invitation letter and subsequently agreed to be contacted for future research participation. The first parent interview and survey about toddler temperament, parenting and challenging behaviors occurred in Study 2a, when the twins were approximately 24 months old. After the toddler screen, they were assessed again via parental report at age 7 years in Study 2b. If either twin’s scores met selection criteria in Study 2b (e.g., mild enrichment for psychopathology), they were tested up to three times in Study 2c at ages 7, 12 and 15 years, and a final time around age 17 years in Study 6, with neuroimaging and behavioral assessment. The arrows show other pathways to Study 6.

As another example, consider a different twin pair located under the multimethod recruitment (e.g., local advertisement) shortly after birth, at an age before state birth records were available. This twin pair was first tested in Study 1 and tested with lab-based observational assessment on multiple occasions between birth and age 3 years. This twin pair was tested again in Study 5 with laboratory measurement of psychophysiology and then a final time in Study 6, the same final study as for the twin pair described in the previous paragraph.

Twin family recruitment and early results were covered in prior overviews of the project (Goldsmith et al., Reference Goldsmith, Lemery-Chalfant, Schmidt, Arneson and Schmidt2007; Schmidt et al., Reference Schmidt, Van Hulle, Brooker, Meyer, Lemery-Chalfant and Goldsmith2013). Briefly, initial contact was attempted with a mailed letter and contact form. Contact was maintained with multiple phone numbers, email addresses, a toll-free phone number and secondary contact information from a family friend or relative. Sample retention efforts included newsletters and a website devoted to participant communication. We attempted to recapture twin families at later testing occasions, where possible. We used Web-based tracing methods (e.g., public court records) to locate families with whom we had lost contact. The University of Wisconsin Survey Center also provided tracing services. All of these procedures helped maintain the research sample longitudinally.

The research is conducted at the University of Wisconsin–Madison’s Waisman Center and the Department of Psychology (https://goldsmithtwins.waisman.wisc.edu/). Procedures in studies under the Wisconsin Twin Project were approved by University of Wisconsin–Madison Internal Review Boards and comply with the Helsinki Accords of 1975, as revised in 2008.

The Wisconsin Twin Project’s signature approach is its depth and breadth of phenotyping (see Table 1). Sample sizes shown in Table 1 depict longitudinal data collection. For instance, 100% of the sample of 311 twin pairs with neuroimaging were tested in the earlier waves of data collection.

Table 1. Research modality and sample sizes by study

Note: Interview and written survey measures of sensory over-responsivity were included in all studies. Medical record data from the twin pregnancy and birth exist for most twins.

a Genotyping was done with the longitudinal psychopathology study.

b Neuroimaging studies comprise a pair of studies, Studies 6 and 7 from Figure 1. The vast majority (85%) of twins were participants of the RDoC neuroimaging study.

Twin zygosity was classified with multiple methods across testing occasions. Initially, zygosity was classified with the Zygosity Questionnaire for Young Children (Goldsmith, Reference Goldsmith1991). Observational ratings of zygosity were collected during in-person assessments. Ambiguous zygosity was resolved by genotyping.

Twin Neuroimaging Studies

Twin neuroimaging was a focus of the project during the past decade. The neuroimaging studies assessed brain structure and function with multimodal magnetic resonance imaging (MRI). Although MRI methods have varied with improvements in technology, we use T1- and T2-weighted structural scans, diffusion-weighted imaging, arterial spin labeling, resting state functional magnetic resonance imaging (fMRI) and task-related fMRI. The combined neuroimaging sample comprises 600 twins (300 pairs), all of whom have been studied previously, some on seven prior testing occasions. We oversampled MZ twins (66%). Some of our early neuroimaging and epigenetic studies use the MZ difference design (Adluru et al., Reference Adluru, Luo, Van Hulle, Schoen, Davidson, Alexander and Goldsmith2017; Alisch et al., Reference Alisch, Van Hulle, Chopra, Bhattacharyya, Zhang, Davidson and Goldsmith2017; Burghy et al., Reference Burghy, Fox, Cornejo, Stodola, Sommerfeldt, Westbrook and Birn2016). The twin neuroimaging data were also used to illustrate novel computational MRI methods (Chung, Luo, Adluru et al., Reference Chung, Luo, Adluru, Alexander, Davidson and Goldsmith2018; Chung, Luo, Leow et al., Reference Chung, Luo, Leow, Alexander, Davidson, Goldsmith, Frangi, Schnabel, Davatzikos, Alberola-López and Fichtinger2018; Huang et al., Reference Huang, Chung, Carroll and Goldsmith2019).

A majority of our neuroimaging work incorporates Research Domain Criteria (RDoC) as a framework for the behavioral assessments. Specifically, the RDoC twin study used longitudinal and quantitative genetic approaches to establish developmental antecedents and neural substrates for the RDoC positive valence systems (e.g., anticipatory positive affect and contentment) and negative valence systems (e.g., acute fear, potential threat/anxiety, frustrative nonreward and loss; Cuthbert, Reference Cuthbert2014). The RDoC twin study aimed to (a) establish distinctiveness, stability and external validity of each RDoC construct during childhood and adolescence; (b) investigate the relationship between brain structure and function (via MRI) and concurrent and longitudinal RDoC measures; and (c) utilize the MZ difference design to highlight early environmental contributions to later brain structure and function. In the MRI analyses, we focused more on white matter microstructure and on resting state and task-related functional measures (i.e., circuitry and networks) than on gray matter structure.

The RDoC twin study enrolled 518 MZ (56%) and dizygotic (DZ) twin individuals (mean age = 17.4 years, SD = 2.2 years). Approximately 70% were under 18 years of age at the time of assessment. Parents (88% mothers) of adolescents completed surveys. Data collection concluded in early 2019. Tables 2 and 3 list the principal twin-individual-level instruments and family-level instruments collected concurrently with neuroimaging data for the RDoC sample.

Table 2. Principal individual-level instruments for the adolescent and young adult RDoC brain and behaviour study

Note: N = 518 MZ and DZ twins (68% were adolescents; 56% MZ).

a Co-twin ratings also collected.

b Adult twin ratings collected.

Table 3. Principal family-level instruments for the adolescent and young adult brain and behaviour study

Note: We collected parent ratings for twins under 18 years of age at the time of MRI testing.

a Completed separately for each twin.

Future Directions

Although the panel is no longer being expanded, we maintain contact with the full panel of twin families through biannual newsletters and a website. These data could support diverse empirical investigations. The sample sizes afford the possibility to examine selected subsamples (e.g., clinical cases, the MZ twin difference sample). Planned research includes new assessments with early adulthood outcomes, deeper assessment of experiential differences using ecological momentary assessment and a greater focus on general health outcomes. We welcome interest in collaboration. A portion of our data, including the neuroimaging, resides in the National Data Archive (all data related to the study named Validating RDoC for Children and Adolescents: A Twin Study with Neuroimaging, collection #2105; https://ndar.nih.gov/edit_collection.html?id=2105&source=RDoCdb&funding=NIH+-+Extramural).

Acknowledgments

This work was supported by the National Institute of Mental Health (R01-MH101504, R01-MH059785, R01-MH069793 and R37-MH050560), the Wisconsin Center for Affective Science (P50-MH069315), two Conte Neuroscience Centers (P50-MH084051 and P50-MH100031), the Wallace Research Foundation and the National Alliance for Autism Research. Infrastructure support was provided by the Waisman Center via core support from the National Institute of Child Health and Human Development (P30-HD003352 and U54-HD090256). The authors owe special gratitude to Wisconsin twins and their families for their generous time for research participation. We also thank a large team of scientific collaborators, graduate students, postdoctoral trainees, research staff and undergraduate student research assistants.

References

Abidin, R. R. (1995). Parenting stress index (3rd ed.). Odessa, FL: Psychological Assessment Resource.Google Scholar
Adluru, N., Luo, Z., Van Hulle, C., Schoen, A. J., Davidson, R. J., Alexander, A. L., & Goldsmith, H. H. (2017). Anxiety-related experience-dependent white matter structural differences in adolescence: A monozygotic twin difference approach. Scientific Reports, 7, 8749.CrossRefGoogle ScholarPubMed
Alisch, R. S., Van Hulle, C., Chopra, P., Bhattacharyya, A., Zhang, S.-C., Davidson, R. J., … Goldsmith, H. H. (2017). A multi-dimensional characterization of anxiety in monozygotic twin pairs reveals susceptibility loci in humans. Translational Psychiatry, 7, 1282.CrossRefGoogle ScholarPubMed
Baruch, G. K., & Barnett, R. (1986). Role quality, multiple role involvement, and psychological well-being in midlife women. Journal of Personality and Social Psychology, 51, 578585.CrossRefGoogle Scholar
Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck Depression Inventory. San Antonio, TX: The Psychological Corporation.Google Scholar
Berenson, K. R., Gyurak, A., Ayduk, Ö., Downey, G., Garner, M. J., Mogg, K., … Pine, D. S. (2009). Rejection sensitivity and disruption of attention by social threat cues. Journal of Research in Personality, 43, 10641072.CrossRefGoogle ScholarPubMed
Brown, C., & Dunn, W. (2002). The Adolescent/Adult Sensory Profile: User’s manual. San Antonio, TX: Psychological Corporation.Google Scholar
Burghy, C. A., Fox, M. E., Cornejo, M. D., Stodola, D. E., Sommerfeldt, S. L., Westbrook, C. A., … Birn, R. M. (2016). Experience-driven differences in childhood cortisol predict affect-relevant brain function and coping in adolescent monozygotic twins. Scientific Reports, 6, 37081.CrossRefGoogle ScholarPubMed
Buss, K. A., & Goldsmith, H. H. (2000). Manual and normative data for the Laboratory Temperament Assessment Battery — Toddler Version. Madison, WI: University of Wisconsin–Madison.Google Scholar
Cambridge Cognition. (2019). CANTAB® [Cognitive assessment software]. Retrieved July 11, 2019, from www.cantab.comGoogle Scholar
Carbonneau, R., Rutter, M., Simonoff, E., Silberg, J. L., Maes, H. H., & Eaves, L. J. (2001). The Twin Inventory of Relationships and Experiences (TIRE): Psychometric properties of a measure of the non‐shared and shared environmental experiences of twins and singletons. International Journal of Methods in Psychiatric Research, 10, 7285.Google Scholar
Carroll, I. C., Planalp, E. M., Van Hulle, C., & Goldsmith, H. H. (2019). Peer victimization and selective attention in adolescence: Evidence from a monozygotic twin difference design. Journal of Abnormal Child Psychology, 47, 13031313.CrossRefGoogle ScholarPubMed
Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. Journal of Personality and Social Psychology, 67, 319333.CrossRefGoogle Scholar
Chung, M. K., Luo, Z., Adluru, N., Alexander, A. L., Davidson, R. J., & Goldsmith, H. H. (2018). Heritability of nested hierarchical structural brain network. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 554557.CrossRefGoogle Scholar
Chung, M. K., Luo, Z., Leow, A. D., Alexander, A. L., Davidson, R. J., & Goldsmith, H. H. (2018). Exact combinatorial inference for brain images. In Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-López, C., & Fichtinger, G. (Eds.), Medical Image Computing and Computer Assisted Intervention — MICCAI 2018 (pp. 629637). Cham, Switzerland: Springer International Publishing.CrossRefGoogle Scholar
Compas, B. E., Davis, G. E., Forsythe, C. J., & Wagner, B. M. (1987). Assessment of major and daily stressful events during adolescence: The Adolescent Perceived Events Scale. Journal of Consulting and Clinical Psychology, 55, 534541.CrossRefGoogle ScholarPubMed
Crone, E. A., & van der Molen, M. W. (2004). Developmental changes in real life decision making: Performance on a gambling task previously shown to depend on the ventromedial prefrontal cortex. Developmental Neuropsychology, 25, 251279.CrossRefGoogle ScholarPubMed
Crothers, L. M., Schreiber, J. B., Field, J. E., & Kolbert, J. B. (2009). Development and measurement through confirmatory factor analysis of the Young Adult Social Behavior Scale (YASB): An assessment of relational aggression in adolescence and young adulthood. Journal of Psychoeducational Assessment, 27, 1728.CrossRefGoogle Scholar
Cuthbert, B. N. (2014). The RDoC framework: Facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry, 13, 2835.Google ScholarPubMed
da Matta, A., Goncalves, F. L., & Bizarro, L. (2012). Delay discounting: Concepts and measures. Psychology & Neuroscience, 5, 135146.CrossRefGoogle Scholar
Downey, G., Lebolt, A., Rincón, C., & Freitas, A. L. (1998). Rejection sensitivity and children’s interpersonal difficulties. Child Development, 69, 10741091.CrossRefGoogle ScholarPubMed
Ellis, L., & Rothbart, M. (2001). Revision of the Early Adolescent Temperament Questionnaire. Paper presented at the Biennial Meeting of the Society for Research in Child Development, Minneapolis, Minnesota. https://doi.org/10.1037/t07624-000Google Scholar
Freeston, M. H., Rhéaume, J., Letarte, H., Dugas, M. J., & Ladouceur, R. (1994). Why do people worry? Personality and Individual Differences, 17, 791802.CrossRefGoogle Scholar
Frick, P. J., & Hare, R. D. (2001). Antisocial Process Screening Device: APSD. Toronto, Canada: Multi-Health Systems.Google Scholar
Gagne, J. R., Van Hulle, C., Aksan, N., Essex, M. J., & Goldsmith, H. H. (2011). Deriving childhood temperament measures from emotion-eliciting behavioral episodes: Scale construction and initial validation. Psychological Assessment, 23, 337353.Google ScholarPubMed
Goldsmith, H. H. (1991). A zygosity questionnaire for young twins: A research note. Behavior Genetics, 21, 257269.CrossRefGoogle ScholarPubMed
Goldsmith, H. H., Lemery-Chalfant, K., Schmidt, N. L., Arneson, C. L., & Schmidt, C. K. (2007). Longitudinal analyses of affect, temperament, and childhood psychopathology. Twin Research and Human Genetics, 10, 118126.Google ScholarPubMed
Goldsmith, H. H., Lemery-Chalfant, K., Schmidt, N. L., Schmidt, C. K., Chow, O. K., & Justen, A. A. (2010). Field administration manual for the Laboratory Temperament Assessment Battery: Middle childhood version. Madison, WI: Psychology Department, University of Wisconsin–Madison.Google Scholar
Gooding, D. C., Winston, T. M., Pflum, M. J., & Burgin, C. J. (2015). Individual differences in hedonic experience: Further evidence for the construct validity of the ACIPS. Psychiatry Research, 229, 524532.CrossRefGoogle ScholarPubMed
Halberstadt, A. (1986). Family socialization of emotional expression and nonverbal communication styles and skills. Journal of Personality and Social Psychology, 51, 827836.CrossRefGoogle Scholar
Huang, S.-G., Chung, M. K., Carroll, I. C., & Goldsmith, H. H. (2019). Dynamic functional connectivity using heat kernel. In 2019 IEEE Data Science Workshop (DSW), Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 222226.CrossRefGoogle Scholar
Kasch, K. L., Klein, D. N., & Lara, M. E. (2001). A construct validation study of the Response Styles Questionnaire Rumination Scale in participants with a recent-onset major depressive episode. Psychological Assessment, 13, 375383.CrossRefGoogle ScholarPubMed
Kovacs, M. (2003). The Children’s Depression Inventory (CDI): Technical manual. North Tonawanda, NY: Multi-Health Systems.Google Scholar
Lemery-Chalfant, K., Goldsmith, H. H., Schmidt, N. L., Arneson, C. L., & Van Hulle, C. (2006). Wisconsin Twin Panel: Current directions and findings. Twin Research and Human Genetics, 9, 10301037.CrossRefGoogle ScholarPubMed
Meyer, T. J., Miller, M. L., Metzger, R. L., & Borkovec, T. D. (1990). Development and validation of the Penn State Worry Questionnaire. Behaviour Research and Therapy, 28, 487495.CrossRefGoogle ScholarPubMed
Morris, N. M., & Udry, J. R. (1980). Validation of a self-administered instrument to assess stage of adolescent development. Journal of Youth and Adolescence, 9, 271280.CrossRefGoogle ScholarPubMed
Patterson, G. R., & Stouthamer-Loeber, M. (1984). The correlation of family management practices and delinquency. Child Development, 55, 12991307.Google ScholarPubMed
Pearlin, L. I., Lieberman, M. A., Menaghan, E. G., & Mullan, J. T. (1981). The stress process. Journal of Health and Social Behavior, 22, 337356.CrossRefGoogle ScholarPubMed
Petersen, A., Crockett, L., Richards, M., & Boxer, A. (1988). A self-report measure of pubertal status: Reliability, validity, and initial norms. Journal of Youth and Adolescence, 17, 117133.CrossRefGoogle ScholarPubMed
Planalp, E. M., Van Hulle, C., Gagne, J. R., & Goldsmith, H. H. (2017). The infant version of the Laboratory Temperament Assessment Battery (Lab-TAB): Measurement properties and implications for concepts of temperament. Frontiers in Psychology, 8, 846.CrossRefGoogle ScholarPubMed
Raine, A., Dodge, K., Loeber, R., Gatzke-Kopp, L., Lynam, D., Reynolds, C., … Liu, J. (2006). The Reactive–Proactive Aggression Questionnaire: Differential correlates of reactive and proactive aggression in adolescent boys. Aggressive Behavior, 32, 159171.CrossRefGoogle ScholarPubMed
Robbins, T. W., James, M., Owen, A. M., Sahakian, B. J., McInnes, L., & Rabbitt, P. (1994). Cambridge Neuropsychological Test Automated Battery (CANTAB): A factor analytic study of a large sample of normal elderly volunteers. Dementia, 5, 266281.Google ScholarPubMed
Ryff, C. D., & Keyes, C. L. M. (1995). The structure of psychological well-being revisited. Journal of Personality and Social Psychology, 69, 719727.CrossRefGoogle ScholarPubMed
Schmidt, N. L., Brooker, R. J., Carroll, I. C., Gagne, J. R., Luo, Z., Planalp, E. M., … Goldsmith, H. H. (2019). Longitudinal research at the interface of affective neuroscience, developmental psychopathology, health, and behavioral genetics: Findings from the Wisconsin Twin Project. Twin Research and Human Genetics, 22, 233–239.CrossRefGoogle Scholar
Schmidt, N. L., Van Hulle, C., Brooker, R. J., Meyer, L. R., Lemery-Chalfant, K., & Goldsmith, H. H. (2013). Wisconsin Twin Research: Early development, childhood psychopathology, autism, and sensory over-responsivity. Twin Research and Human Genetics, 16, 376384CrossRefGoogle ScholarPubMed
Schoen, S. A., Miller, L. J., & Green, K. (2008). Pilot study of the Sensory Over-Responsivity Scales: Assessment and inventory. American Journal of Occupational Therapy, 62, 393406.Google ScholarPubMed
Small, S. A., & Kerns, D. (1993). Unwanted sexual activity among peers during early and middle adolescence: Incidence and risk factors. Journal of Marriage and Family, 55, 941952.CrossRefGoogle Scholar
Spielberger, C. D., Gorsuch, R. L., Lushene, R. E., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Thompson, M., Kaslow, N. J., Weiss, B., & Nolen-Hoeksema, S. (1998). Children’s Attributional Style Questionnaire — revised: Psychometric examination. Psychological Assessment, 10, 166170.Google Scholar
Torrubia, R., Ávila, C., Moltó, J., & Caseras, X. (2001). The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) as a measure of Gray’s anxiety and impulsivity dimensions. Personality and Individual Differences, 31, 837862.CrossRefGoogle Scholar
Van Hulle, C., Lemery-Chalfant, K., & Goldsmith, H. H. (2002). Wisconsin Twin Panel. Twin Research and Human Genetics, 5, 502505.CrossRefGoogle ScholarPubMed
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 10631070.CrossRefGoogle ScholarPubMed
You have Access

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Wisconsin Twin Project Overview: Temperament and Affective Neuroscience
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Wisconsin Twin Project Overview: Temperament and Affective Neuroscience
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Wisconsin Twin Project Overview: Temperament and Affective Neuroscience
Available formats
×
×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *